Controller Logic for Soft Error Detection Across I/O Modules
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Solution Overview
Problem
Existing systems struggle to accurately determine the occurrence of soft errors in semiconductor chips, leading to simultaneous failure of multiple input/output modules despite their normal operation, affecting system functionality.
Innovation Solution
A controller system that collects data from input/output modules, detects abnormalities, and determines the occurrence of soft errors based on the number of modules with detected abnormalities, allowing for appropriate determination and countermeasures without immediately transitioning modules to a fail state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system transitions input/output modules to a fail state upon detecting abnormality, then system reliability is improved by isolating faulty modules, but measurement precision deteriorates because multiple normal modules are incorrectly identified as faulty due to soft errors in the control unit
Solution Approach 1:
The system performs preliminary actions by collecting data from multiple input/output modules and analyzing the pattern of abnormalities before transitioning any module to a fail state. By examining whether multiple modules report abnormalities simultaneously, the system determines if a soft error has occurred in the control unit, and only then transitions modules to fail state. This preliminary analysis prevents premature or incorrect failure transitions.
Solution Approach 2:
The system implements feedback by continuously monitoring the status of multiple input/output modules and using this information to determine the nature of the error. When multiple modules simultaneously report abnormalities, the system feeds back this pattern recognition to identify a soft error condition, adjusting its response accordingly. This feedback mechanism prevents incorrect isolation of normal modules while maintaining reliability for genuine faults.
2Stability of the object's composition
If the system immediately transitions input/output modules to fail state upon detecting abnormality, then system stability is improved by preventing propagation of errors, but productivity deteriorates due to unnecessary service interruptions and module replacements
Solution Approach 1:
The system performs preliminary analysis by collecting data from multiple input/output modules and determining whether abnormalities are caused by soft errors or genuine module failures. Only after this preliminary assessment confirms actual module failure does the system transition modules to fail state. This prevents unnecessary service interruptions while maintaining system stability for genuine faults.
Solution Approach 2:
The system uses feedback from multiple module status reports to determine the appropriate response. When feedback indicates simultaneous abnormalities across multiple modules, the system identifies this as a soft error pattern and maintains module operation. This feedback-driven approach preserves productivity by avoiding unnecessary module isolation while maintaining stability through appropriate error handling.
3Measurement precision
If the system monitors and analyzes data from multiple input/output modules to determine soft error occurrence, then measurement precision is improved for identifying actual faults, but device complexity increases due to additional data collection and analysis mechanisms
Solution Approach 1:
The control unit performs multiple functions using the same data collection mechanism: it collects status data from input/output modules for both normal operation monitoring and soft error detection. By making the data collection system universal, the patent avoids adding separate dedicated monitoring hardware, thereby improving measurement precision for soft error detection without proportionally increasing device complexity.
Solution Approach 2:
The system merges the soft error detection function with the existing operational monitoring of input/output modules. Instead of implementing a separate complex detection system, the patent combines soft error analysis with routine status checking, allowing multiple functions to share the same data collection and processing infrastructure, thus improving detection accuracy while limiting complexity growth.
Data Source
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AI summary
A controller (10) collects data from each of field devices (20) constituting a plant via each of input/output modules (M), detects, based on the collected data, the input/output module (M) in which abnormality has occurred from among the input/output modules (M), and determines, based on the number of input/output modules (M) in each of which the occurrence of the abnormality has been detected, whether or not a soft error has occurred in the controller (10).