Rolling bearing abnormality detection device and rolling bearing abnormality detection method

Abstract

The rolling bearing abnormality detection device of the present application detects vibration generated in a rolling bearing as vibration data and obtains a frequency spectrum thereof, determines a frequency indicating a peak in a prescribed frequency range including a theoretical frequency that brings a peak on the frequency spectrum when an abnormality occurs as a peak frequency, sets the peak frequency as a monitoring peak frequency that is an object of monitoring in the case where the peak frequency changes over time, and judges the presence or absence of an abnormality based on a peak value of the peak corresponding to the monitoring peak frequency.

Description

Technical Field

[0001] This invention relates to a rolling bearing anomaly detection device and a rolling bearing anomaly detection method. Background Technology

[0002] Rolling bearings are devices that support loads by placing rolling elements, such as balls or rollers, between two components (a shaft and a guide wheel), and are used in various devices with rotating bodies. Such rolling bearings can become malfunctioning due to abnormalities such as wear (abrasion or scratches), fatigue caused by deformation, and fusion caused by pressure, which can impede smooth rolling and lead to failures in the aforementioned devices. Therefore, for example, as proposed in Patent Document 1, abnormalities in the rolling bearings are monitored.

[0003] The evaluation method for mechanical equipment disclosed in Patent Document 1 is used to determine whether a mechanical equipment rotating relative to a stationary part has any abnormalities and the location of the abnormality. It comprises the following steps: a detection step of sensing the sound or vibration emitted by the mechanical equipment and outputting an electrical signal corresponding to the sensed sound or vibration; a processing step of performing frequency analysis on the electrical signal to obtain spectral data; a theoretical frequency calculation step of calculating the theoretical frequency that would cause a peak in the spectrum when an abnormality occurs a predetermined number of times for each of the multiple mechanical elements of the mechanical equipment, based on the rotation information of the rotating body; a detection frequency range determination step of at least once finding the minimum frequency difference between the multiple mechanical elements, assuming a sensing range coefficient of 0.5 or less, and using any one of the minimum frequency differences multiplied by the sensing range coefficient as the detection frequency range; a judgment step of determining whether the peak frequency of the spectral data is within the range of the theoretical frequency ± the detection frequency range; and an abnormality diagnosis step of determining the location of the abnormality in the mechanical element based on the result of the judgment step.

[0004] However, in Patent Document 1, the presence or absence of an anomaly is diagnosed based on the presence or absence of spectral data peaks within a detection frequency range obtained from theoretical frequencies that would cause peaks in the spectrum when an anomaly occurs. However, in reality, besides the vibration of rolling bearings, there are various other vibrations, such as gear meshing or its sidebands, or multiples of shaft rotation (higher harmonic components). Therefore, the method disclosed in Patent Document 1 may incorrectly detect vibrations that are not those of the rolling bearing as vibrations of the rolling bearing.

[0005] Existing technical documents

[0006] Patent documents

[0007] Patent Document 1: Japanese Patent Publication No. 2017-101954 Summary of the Invention

[0008] In view of the above, the object of the present invention is to provide a rolling bearing anomaly detection device and a rolling bearing anomaly detection method that can appropriately sense the vibration of rolling bearings.

[0009] The rolling bearing anomaly detection device and method of the present invention detect the vibration generated in the rolling bearing as vibration data and calculate its spectrum. Based on the spectrum, within a specified frequency range that includes the theoretical frequency that brings a peak in the spectrum when an anomaly occurs, the frequency representing the peak is determined as the peak frequency. When the peak frequency changes over time, it is set as the monitoring peak frequency of the monitored object. The presence or absence of an anomaly is determined based on the peak value of the peak corresponding to the monitoring peak frequency.

[0010] The above and other objects, features and advantages of the present invention will become more apparent from the following detailed description and accompanying drawings. Attached Figure Description

[0011] Figure 1 This is a block diagram illustrating the configuration of the rolling bearing abnormality detection device in the implementation method.

[0012] Figure 2 This is a diagram used to illustrate mechanical equipment equipped with rolling bearings.

[0013] Figure 3 This is a schematic diagram illustrating the method for determining the peak frequency.

[0014] Figure 4 This is a schematic diagram illustrating a method for determining the peak frequency when using multiple vibration detection units.

[0015] Figure 5 This is a schematic diagram illustrating the first method for setting the monitoring peak frequency.

[0016] Figure 6 This is a schematic diagram illustrating the second method for setting the monitoring peak frequency.

[0017] Figure 7 This is a diagram used to illustrate the method for identifying anomalies.

[0018] Figure 8 This is a flowchart illustrating the operation of the rolling bearing anomaly detection device in relation to the monitoring peak frequency setting mode.

[0019] Figure 9 This is a flowchart illustrating the operation of the rolling bearing anomaly detection device in relation to the anomaly monitoring mode. Detailed Implementation

[0020] Hereinafter, one or more embodiments of the present invention will be described with reference to the accompanying drawings. However, the scope of the present invention is not limited to the disclosed embodiments. Furthermore, configurations given the same reference numerals in the various drawings represent the same configurations, and their descriptions are appropriately omitted. In this specification, reference numerals without superscripts or subscripts are used in general contexts, and reference numerals with superscripts or subscripts are used when referring to specific configurations.

[0021] The rolling bearing anomaly detection device in this embodiment includes: a vibration detection unit that detects vibrations generated in the rolling bearing as vibration data; a spectrum processing unit that calculates the spectrum of the vibration data detected by the vibration detection unit; a peak frequency determination unit that, based on the spectrum calculated by the spectrum processing unit, determines the frequency representing the peak as the peak frequency within a predetermined frequency range that includes the theoretical frequency that causes a peak in the spectrum when an anomaly occurs; a monitoring target setting unit that, when the peak frequency determined by the peak frequency determination unit changes over time, sets the peak frequency as the monitoring peak frequency of the monitoring target; and an anomaly judgment unit that determines whether the rolling bearing has an anomaly based on the peak value of the peak corresponding to the monitoring peak frequency set by the monitoring target setting unit. Further details will be provided below.

