Signal processing device, diagnostic system, and signal processing method

Abstract

Provided are a signal processing device, a diagnostic system, and a signal processing method with which it is possible to improve the accuracy of a determination value for determining a lubrication state in a rolling device. A signal processing device (3), which calculates a determination value for determining a lubrication state in a rolling device on the basis of a measurement signal acquired by a sensor (2), is provided with: a first processing unit (321) which converts the measurement signal into a time-domain signal by performing band limitation and envelope processing on the measurement signal; a second processing unit (322) that converts the time-domain signal into a first frequency-domain signal; a third processing unit (323) that converts the logarithmic spectrum of the first frequency domain signal into a first inverse frequency domain signal; a fourth processing unit (324) that generates a second inverted-frequency-domain signal in which the high-order cepstrum domain, which includes the rotation frequency of the scrolling device, of the first inverted-frequency-domain signal is set to a prescribed value; a fifth processing unit (325) that converts the second inverted frequency domain signal into a second frequency domain signal; and a determination value calculation processing unit (33) that calculates a determination value on the basis of the second frequency domain signal.

Description

TECHNICAL FIELD

[0001] The present application relates to a signal processing device, a diagnosis system, and a signal processing method. BACKGROUND

[0002] As a diagnosis method of a rolling device such as a rolling bearing, a linear guide device, a ball screw, a direct acting bearing, and the like, a method has been disclosed in which a measurement signal of vibration, an acoustic wave, AE (Acoustic Emission), and the like is subjected to a high-speed Fourier transform (FFT) process, the influence of a periodic component such as damage generated at a specific site is excluded, and the state of a periodic weak component such as wear of a bearing, deterioration of lubricating oil, and the like is evaluated separately (for example, Patent Literature 1).

[0003] PRIOR ART DOCUMENTS

[0004] PATENT LITERATURE

[0005] Patent Literature 1: Japanese Patent Application Publication No. 2020-148461 SUMMARY

[0006] PROBLEMS TO BE SOLVED BY THE INVENTION

[0007] In the above-described patent literature, a predetermined frequency component is uniformly removed from a frequency spectrum, and a partial overall for abnormality diagnosis is calculated as a determination value. Therefore, there is a possibility that a periodic weak component within the set frequency component is removed from the partial overall as the determination value, and thus the diagnosis precision of wear in a lubricating portion of the rolling device, deterioration of lubricating oil, and the like is decreased.

[0008] The present application has been achieved in view of the above-described problems, and aims to provide a signal processing device, a diagnosis system, and a signal processing method in which the precision of a determination value used to determine the lubrication state in a rolling device is improved.

[0009] SOLUTION TO PROBLEM

[0010] To achieve the above object, a signal processing device according to one embodiment of the present application calculates a determination value for determining a lubrication state in a rolling device, based on a measurement signal acquired by a sensor, and includes: a first processing section that band limits and envelope processes the measurement signal to convert the measurement signal into a time domain signal; a second processing section that converts the time domain signal into a first frequency domain signal; a third processing section that converts a logarithmic spectrum of the first frequency domain signal into a first cepstrum; a fourth processing section that generates a second cepstrum in which a higher-order cepstrum domain of the first cepstrum containing a rotational frequency of the rolling device is set to a predetermined value; a fifth processing section that converts the second cepstrum into a second frequency domain signal; and a determination value calculation processing section that calculates the determination value based on the second frequency domain signal.

[0011] In the above structure, a second frequency domain signal in which a component having a strong periodicity due to the rotational frequency of the rolling device is suppressed can be obtained. Thus, the accuracy of the determination value for determining the lubrication state in the rolling device can be improved.

[0012] As a desirable mode of the signal processing device, the measurement signal can be a vibration signal acquired by a vibration sensor.

[0013] As a desirable mode of the signal processing device, the measurement signal can be an ultrasonic wave signal acquired by an ultrasonic wave sensor.

[0014] As a desirable mode of the signal processing device, the measurement signal can be an elastic wave signal acquired by an AE sensor.

[0015] As a desirable mode of the signal processing device, it is preferable that the fourth processing section set a higher-order cepstrum domain equal to or higher than a quefrency obtained by multiplying the reciprocal of the rotational frequency of the rolling device by 0.9 to the predetermined value.

