Diagnostic device and diagnostic method

Abstract

A diagnostic device (1) diagnoses the state of a target apparatus, which is an electric motor or a rotating mechanism that rotates by receiving rotational force transmitted from the electric motor. The diagnostic device (1) is provided with a data generation unit (11), a first approximate rotation speed acquisition unit (12), a rotation speed acquisition unit (13), and a diagnostic unit (14). The data generation unit (11) generates, from a vibration sensor signal, spectral data indicating the distribution of the vibration level of the target apparatus. The first approximate rotation speed acquisition unit (12) obtains a first approximate rotation speed, which is the approximate value of the rotation speed of the electric motor, from a drive power frequency which is a frequency corresponding to a peak of the vibration level in the spectral data. The rotation speed acquisition unit (13) acquires, as the rotation speed of the electric motor, a frequency corresponding to a peak in a frequency band in which the first approximate rotation speed is the upper limit value. The diagnostic unit (14) diagnoses the state of the target apparatus on the basis of the peak value of a peak in a frequency band including a diagnosis target frequency corresponding to the rotation speed of the electric motor 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 electric motors and rotating mechanisms that rotate by receiving rotational force from the electric motor, contact between components during operation can cause wear or damage. Therefore, the condition of electric motors and rotating mechanisms is diagnosed. One example of a diagnostic method is to analyze vibration data of rotating bodies based on the rotation speed of the rotating bodies. This diagnostic method requires rotation speed data for each rotating body, so a rotation sensor must be installed 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 for diagnosing the condition of a target device that is an electric motor that rotates when supplied with AC power or a rotating mechanism that rotates when rotational force is transmitted from the electric motor, and includes a data generation unit, a first approximate rotation speed acquisition unit, a rotation speed acquisition unit, and a diagnosis unit. The data generation unit generates spectral data indicating a distribution of 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 first approximate rotation speed acquisition unit detects a peak in the vibration magnitude of the spectral data and calculates a first approximate rotation speed that is an approximate value of the rotation speed of the electric motor from a drive power frequency that is a frequency corresponding to the detected peak. The rotation speed acquisition unit detects a peak in the vibration magnitude of the spectral data in a frequency band having an upper limit value for the first approximate rotation speed and acquires, as the rotation speed of the electric motor, the frequency corresponding to the detected peak in the frequency band having an upper limit value for the first approximate rotation speed. The diagnosis unit detects a peak in the vibration magnitude of the spectrum data in a frequency band including the frequency to be diagnosed, using the frequency to be diagnosed that is determined based on the rotation speed of the electric motor acquired by the rotation speed acquisition unit, and diagnoses the condition of the target equipment based on the peak value of the peak detected in the frequency band including the frequency to be diagnosed.

[0008] A diagnostic device according to the present disclosure calculates a drive power supply frequency from spectrum data, calculates a first approximate rotation speed of the electric motor from the drive power supply frequency, and acquires, as the rotation speed of the electric motor, a frequency corresponding to a peak in the spectrum data in a frequency band having the first approximate rotation speed as an upper limit value. The diagnostic device diagnoses the condition of the target equipment from the peak in the spectrum data in a frequency band including a diagnosis target frequency determined based on the rotation speed. The diagnostic device calculates a first approximate rotation speed, which is an approximate value of the rotation speed of the electric motor, and calculates the rotation speed of the rotating body from the first 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 equipment with a simple configuration while reducing the influence of disturbances.