[0022] Figure 1 This is a block diagram illustrating the configuration of the rolling bearing abnormality detection device in the implementation method. Figure 2 This is a diagram used to illustrate mechanical equipment equipped with rolling bearings. Figure 3 This is a schematic diagram illustrating the method for determining the peak frequency. Figure 3 The upper part represents the frequency spectrum of the theoretical frequency ft. Figure 3 The upper part represents the frequency spectrum of the theoretical frequency ft within the frequency range ft-dft to ft+dft. Figure 3 The middle part represents the frequency spectrum ranging from 2*ft-2*dft to 2*ft+2*dft, which is twice the theoretical frequency ft. Figure 3 The lower part represents the frequency spectrum within the range of 3*ft-3*dft to 3*ft+3*dft, which is three times the theoretical frequency ft. The horizontal axis of each graph represents frequency, and the vertical axis represents amplitude (level). Figure 4 This is a schematic diagram illustrating a method for determining the peak frequency when using multiple vibration detection units. Figure 4 A represents the first case where the peak frequency can be determined. Figure 4 B represents the second case where the peak frequency cannot be determined. Figure 4 A and Figure 4In section B, following the order from left to right on the drawing, the spectrum is calculated based on the vibration data from the first vibration detection unit 1-1, the spectrum is calculated based on the vibration data from the second vibration detection unit 1-2, and the spectrum is calculated based on the vibration data from the third vibration detection unit 1-3. The upper, middle, and lower portions are respectively related to... Figure 3 Similarly, the horizontal and vertical axes of these graphs are also... Figure 3 same. Figure 5 This is a schematic diagram illustrating the first method for setting the monitoring peak frequency. Figure 5 A represents the spectrum after new installation or maintenance (the spectrum when the rolling bearing is in good condition). Figure 5 B indicates from Figure 5 The spectrum shown in Figure A is the spectrum one year after the start of the scenario (the spectrum after changes over time, and the spectrum after a specified period). The upper, middle, and lower portions are respectively related to... Figure 3 Similarly, the horizontal and vertical axes of these graphs are also... Figure 3 same. Figure 6 This is a schematic diagram illustrating the second method for setting the monitoring peak frequency. Figure 6 The horizontal axis represents time, and the vertical axis represents the rate of change of the peak frequency. Figure 7 This is a diagram used to illustrate the method for identifying anomalies. Figure 7 The horizontal axis represents the elapsed time, and the vertical axis represents the peak value of the peak in the monitored peak frequency.

[0023] The implementation method relates to a rolling bearing abnormality detection device VD, for example, such as... Figure 1 As shown, it includes a vibration detection unit 1 (1-1 to 1-3), a control processing unit 2, an input unit 3, an output unit 4, an interface unit (IF unit) 5, and a storage unit 6.

[0024] The vibration detection unit 1 is connected to the control processing unit 2 and is a device that detects the vibration generated by the rolling bearing as vibration data according to the control of the control processing unit 2. There may be one vibration detection unit 1, but in this embodiment there are multiple units; as an example, there are three, namely the first to third vibration detection units 1-1 to 1-3. These first to third vibration detection units 1-1 to 1-3 are arranged on a device, such as a machine or similar device equipped with a rolling bearing, which is the object of detection for abnormalities.

[0025] The mechanical device described is an example of a device equipped with rolling bearings; however, it can be any device as long as it includes rolling bearings. For example, the mechanical device M is... Figure 2The reducer M shown generally includes first to third rolling bearings BE-1 to BE-3, first and second rotating shafts AX-1 and AX-2, first and second gears GA-1 and GA-2, and a frame (housing) that houses these first to third rolling bearings BE-1 to BE-3, first and second rotating shafts AX-1 and AX-2, and first and second gears GA-1 and GA-2. The first rotating shaft AX-1 is fixed to the first gear GA-1 and is the rotating shaft of the first gear GA-1, supported by the first rolling bearing BE-1. The second rotating shaft AX-2 is fixed to the second gear GA-2 and is the rotating shaft of the second gear GA-1, supported by the second and third rolling bearings BE-2 and BE-3. The first gear GA-1 and the second gear GA-2 mesh with each other. For example, the rotational force generated by the rotation of the first rotating shaft AX-1 is transmitted to the second rotating shaft AX-2 via the first and second gears GA-1 and GA-2, and the second rotating shaft AX-2 rotates.

[0026] For the speed reducer M configured in this way, the first to third vibration detection units 1-1 to 1-3 are respectively disposed on the outer periphery of the first to third rolling bearings BE-1 to BE-3. Furthermore, the vibration detection unit 1 is not limited to being disposed on the rolling bearing BE, but may also be disposed, for example, on the frame. In short, the vibration detection unit 1 (1-1 to 1-3) is disposed at the location where vibration propagation caused by the rolling bearing BE occurs. Such a vibration detection unit 1 (1-1 to 1-3), for example, is an acceleration sensor or an AE (Acoustic Emission) sensor, and an appropriate sensor can be used according to the frequency of the vibration of the object being detected. The vibration detection unit 1 (1-1 to 1-3) outputs the detection results as vibration data to the control processing unit 2.

[0027] Input unit 3 is connected to control processing unit 2. For example, it is a device that inputs various instructions, such as instructions to begin determining the peak frequency or instructions to begin detecting abnormalities (start monitoring), and various data required to operate the rolling bearing abnormality detection device VD, such as the name of the mechanical equipment being detected (monitored). Examples include multiple input switches, a keyboard, and a mouse with assigned functions. Output unit 4 is connected to control processing unit 2 and is a device that outputs instructions or data input from input unit 3, as well as vibration data, according to the control of control processing unit 2. Examples include display devices such as CRT monitors, LCD monitors, and OLED monitors, or printing devices such as printers.

[0028] Alternatively, the input unit 3 and the output unit 4 can also be configured as a touch panel. In the case of a touch panel, the input unit 3 is, for example, a position input device that detects the operating position using a resistive film or capacitive method and inputs the information, while the output unit 4 is a display device. In this touch panel, the position input device is located on the display surface of the display device, displaying one or more candidate input contents that can be input to the display device. When the user touches the display position showing the desired input content, the position input device detects the position, and the content displayed at the detected position is input to the rolling bearing malfunction detection device VD as the user's input. Such a touch panel allows users to easily and intuitively understand the input operation, thus providing a rolling bearing malfunction detection device VD that is easy for users to use.

