Vibration Bias Analysis for Device Degradation Estimation
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Solution Overview
Problem
Conventional methods for estimating a device's state using sensor data are limited by the need for high sampling frequencies and computing power, making them inconvenient for devices with varying vibration loads, as they require sophisticated sensors and processors for accurate frequency analysis.
Innovation Solution
An information processing system that uses a detection apparatus with a low sampling frequency sensor and a microcontroller-based information processing apparatus to estimate device degradation by calculating the bias and temporal stability of vibration data, eliminating the need for high-frequency analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If frequency analysis is performed to accurately estimate device state, then measurement precision is improved, but device complexity increases due to high sampling frequency sensors and powerful calculators
Solution Approach 1:
The patent extracts only the essential feature needed for degradation estimation - the standard deviation of vibration magnitude - while discarding the complex frequency analysis process. This allows accurate state estimation without requiring high sampling frequency sensors or powerful processors, thus reducing device complexity while maintaining measurement precision
Solution Approach 2:
The invention replaces expensive, high-performance sensors and processors with lower-cost alternatives that have lower sampling frequencies. By using simplified evaluation metrics (standard deviation rather than frequency spectrum), the system achieves adequate measurement precision with less sophisticated, more economical components
2Measurement precision
If high sampling frequency sensors are used for frequency analysis, then measurement precision is improved, but loss of energy increases due to higher data processing requirements
Solution Approach 1:
The patent extracts only the magnitude information and calculates its standard deviation, eliminating the need for computationally intensive frequency analysis. This reduction in processing complexity directly lowers energy consumption while maintaining adequate measurement precision for degradation estimation
Solution Approach 2:
Instead of performing complete frequency analysis with high sampling frequency, the patent applies partial action by only analyzing the magnitude envelope and calculating its statistical properties. This partial analysis approach consumes less energy while providing sufficient information for device state estimation
3Device complexity
If conventional vibration threshold methods are used, then device complexity is reduced, but measurement precision deteriorates due to inability to account for varying load conditions
Solution Approach 1:
The patent applies preliminary action by calculating the standard deviation of vibration magnitude over a period of time before making degradation assessment. This statistical preprocessing of the data provides a more robust metric that accounts for varying operating conditions, improving measurement precision while keeping the overall system relatively simple
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 improves the convenience of estimating device state by allowing the use of lower-cost sensors and processors, enhancing the accuracy and convenience of degradation estimation without requiring complex frequency analysis.
Implementation Method 1
detect vibration of the device by a sensor
Data Source
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AI summary
An information processing system comprises: an acquisition means configured to acquire vibration of a device that vibrates during operation, as time-series data of a physical quantity A indicated by a plurality of axis components in a three-dimensional coordinate system; a calculation means configured to calculate a first evaluation value E indicating a degree of bias of the vibration of the device between axes, based on the time-series data of the physical quantity A; and an estimation means configured to estimate a degradation level G of the device based on the first evaluation value E.