Hydraulic Excavator Malfunction Prediction Using Inspection Feedback
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Solution Overview
Problem
Existing malfunction prediction systems for work machines, such as hydraulic excavators, face challenges in improving prediction accuracy as they do not consider actual performance outside a predetermined time period, leading to incomplete assessment of potential malfunctions.
Innovation Solution
A malfunction prediction system that acquires operation, inspection, and part replacement/repair information, and uses deviation data to predict malfunction probabilities, incorporating these factors to enhance prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If malfunction prediction is based only on predetermined period event occurrence, then the system is simple to operate, but prediction accuracy is insufficient
Solution Approach 1:
The patent merges multiple data acquisition functions into a unified system. The operation information acquisition section, inspection information acquisition section, and part replacement/repair information acquisition section are integrated to collect comprehensive data from multiple sources, combining diverse information types to improve prediction accuracy while managing system complexity through integration.
Solution Approach 2:
The malfunction prediction section serves multiple functions: it processes operation information, inspection information, part replacement/repair information, and deviation information simultaneously. This multi-functional approach allows the system to handle various data types and perform comprehensive analysis, improving prediction accuracy without requiring separate dedicated systems for each data type.
2Measurement precision
If multiple data types are acquired and integrated, then prediction accuracy improves, but information processing complexity increases
Solution Approach 1:
The patent segments the information acquisition process into distinct functional sections: operation information acquisition, inspection information acquisition, and part replacement/repair information acquisition. Each section handles specific data types independently, ensuring comprehensive information collection while organizing processing tasks to manage complexity and prevent information loss.
Solution Approach 2:
The system incorporates deviation information, which represents the difference between predicted malfunction probability and actual inspection results. This feedback mechanism allows the system to learn from past predictions and actual outcomes, continuously improving prediction accuracy by adjusting based on historical performance data.
Data Source
AI summary
A malfunction prediction system 1 includes: an operation data acquisition section 201 that acquires operation data of a hydraulic excavator 10; an inspection data acquisition section 202 that acquires inspection data of the hydraulic excavator 10; a part replacement/repair data acquisition section 203 that acquires part replacement/repair data of the hydraulic excavator 10; and a malfunction prediction section 205 that predicts a malfunction probability of each part of the hydraulic excavator 10, based on the operation data acquired by the operation data acquisition section 201, the inspection data acquired by the inspection data acquisition section 202, and the part replacement/repair data acquired by the part replacement/repair data acquisition section 203.