Direction Change Valve Failure Prediction System and Method, and Direction Change Valve Failure Inspection System and Method
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Solution Overview
Problem
Existing methods for predicting failures in direction change valves are inadequate, leading to incorrect diagnosis of cylinder malfunctions and potential factory shutdowns, as they rely on simplistic metrics like the number of opening/closing operations rather than statistical degradation indexes.
Innovation Solution
A direction change valve failure prediction system that repeatedly detects operation times of multiple direction change valves, calculates statistical degradation indexes such as mean, standard deviation, and skewness from the operation time data, and determines which valves are likely to fail based on sequenced degradation index values and scoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simplistic metrics like number of opening/closing operations are used for failure prediction, then the prediction system is simple to implement, but the prediction accuracy is low leading to incorrect diagnosis
Solution Approach 1:
The patent transforms the failure prediction approach by changing from simple count metrics to statistical parameters (mean, standard deviation, skewness, kurtosis) derived from operation time distributions. This parameter transformation enables more accurate characterization of valve degradation states while maintaining computational feasibility through standardized statistical measures.
Solution Approach 2:
The patent replaces simple mechanical counting mechanisms with statistical analysis systems that process operation time data. By substituting basic counting with distribution-based statistical evaluation, the system achieves higher prediction accuracy while remaining implementable through standard data processing techniques.
2Measurement precision
If statistical degradation indexes are calculated from operation time data, then the failure prediction accuracy is improved, but the data processing complexity increases
Solution Approach 1:
The patent segments the operation time data into distinct operational cycles and calculates statistical indexes for each segment. This segmentation approach allows systematic computation of mean, standard deviation, skewness, and kurtosis for multiple operation cycles, making the complex statistical processing manageable and organized.
Solution Approach 2:
The patent introduces statistical degradation indexes as intermediary parameters between raw operation time data and failure prediction outcomes. These indexes (mean, standard deviation, skewness, kurtosis) serve as intermediate computational steps that transform raw data into meaningful predictive indicators, simplifying the overall analysis process.
3Reliability
If multiple direction change valves are monitored simultaneously, then the overall system reliability is improved, but the inspection time and resources increase
Solution Approach 1:
The patent performs preliminary statistical analysis of operation time data to identify valves with abnormal degradation patterns before actual failure occurs. By calculating degradation indexes and comparing them against thresholds in advance, the system prioritizes inspection resources for high-risk valves, reducing overall inspection time while maintaining system reliability.
Solution Approach 2:
The patent implements a feedback mechanism where degradation index results from previous monitoring cycles inform subsequent inspection priorities. Valves showing abnormal statistical patterns receive heightened attention in next inspection cycles, creating an adaptive monitoring strategy that optimizes resource allocation across multiple valves over time.
Data Source
AI summary
A direction change valve failure prediction system includes: a data obtainer, degradation index value calculator, and a determiner. The obtainer is configured to repeatedly detect operation times of direction change valves over an equipment operation elapsed time to obtain operation time data of each valve. The valves are configured to communicate with a cylinder including a piston rod to change a direction a working fluid is supplied to the cylinder to change rod operation direction. The calculator is configured to calculate degradation index values of statistical degradation indexes representing a failure of the valves based on the time data. The determiner is configured to sequence the index values calculated for the valves according to size, to give scores to valves of higher values within or beyond a predetermined range among the sequenced index values, and to determine a valve expected to fail based on the score sum.