[0016] As a desirable mode of the signal processing device, it is preferable that the fourth processing section set the higher-order cepstrum domain to zero.

[0017] As a desirable mode of the signal processing device, the fourth processing section can generate the second cepstrum using a rotational frequency of the rolling device set in advance.

[0018] As a desirable mode of the signal processing device, the determination value calculation processing section can set a partial sum of the second frequency domain signal to the determination value.

[0019] As a desirable mode of the signal processing device, it can also be a mode in which the determination value calculation processing section calculates a partial sum value by band limiting the second frequency domain signal.

[0020] As a desirable mode of the signal processing device, it can also be a mode in which the determination value calculation processing section sets any one of a maximum value, an effective value, a peak factor, a kurtosis, and a skewness of a time domain signal obtained by performing IFFT processing on the second frequency domain signal as the determination value.

[0021] The diagnostic system according to one embodiment is provided with the signal processing device according to any one of claims 1 to 7, and a pump that supplies a lubricant to the rolling device, in which the signal processing device further includes a determination processing section that performs threshold determination on the determination value to determine a lubrication state in the rolling device, the determination processing section causing the pump to operate in a case where the lubrication state of the rolling device is determined to be abnormal after the lubrication state of the rolling device is determined to be normal, and the determination processing section notifying that the lubrication state of the rolling device is abnormal in a case where the lubrication state of the rolling device is determined to be abnormal twice in succession.

[0022] In the above structure, the lubrication state of the rolling device can be favorably maintained, and notification of abnormality due to mere shortage of the lubricant can be prevented. Thus, the management burden of the rolling device can be reduced.

[0023] The signal processing method according to one embodiment is a signal processing method of calculating a determination value for determining a lubrication state in a rolling device, based on a measurement signal acquired by a sensor, the signal processing method including: a first processing step of band-limiting and envelope processing the measurement signal to convert the measurement signal into a time domain signal; a second processing step of converting the time domain signal into a first frequency domain signal; a third processing step of converting a log spectrum of the first frequency domain signal into a first inverse frequency domain signal; a fourth processing step of generating a second inverse frequency domain signal in which a higher-order cepstrum domain of the first inverse frequency domain signal containing a rotational frequency of the rolling device is set to a prescribed value; a fifth processing step of converting the second inverse frequency domain signal into a second frequency domain signal; and a determination value calculation processing step of calculating the determination value based on the second frequency domain signal.

[0024] In the above structure, the second frequency domain signal in which a component having strong periodicity due to the rotational frequency of the rolling device is suppressed can be obtained. Thus, the accuracy of the determination value for determining the lubrication state in the rolling device can be improved.

[0025] As a desirable mode of the signal processing method, the measurement signal can be a vibration signal acquired by a vibration sensor.

[0026] As a desired aspect of the signal processing method, the measurement signal may be an ultrasonic signal acquired by an ultrasonic sensor.

[0027] As a desired aspect of the signal processing method, the measurement signal may be an elastic wave signal acquired by an AE sensor.

[0028] As a desirable aspect of the signal processing method, it is preferable that, in the fourth processing step, a high-order cepstrum domain having a cepstrum frequency or higher obtained by multiplying the inverse of the rotational frequency of the rolling device by 0.9 is set as a predetermined value.

[0029] As a desired mode of the signal processing method, it is preferred that, in the fourth processing step, the high-order cepstrum domain is set to zero.

[0030] As a preferred embodiment of the signal processing method, the following embodiment may be adopted: in the fourth processing step, the second cepstrum domain signal is generated using a preset rotation frequency of the scrolling device.

[0031] As a preferred embodiment of the signal processing method, the following embodiment may be adopted: in the determination value calculation step, a partial total value of the second frequency domain signal is set as the determination value.

[0032] As a desirable aspect of the signal processing method, the following aspect may be adopted: in the determination value calculation step, the second frequency domain signal is subjected to band limitation to calculate a partial total value.

[0033] As an expected method of the signal processing method, the following method may also be used: in the judgment value calculation processing step, any one of the maximum value, effective value, peak factor, kurtosis, and skewness of the time domain signal obtained by performing IFFT processing on the second frequency domain signal is set as the judgment value.

