Abnormality Diagnosing System For Mechanical Equipment
First Claim
1. An abnormality diagnosing system for a mechanical equipment, which detects sounds or vibrations generated by a mechanical equipment, analyzes thus detected signal and diagnoses an abnormality for a bearing or a bearing related member in the mechanical equipment, comprising:
- an envelope processor that obtains an envelope for the detected signal;
a FFT unit that transforms the envelope obtained by the envelope processor into a frequency spectrum;
a peak detector that smoothes the frequency spectrum obtained by the FFT unit by performing a moving average calculation process and detects peaks in the frequency spectrum; and
a diagnosis processor that diagnoses an abnormality based on the peaks in the frequency spectrum detected by the peak detector.
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Accused Products
Abstract
Provided are an envelope processor 103, for obtaining an envelope for a detected signal; a FFT unit 104, for converting the envelope into a frequency spectrum; a peak detector 105, for smoothing the frequency spectrum by calculating a moving average, for further performing smoothing and differentiation for the spectrum, and detecting, as peaks, frequency points at which a sign of a differential coefficient is changed from positive to negative, for extracting peaks having a predetermined threshold value or greater, and for sorting the extracted peaks and detecting upper peaks; and a diagnosis processor T, for diagnosing an abnormality based on the detected peaks.
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Citations
31 Claims
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1. An abnormality diagnosing system for a mechanical equipment, which detects sounds or vibrations generated by a mechanical equipment, analyzes thus detected signal and diagnoses an abnormality for a bearing or a bearing related member in the mechanical equipment, comprising:
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an envelope processor that obtains an envelope for the detected signal;
a FFT unit that transforms the envelope obtained by the envelope processor into a frequency spectrum;
a peak detector that smoothes the frequency spectrum obtained by the FFT unit by performing a moving average calculation process and detects peaks in the frequency spectrum; and
a diagnosis processor that diagnoses an abnormality based on the peaks in the frequency spectrum detected by the peak detector. - View Dependent Claims (2, 3, 4, 5, 6)
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7. An abnormality diagnosing system for a mechanical equipment, which detects sounds or vibrations generated by the mechanical equipment, analyzes thus detected signal, and diagnoses an abnormality of a bearing or a bearing related member of the mechanical equipment, comprising:
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a filter processor that extracts signals in a frequency band required for a diagnosis from the detected signal;
an envelope processor that obtains an envelope signal of the signal extracted by the filter processor;
a decimation processor that decimates the envelope signal obtained by the envelope processor;
a FFT operation processor that analyzes a frequency of the envelope signal obtained by the decimation processor through decimation; and
a diagnosis processor that diagnoses an abnormality based on analysis results obtained by the FFT operation processor. - View Dependent Claims (9, 10)
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8. An abnormality diagnosing system for a mechanical equipment, which detects sounds or vibrations generated by the mechanical equipment, analyzes thus detected signal, and diagnoses an abnormality of a bearing or of a bearing related member of the mechanical equipment, comprising:
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a sampling processor that samples the detected signal at a sampling frequency that is higher than a required sampling frequency in advance;
a filter processor that extracts a signal in a frequency band required for a diagnosis from the signal obtained by the sampling processor;
a decimation processor that decimates the signal extracted by the filter processor;
an envelope processor that obtains an envelope signal of the signal obtained by the decimation processor through decimation;
a FFT operation processor that analyzes a frequency of the envelope signal obtained by the envelope processor; and
a diagnosis processor that diagnoses an abnormality based on the analysis results obtained by the FFT operation processor.
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11. An abnormality diagnosing system for a mechanical equipment, which detects sounds or vibrations generated by mechanical equipment, analyzes thus obtained signal, and diagnoses an abnormality of a bearing or of a bearing related member of the mechanical equipment, comprising:
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an A/D converter that converts the obtained signal into a digital signal;
a digital filter processor that extracts a signal in a frequency band required for a diagnosis from the digital signal obtained by the A/D converter;
an envelope processor that obtains an envelope signal of the signal extracted by the digital filter processor;
an interpolation processor that performs zero-padding interpolation on the envelope obtained by the envelope processor in order to perform a fast Fourier transform at an arbitrary frequency resolution;
a FFT unit that performs a FFT on a signal obtained by the interpolation processor through the zero-padding interpolation; and
a diagnosis processor that diagnosing an abnormality based on a frequency spectrum obtained by the FFT unit. - View Dependent Claims (12, 13)
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14. An abnormality diagnosis apparatus, which diagnoses an abnormality while a vehicle is moving, comprising:
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a vibration sensor that detects vibrations of the vehicle;
a parameter value detection circuit that obtain one of dimensionless parameter values of a crest factor, a impulse factor, a shape factor and a kurtosis based on a waveform signal output by the vibration sensor; and
a comparison circuit that outputs a first voltage signal indicating that a dimensionless parameter value output by the parameter value detection circuit exceeds a predetermined reference, or a second voltage signal indicating that the dimensionless parameter value is equal to or lower than the predetermined reference, wherein an abnormality is detected based on the output of the comparison circuit. - View Dependent Claims (19)
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15. An abnormality diagnosis apparatus, which diagnoses an abnormality while a vehicle is moving, comprising:
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a vibration sensor that detects vibrations of the vehicle;
