Diagnosis device and diagnosis method

Abstract

A diagnosis device (1) is provided with a data generation unit (11), an approximate rotation speed acquisition unit (12), a rotation speed acquisition unit (13), and a diagnosis unit (14). The data generation unit (11) generates, from a vibration sensor signal output by a vibration sensor (92) for measuring the magnitudes of vibration of a subject appliance, spectrum data indicating the distribution of the per-frequency magnitudes of vibration of the subject appliance. The approximate rotation speed acquisition unit (12) obtains an approximate rotation speed, which is an approximate value of the rotation speed of a rotating body of the subject appliance. The rotation speed acquisition unit (13) acquires, as the rotation speed of the rotating body, a frequency corresponding to the peak of the spectrum data in a frequency band including the approximate rotation speed. The diagnosis unit (14) diagnoses the conditions of the subject appliance on the basis of the peak value of the peak of the spectrum data in the frequency band including the diagnosis subject frequency corresponding to the rotation speed acquired by the rotation speed acquisition unit (13).

Description

Diagnostic device and diagnostic method

[0001] The present disclosure relates to diagnostic devices and methods.

[0002] In equipment having a rotating body, such as an electric motor, bearings, gear devices, etc., contact between components as the rotating body rotates can cause wear or damage. Therefore, the condition of equipment having a rotating body is diagnosed. One example of a diagnostic method is to analyze vibration data of the rotating body based on the rotation speed of the rotating body. This diagnostic method requires rotation speed data for each rotating body, so a rotation sensor must be provided near each rotating body. To prevent the installation of rotation sensors near each rotating body from complicating the equipment to be diagnosed or the diagnostic device, Patent Document 1 discloses an example of a diagnostic device that diagnoses the condition of equipment without using a rotation sensor.

[0003] The diagnostic monitoring device disclosed in Patent Document 1 detects multiple peaks in vibration magnitude from frequency analysis data based on the detection results of vibration acceleration sensors that individually detect vibrations in two orthogonal directions of a rotating machine, and detects the frequencies of the detected multiple peaks.The diagnostic monitoring device determines the rotation speed of the rotating machine from the frequencies of the multiple peaks, and determines the vibration state of the rotating machine based on the rotation speed.

[0004] JP 2010-216938 A

[0005] The diagnostic monitoring device disclosed in Patent Document 1 determines a spectral value to be a peak value when, among spectral values ​​equal to or greater than a threshold, the peak occupancy rate, which indicates the degree to which the spectral value protrudes from surrounding frequency components, is equal to or greater than a threshold. Since the peak occupancy rate of equipment mounted on a mobile object decreases when the mobile object is subjected to vibrations while traveling, it is difficult for the diagnostic monitoring device disclosed in Patent Document 1 to accurately determine the vibration state of a rotating machine.

[0006] The present disclosure has been made in consideration of the above circumstances, and aims to provide a diagnostic device and a diagnostic method that are capable of accurately diagnosing the state of a target device with a simple configuration.

[0007] To achieve the above object, a diagnostic device disclosed herein is a diagnostic device that has a rotor that rotates around a rotation axis and diagnoses the condition of a target device mounted on a mobile object, and includes a data generation unit, an approximate rotation speed acquisition unit, a rotation speed acquisition unit, and a diagnostic unit. The data generation unit generates spectral data indicating a distribution of the vibration magnitude of the target device for each frequency from a vibration sensor signal output by a vibration sensor that measures the vibration magnitude of the target device. The approximate rotation speed acquisition unit calculates an approximate rotation speed, which is an approximate value of the rotation speed of the rotor. The rotation speed acquisition unit detects a peak in the vibration magnitude of the spectral data in a frequency band including the approximate rotation speed, and acquires the frequency corresponding to the detected peak as the rotation speed of the rotor. The diagnostic unit uses a diagnosis target frequency determined based on the rotation speed of the rotor acquired by the rotation speed acquisition unit to detect a peak in the vibration magnitude of the spectral data in the frequency band including the diagnosis target frequency, and diagnoses the condition of the target device based on the peak value of the peak detected in the frequency band including the vibration target frequency.

[0008] A diagnostic device according to the present disclosure calculates an approximate rotation speed of a rotating body, acquires the rotation speed of the rotating body from peaks of spectrum data in a frequency band including the approximate rotation speed, and diagnoses the condition of a target device from the peak value of the peak of the spectrum data in a frequency band including a diagnosis target frequency determined based on the acquired rotation speed. The diagnostic device calculates an approximate rotation speed that is an approximate value of the rotation speed of the rotating body, and then calculates the rotation speed of the rotating body from the approximate rotation speed. Therefore, the diagnostic device does not require a rotation sensor provided for each rotating body, and can accurately diagnose the condition of the target device with a simple configuration while reducing the influence of vibrations caused by the moving body when it is traveling.

[0009] FIG. 1 is a diagram showing an example of mounting an electric motor, which is a diagnosis target of the diagnostic device according to the first embodiment, on a railway vehicle. FIG. 2 is a block diagram of the diagnostic device according to the first embodiment. FIG. 3 is a diagram showing a hardware configuration of the diagnostic device according to the first embodiment. FIG. 4 is a flowchart showing an example of diagnostic processing performed by the diagnostic device according to the first embodiment. FIG. 5 is a diagram showing an example of spectrum data in the first embodiment. FIG. 6 is a block diagram of the diagnostic device according to the second embodiment. FIG. 7 is a block diagram of the diagnostic device according to the third embodiment.

