Engine Bearing Damage Detection Using Knock Sensor FFT Analysis
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Solution Overview
Problem
Current methods for detecting bearing damage in engines using vibration signals are prone to false detection due to increased vibration in both knocking and bearing damage frequency bands, and require significant time and expense to select suitable band-pass filters for each engine, reducing detection performance.
Innovation Solution
A system and method that performs Fast Fourier Transform on vibration signals across the entire frequency band detectable by a knocking sensor, comparing transformed frequencies with preset exclusion conditions to exclude irrelevant signals and prevent false detection, thereby enhancing accuracy and reducing the need for band-pass filter selection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If only the vibration signal in the bearing damage frequency band is monitored using a band-pass filter, then the detection process is simplified, but false detection occurs when knocking signals increase vibration in both knocking and bearing damage frequency bands
Solution Approach 1:
The frequency spectrum is segmented into multiple bands: knocking frequency band (first frequency band) and bearing damage frequency band (second frequency band). By separately analyzing vibration signals in each band and comparing their relative magnitudes, the system can distinguish between knocking-induced vibrations and actual bearing damage, preventing false detection while maintaining detection simplicity.
2Ease of operation
If band-pass filter is used for detecting bearing damage, then the detection method is simplified, but neighboring frequency components are also included reducing detection performance
Solution Approach 1:
Instead of using a broad band-pass filter that includes neighboring frequency components, the system applies localized frequency band analysis with specific frequency ranges: knocking frequency band (e.g., 5-15 kHz) and bearing damage frequency band (e.g., 1-5 kHz). This localized approach ensures that only relevant frequency components are analyzed, improving detection precision while keeping the method simple through defined frequency thresholds.
3Measurement precision
If band-pass filter selection is performed for each engine, then detection accuracy is optimized, but significant time and expense are required
Solution Approach 1:
The system uses a universal detection method that applies the same frequency band analysis approach (knocking frequency band and bearing damage frequency band comparison) across all engine types. This eliminates the need for engine-specific band-pass filter selection while maintaining high detection accuracy, significantly reducing the time and expense associated with customization.
4Productivity
If vibration signal in bearing damage frequency band is monitored alone, then the monitoring process is simplified, but false detection occurs due to strong knocking signals
Solution Approach 1:
The system continuously monitors vibration signals in both knocking frequency band and bearing damage frequency band, comparing the relative magnitudes of these bands. When vibration in the bearing damage band increases, the system checks whether corresponding vibration increase occurs in the knocking band. This feedback mechanism allows the system to distinguish between knocking-induced vibrations (both bands increase) and actual bearing damage (only bearing damage band increases), preventing false detection while maintaining monitoring efficiency.
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 prevents false detection of bearing damage by considering the entire frequency band, improving detection performance and reducing the time and expense associated with selecting suitable filters for each engine.
Implementation Method 1
a vibration signal output from a knocking sensor installed in an engine
Implementation Method 2
which performs Fast Fourier Transform for a signal in an entire frequency band detectable by the knocking sensor
Data Source
AI summary
A method for detecting damage to a bearing of an engine using a knocking sensor includes a data storing step, which stores a vibration signal output from the knocking sensor in a data storing unit, a by-frequency amplitude calculating step, which performs Fast Fourier Transform (FFT) for the vibration signal and calculates an amplitude for each frequency, a detection frequency integrating step, which obtains a detection frequency integration value by adding all amplitudes of detection frequencies, a noise determining step, which determines whether the vibration signal is the vibration signal irrelevant to damage to the bearing by determining whether exclusion frequencies correspond to a preset condition, a counter increasing step, which increases a damage counter, when the detection frequency integration value is greater than a preset damage threshold, and a damage confirming step, which confirms damage to the bearing, when the damage counter equals or exceeds a preset confirmation counter.