Visual Indicator Analysis for Process Station State Deviations
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Solution Overview
Problem
Manual monitoring of process stations is inefficient due to the large number of sample conditioning systems in industrial plants, leading to infrequent detection of deviations from expected operating states, which can result in suboptimal performance and inaccurate analytical measurements.
Innovation Solution
A system that captures digital images of process stations, analyzes visual indicators, and compares them to expected states defined in configuration data to generate indicia for deviations, enabling automated monitoring and alerting operators to potential issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual monitoring of process stations is performed, then operational status can be detected, but monitoring frequency is low and efficiency is poor due to the large number of sample conditioning systems
Solution Approach 1:
The system enables self-service monitoring by automatically capturing images of visual indicators, processing them through image recognition algorithms, and generating alerts without human intervention. The processor autonomously compares current states with expected states and triggers notifications when deviations are detected, eliminating the need for manual operator inspection while maintaining continuous monitoring capability
Solution Approach 2:
The patent replaces the mechanical manual inspection process with an automated image-based monitoring system. Instead of operators physically visiting and reading gauges, a camera captures visual indicators, and a processor analyzes the images using image recognition technology to determine operational status, substituting human mechanical inspection with automated optical and computational systems
2Measurement precision
If digital measurement systems are installed at sample conditioning systems, then monitoring accuracy improves, but the cost of retrofitting thousands of systems becomes prohibitive
Solution Approach 1:
The system uses visual copying of measurement information by capturing images of existing analog gauges and visual indicators with a camera. Instead of installing digital sensors, the system creates optical copies of the visual displays through image capture and processes these copies using image recognition algorithms to extract measurement data, maintaining accuracy while avoiding expensive hardware installation
Solution Approach 2:
The image-based monitoring system provides universal applicability across different types of visual indicators (gauges, dials, LED displays, digital screens) without requiring type-specific sensors or modifications. A single camera and image processing algorithm can monitor multiple different indicator types, making the system cost-effective for retrofitting across thousands of diverse sample conditioning systems
Data Source
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AI summary
In one aspect, a system includes at least one processor configured to identify a digital image of the process station generated during an operation of the process station, identify, in the digital image, a visual indicator of the process station, and analyze the visual indicator to identify a current state of the visual indicator. The at least one processor is further configured to identify configuration data for the process station that defines an expected state of the visual indicator, determine whether the current state deviates from the expected state, and generate indicia representing the identified current state in response to determining that the current state deviates from the expected state.