Abnormality diagnosis device and abnormality diagnosis method for ball screw

Abstract

Provided are an abnormality diagnosis device and an abnormality diagnosis method for a ball screw capable of detecting abnormalities such as damage and wear occurring in a screw shaft. The abnormality diagnosis device is provided with: a vibration sensor (21) that detects vibration during operation of the ball screw; a filter processing unit (23) that performs filter processing for extracting a frequency band including at least a characteristic frequency corresponding to the natural vibration frequency of the ball screw on the vibration signal acquired by the vibration sensor (21); an envelope processing unit (241) that performs envelope processing on the filtered vibration signal; a frequency analysis processing unit (242) that performs fast Fourier transform processing on the time domain signal after the envelope processing; a peak holding average processing unit (243) that performs peak holding average processing of the frequency domain data for each sampling period in the fast Fourier transform processing; and an abnormality determination unit (25) that performs abnormality determination of the ball screw on the basis of the frequency domain data after the peak holding average processing.

Description

Technical Field

[0001] The invention relates to an abnormality diagnosis device and an abnormality diagnosis method for a ball screw. Background Art

[0002] Patent document 1 discloses an abnormality diagnosis device and an abnormality diagnosis method for mechanical equipment. In the patent document 1, the vibration signal of the mechanical equipment is filtered and envelope processed, and abnormality diagnosis is performed based on the size (signal strength) of the frequency spectrum of the characteristic frequency components corresponding to the natural vibration frequency of the bearings and gears after the fast Fourier transform (FFT) processing. In such a vibration analysis process using FFT, the addition and averaging of each data after FFT processing obtained in multiple periods corresponding to the required frequency resolution is generally performed to improve the signal-to-noise ratio. On the other hand, Patent document 2 discloses a method for determining an abnormality of a ball screw using a frequency component below the natural vibration frequency of the nut constituting the ball screw in the abnormality determination based on vibration when the ball screw is working.

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent No. 4581860

[0006] Patent Document 2: Japanese Patent No. 5217743 Summary of the invention

[0007] Problem that the invention aims to solve

[0008] By applying a vibration analysis process using FFT, such as that described in Patent Document 1, it is possible to determine the damage and wear of the bearing and nut of the ball screw. However, in determining the damage and wear of the screw shaft of the ball screw, it is necessary to move the nut over the entire area of ​​the screw shaft. Therefore, when applying a vibration analysis process using FFT, the data obtained multiple times after FFT processing are data at different positions of the screw shaft. Therefore, the natural vibration frequency (characteristic frequency component) generated due to the abnormality of the screw shaft is attenuated due to the additive averaging process after FFT processing, and it may be impossible to detect abnormalities such as damage and wear generated on a part of the screw shaft.

[0009] The present invention has been made in view of the above-mentioned problems, and an object of the present invention is to provide an abnormality diagnosis device and an abnormality diagnosis method for a ball screw that can detect abnormalities such as damage and wear occurring in a screw shaft.

[0010] Solutions for solving problems

[0011] In order to achieve the above-mentioned purpose, an abnormality diagnosis device for a ball screw involved in one embodiment of the present invention comprises: a vibration sensor, which detects the vibration of the ball screw during operation; a filtering processing unit, which performs filtering processing on the vibration signal acquired by the vibration sensor to extract a frequency band containing at least a characteristic frequency corresponding to the natural vibration frequency of the ball screw; an envelope processing unit, which performs envelope processing on the vibration signal after the filtering processing; a frequency analysis processing unit, which performs fast Fourier transform processing on the time domain signal after the envelope processing; a peak hold averaging processing unit, which performs peak hold averaging processing on the frequency domain data during each sampling period in the fast Fourier transform processing; and an abnormality judgment unit, which performs abnormality judgment on the ball screw based on the frequency domain data after the peak hold averaging processing.

[0012] According to the above configuration, the maximum signal strength of each frequency line of the frequency domain data acquired during each sampling period during the operation of the ball screw can be used to perform abnormality determination processing of the ball screw, thereby detecting abnormalities such as damage and wear on the screw shaft of the ball screw.

[0013] As an expected method of an abnormality diagnosis device for a ball screw, it is preferred that the abnormality judgment unit extracts a signal strength corresponding to the damage frequency of the screw shaft based on the rotation frequency of the screw shaft of the ball screw, and outputs an abnormality judgment result of the screw shaft when the signal strength exceeds a prescribed threshold value.

