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A Measurement System for Performance Monitoring on Small Sailing Dinghies

Christoph Boehm, Yacht Research Unit Kiel, Germany / Delft University of Technology, The Netherlands Robert Brehm, Mads Clausen Institute, University of Southern Denmark, Denmark Janek Meyer, Yacht Research Unit Kiel, Germany Lars Duggen, Mads Clausen Institute, University of Southern Denmark, Denmark Kai Graf, Institute of Naval Architecture, University of Applied Sciences Kiel (UAS), Germany

1 ABSTRACT This paper describes a new performance

monitoring system for dinghies and small sailing boats, developed in a collaborative project of the Yacht Research Unit Kiel (YRUK) and the Mads Clausen Institute (MCI)of the University of Southern Denmark. The system under development features a complete set of nautical instruments (wind, boat speed and heading, position) as well as dynamic sensors measuring the motion of the dinghy with additional audio and video streams for crew observations. Most sensors are integrated in a small lightweight housing also containing a main processing unit to be mounted on a dinghy. Some external miniaturized sensors (wind and water anemometers) are connected wirelessly. Data and media streams are recorded. Further a telemetry system allows online data transmission to a remote client operated on a coach boat. Analysis software allows the coach to visualize and analyze the performance of the dinghy. Both, the hardware system and the analysis software are presented here including first results from a field trial.

2 NOTATION Leeway angle (°) Rudder angle (°)

AWA Apparent wind angle (°) COG Course over Ground (°) HDG Heading (°) LAT Latitude LON Longitude SOG Speed over ground (m/s) TWA True wind angle (°) TWD True wind direction (°) TWS True wind speed (m/s) VMG Velocity made good (m/s) VPP Velocity prediction program

3 INTRODUCTION Modern nautical instrument systems are widely

used on contemporary racing yachts. They allow monitoring of nautical data such as wind speed and angle, boat velocity in an absolute and water bound frame. Additional sensors provide information about dynamic motions and loads. Software systems tracking the course on digital maps help to assess the performance of the yacht and support tactical decisions while racing. These systems are widely available and have proven their value for racing crews.

Similar systems on dinghies are rare. Instrumentation on dinghies is usually restricted to dedicated sensor/instrument pairs for an isolated particular purpose, e.g. wind or position/course (one of the few exceptions is the PiGarda © system from Cosworth Ltd, /GB)Ref.: [1]. While sailors on board may take advantage from these data, they are not available to a coach responsible for developing the performance of the sailors. In addition a coach would need a complete integrated set of measurement data in order to analyze the performance and aid its development

In a joint project YRUK and MCI are addressing this. YRUK and MCI are developing a system measuring nautical as well as dynamic motion data on dinghies as described above for bigboats. In addition audio and video streams for crew and sail observations are generated. While data streams are recorded on board the dinghy, a telemetry system is available for online data transfer. A coach boat nearby may receive the data streams from one or many dinghies equipped with the system. Software running on a laptop or tablet computer, connected to the sailing dinghies by a client server principle, allows the coach to observe onboard action and performance of the dinghies

THE 21th CHESAPEAKE SAILING YACHT SYMPOSIUM

ANNAPOLIS, MARYLAND, MARCH 2013

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Analysis software is available to support the coach in assessing the performance of the sailors and help them to improve it. It is up to the coach to derive conclusions and take respective action in order to develop the performance of the racing crew.

The following chapters will describe the hardware and software system in detail. First results of field tests will be presented and the next steps in the system development are outlines.

4 THE PERFORMAND SYSTEM It has been explicated in the introduction that

available systems to measure boat and crew performance nowadays are principally aimed on application for larger boats. Performance assessment during training sessions onsmaller boats and dinghies in still depend significantly on the subjective judgment of coaches. Practice evaluation based on scientific methods as it is progressively used in professional sports like football, soccer or formula 1 racing is virtually unheard of in small boat yacht racing. The system described here, christened PerforManD(Performance Monitoring and Development), allows a coach to monitor practice performance of a specific boat, compare the results with other boats and thus helps to enhance the efficiency of practical training sessions.

The PerforManD system consists of a set of onboard sensors measuring nautical and dynamic data. These transmit data to a central data aggregation unit placed on the respective dinghy. This unit records thesensor data for later review and simultaneously transmits the data to a data visualizing unit onboard the coach boat. This data visualizing unit is currently a laptop computer, but future software versions might be ported to tabletcomputers or even smartphones. A descriptive overview of the system is given in Figure 1.

Figure 1: System Principle

Within the PerforManD system every boat is equipped with a wind anemometer to measure apparent wind and a paddlewheel or impeller velocimeter to measure speed through water. Further sensors include video camera(s), GPS position, orientation and speed and an inertial measurement unit. When possible, instruments have been housed into the data aggregation unit which, beside its data logging capabilities also includes telemetry modules like Wi-Fi and Bluetooth for wireless communication. Since the use case of PerforManD aims at small boats and dinghies, great care has been taken that all sensors can be mounted to the sail boat without permanent destruction like e.g. drilling holes. Furthermore, no cabling is required since all sensors connect wirelessly to the data aggregation unit or are embedded in it. This allows for fast setup of the system on an individual boat. Compared to big boats instruments all components have been miniaturized with respect to size and weight. Both, the data aggregation unit and the sensor nodes are powered autonomously by lithium batteries in addition to solar panels which allow for data logging sessions of approximately 8 hours.