[0034] As an expected mode of the signal processing method, it also includes a judgment processing step, in which a threshold judgment is performed on the judgment value to determine the lubrication state in the rolling device. In the judgment processing step, when the lubrication state of the rolling device is judged to be abnormal after the lubrication state of the rolling device is judged to be normal, lubricant is supplied to the rolling device. When the lubrication state of the rolling device is judged to be abnormal twice in a row, the lubrication state of the rolling device is notified that it is abnormal.

[0035] In the above configuration, the lubrication state of the rolling device can be maintained well, and abnormality notifications due to lubricant shortage alone can be prevented, thereby reducing the management burden of the rolling device.

[0036] Effects of the Invention

[0037] According to the present application, a signal processing device, a diagnostic system, and a signal processing method capable of improving the precision of a determination value used to determine the lubrication state in a rolling device can be obtained. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 is a diagram showing an example of a diagnostic system according to Embodiment 1.

[0039] Figure 2 is a diagram showing an example of a block structure of a signal processing device according to Embodiment 1.

[0040] Figure 3 is a flowchart showing an example of a diagnostic process in the signal processing device according to Embodiment 1.

[0041] Figure 4 is a diagram showing an example of a measurement signal.

[0042] Figure 5 is a diagram showing an example of a measurement signal after band limitation.

[0043] Figure 6 is a diagram showing an example of a time-domain signal after envelope processing.

[0044] Figure 7 is a diagram showing an example of a first frequency-domain signal.

[0045] Figure 8 is a diagram showing an example of a first inverse frequency-domain signal.

[0046] Figure 9 is a diagram showing an example of a second inverse frequency-domain signal.

[0047] Figure 10 is a diagram showing an example of a second frequency-domain signal.

[0048] Figure 11 is a diagram showing an example of a block structure of a signal processing device according to Embodiment 2.

[0049] Figure 12 is a diagram showing an example of a diagnostic system according to Embodiment 3.

[0050] Figure 13 is a diagram showing an example of a block structure of a signal processing device according to Embodiment 3.

[0051] Figure 14 is a diagram showing an example of a diagnostic system according to Embodiment 4.

[0052] Figure 15 is a diagram showing an example of a block structure of the signal processing device according to Embodiment 4.

[0053] Figure 16 is a flowchart showing an example of the diagnosis processing in the signal processing device according to Embodiment 4. DETAILED DESCRIPTION

[0054] Hereinafter, modes for carrying out the present application (hereinafter, referred to as embodiments) will be explained in detail with reference to the drawings. Furthermore, the present application is not limited by the following embodiments. In addition, the constituent elements in the following embodiments include those which can be easily conceived by those skilled in the art, substantially identical constituent elements, and those within the scope of so-called equivalents. Furthermore, the constituent elements disclosed in the following embodiments can be appropriately combined.

[0055] (Embodiment 1)

[0056] Figure 1 is a diagram showing an example of the diagnosis system according to Embodiment 1. In the example shown in Figure 1 , the signal processing device 3 according to Embodiment 1 is applied to the diagnosis system 1 of a rolling bearing (hereinafter, also simply referred to as "bearing") 11 assembled to a mechanical device 10.

[0057] As the mechanical device 10, for example, a railway vehicle, a machine tool, a wind power generation device, an elevator device, and the like are exemplified. In the example shown in Figure 1 , the signal processing device 3 determines the lubrication state of the bearing 11 based on a measurement signal acquired by a sensor 2 provided to the mechanical device 10.

[0058] Furthermore, the application range of the signal processing device 3 according to the present disclosure is not limited to the bearing diagnosis system as shown in Figure 1 , for example, and can be widely applied to rolling devices such as a rolling bearing, a linear guide device, a ball screw, a direct acting bearing, and the like.

[0059] As the sensor 2, for example, an acceleration sensor such as an acceleration pickup is exemplified. The position of the sensor 2 can be any position at which a vibration generated in association with the rotation of the bearing 11 can be detected. In addition, as the sensor 2, in addition to the acceleration sensor, for example, an ultrasonic sensor, an AE (Acoustic Emission) sensor, an impact pulse sensor, and the like can be used. In addition, a device which can equivalently detect a vibration by detecting acceleration, speed, deformation, stress, displacement, and the like and convert the same to an electric signal can be appropriately used.