[0014] This makes it possible to output a diagnosis result that determines that an abnormality has occurred in the screw shaft of the ball screw due to damage or wear.

[0015] As an expected method of an abnormality diagnosis device for a ball screw, it is preferred that the abnormality judgment unit extracts the maximum value of the signal intensity within a specified range including the damage frequency of the screw shaft of the ball screw, and outputs the abnormality judgment result of the screw shaft when the maximum value exceeds a specified threshold value.

[0016] This makes it possible to output a diagnosis result that determines that an abnormality has occurred in the screw shaft of the ball screw due to damage or wear.

[0017] A method for diagnosing an abnormality of a ball screw according to one embodiment of the present invention comprises the following steps: a first step of detecting the vibration of the ball screw during operation; a second step of performing filtering processing on the vibration signal acquired in the first step to extract a frequency band containing at least a characteristic frequency corresponding to the natural vibration frequency of the ball screw; a third step of performing envelope processing on the vibration signal after filtering; a fourth step of performing fast Fourier transform processing on the time domain signal after envelope processing; a fifth step of performing peak hold averaging processing on the frequency domain data during each sampling period in the fast Fourier transform processing; and a sixth step of making an abnormality judgment on the ball screw based on the frequency domain data after the peak hold averaging processing.

[0018] According to the above configuration, the maximum signal intensity of each frequency line of the frequency domain data acquired during each sampling period during the operation of the ball screw can be used to perform abnormality determination processing of the ball screw, thereby detecting abnormalities such as damage and wear occurring on the screw shaft.

[0019] As an expected method of diagnosing abnormality of a ball screw, it is preferred that, in the sixth step, a signal strength corresponding to the damage frequency of the screw shaft is extracted based on the rotation frequency of the screw shaft of the ball screw, and when the signal strength exceeds a prescribed threshold value, an abnormality judgment result of the screw shaft is output.

[0020] This makes it possible to output a diagnosis result that determines that an abnormality has occurred in the screw shaft of the ball screw due to damage or wear.

[0021] As an expected method of diagnosing abnormality of a ball screw, it is preferred that, in the sixth step, the maximum value of the signal intensity within a specified range of the damage frequency of the screw shaft of the ball screw is extracted, and when the maximum value exceeds a specified threshold value, the abnormality judgment result of the screw shaft is output.

[0022] This makes it possible to output a diagnosis result that determines that an abnormality has occurred in the screw shaft of the ball screw due to damage or wear.

[0023] Effects of the Invention

[0024] According to the present invention, an abnormality diagnosis device and an abnormality diagnosis method for a ball screw capable of detecting abnormalities such as damage and wear occurring in the screw shaft are obtained. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a diagram showing an example of a schematic configuration of a ball screw abnormality diagnosis system.

[0026] Figure 2This is a block diagram showing an example of a ball screw abnormality diagnosis device according to the embodiment.

[0027] Figure 3 It is an image diagram schematically showing a vibration signal acquired in the abnormality diagnosis process according to the embodiment.

[0028] Figure 4 It is a diagram showing a specific example of a vibration signal acquired in the abnormality diagnosis process according to the embodiment.

[0029] Figure 5A It is a schematic diagram showing an example of frequency domain data acquired by FFT processing.

[0030] Figure 5B It is a schematic diagram showing an example of frequency domain data acquired by FFT processing.

[0031] Figure 6 Schematic diagram showing an example of frequency domain data after the addition and averaging process.

[0032] Figure 7 : is a schematic diagram showing an example of frequency domain data after the peak hold averaging process.

[0033] Figure 8 This is a flowchart showing an example of abnormality diagnosis processing of the ball screw according to the embodiment.

[0034] Fig. 9 This is a sub-flow chart showing an example of peak hold averaging processing. DETAILED DESCRIPTION

[0035] Below, the mode for implementing the invention (hereinafter referred to as the embodiment) is described in detail with reference to the accompanying drawings. In addition, the present invention is not limited by the following embodiments. In addition, the structural elements of the following embodiments include elements that can be easily thought of by those skilled in the art, substantially the same elements, and elements of the so-called equivalent scope. In addition, the structural elements disclosed in the following embodiments can be appropriately combined.