To provide the coach with access to real-time data during training sessions, a Wi-Fi module with external antenna is mounted onboard the coach boat to extend the connection range of the visualizing and analyzing unit. . If several boats are in range, the coach is able to switch between the individual boats or to monitor the data of multiple boats simultaneously. This allows for either the direct performance comparison of boats sailing in similar conditions, the monitoring of a complete fleet, or giving special attention to a particular boat by dedicated exclusive monitoring.

The second mode in which PerforManD may be used is the review mode. In this mode data collected by the data aggregation unit onboard the dinghies during previous practice sessions may be reviewed and compared. Several ways of using the review mode are thinkable:

A coach may choose to review practice sessions to draw conclusions regarding success of training sessions which he then presents to the sailors. Coach and crew(s) may review training sessions simultaneously to discuss maneuvers and evaluate performance. A performance analyst can use the review mode to generate debriefing documents to present them to the sailing team. He can also feed performance data regarding training sessions into an external database.

Besides the ability to monitor and display measured boat data, PerforManD also incorporates sophisticated analyzing tools which have been developed to help the coach evaluating the performance of sailors. Among the available analysis methods, a 3D velocity polar plot and a data processing algorithm to obtain velocity

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polars is of outstanding importance, since it allows assessing performance relative to a target, which can be derived from field tests as well as from theoretical predictions. PerforManD thus is a coaching tool, which aids helps coaches to improve efficiency of sailing training sessions.

5 HARDWARE - SOFTWARE CONCEPT The introduced sailing performance quantification

system puts very specific and hard constraints on the hardware and software design and its respective specific topologies. Obviously the hard- and software needs to be designed to meet the specific rough (wet and dynamic) conditions onboard a sailing dinghy while still providing the usability suitable for quick & easy installation andmaintenance. In addition it should provide maximum reliability, flexibility and both power and processing efficiency. In any situation the installed system should uncontestably not interfere with the sailors onboard norshall the installation influence the sailing performance of the boat in any respect. The pre-session installation overhead time should be zero or at least limited to a minimum so that hardly any time effort is spend before each new training session, while system components likethe sensors should be temporary and durable mountable without any permanent fixations at the boats structure.

Physically the system consists of the following components:

1. A central data aggregation and processing system onboard the dinghy

2. Different sensors, distributed over a star network for performance measure and sailing performance quantification.

3. Mobile or stationary computer executing the analyzing software in real-time or server-less.

The development and design of the hard- /software topology has been led by the natural distribution of the system consisting of the two major distributed components, on one side the coach, using the data visualization and analyzing software executed on a (mobile) computer and the sailboat as the sailing performance data aggregation and provision system. On the bases of this given natural structure it is obvious to choose a classical client-server topology as underlying framework for the system topology where the hardware onboard the sailing Dinghy acts as data server and the data receiving computer executing the analyzing software actsas client as shown in Figure 2.

Figure 2: - Server (Dinghy) transmits measured data to Client (Coach Boat)

The advantages of this client-server scheme are not far to seek; the system is divided into two components, client and server, which interact only over a defined communication interface and protocol. Once this interface and protocol is defined both hard- and software components on their respective sides can be developed independently and there are no hard- /software constraints to one another. The analyzing software on its executing platform and the data server onboard the dinghy are physically decoupled and completely independent platforms.

This client-server scheme improves the flexibility and maintenance of the system. The server and the client are able to operate head / body-less (stand-alone) and both can easily adapt to system changes on the opposite side. In addition, the client-server decoupling improves reliability on either side and reduces code complexity which results in easier hard- and software maintenance but also in greater stability and reliability.

In fact such client/server scheme also simplifies the hard- software development as well as its management. Independent non-parallel development work becomes easily possible and independent programming languages can be used as long as the agreed interfacing is provided.

This client-server scheme is consistently further brought down onboard the sailing dinghy where sensors act as data servers and the central data aggregation unit acts as the client which connects to these. Again this improves flexibility in terms of modular hardware extensions and changes of the system onboard the dinghy.

5.1 Hardware topology The hardware onboard each sailing dinghy consists

of a star topology sensor network with wired and wireless sensor node connections with a central data aggregation and processing unit as the star point of the system.

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The general approach for using partly wireless communication links has been driven by the constraint to minimize or completely prevent interference of the installed system with the sailor and the sailing performance of the dinghy. Cable connections obviously break this constraint. The wireless approach solves the cable problems, it however brings up new problems that are inherent to wireless communication systems, the primary problem being that of autonomous power supply. The remote sensor nodes need to be powered autonomously and the individual power budget need to suit the global runtime of the system. This requires the appropriate choice of the wireless network technology as well as suitable protocols and autonomous power supplies.

In order to design a generic and modular exchangeable and extendable system, a standard wireless communication technology has been chosen for onboard wireless data communication between the data aggregator unit and the sensor nodes. This allows for access to sensor nodes even with standard communication devices such like smart phones and tablet computers without the need of the central data aggregation device. This in particular becomes interesting in cases where the system is installed on semi-professional sailboats where the full extent of the here described PerforManD system might not be used.

Several suitable wireless technologies are available fordecades such as ANT, ANT+, ZigBee, ZigBee RF4CE, Wi-Fi, Bluetooth, Nike+, IrDA, and the near-field communications (NFC) standard all featuring specific capabilities but also shortcomings. However, only two are generally and widely accepted communication market being Bluetooth and Wi-Fi. These are supported generically; almost all of the available mobile communication devices such as Smart-Phones and tablet computers support Wi-Fi and Bluetooth communication. In order to allow for maximum compatibility of the PerforManD system to state-of-art embedded mobile devices and because of its extremely low power consumption, Bluetooth 4.0 (Bluetooth Low Energy - BLE) has been chosen as the sensor networks communication layer in the PerforManD system.