[0010] A diagnostic device and a diagnostic method according to an embodiment of the present disclosure will be described in detail below with reference to the drawings, in which the same or equivalent parts are designated by the same reference numerals.

[0011] (Embodiment 1) A diagnostic device according to embodiment 1 will be described using, as an example of a target device mounted on a moving body, a diagnostic device that diagnoses the state of an electric motor mounted on a railway vehicle and generates propulsive force for the railway vehicle. Two bogies 41 shown in Fig. 1 are attached to each carriage of the railway vehicle, for example, to support the car body. In Fig. 1, the X-axis direction indicates the width direction of the carriage. The Y-axis direction indicates the direction of travel of the railway vehicle. The Z-axis is perpendicular to both the X-axis and the Y-axis. When the railway vehicle is positioned horizontally, the Z-axis direction indicates the vertical direction.

[0012] At least one of the vehicles is an electric vehicle. FIG. 1 shows a bogie 41 that supports the body of the electric vehicle. Two electric motors 91 are attached to the bogie 41. The electric motors 91 rotate by receiving power from a power conversion device (not shown). A vibration sensor 92 is provided near a shaft 91a, which is an example of a rotating body, of each electric motor 91. The vibration sensor 92 is an acceleration sensor, a displacement sensor, a speed sensor, or the like. As an example, the vibration sensor 92, which is a three-axis acceleration sensor, is preferably provided such that one of its measurement axes coincides with the rotation axis of the rotating body of the target device, i.e., the rotation axis AX1 of the shaft 91a of the electric motor 91.

[0013] The bogie 41 includes a joint 43 connected to the shaft 91 a of each electric motor 91, a gear device 44 that transmits the rotational force transmitted from the electric motor 91 via the joint 43 to the axle 45, the axle 45, and wheels 42 attached to both ends of the axle 45. When each electric motor 91 receives a supply of electric power from the power conversion device and operates, the shaft 91 a of each electric motor 91 rotates, and the rotational force of the shaft 91 a is transmitted to the axle 45 via the joint 43 and the gear device 44. Then, as the axle 45 rotates, the wheels 42 attached to both ends of the axle 45 rotate, generating propulsive force for the railway vehicle.

[0014] As shown in FIG. 2 , a diagnostic device 1 for diagnosing the condition of a target device having a rotating body, for example, an electric motor 91 having a rotating shaft 91 a, includes a data generation unit 11 for generating spectral data indicating the distribution of the vibration magnitude of the electric motor 91 for each frequency from the measurements of a vibration sensor 92, an approximate rotation speed acquisition unit 12 for obtaining an approximate rotation speed that is an estimate of the rotation speed of the shaft 91 a, a rotation speed acquisition unit 13 for obtaining the rotation speed of the shaft 91 a from the approximate rotation speed and the spectral data, and a diagnostic unit 14 for diagnosing the condition of the electric motor 91 from the rotation speed and the spectral data.

[0015] The hardware configuration of the diagnostic device 1 having the above configuration is shown in Fig. 3. The diagnostic device 1 includes a processor 81, a memory 82, and an interface 83. The processor 81, the memory 82, and the interface 83 are connected to one another via a bus 80. The processor 81 includes any electronic circuit including a transistor, and is considered to be a circuit or a processor circuit.

[0016] The functions of the diagnostic device 1 are realized by software, firmware, which is software built into an electronic device, or a combination of software and firmware. The software is written as a program and stored in the memory 82. The processor 81 reads and executes the program stored in the memory 82, thereby realizing the functions of the above-mentioned parts. In other words, the memory 82 stores a program for executing the processing of the diagnostic device 1.

[0017] The memory 82 includes, for example, non-volatile or volatile semiconductor memory such as RAM (Random Access Memory), ROM (Read-Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), EEPROM (Electrically Erasable and Programmable Read-Only Memory), magnetic disk, flexible disk, optical disk, compact disk, mini disk, DVD (Digital Versatile Disc), etc.

[0018] The diagnostic device 1 is connected to the vibration sensor 92 via an interface 83. The interface 83 has an interface module that complies with one or more standards depending on the connected device.

[0019] As an example, the diagnostic device 1 having the above configuration continuously executes the diagnostic process shown in Fig. 4 during operation. The approximate rotation speed acquisition unit 12 included in the diagnostic device 1 acquires position information of the railway vehicle, estimates the speed of the railway vehicle from changes in the position information of the railway vehicle per unit time, and calculates the approximate rotation speed from the estimated railway vehicle speed (step S11).

[0020] 2 acquires railcar position information from a GPS (Global Positioning System) receiver (not shown). The approximate rotation speed acquisition unit 12 calculates the railcar speed from changes in the railcar position information per unit time. The approximate rotation speed acquisition unit 12 calculates the approximate rotation speed, which is an estimate of the rotation speed of the shaft 91a, from the calculated railcar speed based on the gear ratio of the gear device 44 and the diameter of the wheels 42.