[0009] FIG. 1 is a diagram showing an example of mounting a drive device according to embodiment 1 on a railway vehicle. FIG. 2 is a block diagram of a drive device according to embodiment 1. FIG. 3 is a block diagram of a modified example of a drive device according to embodiment 1. FIG. 4 is a diagram showing a hardware configuration of a diagnostic device according to embodiment 1. FIG. 5 is a flowchart showing an example of diagnostic processing performed by the diagnostic device according to embodiment 1. FIG. 6 is a timing chart showing an example of vibration data and presence or absence of current flow in embodiment 1. FIG. 7 is a diagram showing an example of spectrum data in embodiment 1. FIG. 8 is a block diagram of a diagnostic device according to embodiment 2. FIG. 9 is a diagram showing an example of spectrum data in embodiment 2. FIG. 10 is a block diagram showing a modified example of a diagnostic device according to an embodiment. FIG. 11 is a diagram showing a modified example of a hardware configuration of a diagnostic device according to an 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 a diagnostic device that is mounted on a railway vehicle and diagnoses the condition of a target device that is an electric motor that generates propulsive force for the railway vehicle or a rotation mechanism that rotates by receiving rotational force from the electric motor. The bogies 41 shown in FIG. 1 are attached to each carriage of the railway vehicle, for example, two bogies 41, and support the car body. In FIG. 1, the X-axis direction indicates the width direction of the vehicle. 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 are induction motors that 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, wheels 42 attached to both ends of the axle 45, and air springs 46 that support the car body. 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] The target equipment to be diagnosed by the diagnostic device 1 shown in Fig. 2 is an electric motor 91 and a rotating mechanism that rotates by receiving rotational force from the electric motor 91, such as a joint 43, a gear device 44, an axle 45, and wheels 42. The diagnostic device 1 for diagnosing the condition of the electric motor 91, which is an example of the target equipment, includes a data generation unit 11 that generates spectrum data indicating the distribution of vibration magnitude of the electric motor 91 for each frequency from measurements taken by a vibration sensor 92, a first approximate rotation speed acquisition unit 12 that calculates a first approximate rotation speed, which is an approximate value of the rotation speed of the electric motor 91, a rotation speed acquisition unit 13 that calculates the rotation speed of the electric motor 91 from the first approximate rotation speed and the spectrum data, and a diagnostic unit 14 that diagnoses the condition of the electric motor 91 from the rotation speed and the spectrum data. As shown in Fig. 3, the diagnostic device 1 preferably further includes an energization determination unit 15 that determines whether the electric motor 91 is energized based on measurements taken by a current sensor 93.

[0015] The hardware configuration of the diagnostic device 1 having the above configuration is shown in Fig. 4. 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 a vibration sensor 92 and a current sensor 93 via an interface 83. The interface 83 has interface modules that comply with one or more standards depending on the connected device.

[0019] The diagnostic device 1 having the above configuration continuously executes the diagnostic process shown in Fig. 5 during operation. The data generator 11 included in the diagnostic device 1 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 S11). The data generator 11 shown in Fig. 3 acquires, from the vibration sensor 92, the vibration sensor signal, which is an analog data signal whose amplitude changes depending on the vibration magnitude of the measurement target. The data generator 11 generates spectrum data, which is frequency domain data, from the vibration sensor signal, which is a time domain signal.

[0020] 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 (e.g., one second). The data generator 11 sends the generated spectral data to the first approximate rotation speed acquirer 12.

[0021] As shown in Fig. 5, the energization determiner 15 determines whether the electric motor 91 is energized (step S12). Specifically, the energization determiner 15 shown in Fig. 3 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 a 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 determiner 15 outputs the determination result to the first approximate rotation speed acquirer 12.

[0022] As shown in FIG. 5 , if the electric motor 91 is not energized (step S12; No), the above-described process is repeated from step S11. If the electric motor 91 is energized (step S12; Yes), the first approximate rotation speed acquisition unit 12 calculates the drive power supply frequency from the spectrum data generated in step S11 (step S13). The drive power supply frequency is the frequency of AC power supplied to the electric motor 91. 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 harmonic components of the drive power supply frequency. Therefore, the first approximate rotation speed acquisition unit 12 calculates the drive power supply frequency from the spectrum data.

[0023] FIG. 6 shows a timing chart illustrating an example of vibration data and whether or not current is being applied. In FIG. 6, 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 an H (High) level when the electric motor 91 is energized and at an L (Low) level when the electric motor 91 is not energized. The time when the supply of current to the electric motor 91 starts is defined as T1, and the time when the supply of current to the electric motor 91 stops is defined as T2. The first approximate rotation speed acquisition unit 12 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, a 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.

[0024] 7 shows an example of the spectrum data generated by the data generator 11 during the period from time T1 to time T2. The horizontal axis of FIG. 7 represents frequency (unit: Hz), and the vertical axis represents the magnitude of vibration as the amplitude of acceleration (unit: m / s ２ As described above, the spectrum data includes components of the drive power supply frequency and components of harmonics of the drive power supply frequency, so the first approximate rotation speed obtaining unit 12 obtains the drive power supply frequency by, for example, detecting the peak of the amplitude of vibration of the spectrum data in a frequency band whose upper limit is the drive power supply frequency Fmax.