[0036] Figure 1 1 is a diagram showing an example of a schematic configuration of a ball screw abnormality diagnosis system. The ball screw 1 includes a screw shaft 11 and a nut 12 slidably fitted to the screw shaft 11 via a plurality of rolling elements (not shown).

[0037] Both ends of the screw shaft 11 are rotatably supported by bearings 13 and 14, respectively. Figure 1 The nut 12 is connected to the output shaft of the driving motor 15 as the screw shaft 11 rotates. Figure 1The distance between the A end and the B end shown in the figure is along the axial direction of the screw shaft 11 ( Figure 1 Direction of the arrow shown).

[0038] In the present disclosure, the abnormality diagnosis device 2 of the ball screw 1 involved in the embodiment performs vibration analysis processing during the operation of the ball screw 1, and diagnoses damage and wear of the screw shaft 11. Specifically, when the abnormality diagnosis device 2 performs the abnormality diagnosis processing of the ball screw 1 involved in the embodiment, it outputs the drive control instructions and rotation control instructions of the motor 15 to the drive control device 3. The drive control device 3 drives the motor 15 based on the control instructions from the abnormality diagnosis device 2 to operate the ball screw 1, thereby moving the nut 12 over the entire area of ​​the screw shaft 11. The drive control device 3 outputs the rotation frequency of the motor 15 to the abnormality diagnosis device 2, in other words, outputs the rotation frequency of the screw shaft 11 of the ball screw 1.

[0039] Figure 2 1 is a block diagram showing an example of an abnormality diagnosis device for a ball screw according to an embodiment of the present invention. Figure 2 As shown, the ball screw abnormality diagnosis device 2 according to the embodiment includes a vibration sensor 21 , an AD conversion processing unit 22 , a filter processing unit 23 , a vibration analysis processing unit 24 , and an abnormality determination unit 25 .

[0040] The vibration sensor 21 is provided, for example, at Figure 1 The nut 12 of the ball screw 1 is shown. In the present disclosure, regarding the vibration sensor 21, an acceleration sensor such as an acceleration pickup is exemplified. The acceleration detection direction of the vibration sensor 21 can be either the axial direction ( Figure 1 The vibration sensor 21 may be in the direction of the arrow shown in the figure, or in the direction orthogonal to the axial direction of the screw shaft 11. In addition, the vibration sensor 21 may be set at a position that can detect the vibration of the ball screw 1 during operation, and is not limited to the nut 12. Furthermore, the vibration sensor 21 is not limited to an acceleration sensor. The vibration sensor 21 may also be, for example, a displacement sensor, a microphone or other sound pressure sensor.

[0041] The AD conversion processing unit 22 converts the vibration signal detected by the vibration sensor 21 into digital data.

[0042] The filter processing unit 23 performs a predetermined filter processing on the vibration signal converted into digital data. Specifically, the filter processing unit 23 extracts a frequency band containing characteristic frequencies corresponding to various natural vibration frequencies of the ball screw 1. As the filter processing unit 23, for example, a low-pass filter is illustrated, but it is not limited to this. The filter processing unit 23 can be a high-pass filter, a band-pass filter, or a band-stop filter as long as it can extract a frequency band containing characteristic frequencies corresponding to various natural vibration frequencies of the ball screw 1.

[0043] In the present disclosure, the frequency of the natural vibration caused by damage and wear of the screw shaft 11 of the ball screw 1 is set as the characteristic frequency. Hereinafter, the frequency of the natural vibration caused by damage and wear of the screw shaft 11 of the ball screw 1 is also referred to as the "damage frequency of the screw shaft 11".

[0044] The damage frequency of the screw shaft 11 is represented by the value obtained by multiplying the relative rotation frequency fi of the screw shaft 11 relative to the revolution frequency of the rolling element of the nut 12 by the rolling logarithm Z per lead (=Z×fi, hereinafter also referred to as "Zfi"). When the shaft rotation frequency of the screw shaft 11 is set to fr, the rolling element diameter is set to Dw, the center circle diameter of the rolling element is set to Da, the thread groove contact angle is set to α, and the lead angle is set to β, the damage frequency Zfi of the screw shaft 11 is given by the following formula (1). The shaft rotation frequency fr of the screw shaft 11 can be calculated based on the rotation frequency of the motor 15 (the rotation frequency of the screw shaft 11 of the ball screw 1).