[0021] In detail, the approximate rotation speed obtaining unit 12 obtains the approximate rotation speed Fa (unit: Hz) per unit time by multiplying the speed V1 (unit: m / s) of the railway vehicle by the gear ratio Rg of the gear device 44, and dividing the result by π·D1, which is the product of π and the diameter D1 (unit: m) of the wheels 42, as expressed in the following equation (1). The approximate rotation speed Fa obtained by the following equation (1) is the number of times the shaft 91a rotates per unit time, specifically, per second, and can be expressed in rps (revolutions per second). 1 rps = 1 s －１ Therefore, the estimated rotation speed Fa is －１ , that is, expressed in units of Hz. The approximate rotation speed acquisition unit 12 is assumed to have stored in advance information on the gear ratio of the gear device 44 and the diameter of the wheel 42. The gear ratio indicates the number of rotations of the shaft 91 a required for the wheel 42 to rotate once. The approximate rotation speed acquisition unit 12 sends the obtained approximate rotation speed to the rotation speed acquisition unit 13.

[0022]

[0023] As shown in Fig. 4, the data generator 11 generates spectrum data indicating the distribution of the vibration magnitude of the target device from the vibration sensor signal acquired from the vibration sensor 92 (step S12). The data generator 11 shown in Fig. 2 acquires the vibration sensor signal, which is an analog data signal whose amplitude changes depending on the vibration magnitude of the measurement target, from the vibration sensor 92. The data generator 11 generates spectrum data, which is frequency domain data, from the vibration sensor signal, which is a time domain signal.

[0024] Specifically, the data generator 11 generates spectral data by performing an FFT (Fast Fourier Transform) on digital data obtained by sampling the vibration sensor signal over a unit time. It is preferable that the unit time used to calculate the approximate rotation speed and the unit time used to generate the spectral data are the same. The unit time is, for example, one second. The data generator 11 sends the generated spectral data to the rotation speed acquisition unit 13 and the diagnosis unit 14.

[0025] 4, the rotation speed acquisition unit 13 determines the rotation speed of the shaft 91a from the estimated rotation speed determined in step S11 and the spectrum data generated in step S12 (step S13). Specifically, the rotation speed acquisition unit 13 detects a peak in the amplitude of vibration of the spectrum data in a frequency band including the estimated rotation speed, and acquires the frequency corresponding to the detected peak as the rotation speed of the shaft 91a. As described above, 1 rps = 1 s －１ Therefore, the rotation speed acquisition unit 13 uses the estimated rotation speed calculated by the above formula (1) as a frequency expressed in units of Hz, and detects the peak of the vibration magnitude of the spectrum data in a frequency band including the estimated rotation speed (unit: Hz).

[0026] An example of spectrum data is shown in Figure 5. The horizontal axis of Figure 5 represents frequency (unit: Hz), and the vertical axis represents the magnitude of vibration as acceleration amplitude (unit: m / s ２ ) The frequency band ΔF1 including the estimated rotation speed Fa is, for example, a frequency band having the estimated rotation speed Fa as its center frequency. The bandwidth of the frequency band ΔF1 is determined according to the possible error between the estimated rotation speed Fa and the actual rotation speed of the electric motor 91. The error between the estimated rotation speed Fa and the actual rotation speed of the electric motor 91 is determined by the diameter of the wheels 42 and the speed of the railway vehicle. The frequency band ΔF1 is a frequency range estimated to include the estimated rotation speed Fa and the actual rotation speed of the electric motor 91 based on the error between the estimated rotation speed Fa and the actual rotation speed of the electric motor 91. For example, the frequency band ΔF1 is a band having the estimated rotation speed Fa as its center frequency and including a range of 5% above and below. Specifically, when the estimated rotation speed Fa is 10 Hz, the frequency band ΔF1 is in the range of ±0.5 Hz centered at 10 Hz, in other words, a range of 9.5 Hz to 10.5 Hz.

[0027] The rotation speed acquisition unit 13 detects a peak in the vibration magnitude of the spectrum data within the frequency band ΔF1 and acquires the frequency Fe corresponding to the detected peak as the rotation speed of the shaft 91 a. If no peak exists within the frequency band ΔF1, the rotation speed acquisition unit 13 uses the estimated rotation speed Fa as the rotation speed of the shaft 91 a. The rotation speed acquisition unit 13 sends the rotation speed of the shaft 91 a to the diagnosis unit 14.

[0028] As shown in FIG. 4 , the diagnoser 14 determines a diagnosis target frequency from the rotation speed calculated in step S13 and detects a spectrum value representing the magnitude of vibration corresponding to the diagnosis target frequency from the spectrum data (step S14). The diagnosis target frequency is determined based on the rotation speed of the shaft 91a. For example, vibrations occur in a bearing included in the electric motor 91 that rotatably supports the shaft 91a due to whirling of the bearing's cage, a vertical drop, or damage to the bearing. These vibrations are larger than those caused by the running of a railway vehicle and occur periodically. The vibration period depends on the rotation speed of the shaft 91a. In other words, a peak occurs in the spectrum data when the frequency coincides with the reciprocal of the vibration period. Therefore, the diagnoser 14 detects the spectrum value of the diagnosis target frequency by setting the reciprocal of the vibration period as the diagnosis target frequency.

[0029] As an example, the frequency to be diagnosed is the inner ring rolling element passing frequency Ft expressed by the following formula (2), specifically, the frequency of vibration that occurs periodically when a flaw occurs in the inner ring of the electric motor 91. In the following formula (2), Z indicates the number of rolling elements of the bearing that rotatably supports the shaft 91a, Fe indicates the rotation speed of the shaft 91a, and D ｐｗ indicates the pitch diameter of the rolling element, d indicates the diameter of the rolling element, and α indicates the contact angle of the bearing. ｐｗ , the diameter d of the rolling element, and the contact angle α of the bearing.

