Rotating body inspection device, rotating body inspection method, and program

Abstract

To provide a technique for detecting abnormal sound having a relatively small amplitude in a rotating body such as a motor.SOLUTION: A rotating body inspection device includes a frequency spectrum generation unit, a cepstrum generation unit, an order cepstrum generation unit, and an abnormal sound detection unit. The frequency spectrum generation unit generates a frequency spectrum for each measurement section in time series from vibration data that is data of vibration for each rotation speed of the rotating body. The cepstrum generation unit generates a cepstrum from the frequency spectrum for each measurement section. The order cepstrum generation unit generates an order cepstrum that is data obtained by converting a quefrency of the cepstrum into an order for each measurement section. The abnormal sound detection unit detects abnormal sound of the rotating body based on the order cepstrum for each measurement section.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present disclosure relates to a rotating body inspection device, a rotating body inspection method, and a program. [Background technology]

[0002] Conventionally, systems have been used to detect abnormal noise from rotating bodies such as motors. For example, a system has been proposed in which a measurement sound is subjected to a Discrete Fourier Transform (DFT) to generate a rotation speed signal in the frequency domain, and the frequency of this rotation speed signal is converted into an order that is a multiple of one rotation of the motor to detect abnormal noise based on rotation order data (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2020-064286 Summary of the Invention [Problem to be solved by the invention]

[0004] The above-described conventional technology has a problem in that it is difficult to detect abnormal noises that are harsh to the ear despite having a relatively small amplitude, for example, abnormal noises whose amplitude increases and decreases periodically.

[0005] The present disclosure provides a technique for detecting abnormal noise of a relatively small amplitude in a rotating body such as a motor. [Means for solving the problem]

[0006] A rotating body inspection device according to one aspect of the present disclosure includes a frequency spectrum generation unit, a cepstrum generation unit, an order cepstrum generation unit, and an abnormal sound detection unit. The frequency spectrum generation unit generates a frequency spectrum for each time-series measurement interval from vibration data, which is vibration data for each rotation speed of the rotating body. The cepstrum generation unit generates a cepstrum from the frequency spectrum for each measurement interval. The order cepstrum generation unit generates an order cepstrum, which is data obtained by converting the quefrency of the cepstrum into an order, for each measurement interval. The abnormal sound detection unit detects abnormal sounds from the rotating body based on the order cepstrum for each measurement interval. [Effects of the Invention]

[0007] According to the present disclosure, it is possible to detect abnormal noise of a relatively small amplitude in a rotating body such as a motor. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of an abnormal noise according to an embodiment of the present disclosure. [Figure 2] FIG. 2 is a diagram illustrating a configuration example of a rotating body inspection system according to an embodiment of the present disclosure. [Figure 3] FIG. 3 is a diagram illustrating an example of a processing procedure of the abnormal sound detection processing according to the embodiment of the present disclosure. [Figure 4] FIG. 4 is a diagram illustrating an example of data according to an embodiment of the present disclosure. [Figure 5] FIG. 5 is a diagram illustrating an example of acquiring vibration data for each measurement section according to an embodiment of the present disclosure. [Figure 6] FIG. 6 is a diagram illustrating an example of a frequency spectrum according to an embodiment of the present disclosure. [Figure 7] FIG. 7 is a diagram illustrating an example of a setting for a discrete Fourier transform according to an embodiment of the present disclosure. [Figure 8] FIG. 8 is a diagram illustrating an example of a cepstrum according to an embodiment of the present disclosure. [Figure 9]FIG. 9 is a diagram illustrating an example of rotation speed data for each measurement section according to the embodiment of the present disclosure. [Figure 10] FIG. 10 is a diagram illustrating an example of an order table according to an embodiment of the present disclosure. [Figure 11] FIG. 11 is a diagram illustrating an example of setting a table of degrees according to an embodiment of the present disclosure. [Figure 12] FIG. 12 is a diagram illustrating an example of an order cepstrum according to an embodiment of the present disclosure. [Figure 13] FIG. 13 is a diagram illustrating an example of detection of abnormal noise according to an embodiment of the present disclosure. [Figure 14] FIG. 14 is a diagram illustrating an example of settings for abnormal sound detection according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. The description will be given in the following order. In the following embodiments, the same components are designated by the same reference numerals, and redundant description will be omitted. 1. Abnormal noise 2. Embodiment

[0010] (1. Abnormal noise) The abnormal noise that is the detection target of the rotating body inspection device of the present disclosure will be described with reference to FIG.