The Bluetooth Low Energy technology was designed for lowest possible power consumption. The advantage of Bluetooth Low Energy is that it can be placed into deep sleep mode where it only awakes event-driven to send active files to its gateway. The maximum peak current consumption is less than 20 mA and the average currentconsumption depending on the transmission rate can be brought down to about 1 A which releases power load off the energy supplying system (battery). One reason for the ultra-low power consumption is the low latency for gateway linking and little message overhead. Therefore, the energy consumption is reduced to a tenth of that of classical Bluetooth communication which suits well to the here described autonomous sensor network. The above

described power advantages make it possible to use standard rechargeable lithium cells for energy storage which provide the necessary individual sensor node lifetimes to cover the global onboard system lifetime.

Based on Bluetooth the onboard wireless sensor network uses a simple star topology where all sensor nodes are slaves and the data aggregator is the central master device. The slaves use an advertising function to periodically announce availability of sensor data within the sensor network which are then read by the master (data aggregator). A generic BLE board has been developed to bridge classical communication interfaces such as UART over Bluetooth. This allows to connect standard sensor technology via a wireless link which is essential for those sensors not embedded inside the central data aggregator. In particular so far this is true for the Wind Anemometer and the Log (Speed through the water) which is currently under development.

The remote sensor nodes are powered by rechargeable batteries. To extend lifetime for sensors which demand high energy density, additional supply is added in form of a solar panel which extends the battery lifetime of the sensor. This is the case for the mast top ultrasonic wind anemometer which ultrasonic sensing scheme consumes extra energy. The energy harvesting also reduces efforts on maintenance and pre-session overhead time for system installation since battery changes are less frequent required or completely prevented.

The goal for the development of the central onboard hardware was to allow for easily modular expansion of the system with high level user-experience. This means that software- and hardware-wise the system is easily scalable. In terms of hardware this scalability is reached through the above described master/slave sensor star topology, and the client-server scheme for data aggregator and analyzing graphical user interface at the receiving mobile computer.

All location independent sensors are embedded in the data aggregation unit and are connected to the main processor by internal serial communication busses. These wired sensors are in particular the Global Positioning System (GPS) and the Inertial Measurement Unit (IMU) to measure the craft's velocity over ground, and 3D orientation and dynamics on the water surface.

The complete sensor network is built around a powerful 32-bit ARM Cortex processor core which is the heart of the data aggregator where the integrated peripherals are used to implement the various communication interfaces and protocols to interface to the attached sensor periphery and the client side, see Figure 3: Hardware layer. This for server-sensor communication is mainly the I2C bus, UART and SPI as well as Bluetooth and for the client side communication this is an Ethernet, USB and a WI-FI controller.

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Data at the data aggregation unit is stored on a micro-SD card. This card can be accessed via a standard mini-USB cable or via the network interface and an FTP connection.When a USB cable is connected to the data aggregation unit it gets mounted as an external hard drive so that the recorded data can be easily accessed from any host computer.

Figure 3: Hardware layer

5.2 Sensor technology In the first instance the sensor topology onboard the dinghyis able to collect the following dynamic parameters:

1. Wind Speed and direction

2. Position, Speed-over-Ground, Heading

3. Pitch Roll Yaw

4. (Speed through the water)

Wind Anemometer: The wind speed and direction is measured by a wireless ultrasonic wind anemometer which is easily installed on the mast top without the need of cabled connections. The wind anemometer is powered through a buffer battery connected to a solar panel. It submits data autonomously at a maximum sample rate of 1Hz. A future version will be able to sample at 2 and 4Hz. The dynamic range of the sensor is 0.25 80 knots at a resolution of 0.1knots. The directional resolution is ±1º. The weight of the unit is approximately 200g. The sensor has a cylindrical form with a diameter of about 150mm and a height of about 80mm.

GPS: A Global Positioning System chip is embedded into the central data aggregator unit which provides the current position, speed-over-ground and the heading. A high performance GPS module is used which enables high performance navigation for harsh GPS environments and low signal reception. A fix rate is configurable up to 10Hz to track highly dynamic movements of the sailboat. The device has a high sensitivity to compensate for possible negative effects of the surrounding server system EMI(Electromagnetic Interference) and an efficient current

consumption of just 25mA. Communication with the main processor is provided through a standard UART interface.

Inertial Measurement Unit (IMU): The IMU is based on a System-in-Package module which combines a 3-axis gyroscope, a 3-axis accelerometer, a 3-axis magnetometer as well as an onboard digital motion processor which is capable of processing 9-axis motion algorithms. For high precision and dynamic motion tracking the gyro offers 16 bits resolution and a programmable full scale range of ±250, ±500, ±1000, and ±2000°/sec. The range of the accelerometer is programmable to be ±2g, ±4g, ±8g, and ±16g at a resolution of 16 bits, the compass resolution is 13 bits and the range ±1200µT. The IMU features an embedded co-processor in addition to the main data aggregation processor to offload timing requirements and processing power needed for the motion processing algorithms. Communication with the main processor is provided through the I2C interface.

Speed-through-the-water: This sensor is still under bench construction but will be available in the next prototype series introduction. A small impeller is mounted (glued) on the outer wall under the sailing dinghy. The rotating impeller creates a rotating magnetic field which is measured by a Hall-Effect sensor mounted at the opposite inner wall of the boats hull. A Hall-Effect sensor varies its output voltage in response to a magnetic field. This sensor is attached to microcontroller which processes the data and links them to the data aggregation unit via Bluetooth link. Accuracy and resolution are still to be defined in the calibration laboratory.