[0030]

[0031] The diagnosing unit 14 diagnoses the state of the electric motor 91 based on the peak value of the detected peak (step S15). For example, the diagnosing unit 14 determines whether the peak value is equal to or greater than an amplitude threshold, and if the peak value is equal to or greater than the amplitude threshold, determines that an abnormality has occurred in the electric motor 91. The amplitude threshold may be set to a value between the spectrum value of the electric motor 91 when it is normal and the spectrum value of the electric motor 91 when it is abnormal, for each frequency corresponding to the type of abnormality in the electric motor 91, based on simulation, test data, etc. The diagnosing unit 14 outputs the diagnosis result to an external device, for example, a display device provided in the driver's cab of the railway vehicle. After completing the process of step S15, the diagnosing device 1 repeats the above-described process from step S11.

[0032] As described above, the diagnostic device 1 according to the first embodiment calculates the speed of a railway vehicle from its position information and calculates, from the speed, an approximate rotation speed of the shaft 91a, which is a rotating body of the electric motor 91, which is the equipment to be diagnosed. The diagnostic device 1 detects a peak in the vibration magnitude of spectrum data based on a vibration sensor signal in a frequency band including the approximate rotation speed and acquires the frequency corresponding to the peak as the rotation speed of the shaft 91a. The diagnostic device 1 diagnoses the condition of the electric motor 91 based on the spectrum value at a diagnosis target frequency corresponding to the rotation speed. Because the diagnostic device 1 does not require a rotation sensor to detect the rotation speed of the shaft 91a, the configuration of the diagnostic device 1 is simple. Because the diagnostic device 1 detects a peak in a frequency band including the approximate rotation speed, searching for a peak in a limited frequency band reduces false detections and is less susceptible to the influence of disturbance vibrations. As a result, the diagnostic device 1 can accurately calculate the rotation speed of the shaft 91a. This enables the diagnostic device 1 to accurately diagnose the condition of the electric motor 91 with a simple configuration.

[0033] (Embodiment 2) The method for calculating the approximate rotation speed of the shaft 91a, which is an example of a rotating body of the target device, is not limited to the above example. In embodiment 2, a diagnostic device that calculates the approximate rotation speed of the shaft 91a using a method different from embodiment 1 will be described, focusing on the differences from embodiment 1.

[0034] As shown in Fig. 6, the configuration of a diagnostic device 2 according to the second embodiment is the same as that of the diagnostic device 1, but the diagnostic device 2 does not acquire position information of the railway vehicle from an external device. The diagnostic device 2 calculates an approximate rotation speed from spectrum data. The hardware configuration of the diagnostic device 2 is the same as that of the diagnostic device 1.

[0035] The vibration sensor 92 is an acceleration sensor that measures static acceleration and dynamic vibration. One of the measurement axes of the vibration sensor 92 is aligned with the rotation axis of the rotating body of the target device, i.e., the rotation axis AX1 of the shaft 91a, and the other measurement axis is oriented to indicate the direction of travel of the moving body on which the target device is mounted, i.e., the railway vehicle. As an example, the vibration sensor 92, which is a three-axis acceleration sensor, is aligned with each measurement axis aligned with the X-axis, Y-axis, and Z-axis. By arranging the vibration sensor 92 as described above, the vibration sensor 92 can measure changes in acceleration corresponding to the acceleration and deceleration of the railway vehicle.

[0036] The approximate rotation speed acquisition unit 12 extracts a DC component indicating static acceleration from the vibration sensor signal, specifically, from the vibration sensor signal corresponding to the measurement axis that coincides with the Y-axis indicating the direction of travel of the railway vehicle, and integrates the extracted DC component to determine the railway vehicle speed. Specifically, the approximate rotation speed acquisition unit 12 has an LPF (Low Pass Filter) and an integration circuit. The cutoff frequency of the LPF is set to a frequency that is sufficiently low enough to extract the DC component from the vibration sensor signal, for example, 1 Hz. The approximate rotation speed acquisition unit 12 processes the vibration sensor signal that has passed through the LPF using the integration circuit, thereby integrating the acceleration and determining the railway vehicle speed.

[0037] The approximate rotation speed acquisition unit 12 calculates the approximate rotation speed, which is an approximate value of the rotation speed of the shaft 91 a, from the calculated speed of the railway vehicle based on the gear ratio of the gear device 44 and the diameter of the wheels 42. The approximate rotation speed acquisition unit 12 sends the approximate rotation speed to the rotation speed acquisition unit 13.

[0038] As in the first embodiment, the data generation unit 11 generates spectral data by performing an FFT on digital data obtained by sampling the vibration sensor signal over a unit time. By performing the FFT to generate spectral data indicating the magnitude of vibration for each frequency, it becomes possible to separate the DC component from the AC component of the vibration sensor signal. The data generation unit 11 sends the generated spectral data to the rotation speed acquisition unit 13 and the diagnosis unit 14. The processing by the rotation speed acquisition unit 13 and the diagnosis unit 14 is the same as in the first embodiment.

[0039] As explained above, the diagnostic device 2 according to the second embodiment does not acquire position information of the railcar from an external source, but instead calculates the speed of the railcar from the DC component of the vibration sensor signal, and calculates an approximate rotation speed from the calculated speed of the railcar. Because the diagnostic device 2 does not need to acquire position information of the railcar from an external source, it can be realized with a simpler configuration than the diagnostic device 1.