[0029] The IF section 5 is connected to the control processing section 2 and is a circuit that performs data input / output with external devices according to the control of the control processing section 2. Examples include an interface circuit for serial communication (RS-232C), an interface circuit using the Bluetooth standard, an interface circuit for infrared communication using the IrDA (Infrared Data Association) standard, and an interface circuit using the USB (Universal Serial Bus) standard. Furthermore, since the IF section 5 is a circuit for communication with external devices, it can also be, for example, a data communication card or a communication interface circuit conforming to the IEEE 802.11 standard.

[0030] The storage unit 6 is connected to the control processing unit 2 and is a circuit that stores various prescribed programs and various prescribed data according to the control of the control processing unit 2. These various prescribed programs include, for example, a control processing program that controls each part 1, 3 to 6 of the rolling bearing abnormality detection device VD according to its function; a spectrum processing program that calculates the spectrum of the vibration data detected by the vibration detection units 1 (1-1 to 1-3); a peak frequency determination program that, based on the spectrum obtained by the spectrum processing program, determines the frequency representing the peak as the peak frequency within a prescribed frequency range that includes the theoretical frequency that would cause a peak in the spectrum when an abnormality occurs; a monitoring object setting program that sets the peak frequency determined by the peak frequency determination program as the monitoring peak frequency of the monitoring object when the peak frequency changes over time; and an abnormality judgment program that determines whether the rolling bearing has an abnormality based on the peak value of the peak corresponding to the monitoring peak frequency set by the monitoring object setting program, etc. The various specified data include, for example, vibration data detected by the vibration detection unit 1 (1-1 to 1-3), theoretical frequency, peak frequency determined by the peak frequency determination program, monitoring peak frequency set by the monitoring object setting program, and data required to execute each program. Such a storage unit 6 includes, for example, a non-volatile storage element, i.e., ROM (Read Only Memory), or a rewritable non-volatile storage element, i.e., EEPROM (Electrically Erasable Programmable Read Only Memory). Furthermore, the storage unit 6 includes the working memory of the so-called control processing unit 2, i.e., RAM (Random Access Memory), which stores data generated during the execution of the specified programs. Additionally, the storage unit 6 may also include a hard disk device capable of storing a relatively large amount of learning data.

[0031] The control processing unit 2 is a circuit that controls each of the sections 1, 3 to 6 of the rolling bearing abnormality detection device VD to detect abnormalities in the rolling bearing (abnormalities in mechanical equipment equipped with rolling bearings). The control processing unit 2 includes, for example, a CPU (Central Processing Unit) and its peripheral circuitry. By executing the control processing program, the control processing unit 2 functionally comprises a control unit 21, a spectrum processing unit 22, a peak frequency determination unit 23, a monitoring object setting unit 24, and an abnormality judgment unit 25.

[0032] The control unit 21 controls each of the sections 1, 3 to 6 of the rolling bearing anomaly detection device VD, respectively, and is responsible for the overall control of the rolling bearing anomaly detection device VD. The control unit 21 controls the rolling bearing anomaly detection device VD according to its operating mode. In this embodiment, since the rolling bearing anomaly detection device VD determines whether there is an anomaly in the rolling bearing after setting the monitoring peak frequency, the operating mode includes a mode for setting the monitoring peak frequency (monitoring peak frequency setting mode) and a mode for monitoring anomalies in the rolling bearing (anomalies in the mechanical equipment equipped with the rolling bearing) (anomaly monitoring mode). The control unit 21 stores the vibration data detected by the vibration detection units 1 (1-1 to 1-3) in the storage unit 6 in a corresponding manner with the detection time. More specifically, the control unit 21 acquires the detection results of the vibration detection units 1 (1-1 to 1-3) at a predetermined sampling interval for a predetermined time period (predetermined time length), and stores each detection result consecutively in time sequence according to the sampling interval as vibration data in the storage unit 6 in a corresponding manner with the detection time. Furthermore, since the vibration data depends on the rotational speed of the reducer M, in this embodiment, a rotary meter (e.g., a pulse generator (rotary encoder)) for measuring the rotational speed of the reducer M is arranged in the reducer M. The control unit 21 acquires the output of the rotary meter synchronously with the detection results of the vibration detection unit 1 (1-1 to 1-3), and stores each output of the rotary meter in the storage unit 6 corresponding to the vibration data. That is, the control unit 21 acquires the detection results of the vibration detection unit 1 (1-1 to 1-3) and the output of the rotary meter for a predetermined time period (predetermined time length) at a predetermined sampling interval, and stores each detection result and each output in a time sequence according to the sampling interval as vibration data and rotational speed data corresponding to the detection time in the storage unit 6. Because the change of the peak frequency is observed over time, the control unit 21 can perform the process of acquiring vibration data and rotational speed data at least twice at predetermined intervals. The predetermined period (first period, peak frequency monitoring setting period) can be appropriately set to, for example, three months, six months, twelve months, etc. In addition, even without sensors (without using a gyrometer), vibration components caused by changes in the rotational speed of the reducer M can be extracted from the vibration data, and rotational speed data can be generated based on the extracted vibration components.

[0033] The spectrum processing unit 22 calculates the spectrum of the vibration data detected by the vibration detection unit 1 (1-1 to 1-3). More specifically, as preprocessing, the spectrum processing unit 22, using conventional methods, eliminates (corrects) the influence of speed variation from the vibration data based on the speed data, calculates the vibration data when the reducer M rotates at a constant speed of a specified speed, and calculates the spectrum of the vibration data by performing, for example, a fast Fourier transform on the calculated vibration data. The spectrum is calculated for each vibration data acquired during each monitoring peak frequency setting period.

[0034] The peak frequency determination unit 23 determines the frequency representing the peak as the peak frequency within a predetermined frequency range that includes the theoretical frequency that causes a peak in the spectrum when an anomaly occurs, based on the spectrum obtained by the spectrum processing unit 22. In this embodiment, the peak frequency determination unit 23 also determines one or more frequencies that represent the peak at integer multiples of the peak frequency as one or more integer multiple peak frequencies. For example, it determines a peak frequency that is twice the frequency and a peak frequency that is three times the frequency. In addition, the integer multiple frequency is not limited to this, and it can be appropriately set, for example, frequencies that are 2 times, 3 times, and 4 times, frequencies that are 3 times and 4 times, frequencies that are 2 times and 4 times, frequencies that are 3 times and 5 times, etc. Moreover, in this embodiment, the peak frequency determination unit 23 ultimately sets the frequency that can be set as the peak frequency to at least two of the multiple vibration data detected by the multiple vibration detection units 1.