[0045] [Number 1]

[0046]

[0047] The rotation frequency of the motor 15 (the rotation frequency of the screw shaft 11 of the ball screw 1 ) corresponds to the moving speed of the nut 12 when the abnormality diagnosis process of the present disclosure is performed.

[0048] In the present disclosure, the abnormality determination unit 25 pre-maintains a signal strength threshold corresponding to the damage frequency Zfi of the screw shaft 11 shown by the above formula (1). The abnormality determination unit 25 performs a threshold determination process of the signal strength threshold corresponding to the damage frequency Zfi of the screw shaft 11 maintained in advance and the signal strength corresponding to the damage frequency Zfi obtained by the vibration analysis processing unit 24. Next, the structure and operation of the vibration analysis processing unit 24 involved in the embodiment are described.

[0049] The vibration analysis processing unit 24 involved in the embodiment includes an envelope processing unit 241, a frequency analysis processing unit 242, and a peak hold average processing unit 243. The envelope processing unit 241 performs envelope processing (envelope detection processing) on ​​the vibration signal that has been filtered in the filter processing unit 23. Specifically, the envelope processing unit 241 performs envelope processing on the vibration signal using, for example, Hilbert transform. The envelope processing unit 241 may also perform envelope processing on the vibration signal by, for example, absolute value detection.

[0050] The frequency analysis processing unit 242 performs spectrum analysis processing on the time domain signal. Specifically, the frequency analysis processing unit 242 performs fast Fourier transform (FFT) processing on the time domain signal after the envelope processing. Figure 3 FIG. 1 is a diagram schematically showing an image of a vibration signal acquired in the abnormality diagnosis process according to the embodiment. Figure 3 In the graph, the horizontal axis represents time, and the vertical axis represents the magnitude of the vibration signal (acceleration a).

[0051] exist Figure 3 In the embodiment, the period for data acquisition in the abnormality diagnosis process is set to T. The frequency resolution in the FFT process is determined by the sampling rate (sampling frequency) and the block size (number of sampled data). The sampling period (time window length) D of the FFT process in the data acquisition period T is defined by the inverse of the frequency resolution in the FFT process.

[0052] In the abnormality diagnosis processing of bearings, gears, etc., the frequency domain data (signals after FFT processing) acquired multiple times within the data acquisition period T are generally subjected to the addition and averaging processing to improve the signal-to-noise ratio. However, in the present disclosure, when determining the damage or wear of the screw shaft 11 of the ball screw 1 that is the object of abnormality diagnosis, it is necessary to move the nut 12 over the entire area of ​​the screw shaft 11. Therefore, the frequency domain data acquired multiple times within the data acquisition period T are vibration data acquired at different positions of the screw shaft 11. Therefore, the signal intensity corresponding to the damage frequency Zfi of the screw shaft 11 is attenuated due to the addition and averaging processing, and it may be impossible to detect abnormalities such as damage or wear generated in a part of the screw shaft 11. Below, the concept of the vibration analysis processing involved in the present disclosure is explained.

[0053] Figure 4 1 is a diagram showing a specific example of a vibration signal acquired in the abnormality diagnosis process according to the embodiment. Figure 4 The example shown shows that the nut 12 is moved in the data acquisition period T. Figure 1 The example shown is a three-way reciprocation between end A and end B.

[0054] exist Figure 4 In the example shown, during the period T21 and the period T31, the magnitude of the vibration signal (acceleration a) is an abnormal value at point C close to end A. At this point C, there is a possibility that the screw shaft 11 is damaged or worn.

[0055] Figure 5A and Figure 5B It is a schematic diagram showing an example of frequency domain data acquired by FFT processing. Figure 6 Schematic diagram showing an example of frequency domain data after the addition and averaging process. Figure 7 FIG. 1 is a schematic diagram showing an example of frequency domain data after peak hold averaging processing. Figure 5A , Figure 5B , Figure 6 as well as Figure 7 In FIG, the horizontal axis represents frequency, and the vertical axis represents signal strength of frequency domain data.