[0060] The measurement signal acquired by the sensor 2 (for example, a vibration signal acquired by an acceleration pickup or the like, an ultrasonic wave signal acquired by an ultrasonic wave sensor, an elastic wave signal acquired by an AE sensor) is input to the signal processing device 3.

[0061] As a determination value for diagnosing the bearing 11, a partial sum value (POA) of a power spectrum obtained by converting the measurement signal acquired by the sensor 2 into a frequency domain signal, or a scalar value such as a maximum value, a root mean square (RMS) value, a peak value, a kurtosis, a skewness, or the like of a time domain signal that can be acquired by further converting the frequency domain signal into a time domain signal is exemplified.

[0062] A vibration component due to the amount of lubricant, the degree of deterioration, the load (pre-pressing state) of the bearing 11, or the lubrication state of the bearing 11 in the bearing 11 is relatively small with respect to, for example, a periodic vibration component generated when a damage occurs in the track surface of the inner ring 111, the outer ring 112, or the rolling element 113 of the bearing 11. Therefore, in order to accurately determine the lubrication state of the bearing 11, it is necessary to suppress a periodic vibration component generated in conjunction with the rotation of the bearing 11. Hereinafter, the structure of the signal processing device 3 according to Embodiment 1 capable of suppressing a periodic vibration component generated in conjunction with the rotation of the bearing 11, and a specific example of signal processing in the signal processing device 3 according to Embodiment 1 will be described with reference to the drawings. Figures 2 to 10

[0063] Figure 2 is a diagram showing an example of a block structure of the signal processing device according to Embodiment 1. As shown in Figure 2 The signal processing device 3 according to Embodiment 1 has an AD conversion section 31, a first processing section 321, a second processing section 322, a third processing section 323, a fourth processing section 324, a fifth processing section 325, a determination value calculation processing section 33, and a storage section 34. The first processing section 321, the second processing section 322, the third processing section 323, the fourth processing section 324, the fifth processing section 325, and the determination value calculation processing section 33 are, for example, structural sections that can be realized by processing of an arithmetic processing device such as a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. The storage section 34 is constituted by, for example, a storage device such as a ROM (Read Only Memory), a RAM (Random Access Memory), or the like.

[0064] Figure 3 is a flowchart showing an example of diagnosis processing in the signal processing device according to Embodiment 1. The signal processing device 3 first acquires a measurement signal input from the sensor 2 (step S101).​

[0065] The AD conversion section 31 performs AD conversion processing on the measurement signal input from the sensor 2 in step S101, to convert the measurement signal into digital data (step S102). Figure 4 is a schematic diagram showing an example of the measurement signal.

[0066] The first processing section 321 performs band limitation processing (step S103) and envelope processing (envelope line processing) on the measurement signal converted into digital data in the AD conversion section 31, to convert the measurement signal into a time-domain signal (step S104). Figure 5 is a schematic diagram showing an example of the measurement signal after band limitation. Figure 6 is a schematic diagram showing an example of the time-domain signal after envelope processing. In Figure 5 and Figure 6 Examples of the vibration component of the T period appearing in the time-domain signal are shown in

[0067] The second processing section 322 performs high-speed Fourier transform (FFT: Fast Fourier Transform) processing on the time-domain signal after envelope processing, to convert the time-domain signal into a first frequency-domain signal containing the signal intensity of each frequency (step S105). Figure 7 is a schematic diagram showing an example of the first frequency-domain signal.

[0068] Figure 7 Zfn shown in the drawing indicates the rotational frequency component of the bearing 11. In addition, Figure 7 2Zfn shown in the drawing indicates the second harmonic component of the rotational frequency of the bearing 11. In addition, Figure 7 3Zfn shown in the drawing indicates the third harmonic component of the rotational frequency of the bearing 11. In addition, Figure 7 4Zfn shown in the drawing indicates the fourth harmonic component of the rotational frequency of the bearing 11. It is assumed that these periodic strong frequency components are frequency components due to the rotation of the bearing 11.

[0069] The third processing section 323 performs logarithmic conversion processing on the first frequency-domain signal after FFT processing (step S106), and performs high-speed inverse Fourier transform (IFFT: Inverse Fast Fourier Transform) processing on the logarithmic spectrum after logarithmic conversion processing, to convert it into a first quefrency-domain signal (step S107). Figure 8 is a schematic diagram showing an example of the first quefrency-domain signal.

