Controller Soft Error Detection via I/O Module Abnormality Patterns
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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 a soft error by counting the number of input/output modules, and determines a soft error by counting the number of input/output modules with abnormalities, replacing control units if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the system monitors abnormalities in input/output modules to detect soft errors, then the reliability of error detection is improved, but the complexity of the detection system increases
Solution Approach 1:
The detection system is segmented into multiple independent input/output modules, each capable of autonomous abnormality detection. By dividing the monitoring function across multiple modules rather than using a centralized complex system, the patent achieves reliable soft error detection while keeping individual module complexity manageable. Each module independently monitors its own operations and reports abnormalities to the control unit.
Solution Approach 2:
The system implements feedback mechanisms where each input/output module continuously monitors its own operational status and provides abnormality information back to the control unit. This feedback loop enables the system to detect soft errors by analyzing patterns of abnormalities across multiple modules, improving detection reliability without requiring overly complex external monitoring infrastructure.
2Measurement precision
If multiple input/output modules are monitored simultaneously for abnormalities, then the precision of soft error identification is improved, but the time required for detection increases
Solution Approach 1:
Each input/output module performs preliminary self-diagnosis and abnormality detection continuously in the background during normal operations. By preparing abnormality data in advance rather than performing comprehensive checks only when errors are suspected, the system achieves precise soft error identification without significant detection delays. The control unit can quickly determine soft errors by comparing pre-collected abnormality patterns from multiple modules.
3Reliability
If the system implements comprehensive abnormality detection across all input/output modules, then the reliability of system operation is improved, but the energy consumption increases
Solution Approach 1:
The system implements partial monitoring where each input/output module performs abnormality detection at optimized levels rather than exhaustive comprehensive checks. The control unit analyzes abnormality patterns from multiple modules to identify soft errors, allowing the system to achieve high reliability through coordinated partial detections rather than requiring each module to perform full-spectrum monitoring, thereby reducing overall energy consumption.
Data Source
AI summary
A controller includes a first processor that performs a process of collecting data from each device constituting a system via each input/output module, detecting, based on the collected data, the input/output module in which abnormality has occurred from among the input/output modules, and determining, based on the number of the input/output modules in each of which the occurrence of the abnormality has been detected, whether or not a soft error has occurred in the own controller.