[0035] The theoretical frequency ft that produces a peak in the spectrum when an anomaly occurs is known, and varies depending on the location of the damage to the rolling bearing (bearing damage), for example, as shown in Table 1 below. The location of the bearing damage includes, for example, the inner wheel, outer wheel, rolling elements, and cage. Here, fti is the theoretical frequency at which bearing damage occurs on the inner wheel, fto is the theoretical frequency at which bearing damage occurs on the outer wheel, ftb is the theoretical frequency at which bearing damage occurs on the rolling elements, and ftm is the theoretical frequency at which bearing damage occurs on the cage. d is the diameter of the rolling element, D is the pitch circle diameter of the rolling element, Z is the number of rolling elements, and α is the contact angle.

[0036] Table 1

[0037]

[0038] The frequency range used to determine the peak frequency relative to such theoretical frequencies ft (fti, fto, ftb, ftm) is, for example, ±dft centered on the theoretical frequency ft, set for multiples of 1 to n as shown in Table 2 below. Additionally, the operator * is the multiplication operator. For example, the frequency ranges relative to 1, 2, and 3 times the theoretical frequency at which bearing damage occurs on the outer wheel are fto-dft to fto+dft, 2*fto-2*dft to 2*fto+2*dft, and 3*fto-3*dft to 3*fto+3*dft.

[0039] Table 2

[0040] Center frequency Lower limit frequency Upper limit frequency 1x ft ft-dft ft+dft 2 times 2*ft 2*(ft-dft) 2*(ft+dft) 3 times 3*ft 3*(ft-dft) 3*(ft+dft) 4 times 4*ft 4*(ft-dft) 4*(ft+dft) … … … … n times n*ft n*(ft-dft) n * (ft + dft)

[0041] When the peak frequency and integer multiples of the peak frequency are determined, the peak frequency determination unit 23 determines the peak frequency, which is the frequency of a peak that coexists in the frequency spectrum of the theoretical frequency range and the frequency spectrum of the frequency range of integer multiples of the theoretical frequency. For example, in a vibration detection unit 1, the peak frequency is determined based on its vibration data. Figure 3 In the cases shown for each spectrum, frequency f1 has a peak in the spectrum (upper part) of the frequency range ft-dft to ft+dft of the theoretical frequency ft. Frequency 2*f1, which is twice the frequency of f1, and frequency 3*f1, which is three times the frequency of ft, do not have peaks in the spectrum (middle part) of the frequency range 2*ft-2*dft to 2*ft+2*dft of the theoretical frequency ft, and in the spectrum (lower part) of the frequency range 3*ft-3*dft to 3*ft+3*dft of the theoretical frequency ft. Therefore, the peak frequency determination unit 23 does not determine frequency f1 as the peak frequency. On the other hand, frequency f2 has a peak in the spectrum (upper part) of the frequency range ft-dft to ft+dft of the theoretical frequency ft. Frequency 2*f2 (twice the theoretical frequency ft) and frequency 3*f2 (three times the theoretical frequency ft) also have peaks in the spectrum (middle part) of the frequency range 2*ft-2*dft to 2*ft+2*dft of the theoretical frequency ft, and in the spectrum (lower part) of the frequency range 3*ft-3*dft to 3*ft+3*dft of the theoretical frequency ft. Therefore, the peak frequency determination unit 23 determines frequency f2 as the peak frequency. For example, by performing this determination process on each peak (e.g., a peak with an amplitude of a predetermined threshold or higher) existing in the frequency range ft-dft to ft+dft of the theoretical frequency ft, the peak frequency and integer multiples of the peak frequency can be determined.

[0042] When using multiple vibration detection units 1, when determining the peak frequency and integer multiples of the peak frequency, the vibration generated in the rolling bearing BE will propagate to the rotating shaft AX, gear GA, or the frame, and be detected by the multiple vibration detection units 1. Therefore, for at least two vibration data points detected by the multiple vibration detection units 1, the frequency of the peak that coexists in the frequency spectrum of the theoretical frequency range and the frequency spectrum of the frequency range of integer multiples of the theoretical frequency is determined by the peak frequency determination unit 23 as the peak frequency. For example, in the three first to third vibration detection units 1-1 to 1-3, the peak frequency is determined based on their respective vibration data. Figure 4 A and Figure 4 In the cases of the spectra shown in B, firstly, in Figure 4 In case B, in the first vibration detection unit 1-1, the peak of frequency f4 in the frequency range of the theoretical frequency ft (ft-dft to ft+dft), the frequency 2*f4 in the frequency range of 2*ft-2*dft to 2*ft+2*dft (middle part) which is twice the theoretical frequency ft, and the frequency 3*f4 in the frequency range of 3*ft-3*dft to 39ft+3*dft (lower part) which is three times the theoretical frequency ft. A peak also exists in f4, therefore, frequency f4 becomes a candidate for peak frequency. However, in the second and third vibration detection units 1-2 and 1-3, there are no peaks in the spectrum (upper part) of each theoretical frequency ft in each frequency range ft-dft to ft+dft, in each spectrum (middle part) of each theoretical frequency ft twice in each frequency range 2*ft-2*dft to 2*ft+2*dft, and in each spectrum (lower part) of each frequency range 3*ft-3*dft to 3*ft+3*dft three times in each theoretical frequency ft. Therefore, the peak frequency determination unit 23 ultimately does not determine frequency f4 as the peak frequency. On the other hand, in Figure 4In case A, because in the first vibration detection unit 1-1, the peak of frequency f3 in the frequency range of the theoretical frequency ft (ft-dft to ft+dft) is in the frequency range of 2*ft t-2*dft to 2*ft+2*dft (middle part) and the frequency range of 3*ft t-3*dft is in the frequency range of 3*ft t-3*dft. A peak also exists in the frequency 3*f3 of the spectrum (lower part) of the range dft to 3*ft+3*dft. Therefore, frequency f4 becomes a candidate for the peak frequency. Furthermore, in the second and third vibration detection units 1-2 and 1-3, peaks also exist in the spectrum (upper part) of each frequency range ft-dft to ft+dft of each theoretical frequency ft, the spectrum (middle part) of each frequency range 2*ft-2*dft to 2*ft+2*dft of each twice the theoretical frequency ft, and the spectrum (lower part) of each frequency range 3*ft-3*dft to 3*ft+3*dft of each three times the theoretical frequency ft. Therefore, the peak frequency determination unit 23 finally determines frequency f3 as the peak frequency. For example, by performing such determination processing on each peak (e.g., a peak with an amplitude above a predetermined threshold) existing in the frequency range ft-dft to ft+dft of the theoretical frequency ft in the spectrum of vibration data detected by the first vibration detection unit 1-1, the peak frequency can be finally determined, and the peak frequency and integer multiples of the peak frequency can be determined. Figure 4 In the case shown in A, all three vibration detection units -1 to 1-3 share a common wave peak; however, as mentioned above, there can be at least two.