[0070] The fourth processing section 324 multiplies the inverse 1 / Zfn of the rotational frequency component of the bearing 11 by a prescribed coefficient (for example, 0.9) to generate a second cepstrum signal in which a high-order cepstrum domain of 1 / Zfn x 0.9 or more is set to a prescribed value (for example, zero) (step S108). Figure 9 FIG. 6 is a diagram showing an example of the second cepstrum signal.

[0071] The coefficient multiplied by the inverse 1 / Zfn of the rotational frequency component of the bearing 11 is not limited to 0.9. As the coefficient, for example, a value can be set that enables a region in which the inverse 1 / Zfn of the rotational frequency component of the bearing 11 and the cepstrum intensity spread in the cepstrum direction (horizontal axis direction) are high to be set. Further, it is desirable that the coefficient multiplied by the inverse 1 / Zfn of the rotational frequency component of the bearing 11 be set to a value around 0.9. Specifically, for example, in a case in which the coefficient multiplied by the inverse 1 / Zfn of the rotational frequency component of the bearing 11 is set to around 1 or more, the inverse component of the rotational frequency component of the bearing 11 cannot be sufficiently suppressed. Also, for example, in a case in which the coefficient multiplied by the inverse 1 / Zfn of the rotational frequency component of the bearing 11 is set to around 0.8 or less, a component in which periodicity is low due to the lubrication state of the bearing 11 is removed, and the precision of the determination value for determining the lubrication state of the bearing 11 can decrease.

[0072] Specifically, the fourth processing section 324, for example, performs a liftering process in which the high-order cepstrum domain of 1 / Zfn x 0.9 or more of the first cepstrum signal is set to zero. Further, the coefficient multiplied by 1 / Zfn is not limited to 0.9. Also, the high-order cepstrum domain is not limited to zero. Specifically, as the coefficient multiplied by 1 / Zfn, for example, a method in which a LAS (Logarithmic Amplitude Spectrum) value corresponding to 1 / Zfn x (a prescribed coefficient) of the first cepstrum signal is applied, or a method in which a sufficiently small minute value equal to or less than the LAS value corresponding to 1 / Zfn x (a prescribed coefficient) of the first cepstrum signal is applied can be used.

[0073] In the structure of the signal processing device 3 according to Embodiment 1, the rotational frequency of the bearing 11 is a prescribed value, and is stored in the storage section 34. The fourth processing section 324 reads the prescribed value Zfn of the rotational frequency of the bearing 11 stored in the storage section 34, and performs the processing of step S108.

[0074] The fifth processing section 325 performs FFT processing on the second cepstrum signal to convert the second cepstrum signal into a second frequency domain signal (step S109). Figure 10is a diagram showing an example of the second frequency domain signal.

[0075] Thus, as shown in Figure 10 , a second frequency domain signal in which periodic strong frequency components assumed to be frequency components due to rotation of the bearing 11 appearing in a first frequency domain signal shown in Figure 7 is obtained.

[0076] The determination value calculation processing section 33 calculates a determination value for determining the lubrication state of the bearing 11 using the second frequency domain signal in which the periodic strong frequency components are suppressed (step S110).

[0077] Specifically, the determination value calculation processing section 33, for example, calculates a partial sum value (POA) of the second frequency domain signal as the determination value for determining the lubrication state of the bearing 11. At this time, for example, for the purpose of removing interference noise and the like, it can be a manner of band limiting the second frequency domain signal to calculate the partial sum value.

[0078] Alternatively, the determination value calculation processing section 33, for example, finds any one of a maximum value, a root mean square (RMS) value, a peak value, a kurtosis, a skewness, and the like of a time domain signal obtained by further performing IFFT processing on the second frequency domain signal, and sets it as the determination value for determining the lubrication state of the bearing 11.

[0079] Thus, a determination value in which periodic strong vibration components generated in conjunction with rotation of the bearing 11 are suppressed can be obtained.

[0080] The signal processing device 3 determines the lubrication state of the bearing 11 using the determination value calculated through the processes of steps S101 to S110 (step S111). Thereafter, the process of step S101 is returned to, and the processes of steps S101 to S111 are repeatedly executed.

