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How can you ensure consistent sensor data in distributed control systems?

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Distributed control systems (DCS) are widely used in industrial automation, robotics, and smart environments. They rely on a network of sensors, actuators, and controllers to monitor and control complex processes. However, sensor data can be affected by noise, delays, errors, and inconsistencies, which can compromise the performance and safety of the system. How can you ensure consistent sensor data in DCS? Here are some tips and techniques to improve the quality and reliability of your sensor data.

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Abdul Rehman

Specialist Engineer (SAS - Safety & Automation Systems) at Aker Solutions

1 Sensor fusion

Sensor fusion is the process of combining data from multiple sensors to produce a more accurate and robust estimate of the state of the system. Sensor fusion can help reduce noise, compensate for missing or faulty data, and resolve conflicts or ambiguities among sensors. Sensor fusion can be performed at different levels: data level, feature level, or decision level. Data level fusion combines raw sensor measurements, feature level fusion extracts relevant information from sensor data, and decision level fusion integrates the outputs of different sensors or controllers.

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2 Sensor calibration

Sensor calibration is the process of adjusting the parameters of a sensor to match a reference or standard value. Sensor calibration can help correct systematic errors, biases, or drifts in sensor data. Sensor calibration can be performed offline or online. Offline calibration requires a known input or output to compare with the sensor data, while online calibration uses feedback from the system or other sensors to adjust the sensor parameters. Online calibration can be adaptive or self-calibrating, depending on whether the calibration is done periodically or continuously.

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Abdul Rehman

Specialist Engineer (SAS - Safety & Automation Systems) at Aker Solutions
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Sensor calibration helps confirming the URL (upper range limit) and LRL (Lower Range Limit) and thus the span of sensor measurements capability.

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3 Sensor placement

Sensor placement is the process of selecting the optimal locations and orientations of sensors in a DCS. Sensor placement can affect the coverage, redundancy, diversity, and resolution of sensor data. Sensor placement can be done manually or automatically. Manual sensor placement requires domain knowledge and experience, while automatic sensor placement uses optimization algorithms or heuristic methods to find the best sensor configuration. Automatic sensor placement can be static or dynamic, depending on whether the sensor positions are fixed or adjustable.

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4 Sensor communication

Sensor communication is the process of transmitting and receiving sensor data in a DCS. Sensor communication can be affected by bandwidth, latency, packet loss, interference, and security issues. Sensor communication can be improved by using appropriate protocols, standards, and architectures. Protocols define the rules and formats of data exchange, standards ensure compatibility and interoperability among devices, and architectures determine the topology and hierarchy of the network. Sensor communication can be centralized or decentralized, depending on whether the data is processed by a single or multiple nodes.

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Abdul Rehman

Specialist Engineer (SAS - Safety & Automation Systems) at Aker Solutions
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Scan time of DCS input card must be higher than sensor update / cycle frequency. Thus there will be consistency in the value being read during logic or application programming in the Control system.

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5 Sensor validation

Sensor validation is the process of verifying and evaluating the quality and reliability of sensor data in a DCS. Sensor validation can help detect and correct anomalies, outliers, or faults in sensor data. Sensor validation can be done by using statistical methods, logical methods, or model-based methods. Statistical methods use probability and distribution models to analyze sensor data, logical methods use rules and constraints to check sensor data, and model-based methods use physical or mathematical models to simulate sensor data.

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6 Sensor management

Sensor management is the process of coordinating and controlling the operation and behavior of sensors in a DCS. Sensor management can help optimize the performance and efficiency of the system by allocating resources, scheduling tasks, and adjusting parameters of sensors. Sensor management can be done by using feedback control, optimization, or learning methods. Feedback control uses sensors and actuators to regulate the system state, optimization uses objective functions and constraints to find the best solution, and learning uses data and algorithms to improve the system behavior.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Abdul Rehman

Specialist Engineer (SAS - Safety & Automation Systems) at Aker Solutions
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Also other factors like Sourcing and Sinking type, NAMUR, fail safe (NC contact), Non Fail safe (NO contact), intrinsic or non intrinsic type shall also be considered as per application.

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How can you ensure consistent sensor data in distributed control systems?

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1 Sensor fusion

2 Sensor calibration

3 Sensor placement

4 Sensor communication

5 Sensor validation

6 Sensor management

7 Here’s what else to consider

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