[0043] The monitoring target setting unit 24 sets the peak frequency determined by the peak frequency determination unit 23 as the monitoring peak frequency of the monitoring target when the peak frequency changes over time. In this embodiment, the monitoring target setting unit 24 also additionally sets at least one of the one or more integer multiple peak frequencies determined by the peak frequency determination unit 23 as the monitoring peak frequency when the peak frequency changes over time synchronously with the change of the peak frequency.

[0044] For example, such as Figure 5 As shown in Figure A, after the reducer M is newly installed or overhauled, and given the determined first peak frequency a [Hz] and first integer multiples of peak frequencies 2*a and 3*a [Hz], as well as the second peak frequency b [Hz] and second integer multiples of peak frequencies 2*b and 3*b [Hz], one year later, as follows... Figure 5As shown in B, the peaks of the second peak frequency b [Hz] and the second integer multiple peak frequencies 2*b and 3*b [Hz] do not change with time. On the other hand, when the first peak frequency a [Hz] and the first integer multiple peak frequencies 2*a and 3*a [Hz] change synchronously with time by Δc, 2*Δc, and 3*Δc respectively, the monitoring target setting unit 24 sets the first peak frequency a [Hz] and the first integer multiple peak frequencies 2*a and 3*a [Hz] as the monitoring peak frequencies.

[0045] As described above, although the monitoring peak frequency can be set by changing it once over time, in this embodiment, the monitoring peak frequency is set by changing it multiple times over time. That is, the monitoring target setting unit 24 sets the peak frequency determined by the peak frequency determination unit as the monitoring peak frequency of the monitoring target when the peak frequency changes multiple times over time at multiple different time points.

[0046] For example, during the period of monitoring the peak frequency setting, the results of multiple observations of the peak frequency determined by the peak frequency determination unit 23 for each specified period (the second period, the observed period) are as follows: Figure 6 As shown. Figure 6 As shown, if multiple observations are conducted during the monitoring peak frequency setting period (one year in this example, 12 observations for each month in this example), using... Figure 5 The second peak frequency b[Hz](Δ) remains constant in each iteration. On the other hand, utilizing... Figure 5 The first peak frequency a [Hz](●) varies gradually with time in each iteration, exhibiting multiple variations over time. Figure 6 In the example shown, the rate of change per unit time with time (=Δc / (1 month)) is approximately constant (assuming 1 month is 30 days). Furthermore, the aforementioned frequency changes not only increase, but sometimes decrease or increase / decrease discontinuously. The monitoring target setting unit 24 sets the first peak frequency a [Hz] of the observed trend of multiple changes with time, each gradually changing, as the monitoring peak frequency of the monitoring target. On the other hand, the monitoring target setting unit 24 sets the second peak frequency b [Hz] of the monitoring target, which hardly changes with time each time, as the monitoring peak frequency of the monitoring target. Additionally, in Figure 6 Although only the peak frequency is shown, the same applies to the peak frequencies that are integer multiples of the peak frequency (the first integer multiple peak frequency 2*a, 3*a [Hz], the second integer multiple peak frequency 2*b, 3*b [Hz]).

[0047] The abnormality determination unit 25 determines whether there is an abnormality in the rolling bearing based on the peak value of the peak in the monitored peak frequency set by the monitored object setting unit 24. In the present embodiment, the abnormality determination unit 25 determines whether there is an abnormality in the rolling bearing based on a prescribed threshold value based on the peak value of the peak in the monitored peak frequency when the rolling bearing is in good condition. When the rolling bearing is in good condition means, for example, soon after newly installing the rolling bearing (the mechanical equipment equipped with the rolling bearing) (at the time of new installation) or soon after overhauling the rolling bearing (the mechanical equipment equipped with the rolling bearing) (at the time of overhaul), etc., when it can be confirmed that there is no abnormality in the rolling bearing (the mechanical equipment equipped with the rolling bearing). The threshold value can be appropriately set based on the peak value of the peak in the monitored peak frequency when the rolling bearing is in good condition. For example, when taking the peak value of the peak in the monitored peak frequency when the rolling bearing is in good condition as a reference 1, it is set to an integer value such as 3, 4, 5, etc. (an integer multiple of the reference 1). In this case, the abnormality determination unit 25 obtains the ratio of the peak value of the peak corresponding to the monitored peak frequency at the time of the current abnormality determination to the peak value of the peak in the monitored peak frequency when the rolling bearing is in good condition as an evaluation value, and determines whether there is an abnormality in the rolling bearing based on the obtained evaluation value and the prescribed threshold value (evaluation value = (the peak value of the peak corresponding to the monitored peak frequency at the time of the current abnormality determination) / (the peak value of the peak in the monitored peak frequency when the rolling bearing is in good condition)).