[0011] FIG. 1 is a diagram showing an example of an abnormal noise according to an embodiment of the present disclosure. The figure shows a waveform of vibration of a rotating body such as a motor. The vertical axis of the figure represents amplitude [dB]. The horizontal axis of the figure represents order. Here, order is a multiple of the frequency of the vibration of the rotating body per one rotation of the motor. The waveform in the figure is obtained by performing a discrete Fourier transform on the vibration data of the rotating body to generate a rotation speed signal in the frequency domain, and then converting the horizontal axis into order. Analysis performed by changing the frequency of the vibration of a rotating body or the like into order in this way is called order ratio analysis.

[0012] As shown in Figure 1, waveforms with periodic increases in amplitude in the order direction are observed. Although these waveforms do not have large amplitudes, the periodic increases in amplitude result in harsh noises. The waveforms of these noises are difficult to detect because the increase in amplitude is lower than the other peaks. The rotating body inspection device of the present disclosure detects the abnormal noises shown in the figure.

[0013] (2. Embodiment) [Configuration of Rotating Body Inspection System] 2 is a diagram showing a configuration example of a rotating body inspection system according to an embodiment of the present disclosure. The figure is a block diagram showing a configuration example of a rotating body inspection system 1. The rotating body inspection system 1 includes a measurement unit 10, a control unit 20, and a rotating body inspection device 30.

[0014] The measurement unit 10 drives a rotating body to generate sound and vibration data and rotational speed data. The measurement unit 10 includes a rotating body drive device 11, a sound vibration sensor 12, and a tachometer 13. The rotating body drive device 11 drives the rotating body (motor) to be inspected. The sound vibration sensor 12 generates data on sound or vibration from the rotating body. The tachometer 13 detects the rotational speed.

[0015] The control unit 20 controls the measurement unit 10. The control unit 20 includes a drive control unit 21 and a measurement control unit 22. The drive control unit 21 controls the rotating body drive device 11 of the measurement unit 10. The measurement control unit 22 controls the sound vibration sensor 12 and tachometer 13 of the measurement unit 10. The measurement control unit 22 also outputs the sound, vibration data, and rotational speed data output from the sound vibration sensor 12 and tachometer 13 to the rotating body inspection device 30.

[0016] The rotating body inspection device 30 detects the abnormal noise described above and includes a data acquisition unit 31, a frequency spectrum generation unit 32, a cepstrum generation unit 33, an order cepstrum generation unit 34, an abnormal noise detection unit 35, a display unit 36, and a setting management unit 37.

[0017] The data acquisition unit 31 acquires sound, vibration data, and rotation speed data via the control unit 20. The acquired sound, vibration data, and rotation speed data are input to the frequency spectrum generation unit 32. The rotation speed data is also input to the order cepstrum generation unit 34. Details of the sound, vibration data, and rotation speed data will be described later. Note that hereinafter, "sound, vibration data" will be referred to as "vibration data."

[0018] The frequency spectrum generation unit 32 generates a frequency spectrum. This frequency spectrum generation unit 32 generates a frequency spectrum from vibration data, which is data on vibrations at each rotation speed of a rotating body. The frequency spectrum can be generated by performing a discrete Fourier transform on the vibration data. The frequency spectrum generation unit 32 generates a frequency spectrum for each measurement interval in a time series. The generation of the frequency spectrum will be described in detail later.