The newest prototype series of the data aggregation unit will provide video and audio data via a real time stream and an embedded camera.

5.3 Server-Client Communication Data collected by the server from the individual

sensors are simply forwarded to the client over a standard secured IEEE 802.11 Wi-Fi connection layer. An ad-hoc wireless LAN network is used where the client and the server communicate peer-to-peer (P2P). In a peer to peer network each network node is allowed to directly communicate with one another within a defined P2P group. Nodes within range of each other can discover and communicate directly without involving central access points or routers. This allows for flexible setup and extension of the PerforManD system network so that multiple sailing dinghies can server data to just one single client (coach).

The Transmission Control Protocol (TCP) is used to transfer the data collected at the server onboard the sailboat to the client which is executed on a mobile computer and runs the data analyzing software. TCP is chosen for its reliability and its easy implementation. TCP is optimized

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for accurate delivery rather than low package delivery latency. Therefore in heavy loaded networks long transfer latencies sometimes occur because of out-of-order message delays or retransmission of lost messages. However, the simplicity and easy implementation of TCP prevails these drawbacks in this application where network complexity respectively network traffic is readily comprehensible in the insular peer-to-peer network.

Data are sent to the data analyzing unit and software in an ASCII XML formatted TCP stream as shown below:<sensordatacollection> <sensordataset id="1"> <gps> <gmttime> <hours>09</hours> <minutes>08</minutes> <seconds>24</seconds> </gmttime> <date> <dd>27</dd> <mm>04</mm> <yyyy>2012</yyyy> </date> <latitude> <degrees>54</degrees> <minutes>54</minutes> <seconds>45</seconds> <hemisphere>N</hemisphere> </latitude> <longitude> <degrees>009</degrees> <minutes>46</minutes> <seconds>48</seconds> <hemisphere>E</hemisphere> </longitude> <speedMS>0.02</speedMS> <heading>0.0</heading> </gps> <wind> <timestamp>1334492563</timestamp> <speedMS>0.3086</speedMS> <reldirection>135.0</reldirection> <temperatureC>25.0</temperatureC> </wind> <acceleration> <x>0</x> <y>3</y> <z>56</z> </acceleration> </sensordataset> </sensordatacollection>

In the next prototype revision the audio/video stream will be transported as a parallel data stream using the Real-time Streaming Protocol (RTSP) as shown in Figure 4: Data streams. In addition to USB, network data access is provided through the Secure File Transfer Protocol (SFTP) and the setup of the data aggregation unit is done through a web interface and the Hypertext Transfer Protocol (HTTP). These several data protocols and data stream are used in collaboration as shown in Figure 4: Data streams

Figure 4: Data streams

5.4 Server Software The hardware onboard the sail boat is built around a powerful but efficient 32-bit embedded processor which allows for execution of a state-of-art rich 32-bit operation system kernel. A standard kernel is optimized for embedded usage and features an advanced power management which adapts to the underlying hardware to maximize battery lifetime. On top of the kernel sits a modular extendable operating system which provides maximum usability, user experience and flexibility for system extension. The actual PerforManD system functionality is build modular into the operating system kernel so that the system gets cross-platform compatible. This allows for easy porting of the complete PerforManDserver software structure to other hardware platforms which can be smart phones or tablet computers.

Software access to peripheral devices such as all attached sensors is provided through loadable kernel modules which abstract the underlying hardware to accessible files in the file system of the operating system from which individual sensor data are read. Once a module is loaded into the kernel a new (sensor) service comes available to the user-space through standard entry points, known technically as system calls. This scheme protects the system from user access to the underlying hardware of the sensor interfaces and protocols which provides maximum system stability and reliability since all hardware is completely secured for user access and potential mess-up or bug introduction. Each sensor has its individual kernel module which is responsible for the sensor hardware interrogation but also power control. It runs secured and protected inside the kernel as an individual process which is scheduled by the kernel scheduler only. These modules are individually programmed for each sensor type and they can be loaded (or unloaded) into the kernel on demand depending on the system configuration onboard each individual sailing dinghy. Depending on the attached sensor the related module will poll for sensor data at defined sample rates or it listens for incoming data which it makes accessible to the user-space through individual files named after the sensor inside the file system of the operating system.

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All sensor interfacing modules are programmed for maximum power efficiency and where possible hardware is put asleep if not accessed to reach maximum power efficiency. Where possible an event/interrupt driven approach is used. This allows for precise runtime and battery lifetime prediction which is of major importance for the described system. For each system configuration a specific energetic load can be predicted and from that the maximum battery lifetime of the system.

Naturally the kernel implements the used TCP networking protocol which provides the server-to-client communication over the peer-to-peer wireless network. Afeatured networking utility (application) which reads and writes data across network connections using TCP is used for the client communication. This utility can be accessed from user-space applications or scripts.

Additional communication channels can be added as loadable kernel modules as well. This for example can be a General Packet Radio Service (GPRS) connection via a GSM (Global System for Mobile Communications) modem. In such case the system provides direct data backup and access via modern data cloud systems via a file hosting service that offers cloud storage and file synchronization. If a GSM connection is available data are written (backup) directly into the data cloud. Therefore no manual data transfer via USB/Network has to be performed.

To provide maximum user experience the complete system set-up and configuration is done through a graphical user web-interface. Hidden behind this graphical user interface,the web-interface generates the required system calls to load and unload kernel modules respectively, and initialize the system for specific configurations. Once the configuration for the system is done, a configuration script is generated which is executed at each system boot.