[0048] In Figure 7 In the example shown, the threshold value, in addition to the first threshold Th1 for determining whether there is an abnormality, further has a second threshold Th2 for determining the omen of the abnormality (reference 1 < Th2 < Th1). The abnormality determination unit 25 determines whether there is an abnormality, and in the case of determining that there is an abnormality, not only outputs a warning of the abnormality from the output unit 4, but also determines whether there is an omen, and in the case of determining that there is an omen, outputs the omen of the abnormality from the output unit 4. For example, the rolling bearing abnormality detection device VD, for example, obtains the peak value of the peak corresponding to the monitored peak frequency at a prescribed time interval such as one day or one week, obtains the evaluation value of the obtained peak value through the abnormality determination unit 25, compares the obtained evaluation value with the first and second threshold values Th1 and Th2 respectively. When the result of the comparison is that the obtained evaluation value is above the first threshold Th1, it is determined as an abnormality and a warning of the abnormality is output from the output unit 4. When the obtained evaluation value is less than the first threshold Th1 and above the second threshold Th2, it is determined as an omen of the abnormality, and a warning of the omen is output from the output unit 4. When the obtained evaluation value is less than the second threshold Th2, it is determined that there is neither an abnormality nor an omen, and no abnormality and no omen are output from the output unit 4. In addition, the process can also be ended without outputting no abnormality and no omen.

[0049] The control processing unit 2, input unit 3, output unit 4, IF unit 5, and storage unit 6 can be configured, for example, by a desktop, laptop, or tablet computer.

[0050] Next, the operation of this embodiment will be explained. Figure 8 This is a flowchart illustrating the operation of the rolling bearing anomaly detection device in relation to the monitoring peak frequency setting mode. Figure 9 This is a flowchart illustrating the operation of the rolling bearing anomaly detection device in relation to the anomaly monitoring mode.

[0051] The rolling bearing anomaly detection device VD configured in this way performs the necessary initialization of each part and starts working once the power is turned on. The control processing unit 2, by executing its control processing program, functionally consists of a control unit 21, a spectrum processing unit 22, a peak frequency determination unit 23, a monitoring object setting unit 24, and an anomaly judgment unit 25.

[0052] The rolling bearing anomaly detection device VD according to the embodiment, as described above, determines whether the rolling bearing has an anomaly after setting the monitoring peak frequency. Therefore, firstly, the operation of the rolling bearing anomaly detection device related to setting the monitoring peak frequency will be explained, and secondly, the operation of the rolling bearing anomaly detection device related to determining whether the rolling bearing has an anomaly will be explained.

[0053] For example, when it is in good condition after maintenance, etc., execute Figure 8 Each of the processes S1 to S7 shown stores the monitoring peak frequency when the status is good as a reference for its change over time in the storage unit 6. For example, when the monitoring peak frequency setting mode is specified and it is first input to the input unit 3, Figure 8 Each of the processes S1 to S8 shown is repeatedly executed for each observed period during the monitoring peak frequency setting period.

[0054] exist Figure 8 In the rolling bearing abnormality detection device VD, firstly, the control unit 21 of the control processing unit 2 acquires the detection results of the vibration detection unit 1 (1-1 to 1-3) and the output of the rotator at a predetermined sampling interval within a predetermined time. Then, the detection results and outputs, which are sequentially stored in the time sequence according to the sampling interval, are stored as vibration data and rotational speed data corresponding to the detection time in the storage unit 6 (S1).

[0055] Then, the rolling bearing abnormality detection device VD, through the spectrum processing unit 22 of the control processing unit 2, eliminates (corrects) the influence of speed change from the vibration data based on the speed data, calculates the vibration data when the reducer M rotates at a constant speed of a specified speed, and stores it in the storage unit 6 (S2).

[0056] Then, the rolling bearing abnormality detection device VD calculates the spectrum of the obtained vibration data by the spectrum processing unit 22 and stores it in the storage unit 6 (S3).

[0057] Then, the rolling bearing abnormality detection device VD calculates the theoretical frequency ft that causes a peak in the spectrum when an abnormality occurs, as shown in Table 1, through the peak frequency determination unit 23 of the control processing unit 2, and stores it in the storage unit 6 (S4). Alternatively, the theoretical frequency ft can also be calculated in advance and stored in the storage unit 6 for later use.

[0058] Then, the rolling bearing abnormality detection device VD, through the peak frequency determination unit 23, determines the frequency range shown in Table 2, which includes the theoretical frequency ft used for detecting peak frequencies, and the frequency range that includes integer multiples of the theoretical frequency ft used for detecting integer multiples of peak frequencies, and stores them in the storage unit 6 (S5). Alternatively, each frequency range can be predetermined and stored in the storage unit 6 for later retrieval.

[0059] Then, the rolling bearing abnormality detection device VD utilizes the peak frequency determination unit 23. Figure 3 The above processing temporarily determines the peak frequency and integer multiples of the peak frequency, and stores them in the storage unit 6 (S6).

[0060] Then, the rolling bearing abnormality detection device VD utilizes the peak frequency determination unit 23. Figure 4 The above processing determines the final peak frequency, determines the peak frequencies that are integer multiples of each other, and stores them in the storage unit 6 (S7).

[0061] Then, the rolling bearing abnormality detection device VD is utilized by the monitoring target setting unit 24 of the control processing unit 2. Figure 6 The above process sets the monitoring peak frequency and stores it in the storage unit 6 (S8). Here, for example, the monitoring peak frequency set in the process at the end of the monitoring peak frequency setting period is finally set as the monitoring peak frequency.

[0062] These processes allow for the setting and customization of monitoring peak frequencies for physical equipment with rolling bearings.

[0063] After setting the monitoring peak frequency, the operator (user) first sets and stores the first and second thresholds Th1 and Th2. For example, when the abnormal monitoring mode is specified and input is started into the input unit 3, Figure 9 Each of the processes S11 to S14 shown is executed repeatedly every half day or every day, for example, in the case of operation of 8 hours a day, or in the case of continuous operation (24-hour operation).

[0064] When setting the first and second thresholds Th1 and Th2, the peak value of the wave peak in the monitoring wave peak frequency is obtained when the mechanical equipment rotates at a constant speed when it is in good condition. For example, based on the peak value, 6 and 3 are set as the first and second thresholds Th1 and Th2 respectively, and stored in the storage unit 6.

[0065] exist Figure 9 In the process, the rolling bearing anomaly detection device VD calculates the peak value of the wave corresponding to the monitored wave peak frequency and calculates its evaluation value (S11). More specifically, the control unit 21 calculates each vibration data based on the detection results of the first to third vibration detection units 1-1 to 1-3, the spectrum processing unit 22 calculates each spectrum of each vibration data, and the anomaly judgment unit 25 searches for the wave peak corresponding to the monitored wave peak frequency from each spectrum, calculates the peak value of the searched wave peak, and calculates the evaluation value of the calculated wave peak.