[0025] The drive power supply frequency f and the rotation speed N (unit: Hz) of the electric motor 91 satisfy the relational expression of the following equation (1). In the following equation (1), 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. The rotation speed N of the electric motor 91 calculated by the following equation (1) is the number of times the electric motor 91 rotates per unit time, specifically, per second, and can be expressed in rps (revolutions per second). 1 rps = 1 s －１ Therefore, the rotation speed N is －１ , that is, expressed in units of Hz. By substituting the number of poles p determined as an operational specification of the motor 91 for the number of poles p in the following equation (1), substituting the maximum rotation speed Nmax determined as an operational specification of the motor 91 for the rotation speed N, and setting s = 0, the drive power supply frequency f when the rotation speed of the 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 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.

[0026]

[0027] As an example, the first approximate rotation speed obtaining unit 12 detects peaks in the amplitude of vibration of the spectrum data within a frequency band ΔF0 of 0 Hz or more and Fmax or less, and obtains the frequency Fp corresponding to the detected peak as the drive power supply frequency, as shown in Fig. 7. Specifically, the first approximate rotation speed obtaining unit 12 obtains the frequency Fp corresponding to the largest peak among the peaks detected within the frequency band ΔF0 of 0 Hz or more and Fmax or less, as the drive power supply frequency.

[0028] As shown in Fig. 5, the first approximate rotation speed obtaining unit 12 obtains a first approximate rotation speed, which is an approximate value of the rotation speed of the electric motor 91, from the drive power supply frequency Fp (step S14). Specifically, the first approximate rotation speed obtaining unit 12 shown in Fig. 3 substitutes the number of poles p determined as an operational specification of the electric motor 91 for the number of poles p in the above equation (1), substitutes the frequency Fp (unit: Hz) for the drive power supply frequency f, and obtains the rotation speed N obtained when s = 0 as the first approximate rotation speed Fa1. The first approximate rotation speed obtaining unit 12 outputs the first approximate rotation speed Fa1 to the rotation speed obtaining unit 13. If the electric motor 91 is an induction motor with four poles, Fa1 = Fp / 2 holds.

[0029] Because slip occurs in the electric motor 91, the actual rotation speed of the electric motor 91 is smaller than the first approximate rotation speed Fa1 calculated in the above formula (1) with the slip s = 0. Therefore, as shown in Fig. 5 , the rotation speed acquisition unit 13 detects a peak in the amplitude of vibration of the spectrum data in a frequency band whose upper limit value is the first approximate rotation speed calculated in step S14, and acquires the frequency corresponding to the detected peak as the rotation speed of the electric motor 91 (step S15).

[0030] 7 , the rotation speed acquisition unit 13 detects a peak in the amplitude of vibration of the spectrum data in a frequency band ΔF1, the upper limit of which is the first approximate rotation speed Fa1 calculated by the first approximate rotation speed acquisition unit 12, and acquires the frequency Fe corresponding to the peak detected in the frequency band ΔF1 as the rotation speed of the electric motor 91. The bandwidth of the frequency band ΔF1 is determined according to 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 defined as the operating specifications of the electric motor 91 for the number of poles p in Equation (1) above, substituting the maximum value of slip that can occur during operation of the electric motor 91 for the slip s, and substituting the frequency Fp for the drive power frequency f may be set as the lower limit of the frequency band ΔF1. The maximum value of slip is, for example, 5%.

[0031] When no peak exists in the frequency band ΔF1, the rotation speed acquisition unit 13 acquires the first approximate rotation speed Fa1 as the rotation speed of the electric motor 91. The rotation speed acquisition unit 13 outputs the rotation speed of the electric motor 91 to the diagnosis unit 14.

[0032] As shown in FIG. 5 , the diagnoser 14 determines a diagnosis target frequency from the rotational speed calculated in step S15 and detects a spectrum value representing the magnitude of vibration corresponding to the diagnosis target frequency from the spectrum data (step S16). The diagnosis target frequency is determined based on the rotational speed of the electric motor 91. Specifically, for example, vibrations occur in a bearing included in the electric motor 91 and rotatably supporting the shaft 91 a 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 period of the vibration depends on the rotational speed of the electric motor 91. 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.

[0033] 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.

[0034]

[0035] The diagnosing unit 14 diagnoses the state of the electric motor 91 based on the peak value of the detected peak (step S17). 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, based on simulations, test data, etc., for each frequency corresponding to the type of abnormality in the electric motor 91. 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 S17, the diagnosing device 1 repeats the above-described process from step S11.

