Streamed Sensor Processing With Adaptive Modes for Anomaly Detection
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Solution Overview
Problem
Existing control systems for industrial automation processes face inefficiencies in processing sensor data, particularly due to the time-consuming nature of batch processing, which hinders real-time monitoring and operational efficiency.
Innovation Solution
Implementing smart sensor devices capable of processing streamed sensor data using learning algorithms for anomaly detection, preventative maintenance, and diagnostics, allowing them to toggle between operational modes with varying levels of complexity to reduce computational load and extend device lifetime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If batch processing is used for sensor data, then processing accuracy is improved, but processing time increases significantly
Solution Approach 1:
The system dynamically adjusts processing modes based on operational conditions. The smart sensor device toggles between first operational mode (streamed processing with learning algorithms) and second operational mode (batch processing) depending on whether anomaly conditions are detected, optimizing both response time and processing accuracy adaptively
Solution Approach 2:
The processing system is segmented into multiple operational modes: streamed processing mode for real-time anomaly detection using learning algorithms, and batch processing mode for comprehensive analysis. This segmentation allows the system to apply appropriate processing depth to different data scenarios
2Reliability
If complex learning algorithms are continuously executed, then anomaly detection capability is improved, but device lifetime decreases due to increased power consumption
Solution Approach 1:
The learning algorithms are executed periodically rather than continuously. The system monitors sensor data streams and only activates complex learning algorithm processing when anomaly conditions are detected or suspected, otherwise operating in a lower-power monitoring state
Solution Approach 2:
The system dynamically toggles between operational modes based on detected conditions. When normal operation is detected, the system uses minimal processing; when anomalies are detected, it switches to intensive learning algorithm processing, optimizing the balance between detection capability and power consumption
3Measurement precision
If all sensor data is transmitted for processing, then monitoring accuracy is improved, but computational load on external systems increases
Solution Approach 1:
The system extracts and processes only relevant anomaly-indicating features locally using learning algorithms before transmitting results to external systems. This prevents transmission of all raw sensor data, reducing computational load on external systems while maintaining monitoring accuracy for critical events
Solution Approach 2:
The smart sensor device acts as an intermediary that performs preliminary processing and filtering of sensor data using learning algorithms. It extracts meaningful anomaly information and transmits only this processed information to external systems, reducing their computational burden
Data Source
AI summary
A system may include sensor device comprising a sensor configured to measure sensor data indicating an operational parameter of industrial automation equipment associated with an industrial automation process. The system may also include communication circuitry configured to transmit the sensor data. Additionally, the system includes a processor configured to receive the sensor data. Further, the system includes a non-transitory computer-readable medium comprising computer-executable instructions that, when executed, are configured to cause the processor to perform operations including identifying an operational state of the industrial automation equipment based on the sensor data. The operations may also include determining a discrepancy between the sensor data and the operational state. Further, the operations may include modifying an operation of the processor from a first operational mode to a second operational mode of a plurality of operational based on the comparison.