[0066] Then, the rolling bearing anomaly detection device VD determines, via the anomaly judgment unit 25 of the control processing unit 2, whether the evaluation value of the peak corresponding to the monitoring peak frequency obtained in processing S11 is above the first or second threshold Th1 or Th2. If the result of this determination is that the evaluation value is above the first or second threshold Th1 or Th2 (yes, the evaluation value is above the first threshold Th1, or the evaluation value is above the second threshold Th2), the rolling bearing anomaly detection device VD then executes processing S13 and ends the current processing. On the other hand, if the result of this determination is that the evaluation value is neither above the first threshold Th1 nor above the second threshold Th2 (no), the rolling bearing anomaly detection device VD then executes processing S14 and ends the current processing.

[0067] In this process S13, the rolling bearing abnormality detection device VD, through the abnormality judgment unit 25, determines that there is an abnormality when the evaluation value is above the second threshold Th2 and below the first threshold Th1, and outputs a warning of the abnormality from the output unit 4. When the evaluation value is above the first threshold Th1, it determines that there is an abnormality and outputs a warning of the abnormality from the output unit 4.

[0068] In the above process S14, the rolling bearing abnormality detection device Vd outputs "no abnormality" and "no warning signs (within the allowable range)" from the output unit 4 through the abnormality judgment unit 25.

[0069] Through this process, the rolling bearing (mechanical equipment equipped with the rolling bearing) can be monitored, it can be determined whether there are any signs of the abnormality and whether the abnormality exists, and the determination result can be output.

[0070] The vibration frequency of rolling bearings changes over time due to factors such as wear. However, the frequency of vibrations caused by gear meshing or high-harmonic components of rotating shafts is generally considered to remain constant over time. The rolling bearing anomaly detection device VD and the rolling bearing anomaly detection method mounted on it, according to this embodiment, can appropriately sense the vibration of rolling bearings by setting the determined peak frequency as the monitoring peak frequency of the monitored object when the peak frequency changes over time. Therefore, the rolling bearing anomaly detection device VD and the rolling bearing anomaly detection method can more appropriately determine whether a rolling bearing has an anomaly.

[0071] The aforementioned rolling bearing anomaly detection device VD and rolling bearing anomaly detection method additionally set at least one of one or more integer multiples of the peak frequency, representing the peak frequency as an integer multiple of the peak frequency, as the monitoring peak frequency. Therefore, the vibration of the rolling bearing can be sensed more appropriately. Consequently, the rolling bearing anomaly detection device VD and rolling bearing anomaly detection method can more appropriately determine whether the rolling bearing has an anomaly.

[0072] The rolling bearing abnormality detection device VD and rolling bearing abnormality detection method set the frequency of the wave peaks that can be detected by at least two vibration detection units 1 as the wave peak frequency. Therefore, even when the wave peak frequency is low (the peak value of the wave peak is small), the wave peak of the wave peak frequency and noise can be easily distinguished, and the vibration of the rolling bearing can be appropriately sensed.

[0073] The rolling bearing anomaly detection device VD and rolling bearing anomaly detection method set the peak frequency of the monitored object to the peak frequency of the wave at multiple different time points when the wave frequency changes over time. Therefore, the situation of temporary changes over time can be eliminated, and the peak frequency of the monitored object can be set more appropriately.

[0074] The rolling bearing anomaly detection device VD and rolling bearing anomaly detection method use a first threshold Th1, based on the peak value of the peak in the monitoring peak frequency when the rolling bearing is in good condition, to determine whether the rolling bearing is abnormal. Therefore, even if the rolling bearing has product deviation, it can be customized to determine whether the rolling bearing is abnormal.

[0075] This specification discloses the technologies involved in various embodiments as described above, and the main technologies are summarized below.

[0076] One embodiment of the rolling bearing anomaly detection device includes: a vibration detection unit that detects vibrations generated in the rolling bearing as vibration data; a spectrum processing unit that calculates the spectrum of the vibration data detected by the vibration detection unit; a peak frequency determination unit that, based on the spectrum calculated by the spectrum processing unit, determines a frequency representing a peak as a peak frequency within a predetermined frequency range that includes theoretical frequencies that would cause a peak in the spectrum when an anomaly occurs; a monitoring target setting unit that, when the peak frequency determined by the peak frequency determination unit changes over time, sets the peak frequency as a monitoring peak frequency of a monitoring target; and an anomaly judgment unit that determines whether the rolling bearing has an anomaly based on the peak value of the peak corresponding to the monitoring peak frequency set by the monitoring target setting unit.

[0077] The vibration frequency of rolling bearings changes over time due to factors such as wear. The aforementioned rolling bearing anomaly detection device is designed with this in mind. This rolling bearing anomaly detection device sets the determined peak frequency as the monitoring peak frequency of the object being monitored, thus enabling appropriate sensing of the rolling bearing's vibration.

[0078] In another embodiment of the rolling bearing abnormality detection device, the peak frequency determination unit further determines one or more frequencies representing the peak among integer multiples of the peak frequency as one or more integer multiple peak frequencies. The monitoring target setting unit further sets at least one of the one or more integer multiple peak frequencies as the monitoring peak frequency when the one or more integer multiple peak frequencies determined by the peak frequency determination unit change with time synchronously with the change of the peak frequency over time.

[0079] Such a rolling bearing anomaly detection device can more appropriately sense the vibration of the rolling bearing because it additionally sets at least one of one or more integer multiples of the peak frequency, which represents the peak frequency as an integer multiple of the peak frequency, as the monitoring peak frequency.

[0080] In another embodiment of the rolling bearing abnormality detection device, there are multiple vibration detection units, and the peak frequency determination unit ultimately sets the frequency that can be set as the peak frequency to at least two of the multiple vibration data detected by the multiple vibration detection units.

[0081] Such a rolling bearing abnormality detection device, because it sets the peak frequency detected by at least two vibration detection units as the peak frequency, can easily distinguish the peak of the peak frequency from noise, even when the peak of the peak frequency is low, and properly sense the vibration of the rolling bearing.