Because all complex sensor hardware interfacing, housekeeping, communication protocol implementations and timing or interrupt functionalities are implemented inside loadable kernel modules and hidden, the actual data sampling and the data forwarding via a TCP stream or other communication interfaces can completely be programmed in a simple scripting language which is executed in the user space of the kernel. This makes the system extremely flexible and provides maximum stability and reliability. The script is automatically generated by the web-interface depending on the individual settings of the user. Just like each sensor and communication module, the kernel then executes this script as a separate process.

6 CLIENT SOFTWARE In the following the client software (Figure 5) and

its visualization and analyzing tools will be described in detail. The software is aimed to give a coach or

performance analyst the possibility to visualize data measured using the PerforManD sensor system, to assist the assessment in sailing performance with additional analysis tools. In addition a review mode is available for visualization and analyzing of the recorded measurement stream during debriefing sessions of sailors and coaches.

Figure 5: The Client - Software

Before training, a boat/training specific software setup can be initiated which can be used as default setup.. On the water several views on the measured performance data are available. There are two categories:

1. The coach can choose to focus on one particular boat out of the fleet equipped with the system.

2. More than one boat can be chosen for a comparative view of performances.

This feature is available online during training sessions as well as in the debriefing sessions. In a debriefing session a user is able to focus on arbitrary situations on the timeline and do a training data replay with adjustable speed. This can be done for a particular boat or for the entire fleet fully synchronized.

A major aspect of the software development process has been cross-platform portability. Therefore the client software has been written in C++ programming language, portable GUI development libraries and OpenGL graphics.

6.1 3D/2D Polar Plot A velocity polar diagram showing the speed a

sailing yacht can achieve depending on true wind speed and direction is widely used by yacht designers. It allows assessing a particular design and comparing it to others. Velocity polars are also valuable to the sailor. They provide operational parameters like tack and gybe angles and cross overs for different sail sets. However primarily

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they provide the maximum speed of the yacht as a target, depending on wind conditions. A velocity plot provides a target for the sailor to achieve during training sessions. If he routinely exceeds the target, the velocity polar is invalid and has to be modified. Obviously an accurate velocity polar is of great value to a coach of a dinghy.

Standard velocity polar diagrams are based on an aerodynamic and a hydrodynamic model of the sail boatderived from experimental or numerical flow analysis. The PerforManD system uses a different approach: it generates a velocity polar from performance measurements aboard. These measurements are obtained while sailing and do not need any special attention.

To this end PerforManD uses a three dimensional description of the boat speed depending on TWA and TWS, where TWS is given as a continuous value rather than a set of discrete values as a conventional polar plot. The geometric representation of this three-dimensional boat performance description is a torus surface in a three dimensional cylindrical coordinate system, see Figure 3.

Figure 6: 3D Polar Plot

A conventional polar plot can be derived easily from this 3D-torus. Any horizontal intersection through the torus at a particular height, e.g. wind speed, gives the velocity polar for this particular wind speed.

PerforManD presents the intersection of the polar torus at the currently measured wind speed. In addition the current boat speed at current TWA is also shown in the diagram, see Figure 3. A conventional 2D polar diagram derived from the torus is shown in Figure 4.

Figure 7: 2D Polar Plot based on the 3D calculation

The advantages of this 2D/3D polar plot are:

for polar plot generation, measured boat performance is used in the polar diagram for any arbitrary wind speed as measured, without additional interpolation. a single graphical presentation allows a coach to observe the current sailing state of the dinghy, he is working with: Does the boat reach its target speed, does the boat sail its target upwind or downwind TWA? Is it expected to gybe. Tracks of measured performance points in the 3D-polar visualize changes of boat speed, wind speed and wind angle and allows assessing whether they correlate (appropriately). Comparisons of different sailors tori allow identifying strengths and weaknesses of a crew. Comparisons of theoretical and measured tori allow assessing a theoretical VPP method.

The process of generation of a performance torus is split into five steps: (1) filtering the data, (2) data storage, (3) best-of method, (4) interpolating and (5) smoothing.

Performance relevant data such as wind and boat speed and angles, respectively, are acquired with a data rate of 5 to 10 Hz and averaged to 1 to 2 Hz. A filtering procedure excludes maneuver situations and handles wind gaps or shifts. Manoeuvers are detected using the AWA and other course-relevant values. Wind gaps or rapid wind changes have to be recognized, since they correlate with boat speed changes only with some phase difference and would degenerate the accuracy of a boat speed to wind speed mapping.

Filtered data is stored in a three dimensional array with the velocity of the boat, the true wind speed and its direction as the three dimensions. Array elements count the

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absolute frequency of occurrence of a particular combination of boat speed, TWA and TWS. Due to the gridded character of speed, AWA and AWS in the array,any measurement has to be distributed by a reverse tri-linear interpolation to the eight nearest neighbor fields as illustrated in Figure 8.

Figure 8: Reverse Trilinear Interpolation

Due to the data storage concept in a three-dimensional array, exact measured values cannot beretrieved; however averaged values over a data set areequal to those of conventional averages. The method allows efficient data storage even if millions of individual samples are taken into account. The storage concept involves a given inherent inaccuracy. Since using a reasonable large array this inaccuracy is by far smaller than the accuracy of the wind and boat speed sensors and can be neglected.

Special care has been taken to avoid considering sub-optimal boat speeds in the averaging process. This is done using an approach similar to the definition of significant wave height - . To get suitable polar tori, some interpolation of missing values and additional smoothing is necessary. This is done using local low order polynomial approximation derived from least square calculations.