an operation circuit that employing a waveform signal output by the vibration sensor to obtains one of parameter values, either an RMS (a root mean square) or an absolute value average;
a peak detection circuit that obtains a peak value of the waveform signal; and
a comparison circuit that;
compares a value which is a constant times of the parameter value with the peak value output by the peak detection circuit, and in accordance with the comparison result, outputs a first voltage signal, which indicates that a dimensionless parameter value obtained as a ratio of the peak value to the parameter value exceeds a predetermined reference, or outputs a second voltage signal, which indicates that the dimensionless parameter is equal to or lower than the predetermined reference wherein an abnormality is detected based on the output of the comparison circuit. - View Dependent Claims (16, 17, 18)
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20. An abnormality diagnosis apparatus, for a mechanical apparatus that includes a plurality of parts having different vibration properties, comprising:
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a sensor signal processor that samples a signal output by a vibration sensor which detects vibrations of the mechanical apparatus; and
a diagnosis processor that performs an abnormality diagnosis based on a sampled vibration data by the sensor signal processor, wherein the diagnosis processor sequentially samples vibration data from the sensor signal processor and divides the vibration data into intervals for predetermined cycles;
processes the divided vibration data for one interval as vibration data for a diagnosis of parts having a first vibration property; and
processes data obtained by such that the data of a predetermined period of time in the preceding interval is added to a head of the vibration data for one interval as vibration data of the abnormality diagnosis for a member having a second vibration property. - View Dependent Claims (28)
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21. An abnormality diagnosis apparatus, for axle bearings and wheels of a railway vehicle, comprising:
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a sensor signal processor that samples a signal output by a vibration sensor which detects vibrations of axle bearings and wheels; and
a diagnosis processor that performs abnormality diagnoses for the axle bearings and wheels based on a sampled vibration data obtained by the sensor signal processing, wherein the diagnosis processor sequentially samples the vibration data from the sensor signal processor and divides the vibration data into intervals for predetermined cycles;
processes the divided vibration data for one interval as vibration data for a bearing diagnosis; and
processes data obtained by such that data of a predetermined period of time in the preceding interval is added to a head of the vibration data for one interval as vibration data of the abnormality diagnosis for the wheel. - View Dependent Claims (22, 23, 24, 27)
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25. An abnormality diagnosis apparatus, for a mechanical apparatus comprising a plurality of parts having different vibration properties, comprising:
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a sensor signal processor that samples a signal output by a vibration sensor which detects vibrations of the mechanical apparatus; and
a diagnosis processor that performs an abnormality diagnosis based on a sampled vibration data by the sampled sensor signal processor, wherein the diagnosis processor sequentially samples the vibration data from the sensor signal processor, and converts the vibration data into two kind of data having two different sampling frequencies or two different sampling lengths, wherein one is for diagnosis of parts having a first vibration property, and the other is for diagnosis of parts having a second vibration property.
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26. An abnormality diagnosis apparatus, for axle bearings and wheels of a railway vehicle, comprising:
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a sensor signal processor that samples a signal output by a vibration sensor which detects vibrations of the axle bearing and wheels of a railway vehicle; and
a diagnosis processor that performs an abnormality diagnosis based on a sampled vibration data by the sensor signal processor, wherein the diagnosis processor sequentially samples the vibration data from the sensor signal processor, and converts the vibration data into two kinds of data having two different sampling frequencies or two different sampling lengths, wherein one is for an axle bearing diagnosis and the other is for a wheel diagnosis.
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29. An abnormality diagnosis apparatus, for a mechanical apparatus including rotary or sliding parts, comprising:
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an AD converter that converts an analog signal output by a vibration sensor which detects vibrations of the mechanical apparatus into a digital signal; and
a diagnosis processor that performs a Fourier transform for the digital signal obtained by the AD converter; and
performs an abnormality diagnosis based on the results thereof,wherein, during in the Fourier transform process, the diagnosis processor extends a data bit width of the digital signal obtained by the AD converter more than a resolution of the AD converter.
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30. An abnormality diagnosis apparatus, for a mechanical apparatus that includes rotary or sliding parts, comprising:
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an AD converter that converts an analog signal output by a vibration sensor that detects vibrations of the mechanical apparatus into a digital signal; and
a diagnosis processor that performs a Fourier transform for the digital signal obtained by the AD converter, and performs an abnormality diagnosis based on the results thereof, wherein, during the Fourier transform process, a resolution of the AD converter is regard as one bit, and the diagnosis processor expands this resolution to a predetermined data bit width of two or more bits.
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31. An abnormality diagnosis apparatus, for a mechanical apparatus that includes rotary or sliding parts, comprising:
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a comparator that compares a voltage of an analog signal received from a vibration sensor that detects vibrations of the mechanical apparatus with a reference voltage, and for outputting a two-valued signal indicating that the voltage of the analog signal is either higher or lower than the reference voltage, wherein the diagnosis processor expands the signal of the comparator to a predetermined data bit width, and performs a Fourier transform process.
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Specification