[0082] In another embodiment of the rolling bearing abnormality detection device, the monitoring target setting unit sets the peak frequency as the monitoring peak frequency of the monitoring target when the peak frequency determined by the peak frequency determination unit changes multiple times over time at multiple different time points.

[0083] Such a rolling bearing abnormality detection device, by setting the peak frequency of the monitored object to the peak frequency of the monitored object at multiple different time points and when the peak frequency changes over time, can eliminate the situation of temporary changes over time and can more appropriately set the peak frequency of the monitored object.

[0084] In another embodiment of the rolling bearing anomaly detection device, the anomaly determination unit determines whether the rolling bearing is abnormal based on a predetermined threshold valued at the peak value of the peak in the monitoring peak frequency when the rolling bearing is in good condition. Preferably, in the rolling bearing anomaly detection device, the predetermined threshold value is a predetermined multiple of 1 when the peak value of the peak in the monitoring peak frequency when the rolling bearing is in good condition is taken as 1. The anomaly determination unit calculates the ratio of the peak value of the peak corresponding to the monitoring peak frequency at the time of the current anomaly determination to the peak value of the peak in the monitoring peak frequency when the rolling bearing is in good condition as an evaluation value. Based on the calculated evaluation value and the predetermined threshold value, it determines whether the rolling bearing is abnormal (evaluation value = (peak value of the peak corresponding to the monitoring peak frequency at the time of the current anomaly determination) / (peak value of the peak in the monitoring peak frequency when the rolling bearing is in good condition)).

[0085] Such a rolling bearing anomaly detection device, because it uses a predetermined threshold based on the peak value of the peak in the monitoring peak frequency when the rolling bearing is in good condition, to determine whether the rolling bearing is abnormal, can be customized even if there is a product deviation in the rolling bearing, and can determine whether the rolling bearing is abnormal.

[0086] Another embodiment of the rolling bearing anomaly detection method includes the following steps: a vibration detection step, detecting vibration generated in the rolling bearing as vibration data; a spectrum processing step, calculating the spectrum of the vibration data detected in the vibration detection step; a peak frequency determination step, determining the frequency representing the peak as the peak frequency within a specified frequency range that includes the theoretical frequency that brings a peak in the spectrum when an anomaly occurs, based on the spectrum calculated in the spectrum processing step; a monitoring object setting step, setting the peak frequency as the monitoring peak frequency of the monitoring object when the peak frequency determined in the peak frequency determination step changes over time; and an anomaly judgment step, determining whether the rolling bearing has an anomaly based on the peak value of the peak corresponding to the monitoring peak frequency set in the monitoring object setting step.

[0087] This rolling bearing anomaly detection method sets the peak frequency of the monitored object as the peak frequency of the determined peak frequency changes over time, thus allowing the vibration of the rolling bearing to be appropriately sensed.

[0088] This application is based on Japanese Patent Application No. 2021-116597, filed on July 14, 2021, the contents of which are included in this application.

[0089] To illustrate the invention, it has been appropriately and sufficiently described above with reference to the accompanying drawings and embodiments. It should be recognized that those skilled in the art can readily make changes and / or modifications to the above embodiments. Therefore, any changes or modifications implemented by those skilled in the art that do not depart from the scope of the claims set forth in the claims can be interpreted as being included within the scope of the claims.

[0090] Industrial availability

[0091] According to the present invention, a rolling bearing anomaly detection device and a rolling bearing anomaly detection method can be provided for detecting anomalies generated in rolling bearings.

Claims

1. A rolling bearing abnormality detection device, characterized in that... include: The vibration detection unit detects the vibration generated in the rolling bearing and collects the vibration data. The spectrum processing unit calculates the spectrum of the vibration data detected by the vibration detection unit; The peak frequency determination unit determines the frequency representing the peak as the peak frequency based on the spectrum obtained by the spectrum processing unit, within a specified frequency range that includes the theoretical frequency that brings a peak in the spectrum when an anomaly occurs. The monitoring target setting unit sets the peak frequency determined by the peak frequency determination unit as the monitoring peak frequency of the monitoring target when the peak frequency changes over time. as well as The anomaly determination unit determines whether the rolling bearing is abnormal based on the peak value of the peak corresponding to the monitoring peak frequency set by the monitoring object setting unit.

2. The rolling bearing abnormality detection device according to claim 1, characterized in that, The peak frequency determination unit further determines one or more frequencies representing the peak among integer multiples of the peak frequency as one or more integer multiple peak frequencies. The monitoring target setting unit further sets at least one of the one or more integer multiple peak frequencies determined by the peak frequency determination unit as the monitoring peak frequency when the peak frequency changes synchronously with time.

3. The rolling bearing abnormality detection device according to claim 1, characterized in that, The vibration detection unit comprises multiple units. The peak frequency determination unit, for at least two of the multiple vibration data detected by the multiple vibration detection units, ultimately sets the frequency that can be set as the peak frequency as the peak frequency.

4. The rolling bearing abnormality detection device according to claim 1, characterized in that, The monitoring target setting unit sets the peak frequency as the monitoring peak frequency of the monitoring target when the peak frequency determined by the peak frequency determination unit changes multiple times over time at multiple different time points.

5. The rolling bearing abnormality detection device according to claim 1, characterized in that, The anomaly detection unit determines whether the rolling bearing is abnormal based on a predetermined threshold value that is the peak value of the peak in the monitored peak frequency when the rolling bearing is in good condition.

6. A method for detecting abnormalities in rolling bearings, characterized in that... Includes the following steps: The vibration detection procedure involves detecting the vibration generated in the rolling bearing as vibration data. The spectrum processing step is used to obtain the spectrum of the vibration data detected in the vibration detection step. The peak frequency determination step involves determining the frequency representing the peak as the peak frequency within a specified frequency range that includes the theoretical frequency that would cause a peak in the spectrum when an anomaly occurs, based on the spectrum obtained from the spectrum processing step. In the monitoring object setting step, when the peak frequency determined in the peak frequency determination step changes over time, the peak frequency is set as the monitoring peak frequency of the monitoring object. as well as The anomaly detection step determines whether the rolling bearing has any anomalies based on the peak value of the peak corresponding to the monitoring peak frequency set in the monitoring object setting step.

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