Condition-Based Maintenance Using Wavelet Sensor Profiles
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Solution Overview
Problem
Existing condition-based maintenance approaches face challenges in accurately predicting system aging and detecting malfunctions due to noise in sensor data and reliance on manual monitoring, leading to inefficient maintenance and potential over-maintenance costs.
Innovation Solution
A method and apparatus utilizing Hurst coefficients from wavelet transform analysis of sensor data to create a linear profile, which extracts energy spectra, calculates slope and intercept, and uses T2 statistics to monitor for malfunctions, enabling early anomaly detection and predictive maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct condition monitoring is used to monitor properties directly related to malfunctions, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces indirect condition monitoring parameters (vibration, temperature, oil residue) as intermediaries to detect malfunctions. Instead of directly monitoring the malfunction itself, the system monitors related physical quantities that change in response to system degradation, thereby reducing measurement complexity while maintaining detection capability
Solution Approach 2:
The patent replaces manual visual inspection with automated sensor-based monitoring systems. Sensors automatically collect data on vibration, temperature, and other physical parameters, eliminating the need for human operators to manually examine system components, thus reducing operational complexity while improving measurement precision
2Device complexity
If manual monitoring of sensor data is used, then device complexity is reduced, but loss of information increases due to environmental factors and worker ability differences
Solution Approach 1:
The patent implements an automated monitoring system that self-manages sensor data collection, processing, and analysis without human intervention. The system automatically stores sensor data in a database, processes the data through algorithms, and generates maintenance recommendations, eliminating variability introduced by different workers and environmental conditions
Solution Approach 2:
The patent establishes a closed-loop feedback system where sensor data is continuously collected, analyzed, and used to update maintenance decisions. The system provides feedback on system health status and predicts future failures, enabling proactive maintenance while maintaining consistent information quality across different operating conditions
3Ease of operation
If time-scheduled maintenance is used to replace parts unconditionally, then ease of operation is improved, but loss of substance increases due to over-maintenance
Solution Approach 1:
The patent transitions from fixed time-based maintenance parameters to condition-based parameters. Instead of replacing parts at predetermined time intervals, the system monitors actual system conditions (vibration, temperature, oil quality) and schedules maintenance based on measured degradation levels, preventing unnecessary replacements while maintaining reliability
Solution Approach 2:
The patent performs preliminary analysis of sensor data to predict future failures before they occur. By analyzing trends in vibration, temperature, and other parameters, the system identifies components that will fail in the near future and schedules maintenance proactively, avoiding both premature replacement and unexpected failures
4Reliability
If condition based maintenance with real-time sensor monitoring is used, then reliability is improved by preventing malfunctions, but device complexity increases
Solution Approach 1:
The patent divides the monitoring system into distinct functional modules: sensor data collection, data storage, data processing, and maintenance decision support. Each module performs a specific function and can be independently configured or replaced, reducing overall system complexity while maintaining comprehensive monitoring capability
Solution Approach 2:
The patent employs multi-functional sensors and processing algorithms that can monitor multiple system parameters simultaneously. The same sensor infrastructure supports vibration analysis, temperature monitoring, and other condition assessments, reducing the number of separate systems needed while improving reliability through comprehensive monitoring
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach effectively minimizes unnecessary costs and time by accurately determining system anomalies and predicting malfunctions, thereby enhancing maintenance efficiency and reducing the likelihood of system failures.
Implementation Method 1
extracting an energy spectrum as feature values by applying a wavelet transform on the collected sensor data
Data Source
AI summary
Disclosed are a condition based preventive maintenance apparatus and method for a large operation system. The condition based preventive maintenance apparatus for a large operation system comprises: a collection part for collecting sensor data from a plurality of sensors installed in a system; a feature extraction part for wavelet-transforming the collected sensor data and extracting an energy spectrum as a feature value; a calculation part for calculating a slope and an intercept of the extracted feature value; and a monitoring part for monitoring whether the system is broken or not using the calculated slope and intercept.