[0019] The cepstrum generation unit 33 generates a cepstrum from the frequency spectrum generated by the frequency spectrum generation unit 32. The cepstrum can be generated by treating the frequency spectrum as one signal and performing a discrete Fourier transform. The cepstrum generation unit 33 generates a cepstrum for each measurement interval. The generation of the cepstrum will be described in detail later.

[0020] The order cepstrum generating unit 34 generates an order cepstrum, which is data obtained by converting the quefrency of the cepstrum generated by the cepstrum generating unit 33 into an order. The order cepstrum generating unit 34 generates an order cepstrum for each measurement interval. The generation of the order cepstrum will be described in detail later.

[0021] The abnormal sound detection unit 35 detects abnormal sounds from the rotating body based on the order cepstrum generated by the order cepstrum generation unit 34. The abnormal sound detection unit 35 can detect abnormal sounds based on a predetermined threshold value. Details of the detection of abnormal sounds will be described later.

[0022] The setting management unit 37 manages setting values ​​for the processing of the frequency spectrum generation unit 32 and the order cepstrum generation unit 34. The setting management unit 37 outputs analysis setting values ​​to the frequency spectrum generation unit 32 and the order cepstrum generation unit 34. The setting management unit 37 also supplies a threshold value to the abnormal sound detection unit 35.

[0023] The display unit 36 ​​displays the results of abnormal sound detection by the abnormal sound detection unit 35, a parameter setting screen, and the like.

[0024] [Abnormal noise detection processing] 3 is a diagram showing an example of a processing procedure for abnormal sound detection processing according to an embodiment of the present disclosure. The figure is a flowchart showing an example of a processing procedure for abnormal sound detection processing in the rotating body inspection system 1. The processing procedure in the figure will be described in order.

[0025] First, the measuring unit 10 drives the rotating body under the control of the control unit 20. Also, the sound vibration sensor 12 and the tachometer 13 perform measurements to generate vibration data and rotation speed data, respectively (step S101). This vibration data and rotation speed data are output to the rotating body inspection device 30. This vibration data and rotation speed data will be explained using FIG. 4.

[0026] FIG. 4 is a diagram showing an example of data according to an embodiment of the present disclosure. The figure shows an example of vibration data and rotational speed data measured by the measurement unit 10. The upper part of the figure shows vibration data. In this figure, the horizontal axis represents time, and the vertical axis represents amplitude. As such, the vibration data is data showing the change over time in the amplitude of vibration of the rotating body. Furthermore, the lower part of the figure shows rotational speed data. In this figure, the horizontal axis represents time, and the vertical axis represents rotational speed. The figure shows data when the rotating body is decelerating. As such, the rotational speed data is data showing the change over time in the rotational speed of the rotating body.

[0027] Next, the data acquisition unit 31 of the rotating body inspection device 30 acquires data (vibration data) of the measurement section (step S102 in FIG. 3). The acquisition of this data will be described with reference to FIG.

[0028] FIG. 5 is a diagram showing an example of acquiring vibration data for each measurement interval according to an embodiment of the present disclosure. The vibration data is time-series data. To perform a discrete Fourier transform on this vibration data, data from any measurement interval is extracted. This measurement interval can be determined based on the frequency resolution desired for analysis. Adjacent measurement intervals can also be allowed to overlap. This is to prevent data loss at the ends of the measurement intervals. Data (t1-tn) from this measurement interval is extracted sequentially. The overlap rate between measurement intervals is output from the setting management unit 37.

[0029] Next, the frequency spectrum generation unit 32 generates a frequency spectrum (step S103 in FIG. 3). Specifically, the frequency spectrum generation unit 32 performs a discrete Fourier transform on the vibration data for each measurement interval to generate a frequency spectrum. The generated frequency spectrum will be described with reference to FIGS. 6 and 7.