[0040] (Embodiment 3) The method for calculating the approximate rotation speed of the shaft 91a, which is an example of a rotating body of the target device, is not limited to the above example. A diagnostic device that calculates the approximate rotation speed of the shaft 91a by a method different from those of Embodiments 1 and 2 will be described in Embodiment 3, focusing on the differences from Embodiment 1.

[0041] A diagnostic device 3 according to a third embodiment shown in Fig. 7 diagnoses the state of an electric motor 91, which is an induction motor. In addition to the configuration of diagnostic device 1, diagnostic device 3 further includes a current flow determination unit 15 that determines whether or not a current is flowing through electric motor 91, and an approximate current flow rotation speed acquisition unit 16 that calculates an approximate current flow rotation speed, which is an approximate value of the rotation speed of shaft 91a when current is flowing, from spectrum data when current is flowing. The hardware configuration of diagnostic device 3 is the same as that of diagnostic device 1. Diagnostic device 3 is connected to a vibration sensor 92 and a current sensor 93 via an interface 83.

[0042] The diagnostic device 3 having the above configuration continuously performs the diagnostic process shown in FIG. 8 during operation. The processes of steps S11 and S12 are the same as the processes performed by the diagnostic device 1 shown in FIG. 4. The energization determination unit 15 included in the diagnostic device 3 determines whether the electric motor 91 is energized (step S21). Specifically, the energization determination unit 15 acquires a current sensor signal from a current sensor 93 that measures the value of the current flowing from the power conversion device to the electric motor 91, and determines whether the amplitude of the current sensor signal is equal to or greater than the energization threshold. The energization threshold may be determined according to the amplitude of the AC current flowing through the electric motor 91 when the electric motor 91 is driven. For example, the energization threshold may be set to the minimum amplitude of the AC current that can drive the electric motor 91. The energization determination unit 15 outputs the determination result to the energized approximate rotation speed acquisition unit 16.

[0043] If the electric motor 91 is not energized (step S21; No), the above-described process is repeated from step S11. If the electric motor 91 is energized (step S21; Yes), the energized approximate rotation speed acquisition unit 16 calculates the drive power supply frequency from the spectrum data generated in step S12 (step S22). The drive power supply frequency is the frequency of the AC power supplied to the electric motor 91.

[0044] FIG. 9 shows a timing chart illustrating an example of vibration data and whether or not current is being applied. In FIG. 9, the horizontal axis represents time. Graph A represents the vibration sensor signal output by the vibration sensor 92. Graph B represents the output of the energization determination unit 15. For example, the energization determination unit 15 outputs a determination result signal that is at H (High) level when the electric motor 91 is energized and at L (Low) level when the electric motor 91 is not energized. The time when current supply to the electric motor 91 starts is defined as T1, and the time when current supply to the electric motor 91 is stopped is defined as T2. The energization approximate rotation speed acquisition unit 16 detects, from the spectrum data generated by the data generation unit 11 for each unit time during the period from time T1 to time T2, the peak of the vibration magnitude of the spectrum data in a frequency band whose upper limit is the drive power supply frequency determined according to the maximum rotation speed and the number of poles of the electric motor 91.

[0045] 10 shows an example of the spectrum data generated by the data generating unit 11 during the period from time T1 to time T2. The horizontal axis of FIG. 10 represents frequency (unit: Hz), and the vertical axis represents the magnitude of vibration as acceleration amplitude (unit: m / s ２ ) When the electric motor 91 is energized, electromagnetic vibrations are generated due to electromagnetic excitation forces. The electromagnetic vibrations include components of the drive power supply frequency, which is the frequency of the AC power supplied to the electric motor 91, and components of harmonics of the drive power supply frequency. Therefore, the energized approximate rotation speed acquisition unit 16 detects the peak of the vibration magnitude of the spectrum data in a frequency band with the drive power supply frequency Fmax as the upper limit value.

[0046] The drive power supply frequency f, which is the frequency of AC power supplied to the electric motor 91, and the rotation speed N of the shaft 91a satisfy the relational expression (3) below. In the following expression (3), p represents the number of poles determined as an operational specification of the electric motor 91, and s represents slip, which is the delay in the rotor speed relative to the speed of the rotating magnetic field in the electric motor 91. By substituting the number of poles p determined as an operational specification of the electric motor 91 for the number of poles p in the following expression (3), substituting the maximum rotation speed Nmax determined as an operational specification of the electric motor 91 for the rotation speed N, and setting s = 0, the drive power supply frequency f when the rotation speed of the electric motor 91 becomes the maximum rotation speed Nmax, i.e., the maximum value Fmax of the drive power supply frequency f, can be obtained. As an example, if the electric motor 91 is an induction motor with a maximum rotation speed of 100 Hz and the number of poles being four, the maximum value Fmax of the drive power supply frequency is 200 Hz.

[0047]

[0048] As an example, the energized approximate rotation speed acquisition unit 16 detects peaks within a frequency band ΔF0 of 0 Hz or more and Fmax or less, and acquires the frequency Fp corresponding to the detected peak as the drive power supply frequency, as shown in Fig. 10. Specifically, the approximate rotation speed acquisition unit 12 acquires the frequency Fp corresponding to the largest peak among the peaks detected in the frequency band ΔF0 of 0 Hz or more and Fmax or less, as the drive power supply frequency.