While the process of obtaining measurement data streams for polar torus generation is fully automated, it is assumed that many hours of sailing are necessary toachieve a plausible velocity polar torus. At the beginning of the use of a PerforManD system the torus will be incomplete and inaccurate while over time the entire wind range will be covered and accuracy will grow. It is possible to import existing diagrams which will be fitted by additional measurements. The imported diagrams could be either diagrams generated by the PerforManD-Software or by an external VPP.

6.2 Digital Chart A digital chart is available within PerforManD,

showing any dinghy registered and involved in the training process. In online mode this can serve as a conventional

navigation aid. In addition to position it provides information of the current sailing state (speed, wind, etc.) of any boat linked to the coach boat.

Figure 9: digital chart

In review mode the digital chart can show any boat, which has been equipped with the PerforManD system and thus provides recorded data streams. Consequently a debriefing session can visualize an entire fleet simultaneously. For each boat the local wind and performance measures are available. This is of some help for debriefing sessions not only for the orientation of the sailors; but also it can provide information of the relative performance of the boats, how they behave tactically and how they take advantage of the local wind.

6.3 Video Player With the video player, it is possible to get to know

the situation of the boat and the sailors. With a camera position chosen appropriately one can get information like the trim, the wave conditions and the behavior of the sailors. In review mode, the video player is available as well, showing recorded media streams. The video is synchronized to all other instruments and with other boats. This allows correlating action on board with respective performance data. The video mode will be available for the next prototype release of the PerforManD system.

6.4 Time Series Plot Time series plot (Figure 16) allows showing any

available data stream over time, whether it is a native, directly measured stream or a derived one. Its purpose is manifold: it can be used to visualize the change of wind data over time or the correlation between boat speed and motion, for example in waves. It is used to detect wind changes, manoeuvers or performance changes due to some trimming action.

The time series plot can visualize measured and derived data as instant mode values or as averaged values

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over an arbitrary period. In addition, the difference between a long term average (10 sec to 30 min) and the instant value can be shown. A typical application for this would be the change of wind direction around an average in comparison with the change of boat course around an average. This visualizes the ability of the crew on board to take appropriate action in case of wind changes.

6.5 Maneuver Estimation The maneuver estimation allows the trainer to

recognize maneuvers and their qualities on a quick glance. By using the replay mode he is able to analyze the reasonsby means of the recorded video and the plotted data.

The software detects a maneuver by checking changes of the sign of AWA. Additional algorithms recognize if the detected point really belongs to a correct maneuver or if they are measurement errors or hard wind shifts. The maneuver is finished when the new course is reached and the boat has reached its maximum speed in relation to the new course and wind conditions. Because of the unsteadiness of the natural environment, e.g. rapidwind changes, waves and currents, it is not possible to detect the correct start and endpoints automatically. To solve this problem the start- and endpoints are calculated with a constant time-offset with respect to the time where AWA changes its sign. A simple mechanism is available to change the constant time offset for any individual tack.

Each manoeuver is getting a rating, quantifying the quality of the manoeuver. The rating is based on the area between the VMG-curve and the straight line between the start- and endpoint as illustrated in Figure 10 or in Marchaj [2].

Figure 10: Theory of the Maneuver Estimation

The area is defined as follows:

Therefore the rating is the height made good compared to the height made good in the same time without a tack. In theory, this algorithm is not very sensible to the actual value of the start and end time of the tack as long as this is in reasonable distance to the beginning of the manoeuver.

6.6 Velocity-Made-Good-Plot The VMG-Plot is an instrument, which plots the

velocity made good over the apparent wind angle. This instrument provides the best way to get the optimal tack angle. One conceivable scenario is that the sailor will aim for the maximum boat speed, while slowly decreasing the angle to the wind. Meanwhile the coach observes the VMG-value in the plot, where the plotted data will get a tendency like in the blue curve shown in Figure 11. After the sailor has passed the optimal angle it is easy read from the plot.

Figure 11: VMG Plot

Figure 11 shows high VMG values for small AWAs. These are caused by tacks since the boat keeps its initial speed at the beginning of the tack due to boat inertia. To avoid misinterpretation due to these tacks, the trainer is able to clear the plotted points with a single click. Moreover it is possible that the plot only shows a few of the last recorded points. This way outdated points will be deleted automatically.

6.7 Sail Shape Analysis The PerforManD system makes it possible to

analyze sail shapes during a regular training session. For that purpose additional cameras may be placed at suitable places, for example directly on deck or at the masthead. These cameras are wirelessly connected to the display unit on the coach boat. The user may remotely trigger a snapshot of the current state of the sail at any time. This snapshot is then automatically transferred to the display unit.

After the picture of the sail shape is loaded, the coach may look at it to see if the shape matches his expectations and he then is able to define profile stripes (Figure 12). These profile stripes allow deriving typical sail characteristics like chord length, maximum draft position, maximum draft, twist and entry and exit angles.

In combination with performance data from other PerforManD plots, these sail characteristics can be used to

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quantify the influence of trimming on sail shape and thus on sailing performance. A measured sail with its profile stripes as well as the boat ID and recording time may be stored and therefore serve to build a database of ideal configurations for specific environmental conditions (wind conditions and direction, sea state). With input from a large number of training sessions one is able to determine a guide for optimal sail trimming for a specific crew.

Figure 12: Sail Shape measurement

The profile stripes are currently manually defined using B-splines. While we are aware that more sophisticated methods are available which allow the automatic detection of sail shape stripes from images and/or video streams (e.g. line-recognition algorithms based on Hough transformation), we decided against implementing such methods in the current PerforManDversion. This however might change for future versions depending on user demands. For the time being it is considered sufficient since, with the current implementation, one is already able to retrieve performance-relevant information with minimal manual effort.