[0030] FIG. 6 is a diagram showing an example of a frequency spectrum according to an embodiment of the present disclosure. This diagram shows an example of a frequency spectrum generated by the frequency spectrum generation unit 32. The horizontal axis of this diagram represents frequency. The horizontal axis is a linear scale. The vertical axis of this diagram represents amplitude. In this way, the frequency spectrum is obtained by decomposing a time signal with frequency on the horizontal axis and signal strength on the vertical axis. The frequency spectrum in this diagram represents the frequency spectrum of one measurement interval.

[0031] FIG. 7 is a diagram illustrating an example of discrete Fourier transform settings according to an embodiment of the present disclosure. This diagram illustrates an example of discrete Fourier transform settings in the frequency spectrum generation unit 32. The upper part of the diagram illustrates discrete Fourier transform parameters. These parameters include frame length, overlap rate, window function, and output unit. The frame length represents the number of data points included in the measurement interval. The overlap rate represents the overlap rate between measurement intervals. The window function represents the type of window processing function used in preprocessing. The output unit represents the amplitude unit of the frequency spectrum. The lower part of the diagram illustrates an example of a discrete Fourier transform parameter setting screen. This setting screen is displayed on the display unit 36.

[0032] Next, the cepstrum generation unit 33 generates a cepstrum (step S104 in FIG. 3). Here, the cepstrum is a signal obtained by treating the frequency spectrum as a signal and performing a discrete Fourier transform. The cepstrum generation unit 33 regards the frequency spectrum generated by the frequency spectrum generation unit 32 as a single signal and performs the above-mentioned discrete Fourier transform to generate a cepstrum. The generated cepstrum will be described with reference to FIG. 8.

[0033] 8 is a diagram illustrating an example of a cepstrum according to an embodiment of the present disclosure. The figure shows an example of a cepstrum generated by the cepstrum generating unit 33. The horizontal axis of the figure represents quefrency, and the vertical axis represents amplitude.

[0034] Next, the order cepstrum generating unit 34 generates an order cepstrum (step S105 in FIG. 3). Here, the order cepstrum is data obtained by converting the quefrency of the cepstrum into an order. The generation of this order cepstrum will be described with reference to FIGS. 9 to 12.

[0035] 9 is a diagram illustrating an example of rotation speed data for each measurement interval according to an embodiment of the present disclosure. The order cepstrum generation unit 34 extracts rotation speeds (V1-Vn) for each measurement interval that is the same as the measurement interval in FIG. 5. Note that adjacent measurement intervals overlap in the same way as in FIG. 5. The order cepstrum generation unit 34 calculates the average value of the rotation speed data for each measurement interval.

[0036] Next, the order cepstrum generating unit 34 converts the horizontal axis from quefrency to order for the cepstrum data shown in Fig. 8. This conversion to order can be performed based on the following equation. O n =F up / ((M max -M)×V n ) where O n represents the degree. F up represents the upper limit frequency in the discrete Fourier transform shown in Figure 7. Also, M max represents the number of cepstrum data. Also, M represents the cepstrum data number. Here, M=1,2,3,...,M max Also, V n represents the rotation speed. The average value of the rotation speed data described above can be applied to this rotation speed. The order cepstrum generator 34 can generate a table of orders by converting the quefrencies into orders.

[0037] 10 is a diagram showing an example of an order table according to an embodiment of the present disclosure. The figure shows an example of an order table and amplitude values ​​generated by the above-mentioned calculation formula. The order table (first column) in the figure shows the above-mentioned O n The order cepstrum generating unit 34 performs the following process.

[0038] First, the order cepstrum generation unit 34 rounds off the value of the order table to one significant digit based on an arbitrarily set number of digits of the order resolution (one decimal place in FIG. 10 ) to align the number of digits. Next, the order cepstrum generation unit 34 generates the amplitude value (third column) of the cepstrum corresponding to the order table. If multiple amplitude values ​​exist for the same order, the order cepstrum generation unit 34 selects the maximum value as the amplitude value (201 in FIG. 10 ). If no amplitude value exists for the order, the order cepstrum generation unit 34 selects the amplitude value of the immediately preceding order as the amplitude value of the order (202 in FIG. 10 ). The order cepstrum generation unit 34 repeats this process up to the specified maximum order (value “200.0” in FIG. 10 ). By deleting calculations after the maximum order, the amount of calculations can be reduced.