[0049] 8, the energized approximate rotational speed acquisition unit 16 calculates an energized approximate rotational speed, which is an approximate value of the rotational speed of the shaft 91a when energized, from the drive power supply frequency Fp (step S23). Specifically, the energized approximate rotational speed acquisition unit 16 substitutes the number of poles p determined as the operating specifications of the motor 91 for the number of poles p in equation (3) above, substitutes the frequency Fp for the drive power supply frequency f, and acquires the rotational speed N obtained when s = 0 as the energized approximate rotational speed Fa'. The energized approximate rotational speed acquisition unit 16 outputs the energized approximate rotational speed Fa' to the rotational speed acquisition unit 13. If the motor 91 is an induction motor with four poles, Fa' = Fp / 2 holds true.

[0050] Because slip occurs in the electric motor 91, the actual rotation speed of the electric motor 91, i.e., the actual rotation speed of the shaft 91a, is smaller than the energized approximate rotation speed Fa' calculated in equation (3) above with slip s = 0. Therefore, as shown in Fig. 8 , the rotation speed acquisition unit 13 detects peaks in the amplitude of vibration of the spectrum data in a frequency band including the approximate rotation speed calculated by the approximate rotation speed acquisition unit 12 in step S11 and in a frequency band having the energized approximate rotation speed calculated in step S23 as its upper limit value, and acquires the frequency corresponding to the detected peak as the rotation speed of the shaft 91a (step S24).

[0051] Specifically, as shown in FIG. 10 , the rotation speed acquisition unit 13 detects a peak in the amplitude of vibration in the spectrum data in a range where a frequency band ΔF1 centered on the estimated rotation speed Fa calculated by the estimated rotation speed acquisition unit 12 overlaps with a frequency band ΔF2 having an upper limit value equal to the energized estimated rotation speed Fa′ calculated by the energized estimated rotation speed acquisition unit 16. The frequency band ΔF2 corresponding to the detected peak is acquired as the rotation speed of the shaft 91a. The bandwidth of the frequency band ΔF2 is determined based on the maximum value of slip that can occur during operation of the electric motor 91. Specifically, the rotation speed N obtained by substituting the number of poles p, which is determined as an operational specification of the electric motor 91, for the number of poles p in Equation (3) above, the maximum value of slip that can occur during operation of the electric motor 91 for slip s, and the frequency Fp for the drive power frequency f is set as the lower limit of the frequency band ΔF2. The maximum value of slip is, for example, 5%.

[0052] When there is no peak in the range where the frequency bands ΔF1 and ΔF2 overlap, the rotation speed acquisition unit 13 detects a peak in the vibration magnitude of the spectrum data in the frequency band ΔF1 or the frequency band ΔF2, and acquires the frequency corresponding to the detected peak as the rotation speed of the shaft 91a.

[0053] When there is no peak in either of the frequency bands ΔF1 and ΔF2, the rotation speed acquisition unit 13 acquires the estimated rotation speed Fa or the energized estimated rotation speed Fa′ as the rotation speed of the shaft 91a.

[0054] The rotation speed acquisition unit 13 outputs the rotation speed of the shaft 91a to the diagnosis unit 14. The operation of the diagnosis unit 14 is the same as in the first embodiment. In detail, the processes of steps S14 and S15 in Fig. 8 are the same as the processes performed by the diagnosis device 1 shown in Fig. 4. When the process of step S15 is completed, the diagnosis device 3 repeats the above-described processes from step S11.

[0055] As described above, the diagnostic device 3 according to the third embodiment determines the rotation speed of the shaft 91 a from the estimated rotation speed and the energized estimated rotation speed, and therefore can accurately determine the rotation speed of the shaft 91 a. As a result, the diagnostic device 3 can accurately diagnose the condition of the electric motor 91.

[0056] The present disclosure is not limited to the above-described embodiments. The above-described embodiments can be combined in any manner. As an example, the estimated rotation speed acquisition unit 12 included in the diagnosis device 3 may obtain the estimated rotation speed in the same manner as the estimated rotation speed acquisition unit 12 included in the diagnosis device 2.

[0057] The data generator 11 is not limited to the above example, and may perform any signal processing necessary to generate spectrum data. As an example, the data generator 11 included in the diagnostic device 2 may generate spectrum data from a vibration sensor signal passed through a high pass filter (HPF). The cutoff frequency of the HPF is set to a frequency, for example, 1 Hz, that is sufficiently low to separate the DC component from the AC component of the vibration sensor signal. As another example, the data generator 11 may perform envelope processing to detect the envelope of the vibration sensor signal.

[0058] The method by which the approximate rotation speed obtaining unit 12 obtains the approximate rotation speed is not limited to the above example. As one example, the approximate rotation speed obtaining unit 12 may obtain speed information of the railway vehicle from a train control device that controls the operation of the railway vehicle, and obtain the approximate rotation speed of the electric motor 91 from the speed of the railway vehicle indicated by the speed information, based on the gear ratio of the gear device 44 and the diameter of the wheels 42. As another example, the railway vehicle speed may be obtained from a sensor signal output by a PG (Pulse Generator) that is provided in a main electric motor and measures the rotation speed of the electric motor, the period of impact vibration when passing over a rail joint, or the like, and the approximate rotation speed may be obtained from the obtained railway vehicle speed.

[0059] The bandwidth of the frequency band ΔF1 used by the rotation speed acquisition unit 13 may be a constant value, for example, 2 Hz, regardless of the estimated rotation speed.