6.8 Wind Shifts All sailors need the skill to recognize wind shifts

and align their course to the new wind direction, to analyze and train this skill the software contains an instrument called Wind Shifts. As illustrated in Figure 13 the delta value of the heading is shown on the left-hand side and the delta value of the wind direction on the right-hand side. The delta value is calculated based on the difference between the average and current value. In this case it is possible to use a sliding average for the average value or a constant average.

Figure 13: Wind Shifts

When observing a good sailor, the arrow of the HDG-delta value should follow the arrow of the TWD-delta value and the delay should be as small as possible.

6.9 Classical Instruments Important real-time values are shown in the

classical nautical instrument view. The layout is orientated on common instruments on board of a boat. This gives the user a familiar view.

Figure 14: Classical Instruments

7 RESULTS In order to prove the PerforManD system, sea

trials have been conducted. For these first initial trials a small keelboat has been selected as test platform. The platform has been chosen as a compromise between a big boat (stable platform, less dynamics, dry testing conditions) and a dinghy (unstable platform, very dynamic, wet testing conditions). This compromise has been made to

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ease the first trials, which were aimed for testing and debugging of the system concept and its core components.

7.1 Setup of the PerforManD system The platform used is a Waarschip 725, a 7.25m

long quarter-tonner, built in multi-chine plywoodconstruction technique. The principle dimensions are given in Table 1.

Table 1: Principle dimensions of W725

Length over all (m) 7.25Length of water line (m) 5.5Maximum breadth (m) 2.5Draft (m) 1.2Displ. (t) 1.2Keel Weight (t) 0.5Main Sail Area (m²) 9.8Genua-1 sail area (m²) 16.3Genua-2 sail area (m²) 13jib sail area (m²) 6Spinnaker sail area (m²) 36

In order to equip the boat for sea trials the different sensors have been placed on the boat as shown in Figure 15.

The data aggregation unit has been fixed on top of the cabin roof with the following sensors embedded:

GPS sensor for: o speed over ground (SOG) o course over ground (COG) o position (LAT / LON)

Accelerometer o Accelerations and derived values in

3-axis o Orientation 2 angles (PITCH,

HEEL) Fluxgate compass for magnetic course (HDG)Thermometer

The 3D wind anemometer has been placed at the masthead to measure apparent wind speed (AWS) and angle relative to the boat axis (AWA).

To measure the shape of the fore sails, a camera has been installed on the foredeck. In the current development phase this camera is a GoPro Hero 2 with Wi-Fi module which allows transferring the captured images directly to the computer on the coach boat.

Figure 15: Setup of sensor equipment

The single sensor component which we have not been able to integrate so far is the log.

7.2 First Results This initial testing phase has been dictated by

three major goals:

1. Debug hardware (sensors, Wi-Fi, etc.) and software (implementation of derived values, etc.).

2. Test the system in a non-laboratory environment.

3. Collect data which allows to improve the software

Verification by means of quantitative values is very hard to achieve for measurements on a sailing boat, therefore instruments are normally calibrated in laboratory conditions. However, a qualitative assessment of measured values is possible. This approach is necessary, especially when it comes to interaction of the different sensors to deliver data for derived values.

The time series plot shown in Figure 16 is a cut-out of one of the sea trials. It shows the variation of different native and derived values for a time period of approximately 420s (7min). The upper lines, numbered 1 to 5 are plotted over the primary y-Axis (left) whilst values from 6 to 9 are plotted over the secondary axis.

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Figure 16: Time series plot of data from sea trials

The displayed values are:

(1) True Wind Direction [°] , (green) (2) Course over Ground [°] , (dark yellow) (3) Heading [°] , (dark blue) (4) True Wind Angle [°] , (red) (5) Apparent Wind Angle [°] , (dark red) (6) Apparent Wind Speed [m/s] , (dark green) (7) True Wind Speed [m/s] , (white) (8) Speed Over Ground [m/s] , (purple) (9) Velocity Made Good [m/s] , (blue)

The plot allows several observations which are useful for a qualitative assessment. One can see that the variation of the measured values (AWA, AWS, COG, SOG and HDG) is reasonable, without either being too smooth or too much fluctuation.

At point (a) the COG sensor readings (1) shows a sudden drop which at first glance might look like a sensor failure. In truth this is only display-related and originates from the definition of COG as values ranging from 0° to 360°. The derived values (TWS, TWA, TWD, and VMG) also show reasonable values. In comparison values from a local metrological station (Kiel Lighthouse) reported a true wind direction of 270° and a true wind speed of 8.5kts for the time interval displayed in the plot (Figure 17, red line). The measured values of the PerforManD system in Figure 16 give an average TWS of approximately 7.8kts and an average TWD of 280°, thus being very similar to the values from the metrological station.

Figure 17: Wind information from local metrological station

Keeping in mind that the measurements were taking in constrained coastal waters whilst the metrological station is located a few miles away in a more open water these data correlate very well.

At points (b) and (c) in Figure 16 sudden changes in AWA and TWA are observable. At (a) the AWA drops from roughly 40° to -60° and then increase to -40° - TWA follows this pattern, as do AWS, SOG and VMG. This behavior indicates that at point (a) the boat has tacked. Looking at the true wind direction one can see that these values are not affected by the tacking maneuver indicating a correct derived value implementation. The same holds true for TWS which is also not affected by the tack and only shows some natural oscillations originating from gusts.