[0056] exist Figure 5A exemplifies the frequency domain data obtained when the nut 12 passes through the damaged part of the screw shaft 11. Figure 4 When the vibration signal during the period T11A, T21A, and T31A in the interval is processed by FFT, the following is obtained: Figure 5A Such frequency domain data. Figure 5A As shown, in the frequency domain data obtained when the nut 12 passes through the damaged part of the screw shaft 11, the signal strength of the damage frequency Zfi of the screw shaft 11, the second harmonic component 2Zfi of the damage frequency Zfi, the third harmonic component 3Zfi, the fourth harmonic component 4Zfi, etc. becomes high, but in the frequency domain data obtained when the nut 12 passes through the part without damage or slight wear, as shown in FIG. Figure 5B As shown in FIG. 1 , the signal intensity of the frequency components corresponding to the damage frequency Zfi of the screw shaft 11 and its higher harmonic components 2Zfi, 3Zfi, and 4Zfi becomes low. Figure 5B exemplifies a plurality of frequency domain data acquired when the nut 12 passes through a plurality of locations that are not damaged or slightly worn. Figure 4 When the vibration signal during the period T11B, T21B, and T31B in the interval is processed by FFT, the following is obtained: Figure 5B That frequency domain data.

[0057] In such a structure for performing abnormal diagnosis of damage, wear, etc. of the screw shaft 11 of the ball screw 1, as shown in FIG. Figure 6 As shown, when the frequency domain data acquired multiple times are subjected to additive averaging processing, the signal strength of the damage frequency Zfi of the screw shaft 11 and its higher harmonic components 2Zfi, 3Zfi, 4Zfi, etc. is attenuated, and it may be impossible to detect abnormalities such as damage and wear caused to a part of the screw shaft 11.

[0058] In the case where only a portion of the screw shaft of the ball screw 1 is damaged, if frequency domain data is acquired multiple times, most of the frequency domain data is acquired when the nut 12 passes through the undamaged portion. Figure 5B If such frequency domain data with low signal strength is subjected to addition averaging processing, the signal strength after the averaging processing is attenuated by the frequency domain data with low signal strength, so it may not be possible to detect abnormalities such as damage and wear on a part of the screw shaft 11.

[0059] Therefore, in the present disclosure, a peak hold average processing unit 243 is provided at a subsequent stage of the frequency analysis processing unit 242 that performs spectrum analysis of a time domain signal. The peak hold average processing unit 243 performs peak hold average processing on the frequency domain data after the FFT processing.

[0060] Specifically, the peak hold average processing unit 243 obtains the maximum value of each frequency (frequency line) for which spectrum data should be generated, which is determined by the frequency resolution of the frequency domain data after FFT processing, and generates Figure 7 Thus, it is possible to detect the signal strengths of the damage frequency Zfi, the harmonic components 2Zfi, 3Zfi, 4Zfi, etc., which are generated due to damage or wear on a part of the screw shaft 11.

[0061] Next, the abnormality diagnosis process of the ball screw 1 according to the embodiment will be described. Figure 8 This is a flowchart showing an example of abnormality diagnosis processing of the ball screw according to the embodiment.

[0062] exist Figure 1 In the abnormality diagnosis system of the ball screw 1 shown, the abnormality diagnosis device 2 involved in the embodiment performs vibration analysis processing during the operation of the ball screw 1 as described above, and diagnoses the damage and wear of the screw shaft 11. Specifically, when the abnormality diagnosis device 2 performs the abnormality diagnosis processing of the ball screw 1 involved in the embodiment, it outputs the drive control instruction and rotation control instruction of the motor 15 to the drive control device 3. The drive control device 3 drives the motor 15 based on the control instruction from the abnormality diagnosis device 2 to operate the ball screw 1, so that the nut 12 moves in the entire area of ​​the screw shaft 11 at a speed corresponding to the damage frequency Zfi of the screw shaft 11 shown by the above formula (1). In other words, the drive control device 3 causes the motor 15 (screw shaft 11) to rotate in the entire area of ​​the screw shaft 11 in a manner to become the shaft rotation frequency fr corresponding to the damage frequency Zfi of the screw shaft 11 shown by the above formula (1). Specifically, the drive control device 3, for example, causes the nut 12 to rotate as shown in the above formula (1). Figure 4 As shown in Figure 1 The A end and the B end are shown to be moved back and forth many times.

[0063] The vibration sensor 21 detects vibration during operation of the ball screw 1. The vibration signal detected by the vibration sensor 21 is converted into digital data by the AD conversion processing unit 22 and then acquired (step S100).