[0060] The method by which the energization determining unit 15 determines whether or not a current is flowing through the electric motor 91 is not limited to the above example. As an example, the energization determining unit 15 may determine whether or not a current is flowing through the electric motor 91 based on a voltage command value used by a control device that controls a power conversion device that supplies power to the electric motor 91 to control the power conversion device.

[0061] The diagnostic devices 1 and 2 are not limited to diagnosing the condition of the electric motor 91, but can also diagnose the condition of any equipment having a rotating body, specifically, the wheel 42, the joint 43, the gear device 44, the axle 45, etc. In this case, the vibration sensor 92 is preferably provided near the equipment to be diagnosed. As an example, when the diagnostic devices 1-3 diagnose the condition of the gear device 44, the vibration sensor 92 may be provided on the outer surface of the housing of the gear device 44. When the frequencies at which spectrum peaks occur in the event of an abnormality differ for each of the components of the gear device 44, such as the gear wheel, the pinion, the axle bearing in which the gear wheel is fitted, and the shaft bearing in which the pinion gear is fitted, it becomes possible to determine the presence or absence of an abnormality in each component of the gear device 44 from the vibration sensor signal output by the vibration sensor 92 attached to the gear device 44.

[0062] The diagnostic device 3 can diagnose the condition of the rotating mechanism, which rotates around a rotation axis by receiving rotational force from the electric motor 91, such as the wheels 42, the joints 43, the gear device 44, and the axles 45. In detail, the diagnostic device 3 calculates the rotation speed of the rotating mechanism from peaks in a frequency band including an approximate rotation speed of the rotating mechanism and a frequency band including an approximate rotation speed of the shaft 91 a when the electric motor 91 is energized, and diagnoses the condition of the rotating mechanism based on a spectrum value at a diagnosis target frequency corresponding to the rotation speed.

[0063] The diagnostic device 1-3 may be mounted on a railway vehicle and implemented as one function of a train information management system that controls the operation of the railway vehicle. The diagnostic device 1-3 is not limited to being mounted on a railway vehicle, but may also be mounted on a moving body other than a railway vehicle, such as an automobile, a trolleybus, an airplane, a ship, etc.

[0064] The structure and installation position of the vibration sensor 92 are not limited to the above example, and any structure and installation position may be used as long as they are capable of measuring the magnitude of vibration of the device being diagnosed. As an example, when the device being diagnosed rotates, the vibration sensor 92, which is a non-contact vibration sensor, is preferably installed in a position close to the device but away from it.

[0065] Each measurement axis of the vibration sensor 92 may be offset from the rotation axis of the target device or the traveling direction of the moving object. In this case, the data generator 11 stores information about the angle between each measurement axis of the vibration sensor 92 and the rotation axis of the target device or the traveling direction of the moving object, corrects the vibration sensor signal based on the information about the angle, and generates spectrum data from the corrected vibration sensor signal.

[0066] The above hardware configuration and flowchart are merely examples and can be changed or modified as desired. For example, in FIG. 4, the process of step S11 and the process of step S12 may be performed in parallel.

[0067] As another example, a modified example of the hardware configuration of the diagnostic device 1 is shown in Fig. 11. The diagnostic device 1 may be realized by a processing circuit 84 as shown in Fig. 11. The same applies to the diagnostic devices 2 and 3. The processing circuit 84 included in the diagnostic device 1 shown in Fig. 11 is connected to a vibration sensor 92 via an interface circuit 85.

[0068] When the processing circuitry 84 is dedicated hardware, the processing circuitry 84 includes, for example, a single circuit, a composite circuit, a processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof. Each unit of the diagnostic device 1 may be realized by an individual processing circuit 84, or each unit of the diagnostic device 1 may be realized by a common processing circuit 84.

[0069] Some of the functions of the diagnostic device 1 may be realized by dedicated hardware, and other functions may be realized by software or firmware. For example, in the diagnostic device 1, the data generation unit 11 may be realized by a processing circuit 84 shown in Fig. 11, and the estimated rotation speed acquisition unit 12, the rotation speed acquisition unit 13, and the diagnosis unit 14 may be realized by a processor 81 shown in Fig. 3 reading and executing programs stored in a memory 82.

[0070] The present disclosure allows various embodiments and modifications without departing from the broad spirit and scope of the present disclosure. Furthermore, the above-described embodiments are intended to illustrate the present disclosure and do not limit the scope of the present disclosure. That is, the scope of the present disclosure is defined by the claims, not the embodiments. Various modifications made within the scope of the claims and the meaning of equivalent disclosures are considered to be within the scope of the present disclosure.

[0071] 1, 2, 3 Diagnostic device, 11 Data generation unit, 12 Estimated rotation speed acquisition unit, 13 Rotation speed acquisition unit, 14 Diagnosis unit, 15 Power supply determination unit, 16 Power supply approximate rotation speed acquisition unit, 41 Bogie, 42 Wheel, 43 Joint, 44 Gear device, 45 Axle, 80 Bus, 81 Processor, 82 Memory, 83 Interface, 84 Processing circuit, 85 Interface circuit, 91 Electric motor, 91a Shaft, 92 Vibration sensor, 93 Current sensor, AX1 Rotating shaft.

