Diagnosis-Code Data Retransformation in Industrial Safety Control
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Solution Overview
Problem
Existing industrial control systems face challenges in achieving computational efficiency while ensuring high operational safety, particularly in safety-critical environments, where malfunctions can be harmful.
Innovation Solution
An industrial control system utilizing two data channel units and a retransformation unit, employing invertible transformation and inverse functions with a diagnosis code to detect computational errors, allowing for efficient error detection and safe state switching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional redundancy methods are used to ensure operational safety, then reliability is improved, but device complexity and hardware overhead increase
Solution Approach 1:
The patent creates a virtual copy of the diagnosis code through invertible transformation. The first data channel unit receives input data and a diagnosis code, transforms them into transformed data using an invertible transformation function. The retransformation unit then re-transforms this data using the inverse function to regenerate the diagnosis code, which is compared with the original to detect errors. This virtual copying approach achieves redundancy without duplicating physical hardware components.
Solution Approach 2:
The patent replaces physical hardware redundancy with a software-based transformation and retransformation mechanism. Instead of using multiple physical data channel units running in parallel, the system uses a single data channel unit with invertible transformation functions that mathematically generate and verify diagnosis codes. This substitution of mechanical redundancy with algorithmic redundancy reduces hardware overhead while maintaining reliability.
2Productivity
If computational efficiency is improved by using slim architecture, then productivity is improved, but reliability deteriorates
Solution Approach 1:
The patent changes the parameter representation through invertible transformation. The diagnosis code and input data are transformed into a different parameter space using the transformation function, processed efficiently, then transformed back using the inverse function. This parameter transformation allows the system to maintain full error detection capability while operating in a computationally efficient parameter space, resolving the contradiction between slim architecture and reliability.
Solution Approach 2:
The patent implements a feedback mechanism where the retransformation unit regenerates the diagnosis code from the transformed data and compares it with the original diagnosis code. This feedback loop ensures that any computational errors during transformation are detected, maintaining reliability even in a computationally efficient slim architecture. The feedback verification step guarantees that productivity gains do not compromise error detection capability.
Data Source
AI summary
An industrial control system includes a first data channel unit, a second data channel unit, and a retransformation unit. The first data channel unit receives first input data and a diagnosis code and transforms the first input data into first transformed data using an invertible transformation function employing the diagnosis code. The second data channel unit receives second input data and the diagnosis code and transforms the second input data into second transformed data using the invertible transformation function employing the diagnosis code. The retransformation unit receives the first transformed data and the diagnosis code from the first data channel unit and receives the second transformed data from the second data channel unit. The retransformation unit converts the first transformed data into first output data employing an inverse function of the invertible transformation function. The retransformation unit converts the second transformed data into second output data employing the inverse function.