[0039] 11 is a diagram showing an example of setting an order table according to an embodiment of the present disclosure. The figure shows an example of setting an order table in the order cepstrum generation unit 34. The upper side of the figure shows parameters of the order table. These parameters include the number of digits of order resolution and the maximum order. The lower side of the figure shows an example of a setting screen for the parameters of the order table. This screen is displayed on the display unit 36.

[0040] Fig. 12 is a diagram showing an example of an order cepstrum according to an embodiment of the present disclosure. The figure shows an example of an order cepstrum generated by the order cepstrum generating unit 34. The order cepstrum in the figure is a graph generated based on the orders (order table with the same number of digits) and amplitude values ​​(third column) in Fig. 10. Such an order cepstrum is generated for each measurement interval.

[0041] Next, the rotating body inspection device 30 determines whether processing has been performed for all measurement sections (step S106 in FIG. 3). If processing has not been performed for all measurement sections (step S106 in FIG. 3, No), the rotating body inspection device 30 sets the next measurement section and proceeds to processing in step S102 in FIG. 3. On the other hand, if processing has been performed for all measurement sections (step S106 in FIG. 3, Yes), the order cepstrum generation unit 34 generates a representative value for each measurement section (step S107 in FIG. 3). Here, the representative value is the average or maximum value of the amplitude for each order of the order cepstrum. The order cepstrum generation unit 34 generates a final order cepstrum based on the representative value generated for each measurement section. This final order cepstrum corresponds to the order cepstrum for all measurement sections. In this final order spectrum, a peak (211 in FIG. 12) appears at the same order as the period of the increase in the amplitude of the abnormal noise.

[0042] Next, the abnormal sound detection unit 35 detects an abnormal sound from the final order cepstrum (step S108), and ends the process. Detection of an abnormal sound by the abnormal sound detection unit 35 will be described with reference to FIGS.

[0043] 13 is a diagram showing an example of abnormal sound detection according to an embodiment of the present disclosure. The figure shows an example of abnormal sound detection in the abnormal sound detection unit 35. The abnormal sound detection unit 35 detects abnormal sounds based on the abnormal sound detection threshold shown in the figure. Specifically, the abnormal sound detection unit 35 sets a threshold for all or part of the order cepstrum, and can determine that an abnormal sound is present when the order cepstrum is equal to or greater than the threshold.

[0044] It should be noted that the upper and lower threshold values ​​can be set for any order. If the order cepstrum exceeds the upper threshold value, the abnormal sound detection unit 35 can determine that an abnormal sound exists. On the other hand, if the order cepstrum falls below the lower threshold value, the abnormal sound detection unit 35 can determine that there is a problem with the measurement during the test and that the test was not performed correctly. The upper and lower threshold values ​​can also be set for a certain section of the order cepstrum. In this case, unnecessary determination processing can be reduced.

[0045] FIG. 14 is a diagram showing an example of settings for abnormal sound detection according to an embodiment of the present disclosure. This figure shows an example of settings for abnormal sound detection in the abnormal sound detection unit 35. The upper part of FIG. 14 shows an example of a parameter setting screen. These parameters include the number of digits of order resolution and the maximum order. A button 225 at the top of FIG. 14 indicates whether the inspection is enabled or disabled. The first row represents the row of orders (221). The second row represents the upper threshold value (222). The third row represents the lower threshold value (223). Note that "Inf" and "-Inf" are treated as invalid values ​​(224). Note that these threshold setting values ​​can also be read from a file (226). This screen is displayed on the display unit 36.

