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Leveraging Technology to Redefine Critical Data Acquisition
JAMEY HILLEARYELECSYS CORPORATION
PRESENTATION FOCUS
Data Acquisition Technologies Historic data acquisition methods Exception based communications Blending of data acquisition models Getting the right data to the right places Cloud integration Summary
INDUSTRIAL DATA ACQUISITION(HISTORICAL)
I. Critical Data Typically in SCADA system Monitored 24/7 Alarms trigger immediate action
II. Non-Critical Data Typically not related to immediate
safety or catastrophic failure Often monitored “by exception” or
unmonitored entirely
CRITICAL DATA ACQUISITION
• SCADA Poll/response from host system Continually monitored by control room Persistent connection, redundant
communication Expensive, difficult to extend to remote
areas
HISTORIC SCADA POLLING MODEL
Communication typically initiated from the host system
HISTORIC SCADA POLLING MODEL• Limitations
System expansion reduces bandwidth Reduced data throughput/increased lag
time Difficult to integrate legacy field
equipment Data not readily available to all users Inefficient for incorporating “non-
critical” data
NON-CRITICAL DATA ACQUISITION• Exception Based Remote Monitoring
A. Periodic polling or auto-reportingB. Non-critical data C. Low-cost/low-bandwidth
communication (cellular or low-bandwidth satellite)
D. Data accessed over webE. Expands data acquisition field to very
remote locations
EXCEPTION” DATA ACQUISITION MODEL
Communication typically initiated from the field devices
EXCEPTION DATA ACQUISITION
• Limitations
A. Not persistent “real time” communicationB. Small data packet sizeC. Often via 3rd party network (cellular,
satellite)D. Not suited for incorporating “critical”
dataE. Data securityF. Field personnel roles evolving
“EXCEPTION-BASED” INTELLIGENT SENSOR MONITOR SYSTEMS
• Critical and semi-critical data sensors• Cellular/satellite exception-based
communication• “Incremental changes” trending notifications• Local data-logging, remote data retrieval• Multiple data routing paths• Enterprise wide data access
Exception Based CommunicationI. Measurement/report frequency• Measure frequently (typically hourly to once daily)• Report to web periodically (typically once per week)• Override report schedule for alarm conditions
II. Data “burst” communication• Small packet size• Non-persistent connection• Typically public cellular network or low-bandwidth satellite
(Inmarsat Data Pro, Iridium, Orbcomm, etc.)III. Data management/optimization features• Local memory storage (data-logging)/web data retrieval• “Dead-band” incremental
BLENDING DATA ACQUISITION MODELS USING DEVICE TECHNOLOGY
• Traditional SCADA Sensors Sensors, intelligent field devices, PLCs, RTUs
• Remote Monitoring Systems Integrated measurement/communication devices
• Hybrid Exception Based Sensor Monitors Sensor/transducer based remote monitors
BLENDING DATA COMMUNICATION MODELS USING DEVICE TECHNOLOGY
I. Traditional SCADA Sensors Persistent, redundant connectivity with host
II. Remote Monitoring Systems Low-bandwidth, exception based, alarms
III. Hybrid Exception Based Sensor Monitors Low-bandwidth, data-logging, incremental trending
notification, alarms
IV. All Systems Broker connectivity, enterprise wide data routing
GETTING THE RIGHT DATA TO THE RIGHT PLACE(S)?
• Alternative approach to data acquisitionA. Data from all sources and networks sent to
a cloud-based data brokerB. “Smart” monitors extend network footprintC. Personnel granted “publish/subscribe”
access to their required data D. Multiple networks using enabled protocolsE. Broker can be private, secure, and
redundant
BROKER ASSISTED CLOUD INTEGRATION
SUMMARY1. Integration of data acquisition models
increase 2. Data volume3. Ultra-thin protocols (MQTT, AMQP) enable intelligent data routing via brokers4. Hybrid data acquisition systems expand data field footprint5. Broker technology allows hierarchical controlled access to enterprise data6. Broker technology enables data routing between silos, increasing enterprise efficiency