Claims

1. A diagnostic device for diagnosing the condition of a target device having a rotating body that rotates around a rotation axis and is mounted on a mobile body, comprising: a data generation unit that generates spectral data indicating a distribution of the vibration magnitude of the target device for each frequency from a vibration sensor signal output by a vibration sensor that measures the vibration magnitude of the target device; an approximate rotation speed acquisition unit that calculates an approximate rotation speed that is an estimate of the rotation speed of the rotating body; a rotation speed acquisition unit that detects peaks of the vibration magnitude of the spectral data in a frequency band that includes the approximate rotation speed, and acquires the frequency corresponding to the detected peak as the rotation speed of the rotating body; and a diagnostic unit that uses a diagnosis target frequency that is determined based on the rotation speed of the rotating body acquired by the rotation speed acquisition unit to detect peaks of the vibration magnitude of the spectral data in a frequency band that includes the diagnosis target frequency, and diagnoses the condition of the target device based on the peak value of the peak detected in the frequency band that includes the diagnosis target frequency.

2. The diagnostic device according to claim 1, wherein the approximate rotation speed acquisition unit calculates the approximate rotation speed, which is an approximate value of the rotation speed of the rotating body of the target equipment, which is an electric motor that generates the propulsive force of the moving body or a rotating mechanism that rotates by receiving rotational force from the electric motor, from the speed of the moving body.

3. The diagnostic device according to claim 2, wherein the approximate rotation speed acquisition unit calculates the approximate rotation speed, which is an approximate value of the rotation speed of the rotating body of the target equipment, which is the electric motor that generates the propulsive force of the railway vehicle or the rotating mechanism that rotates by receiving rotational force from the electric motor, from the speed of the railway vehicle, which is the moving body on which the target equipment is mounted.

4. A diagnostic device according to claim 2 or 3, wherein the approximate rotation speed acquisition unit acquires position information of the moving body, calculates the speed of the moving body from changes in the position information of the moving body per unit time, and calculates the approximate rotation speed from the calculated speed of the moving body.

5. A diagnostic device as described in claim 2 or 3, wherein the data generation unit generates the spectrum data from the vibration sensor signal output by the vibration sensor, which is an acceleration sensor that measures static acceleration and dynamic vibration, and the approximate rotation speed acquisition unit determines the speed of the moving body from the static acceleration indicated by the vibration sensor signal, and determines the approximate rotation speed from the determined speed of the moving body.

6. The diagnostic device according to claim 5, wherein the data generation unit generates the spectrum data from the sensor signal output by the vibration sensor, which is oriented so that one of its measurement axes coincides with the direction of travel of the moving body.

7. A diagnostic device as described in claim 2 or 3, wherein the estimated rotation speed acquisition unit acquires speed information of the moving body from a train control device that controls the operation of the moving body, which is a railway vehicle, and calculates the estimated rotation speed from the speed of the railway vehicle indicated by the speed information.

8. A diagnostic device according to any one of claims 2 to 7, wherein the estimated rotation speed acquisition unit determines the estimated rotation speed from the speed of the moving body based on the gear ratio of a gear device that transmits the rotational force of the electric motor, which is the target device, to the wheels of the moving body and the diameter of the wheels.

9. A diagnostic device according to any one of claims 2 to 8, further comprising: a current-flow determination unit that determines whether or not current is flowing in the electric motor that rotates upon receiving a supply of AC power; and a current-flow approximate rotation speed acquisition unit that detects peaks in the amplitude of vibration in the spectrum data generated from the vibration sensor signal output during a period in which it has been determined by the current-flow determination unit that current is flowing in the electric motor, and obtains an current-flow approximate rotation speed, which is an approximate value of the rotation speed of the rotating body of the electric motor when current is flowing, from a drive power supply frequency that is a frequency corresponding to the detected peak, wherein the rotation speed acquisition unit detects peaks in the amplitude of vibration in the spectrum data in a frequency band that includes the approximate rotation speed and a frequency band that has the current-flow approximate rotation speed as an upper limit, and acquires, as the rotation speed of the rotating body, the frequency corresponding to the peaks detected in the frequency band that includes the approximate rotation speed and the frequency band that has the current-flow approximate rotation speed as an upper limit.

10. The diagnostic device of claim 9, wherein the rotation speed acquisition unit detects a peak in the magnitude of vibration of the spectrum data in a range where a frequency band including the estimated rotation speed and a frequency band having the estimated rotation speed when powered as an upper limit value overlap, and acquires the frequency corresponding to the peak detected in the range where the frequency band including the estimated rotation speed and the frequency band having the estimated rotation speed when powered as an upper limit value overlap as the rotation speed of the rotating body.

11. A diagnostic device according to any one of claims 1 to 10, wherein the data generation unit generates the spectrum data from the sensor signal output by the vibration sensor, which is oriented so that one of its measurement axes coincides with the rotation axis.

12. A diagnostic method performed by a diagnostic device that has a rotor that rotates around a rotation axis and that diagnoses the condition of a target device mounted on a moving object, the diagnostic method comprising: generating spectral data indicating the distribution of the vibration magnitude of the target device for each frequency from a vibration sensor signal output by a vibration sensor that measures the vibration magnitude of the target device; determining an approximate rotation speed that is an estimate of the rotation speed of the rotor; detecting a peak in the vibration magnitude of the spectral data in a frequency band that includes the approximate rotation speed; obtaining the frequency corresponding to the detected peak as the rotation speed of the rotor; using a diagnosis target frequency that is determined based on the obtained rotation speed of the rotor, detecting a peak in the vibration magnitude of the spectral data in a frequency band that includes the diagnosis target frequency; and diagnosing the condition of the target device based on the peak value of the detected peak.

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