[0064] The filter processing unit 23 performs a predetermined filter process on the vibration signal acquired by the vibration sensor 21 (step S200 ). Specifically, the filter processing unit 23 extracts a frequency band including at least characteristic frequencies corresponding to various natural vibration frequencies of the ball screw 1 .

[0065] The envelope processing unit 241 performs envelope processing on the vibration signal after the filtering process (step S300 ). The frequency analysis processing unit 242 performs fast Fourier transform (FFT) processing on the time domain signal after the envelope processing, and performs spectrum analysis processing (step S400 ).

[0066] During the data acquisition period T in the abnormality diagnosis process of the ball screw 1 according to the embodiment (the operation period of the ball screw 1 in the abnormality diagnosis process), in each sampling period (time window length) D defined by the inverse of the frequency resolution in the FFT process, the frequency domain data after the spectrum analysis process is sequentially input to the peak hold average processing unit 243. The peak hold average processing unit 243 performs the peak hold average processing of the frequency domain data acquired in each sampling period D (step S500). Fig. 9 This is a sub-flow chart showing an example of peak hold averaging processing.

[0067] exist Fig. 9 In , n represents an integer up to the total number N of frequency domain data acquired in the data acquisition period T. Fig. 9 In , m represents an integer up to the total number of frequency lines M determined by the frequency resolution of the frequency domain data after the FFT process. In addition, Sigfm represents the signal strength of each frequency line m.

[0068] The peak hold average processing unit 243 resets the number n of the frequency domain data acquired during the data acquisition period T (n=0, step S501), and determines whether n=N-1 (step S502). If n=N-1 is not (step S502: "No"), the number n of the frequency domain data is incremented (n=n+1, step S503).

[0069] Next, the peak hold average processing unit 243 resets the number m of the frequency line and the maximum value Sigfmmax of the signal strength Sigfm in the frequency line m (m=0, Sigfmmax=0, step S504), and determines whether m=M-1 (step S505). If m=M-1 is not (step S505: "No"), the number m of the frequency line is incremented (m=m+1, step S506).

[0070] When the frequency domain data of the sampling period Dn corresponding to the number n is input, the peak hold average processing unit 243 determines whether the signal strength Sigfm of the frequency line m exceeds the maximum value Sigfmmax (step S507).

[0071] When the signal strength Sigfm exceeds the maximum value Sigfmmax (Sigfm>Sigfmmax, step S507: "Yes"), the signal strength Sigfm is set to the maximum value Sigfmmax of the frequency line m (step S508), and the process returns to step S505, and the process after step S505 is repeatedly executed.

[0072] When the signal strength Sigfm is less than or equal to the maximum value Sigfmmax (Sigfm≤Sigfmmax, step S507: No), the process returns to step S505 and the processes after step S505 are repeatedly executed.

[0073] If m=M-1 in the process of step S505 (step S505: Yes), the process returns to step S502 and the process after step S502 is repeated. If n=N-1 in the process of step S502 (step S502: Yes), the process returns to step S503. Figure 8 The abnormal diagnosis process shown above can be Fig. 9 The peak hold averaging process shown above is used to obtain the maximum value of each frequency line determined by the frequency resolution of the frequency domain data after FFT processing, and it is possible to generate Figure 7 Spectral data shown.

[0074] Back to Figure 8 The abnormality determination unit 25 calculates the shaft rotation frequency fr of the screw shaft 11 of the ball screw 1 based on the rotation frequency of the motor 15 (screw shaft 11), extracts the signal strength SigZfi corresponding to the damage frequency Zfi of the screw shaft 11 shown by the above formula (1) (step S600), and performs a comparison determination process with the pre-held signal strength threshold Sigth (step S700). Specifically, the abnormality determination unit 25 determines whether the signal strength SigZfi extracted in the process of step S600 is below the signal strength threshold Sigth.

[0075] In the present disclosure, the signal strength SigZfi corresponding to the damage frequency Zfi of the screw shaft 11 may be a signal strength that reaches a maximum value within a specified range including the damage frequency Zfi of the screw shaft 11. Specifically, the signal strength SigZfi corresponding to the damage frequency Zfi of the screw shaft 11 is preferably a signal strength that reaches a maximum value within a range of, for example, 0.9Zfi to 0.9Zfi and below Zfi.