[0081] Through the diagnosis process in the signal processing device 3 according to the above-described embodiment 1, high-precision diagnosis in which periodic strong vibration components generated in conjunction with rotation of the bearing 11 are suppressed can be performed at the time of determining the lubrication state of the bearing 11.

[0082] (Embodiment 2)

[0083] Figure 11 is a diagram showing an example of a block structure of a signal processing device according to embodiment 2. Here, the structure different from the above-described embodiment 1 is explained in detail, and detailed explanation of the same structure as the above-described embodiment 1 is sometimes omitted.

[0084] In Figure 11In the configuration of the signal processing device 3a according to the second embodiment shown in FIG. 1 , the fourth processing unit 324a receives the first frequency domain signal (see FIG. 1 ) generated by the second processing unit 322a. Figure 7 ) extracts the rotation frequency component Zfn of the bearing 11 and executes Figure 3 The process of step S108 of the diagnostic process shown.

[0085] This can improve the accuracy of removing the rotation frequency component of the bearing 11 compared to the configuration according to the first embodiment.

[0086] (Implementation 3)

[0087] Figure 12 This is a diagram showing an example of a diagnostic system according to the third embodiment. Figure 13 This diagram shows an example of a block configuration of a signal processing device according to Embodiment 3. Here, configurations different from those in Embodiments 1 and 2 are described in detail, and detailed descriptions of configurations similar to those in Embodiments 1 and 2 are sometimes omitted.

[0088] exist Figure 12 In the illustrated diagnostic system 1 a , a rotation frequency Zfn is input from the bearing 11 to the signal processing device 3 b according to the third embodiment.

[0089] exist Figure 13 In the structure of the signal processing device 3b according to the third embodiment shown in FIG. 1 , the fourth processing unit 324b uses the rotation frequency Zfn input from the rotation sensor 4 provided on the bearing 11 to perform Figure 3 The process of step S108 of the diagnostic process shown.

[0090] Thus, similarly to the configuration according to the second embodiment, the accuracy of removing the rotational frequency component of the bearing 11 can be improved compared to the configuration according to the first embodiment.

[0091] (Implementation 4)

[0092] Figure 14 This is a diagram showing an example of a diagnostic system according to a fourth embodiment. Figure 15 This is a diagram showing an example of a block structure of a signal processing device according to a fourth embodiment. Figure 16 This is a flowchart showing an example of diagnostic processing in the signal processing device according to Embodiment 4. Here, configurations and processing different from those in Embodiment 1 are described in detail, and detailed descriptions of configurations and processing similar to those in Embodiment 1 are sometimes omitted.

[0093] exist Figure 14In the example shown, the signal processing device 3c according to Embodiment 4 is applied, for example, in the diagnostic system lb assembled in the bearing 11 of the mechanical equipment 10 exemplified by a railway vehicle, a machine tool, a wind power generator, an elevator device, and the like, similarly to the signal processing device 3 according to Embodiment 1.

[0094] As shown in Figure 14 , the diagnostic system lb according to Embodiment 4 further includes a pump 200 that supplies a lubricant to the bearing 11, and a notification device 300 that notifies of an abnormality of the bearing 11. In addition, as shown in Figure 15 , the signal processing device 3c according to Embodiment 4 further includes a determination processing section 35 that determines a lubrication state of the bearing 11. Hereinafter, a specific example of the bearing diagnosis processing in the signal processing device 3c will be described with reference to Figure 16

[0095] The determination processing section 35 performs a determination processing of the lubrication state of the bearing 11 (hereinafter, also simply referred to as "bearing determination processing") using the determination value calculated through the processes of Step S101 to Step S110. Specifically, the determination processing section 35 performs a comparison determination processing of the determination value S calculated by the determination value calculation processing section 33 with a determination threshold value Sth set in advance (Step S121). The determination threshold value Sth is, for example, preliminarily stored in the storage section 34a.

[0096] More specifically, the determination processing section 35 determines whether or not the determination value S calculated by the determination value calculation processing section 33 is equal to or greater than the determination threshold value Sth. In a case where the determination value S is less than the determination threshold value Sth (Step S121: "No"), the flag value Flug is set to "0" (Step S122), and the process returns to Step S101. The flag value Flug is, for example, temporarily stored in the storage section 34a.