[0046] The lower part of Fig. 14 shows an example of the display of the order cepstrum test result. The test result is displayed at the upper part of the figure (231). If the test result is a failure, the reason is displayed. The figure also displays the order cepstrum, upper threshold limit (232), and lower threshold limit (233). This screen is displayed on the display unit 36.

[0047] Note that the above-described step S103 is an example of a "frequency spectrum generation procedure" of the present disclosure. Step S104 is an example of a "cepstrum generation procedure" of the present disclosure. Step S105 is an example of an "order cepstrum generation procedure" of the present disclosure. Step S108 is an example of an "abnormal sound detection procedure" of the present disclosure.

[0048] In this way, the rotating body inspection device 30 of the present disclosure can detect abnormal noise that is relatively small in amplitude but occurs periodically and involves increases and decreases in amplitude in a rotating body such as a motor, based on the order cepstrum.

[0049] Although the embodiments of the present disclosure have been described above, the technical scope of the present disclosure is not limited to the above-described embodiments, and various modifications are possible within the scope of the gist of the present disclosure. Furthermore, components of different embodiments and modifications may be combined as appropriate.

[0050] The series of processes performed by each device described in this specification may be realized using software, hardware, or a combination of software and hardware. The programs constituting the software are stored in advance in, for example, a storage medium (non-transitory medium) provided inside or outside each device. Then, each program is loaded into RAM when executed by a computer, and executed by a processor such as a CPU.

[0051] Furthermore, the processes described herein using flowcharts and sequence diagrams do not necessarily have to be performed in the order shown. Some process steps may be performed in parallel. Furthermore, additional process steps may be employed, and some process steps may be omitted.

[0052] (effect) The rotating body inspection device includes a frequency spectrum generation unit, a cepstrum generation unit, an order cepstrum generation unit, and an abnormal sound detection unit. The frequency spectrum generation unit generates a frequency spectrum for each time-series measurement interval from vibration data, which is vibration data for each rotation speed of the rotating body. The cepstrum generation unit generates a cepstrum from the frequency spectrum for each measurement interval. The order cepstrum generation unit generates an order cepstrum, which is data obtained by converting the quefrency of the cepstrum into an order, for each measurement interval. The abnormal sound detection unit detects abnormal sounds from the rotating body based on the order cepstrum for each measurement interval. This makes it possible to detect abnormal sounds whose amplitude periodically increases and decreases.

[0053] The frequency spectrum generating section may generate the frequency spectrum for each of the measurement sections that partially overlap each other between adjacent measurement sections, thereby preventing data loss at ends of the measurement sections.

[0054] The abnormal sound detection unit may detect the abnormal sound based on a predetermined threshold value, thereby enabling objective detection of the abnormal sound.

[0055] The predetermined threshold value may include an upper limit and a lower limit, thereby enabling inspection to be performed based on the upper limit and the lower limit.

[0056] The method for inspecting a rotating body includes generating a frequency spectrum for each measurement interval in a time series from vibration data that is vibration data for each rotation speed of the rotating body, generating a cepstrum from the frequency spectrum for each measurement interval, generating an order cepstrum that is data obtained by converting the quefrency of the cepstrum into an order for each measurement interval, and detecting abnormal noise from the rotating body based on the order cepstrum for each measurement interval. This makes it possible to detect abnormal noise whose amplitude periodically increases and decreases.

[0057] The program causes a computer to execute a frequency spectrum generation procedure for generating a frequency spectrum for each time-series measurement interval from vibration data that is vibration data for each rotation speed of a rotating body, a cepstrum generation procedure for generating a cepstrum from the frequency spectrum for each measurement interval, an order cepstrum generation procedure for generating an order cepstrum that is data obtained by converting the quefrency of the cepstrum for each measurement interval, and an abnormal noise detection procedure for detecting abnormal noise from the rotating body based on the order cepstrum for each measurement interval. This makes it possible to detect abnormal noise whose amplitude periodically increases and decreases.