[0076] When the signal strength SigZfi extracted in the processing of step S600 is below the signal strength threshold Sigth (SigZfi≤Sigth, step S700: "Yes"), it is deemed that no abnormality caused by damage or wear of the screw shaft 11 of the ball screw 1 which is the object of abnormal diagnosis has occurred in the present disclosure, and a normal judgment is made (step S800A), and the diagnostic result of the normal judgment is output (step S900), thereby ending the abnormal diagnosis processing.

[0077] When the signal strength SigZfi extracted in the processing of step S600 exceeds the signal strength threshold Sigth (SigZfi>Sigth, step S700: "No"), it is deemed that an abnormality caused by damage or wear of the screw shaft 11 of the ball screw 1 which is the object of abnormal diagnosis has occurred in the present disclosure, and an abnormal judgment is made (step S800B), and the diagnostic result of the abnormal judgment is output (step S900), thereby ending the abnormal diagnosis processing.

[0078] As described above, according to the abnormality diagnosis device 2 and the abnormality diagnosis method of the ball screw 1 according to the embodiment of the present disclosure, it is possible to detect abnormalities such as damage and wear occurring in the screw shaft 11 of the ball screw 1 .

[0079] Description of Reference Numerals

[0080] 1: ball screw; 2: abnormality diagnosis device; 3: drive control device; 11: screw shaft; 12: nut; 13, 14: bearings; 15: motor; 21: vibration sensor; 22: AD conversion processing unit; 23: filtering processing unit; 24: vibration analysis processing unit; 25: abnormality determination unit; 241: envelope processing unit; 242: frequency analysis processing unit; 243: peak hold average processing unit.

Claims

1. A ball screw abnormality diagnosis device, comprising: A vibration sensor that detects vibrations of the ball screw during operation; a filter processing unit that performs a filter process on the vibration signal acquired by the vibration sensor to extract a frequency band including at least a characteristic frequency corresponding to the natural vibration frequency of the ball screw; An envelope processing unit that performs envelope processing on the vibration signal after the filtering process; A frequency analysis processing unit that performs fast Fourier transform processing on the time domain signal after envelope processing; A peak hold average processing unit that performs a peak hold average processing of the frequency domain data for each sampling period in the fast Fourier transform processing; as well as The abnormality determination unit performs abnormality determination of the ball screw based on the frequency domain data after the peak hold averaging process.

2. The abnormality diagnosis device for a ball screw according to claim 1, wherein: The abnormality determination unit extracts a signal strength corresponding to a damage frequency of the screw shaft based on a rotation frequency of the screw shaft of the ball screw, and outputs an abnormality determination result of the screw shaft when the signal strength exceeds a predetermined threshold value.

3. The abnormality diagnosis device for a ball screw according to claim 1, wherein: The abnormality determination unit extracts a maximum value of signal intensity within a predetermined range including a damage frequency of the screw shaft of the ball screw, and outputs an abnormality determination result of the screw shaft when the maximum value exceeds a predetermined threshold value.

4. A method for diagnosing abnormality of a ball screw, comprising the following steps: The first step is to detect the vibration of the ball screw during operation; A second step is to perform filtering processing on the vibration signal acquired in the first step to extract a frequency band containing at least a characteristic frequency corresponding to the natural vibration frequency of the ball screw; The third step is to perform envelope processing on the vibration signal after filtering; The fourth step is to perform fast Fourier transform processing on the time domain signal after envelope processing; The fifth step is to perform peak-hold average processing of the frequency domain data during each sampling period in the fast Fourier transform processing; as well as The sixth step is to determine the abnormality of the ball screw based on the frequency domain data after the peak hold average processing.

5. The method for diagnosing abnormality of a ball screw according to claim 4, wherein: In the sixth step, a signal strength corresponding to the damage frequency of the screw shaft is extracted based on the rotation frequency of the screw shaft of the ball screw, and when the signal strength exceeds a predetermined threshold value, an abnormality determination result of the screw shaft is output.

6. The method for diagnosing abnormality of a ball screw according to claim 4, wherein: In the sixth step, a maximum value of the signal intensity within a predetermined range including the damage frequency of the screw shaft of the ball screw is extracted, and when the maximum value exceeds a predetermined threshold value, an abnormality determination result of the screw shaft is output.

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