Physical Quantity Sensor Failure Prediction Using Multi-Level Signals
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Solution Overview
Problem
Existing sensor failure prediction systems for physical quantity sensors, such as vibration type gyro sensors, cannot detect the state leading up to failure in advance, as they only output signals indicating normality or abnormality without providing intermediate prediction information.
Innovation Solution
A sensor failure prediction system that includes a processor and memory to analyze signal information from a physical quantity sensor with a vibrator element, using reference information to output prediction information on a stepwise or continuous state until the sensor fails, allowing for early detection of impending failure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only two types of signals (normal/abnormal) are output, then the system is simple, but the ability to detect intermediate failure states is lost
Solution Approach 1:
The failure detection range is segmented into multiple stages (normal state, intermediate failure states, and failure state) with different threshold values. The processor compares the leakage signal amplitude against multiple thresholds to determine whether the sensor is in a normal state, intermediate failure state, or failure state, thereby providing detailed failure progression information.
Solution Approach 2:
The system changes the parameter of signal output from binary (normal/abnormal) to multi-level (normal/intermediate failure/failure) by introducing multiple threshold values for comparison. This allows the system to provide graded information about the sensor's health status without significantly increasing system complexity.
2Reliability
If intermediate failure states are detected, then maintenance can be scheduled in advance, but the system complexity increases
Solution Approach 1:
The system performs preliminary detection of intermediate failure states before complete sensor failure occurs. By monitoring the leakage signal amplitude and comparing it against multiple thresholds, the system can identify deteriorating trends and predict impending failures, allowing maintenance to be scheduled in advance before actual failure disrupts operations.
Solution Approach 2:
The system continuously monitors the leakage signal amplitude and provides feedback about the sensor's health status through multiple output signals indicating different failure stages. This feedback mechanism enables real-time assessment of sensor condition and supports proactive maintenance decision-making.
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
Enables the detection of sensor failure states in advance, reducing the risk of operational disruptions by providing timely prediction information, which can trigger maintenance or adjustments before actual failure occurs.
Implementation Method 1
a vibrator element which is driven and vibrates by a drive signal and outputs a detection signal based on a physical quantity
Data Source
AI summary
A sensor failure prediction system is a sensor failure prediction system that predicts a failure of a physical quantity sensor including a vibrator element which is driven and vibrates by a drive signal and outputs a detection signal based on a physical quantity, and includes a memory that stores reference information on a reference value of the drive signal or the detection signal, and a processor that outputs prediction information on a stepwise or continuous state until the physical quantity sensor fails, based on signal information on a measurement value of the drive signal or the detection signal and the reference information.