[0097] In a case where the determination value S is equal to or greater than the determination threshold value Sth (Step S121: "Yes"), next, the determination processing section 35 determines whether or not the flag value Flug is "1" (Step S123). In a case where the flag value Flug is "0" (Step S123: "No"), the determination processing section 35 sets the flag value Flug to "1" (Step S124), and outputs a control command (hereinafter, also referred to as "lubricant supply command") that instructs the supply of the lubricant to the bearing 11 to the pump 200 (Step S125).

[0098] The pump 200 supplies the lubricant to the bearing 11 based on the lubricant supply command output from the signal processing device 3c.

[0099] ​In a case where the flag value Flug is "1" (step S123: YES), it is indicated that the determination value S has become equal to or higher than the determination threshold value Sth again in the bearing determination processing after the lubricant is supplied to the bearing 11 in the previous step S125 (step S121: YES). In this case, the determination processing section 35 sets the flag value Flug to "0" (step S126), and outputs a control command instructing that an abnormality has occurred in the bearing 11 to the notification device 300 (hereinafter, also referred to as "abnormality notification command") (step S127), and ends the diagnosis processing.

[0100] The notification device 300 issues an alarm indicating that an abnormality has occurred in the bearing 11 based on the abnormality notification command output from the signal processing device 3c. Thereby, it is possible to notify the manager of the mechanical equipment 10 that an abnormality has occurred in the bearing 11 provided in the mechanical equipment 10.

[0101] In the diagnosis processing according to Embodiment 4, it is provided that the lubricant is supplied to the bearing 11 (step S125) in a case where an abnormality is determined in the bearing determination processing when the flag value is "0" (step S121: YES). Thereby, it is possible to maintain the lubrication state of the bearing 11 well.

[0102] In addition, in a case where an abnormality is determined again in the bearing determination processing when the flag value is "1" (step S121: YES) although the lubricant is supplied to the bearing 11 in step S125, it is provided that an abnormality has occurred in the bearing 11, and the manager of the mechanical equipment 10 is notified of the abnormality of the bearing 11 (step S127). Thereby, it is possible to prevent an abnormality notification due to simply a shortage of the lubricant.

[0103] As such, according to the bearing diagnosis processing according to Embodiment 4, it is possible to reduce the management burden of the mechanical equipment 10.

[0104] Explanation of Reference Numerals

[0105] 1, 1a, 1b: diagnosis system; 2: sensor; 3, 3a, 3b, 3c: signal processing device; 4: rotation sensor; 10: mechanical equipment; 11: bearing; 31: AD conversion section; 321: first processing section; 322: second processing section; 323: third processing section; 324: fourth processing section; 325: fifth processing section; 33: determination value calculation processing section; 34, 34a: storage section; 35: determination processing section; 111: inner ring; 112: outer ring; 113: rolling element; 200: pump; 300: notification device.

Claims

1. A signal processing apparatus that calculates a determination value for determining a lubrication state in a rolling device, based on a measurement signal acquired by a sensor, the signal processing apparatus comprising: a first processing section that band-limits and envelope processes the measurement signal to convert the measurement signal into a time domain signal; a second processing section that converts the time domain signal into a first frequency domain signal; a third processing section that converts a logarithmic spectrum of the first frequency domain signal into a first inverse frequency domain signal; a fourth processing section that generates a second inverse frequency domain signal that sets a higher-order cepstrum domain of the first inverse frequency domain signal containing a rotational frequency of the rolling device to a prescribed value; a fifth processing section that converts the second inverse frequency domain signal into a second frequency domain signal; and a determination value calculation processing section that calculates the determination value based on the second frequency domain signal.

2. The signal processing apparatus according to claim 1, wherein the measurement signal is a vibration signal acquired by a vibration sensor.

3. The signal processing apparatus according to claim 1, wherein the measurement signal is an ultrasonic wave signal acquired by an ultrasonic wave sensor.

4. The signal processing apparatus according to claim 1, wherein the measurement signal is an elastic wave signal acquired by an acoustic emission sensor.

5. The signal processing apparatus according to claim 1, wherein the fourth processing section sets a higher-order cepstrum domain equal to or higher than an inverse frequency obtained by multiplying the inverse of the rotational frequency of the rolling device by 0.9 to the prescribed value.