[0058] The effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0059] The present technology can also be configured as follows. (1) a frequency spectrum generating unit that generates a frequency spectrum for each measurement interval in a time series from vibration data that is vibration data for each rotation speed of the rotating body; a cepstrum generation unit that generates a cepstrum from the frequency spectrum for each measurement interval; an order cepstrum generating unit that generates an order cepstrum, which is data obtained by converting the quefrency of the cepstrum into an order for each measurement interval; an abnormal noise detection unit that detects abnormal noise of the rotating body based on the order cepstrum for each measurement section; A rotating body inspection device comprising: (2) The rotating body inspection device according to (1), wherein the frequency spectrum generation unit generates the frequency spectrum for each of the measurement sections that partially overlap each other between adjacent measurement sections. (3) The rotating body inspection device according to (1) or (2), wherein the abnormal sound detection unit detects the abnormal sound based on a predetermined threshold value. (4) The rotating body inspection device according to (3), wherein the predetermined threshold value includes an upper limit and a lower limit threshold value. (5) generating a frequency spectrum for each time-series measurement section from vibration data that is vibration data for each rotation speed of the rotating body; generating a cepstrum from the frequency spectrum for each measurement interval; generating an order cepstrum, which is data obtained by converting the quefrency of the cepstrum into an order for each measurement section; detecting abnormal noise of the rotating body based on the order cepstrum for each measurement section; A rotating body inspection method comprising: (6) a frequency spectrum generation step of generating a frequency spectrum for each time-series measurement interval from vibration data, which is vibration data for each rotation speed of the rotating body; a cepstrum generation step of generating a cepstrum from the frequency spectrum for each measurement interval; an order cepstrum generating step of generating an order cepstrum, which is data obtained by converting the quefrency of the cepstrum into an order for each measurement interval; an abnormal noise detection step of detecting abnormal noise of the rotating body based on the order cepstrum for each measurement section; A program that causes a computer to execute the following. [Explanation of symbols]

[0060] 10 Measuring part 20 Control Unit 30 Rotating body inspection equipment 32 Frequency spectrum generator 33 Cepstrum generator 34-order cepstrum generator 35 Abnormal noise detection unit 37 Settings management section

Claims

1. a frequency spectrum generating unit that generates a frequency spectrum for each measurement interval in a time series from vibration data that is vibration data for each rotation speed of the rotating body; a cepstrum generation unit that generates a cepstrum from the frequency spectrum for each measurement interval; an order cepstrum generating unit that generates an order cepstrum, which is data obtained by converting the quefrency of the cepstrum into an order for each measurement interval; an abnormal noise detection unit that detects abnormal noise of the rotating body based on the order cepstrum for each measurement section; A rotating body inspection device comprising:

2. The rotating body inspection device according to claim 1 , wherein the frequency spectrum generation unit generates the frequency spectrum for each of the measurement sections that partially overlap each other between adjacent measurement sections.

3. The rotating body inspection device according to claim 1 , wherein the abnormal sound detection unit detects the abnormal sound based on a predetermined threshold value.

4. The rotating body inspection device according to claim 3 , wherein the predetermined threshold value includes an upper limit and a lower limit.

5. generating a frequency spectrum for each time-series measurement section from vibration data that is vibration data for each rotation speed of the rotating body; generating a cepstrum from the frequency spectrum for each measurement interval; generating an order cepstrum, which is data obtained by converting the quefrency of the cepstrum into an order for each measurement section; detecting abnormal noise of the rotating body based on the order cepstrum for each measurement section; A rotating body inspection method comprising:

6. a frequency spectrum generation step of generating a frequency spectrum for each time-series measurement interval from vibration data, which is vibration data for each rotation speed of the rotating body; a cepstrum generation step of generating a cepstrum from the frequency spectrum for each measurement interval; an order cepstrum generating step of generating an order cepstrum, which is data obtained by converting the quefrency of the cepstrum into an order for each measurement interval; an abnormal noise detection step of detecting abnormal noise of the rotating body based on the order cepstrum for each measurement section; A program that causes a computer to execute the following.

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