Sensor-Command Association for Industrial Machine Fault Verification
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Solution Overview
Problem
Current technologies face challenges in easily verifying the operation of industrial machines that rely on sensor detection data, making it difficult to identify and address malfunctions effectively.
Innovation Solution
A device and method that acquire detection data from sensors and associate it with executed instructions, allowing operators to search for and verify the cause of malfunctions by correlating detection data with specific operations, facilitating the identification of erroneous detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If detection data is acquired and stored without association to specific instructions, then data storage is simple, but it becomes difficult to verify the cause of malfunctions
Solution Approach 1:
The system performs preliminary association between detection data and instruction information during the normal operation phase, before malfunction verification is needed. This pre-organization of data relationships eliminates the need for complex real-time analysis during malfunction investigation, allowing operators to directly retrieve associated data when verification is required.
Solution Approach 2:
Instruction information serves as an intermediary that links detection data with specific operations. Instead of directly correlating complex detection data with malfunction symptoms, the system uses instruction information as a mediator that organizes detection data by operational context, making verification straightforward through the intermediary layer.
2Difficulty of detecting and measuring
If detection data is associated with each instruction, then malfunction verification is facilitated, but data processing complexity increases
Solution Approach 1:
The system segments detection data by associating it with individual instructions in the operation program. Each detection data set is tagged with corresponding instruction information, creating discrete, searchable units. This segmentation allows operators to isolate and examine specific detection data related to particular instructions, making error detection systematic rather than requiring analysis of the entire data set.
Solution Approach 2:
The system establishes a feedback loop where detection data is continuously associated with instruction execution status. When a malfunction occurs, the pre-associated data provides immediate feedback about what was detected during the problematic operation, enabling rapid identification of detection errors without complex real-time processing.
3Reliability
If all detection data is stored for verification, then complete verification is possible, but storage requirements and processing time increase
Solution Approach 1:
The system performs preliminary organization of detection data by associating it with instruction information during normal operation. This pre-sorting creates an indexed structure where data can be rapidly retrieved based on instruction identifiers, eliminating the need to search through all stored detection data during verification and significantly reducing access time while maintaining complete data availability.
Solution Approach 2:
Instead of processing or retrieving all detection data during verification, the system extracts only the specific detection data associated with the instruction where malfunction occurred. This selective extraction based on pre-established associations minimizes data processing requirements while ensuring complete verification capability for relevant data.
Data Source
AI summary
A device for verifying the operation of an industrial machine that controls operations based on detection data of a sensor includes: a detection data acquisition unit that acquires detection data detected by the sensor during execution of an operation program that includes a plurality of commands causing the industrial machine to execute a plurality of operations; and an association generation unit that associates the executed commands and the detection data used in the control of the operations performed by the executed commands with each other.