6. The signal processing apparatus according to claim 1, wherein the fourth processing section sets the higher-order cepstrum domain to zero.

7. The signal processing apparatus according to claim 1, wherein the fourth processing section generates the second inverse frequency domain signal using a rotational frequency of the rolling device that is set in advance.

8. The signal processing apparatus according to any one of claims 1 to 7, wherein the determination value calculation processing section sets a partial sum value of the second frequency domain signal to the determination value.

9. The signal processing apparatus according to claim 8, wherein the determination value calculation processing section calculates a partial sum value by band-limiting the second frequency domain signal.

10. The signal processing apparatus according to any one of claims 1 to 7, wherein the determination value calculation processing section sets any one of a maximum value, an effective value, a kurtosis factor, a peakness, and a skewness of a time domain signal obtained by performing an inverse high-speed Fourier transform process on the second frequency domain signal to the determination value.

11. A diagnosis system comprising: the information processing apparatus according to any one of claims 1 to 7; and a pump that supplies a lubricant to the rolling device, the signal processing apparatus further comprising a determination processing section that performs threshold determination on the determination value to determine a lubrication state in the rolling device, the determination processing section causing the pump to operate in a case where the lubrication state of the rolling device is determined to be abnormal after the lubrication state of the rolling device is determined to be normal. ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ wherein ​ ​ The determination processing section notifies of an abnormality in the lubrication state of the rolling device when the lubrication state of the rolling device is determined to be abnormal twice in succession.

12. A signal processing method of calculating a determination value for determining a lubrication state in a rolling device, based on a measurement signal acquired by a sensor, the signal processing method comprising the steps of: a first processing step of band-limiting and envelope processing the measurement signal to convert the measurement signal into a time domain signal; a second processing step of converting the time domain signal into a first frequency domain signal; a third processing step of converting a log spectrum of the first frequency domain signal into a first inverse frequency domain signal; a fourth processing step of generating a second inverse frequency domain signal in which a higher-order cepstrum domain containing a rotational frequency of the rolling device of the first inverse frequency domain signal is set to a prescribed value; a fifth processing step of converting the second inverse frequency domain signal into a second frequency domain signal; and a determination value calculation processing step of calculating the determination value based on the second frequency domain signal.

13. The signal processing method according to claim 12, wherein the measurement signal is a vibration signal acquired by a vibration sensor.

14. The signal processing method according to claim 12, wherein the measurement signal is an ultrasonic wave signal acquired by an ultrasonic wave sensor.

15. The signal processing method according to claim 12, wherein the measurement signal is an elastic wave signal acquired by an acoustic emission sensor.

16. The signal processing method according to claim 12, wherein in the fourth processing step, a higher-order cepstrum domain equal to or higher than an inverse frequency obtained by multiplying the inverse of the rotational frequency of the rolling device by 0.9 is set to the prescribed value.

17. The signal processing method according to claim 12, wherein in the fourth processing step, the higher-order cepstrum domain is set to zero.

18. The signal processing method according to claim 12, wherein in the fourth processing step, the second inverse frequency domain signal is generated using a rotational frequency of the rolling device set in advance.

19. The signal processing method according to any one of claims 12 to 18, wherein in the determination value calculation processing step, a partial sum value of the second frequency domain signal is set to the determination value.

20. The signal processing method according to claim 19, wherein in the determination value calculation processing step, a partial sum value is calculated by band-limiting the second frequency domain signal.

21. The signal processing method according to any one of claims 12 to 18, wherein in the determination value calculation processing step, any one of a maximum value, an effective value, a kurtosis factor, a peakness, and an asymmetry of a time domain signal obtained by performing a high-speed inverse Fourier transform process on the second frequency domain signal is set to the determination value.

22. The signal processing method according to any one of claims 12 to 18, further comprising a determination processing step of determining a lubrication state in the rolling device by threshold determining the determination value, in the determination processing step, ​ when the lubrication state of the rolling device is determined to be abnormal after the lubrication state of the rolling device is determined to be normal, supplying a lubricant to the rolling device, when the lubrication state of the rolling device is determined to be abnormal twice in succession, notifying that the lubrication state of the rolling device is abnormal.

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