Point (b) also shows a tacking maneuver, but differences can be seen here. First of all one can see an increase of AWS and TWS of 3.5 and 3.1 m/s during tack, respectively. This indicates that the sailor has tacked in a gust. The consequences for the tacking maneuver are noticeable. Both VMG and SOG only show a very short drop and a significantly faster recovery than during the tack at point (a). One can therefore conclude that because of tacking in a gust, tack (b) was better than tack (a). This is also reflected by the maneuver estimation plot as depicted in Figure 18.

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Figure 18: Rating of tacking maneuvers

For the blue VMG curve the shaded area associated with the curve reflects the amount of distance to windward gained / lost. This results in a rating as described in section 6.5. Comparing the rating of maneuver (a) and (b) clearly shows an advantage for maneuver (b).

7.3 First generated polar diagrams None of the test runs aimed solely for the polar

diagram creation. Therefore, there are lots of maneuvers in the measured data. Additionally, the individual measurements took less than an hour for the same combination of sails. The sailed course has often been close to the wind, resulting in a polar plot which is only sufficiently dense in this TWA region. Nevertheless, it is possible to show some promising results. To get a first overview of the quality of the generated diagrams, these are compared to the calculated diagrams of AVPP. The generated diagrams are only based on the measured data, which results in a lot of gaps due to insufficient data.

In the following 2d polar plots (Figure 20 and Figure 22) the blue curve always represents the polar diagram calculated in AVPP for the Waarschip 725 with its mainsail and the small jib. The first trial presented here was done with three persons on board in wind conditions over 4bft with lots of gusts and wind shifts. The second trial was done with two persons on board and the middle jib. The wind was relatively constant and about 3bft. The generated diagrams are based on a sailing time of about 40 minutes at a sample arte of 0.3Hz which was reduced do to hardware issues.

Figure 19 and Figure 21 show the top view of the 3D-plot. The black points are the real measured points, which are shown only for validation purposes. These points allow judging of the distribution of the measured points, which in this case explains all gaps in the 2D polar lines in Figure 20 and Figure 22.

Looking at the 2D polar plots one can see that in the downwind sector the measured polar lines are misshaped and seem to show wrong values. This is due to a thin data base leaving not enough points for the calculation of a correctly shaped polynomial in the region of the downwind courses. From the generated polar lines at low wind speeds one can see that the displayed boat velocities seem to be too high. This is a result of the wind gaps and the mass inertia of the boat. This indicates that the filter algorithm is not effective enough to handle wind gaps correctly and needs to be revised. In general the tendency of the boat velocity matches very well with the one predicted which was by AVPP. Especially the polar lines of the second trial have a nearly constant offset to the AVPP polar lines. Here one has to mention that the hydrodynamic database used to produce the polar lines is empiric and better suited for racing yachts. The aerodynamic model is based on the assumption of optimum sail trim and modern sails, which is not the case for both crew and boat. Additionally the VPP polar assumes calm water which of course is not the case in a natural environment. It can therefore considered that the VPP polar is roughly half a knot too fast. As mentioned above, the sailors did not aim for the maximum boat speed, but for the validation of the instruments. This gets obvious after comparing the measured data (black points) to the generated body, because the body is always close to the maximal reached boat speed. Indeed one has to consider that the AVPP polar lines are calculated for the small jib, but the second trial was done with the middle jib.

With attention to the insufficient data count and the contradictory trial targets, the here presented results are already promising and one could expect useful results after a few more days on water.

Figure 19: First Trial Top-View of the 3d-Plot

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Figure 20: First Trial 2d Polar Lines

Figure 21: Second Trial Top-View of the 3d-Plot

Figure 22: Second Trial 2d Polar Lines

7.4 Assessment of the first trials The major goals of the first trials were to collect

data to assist and improve the on-going development of the analysis software, test the system in a natural environment and to detect bugs in software and hardware. These goals have been achieved. Whilst a thorough validation of the system is still pending, qualitative analysis of the first results revealed no major bugs in the visualization of native values and the implementation derived values. The results also showed that the system is capable of delivering information regarding crew / boat performance to a coach.Future trials including additional sensors like audio / video and log on more dynamic boat platforms like dinghies, skiffs and catamarans are scheduled for 2013.

8 CONCLUSION The paper presented here describes the

PerforManD system developed in a joint project by Yacht Research Unit Kiel and Mads Clausen Institute (University of Southern Denmark) /Sonderborg. The project is in an

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intermediate state. While hardware and software development is pretty advanced, field measurements are only available in limited number.

The system is aimed to support coaches of sailing dinghy crews. It provides the necessary information to assess and develop the individual performance of a crew in a contemporary racing dinghy. It has to be underlined, that by no means the PerforManD system tries to substitute the work of a coach. The sole purpose of the system is to provide information to a coach.

The next steps of the project focus on field tests and subsequent refinement of the system. To this end, proprietary sensors for wind and boat speed are under development, which are better fitted to be used on a dinghy. Finally calibration and filtering algorithms will be enhanced, since they are of dominant importance to the accuracy of the systems.

The developers of the system are currently investigating options to make use of the system in an extended prototype phase, where further refinements of software and hardware are realized while the system is in use for teams in preparation of the Olympic Games 2016.

9 ACKNOWLEDGMENT The PerforManD project is funded by the

INTERREG4A program of the European Union.

10 REFERENCES 1.

http://cosworth.com/products/marine/performance-sailing/pi-garda-data-logger/[Accessed: 29.12.2012]

2. MARCHAJ, C.A.: Die Aerodynamik der Segel: Theorie und Praxis, Delius Klasing Verlag, Bielefeld, 1996