[0036] As described above, the diagnostic device 1 according to the first embodiment detects a peak in the vibration magnitude of the spectrum data based on the vibration sensor signal, and calculates a first approximate rotation speed of the electric motor 91 from the drive power supply frequency, which is the frequency corresponding to the peak. The diagnostic device 1 detects a peak in the vibration magnitude of the spectrum data in a frequency band having the first approximate rotation speed as its upper limit, and acquires the frequency corresponding to the peak as the rotation speed of the electric motor 91. The diagnostic device 1 diagnoses the condition of the electric motor 91 based on the spectrum value at the diagnosis target frequency corresponding to the rotation speed.

[0037] The diagnostic device 1 does not require a rotation sensor for detecting the rotation speed of the electric motor 91, and therefore has a simple configuration. The diagnostic device 1 detects peaks in a frequency band with the first approximate rotation speed as its upper limit value, and by searching for peaks in a limited frequency band, there are fewer errors in the process of identifying the rotation speed of the electric motor 91 and it is less susceptible to the influence of disturbance vibrations. As a result, the diagnostic device 1 can accurately determine the rotation speed of the electric motor 91. Therefore, the diagnostic device 1 can accurately diagnose the condition of the electric motor 91 with a simple configuration.

[0038] Second Embodiment The method for determining the rotation speed of the electric motor 91 is not limited to the above example. A diagnostic device that determines the rotation speed of the electric motor 91 by a method different from that of the first embodiment will be described in the second embodiment, focusing on the differences from the first embodiment.

[0039] The diagnostic device 2 according to the second embodiment shown in Fig. 8 includes, in addition to the configuration of the diagnostic device 1 according to the first embodiment shown in Fig. 3, a second approximate rotation speed acquisition unit 16 that acquires a second approximate rotation speed, which is an approximate value of the rotation speed of the electric motor 91, from the speed of the railway vehicle. The hardware configuration of the diagnostic device 2 is similar to that of the diagnostic device 1.

[0040] The diagnostic device 2 having the above configuration continuously performs the diagnostic process shown in Fig. 9 during operation. The processes in steps S11 to S15 are the same as the processes performed by the diagnostic device 1 shown in Fig. 5.

[0041] If the electric motor 91 is not energized (step S12; No), the second approximate rotation speed acquisition unit 16 provided in the diagnostic device 2 acquires the position information of the railway vehicle, estimates the speed of the railway vehicle from the change in the position information of the railway vehicle per unit time, and calculates the second approximate rotation speed from the estimated railway vehicle speed (step S21).

[0042] 8 acquires the determination result from the energization determination unit 15 and acquires railcar position information from a GPS (Global Positioning System) receiver (not shown). When the determination result from the energization determination unit 15 indicates that the electric motor 91 is not energized, the second approximate rotation speed acquisition unit 16 calculates the railcar speed from changes in the railcar position information per unit time. The second approximate rotation speed acquisition unit 16 calculates a second approximate rotation speed, which is an approximate value of the rotation speed of the electric motor 91, from the calculated railcar speed based on the gear ratio of the gear device 44 and the diameter of the wheels 42.

[0043] In detail, the second approximate rotation speed obtaining unit 16 obtains the second approximate rotation speed Fa2 (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 (3). The second approximate rotation speed Fa2 obtained by the following equation (3) is the number of rotations of the electric motor 91 per unit time, specifically, per second, and is expressed in rps (revolutions per second). 1 rps = 1 s －１Therefore, the second estimated rotation speed Fa2 is s －１ , that is, expressed in units of Hz. The second approximate rotation speed acquisition unit 16 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 91a required for the wheel 42 to rotate once. The second approximate rotation speed acquisition unit 16 sends the obtained second approximate rotation speed to the rotation speed acquisition unit 13.

[0044]

[0045] As shown in FIG. 9 , when the rotation speed acquisition unit 13 acquires the second approximate rotation speed calculated in step S21 from the second approximate rotation speed acquisition unit 16, it detects a peak in the vibration magnitude of the spectrum data in a frequency band including the second approximate rotation speed, and acquires the frequency corresponding to the detected peak in the frequency band including the second approximate rotation speed as the rotation speed of the electric motor 91 (step S22).

[0046] In detail, as shown in FIG. 10 , the rotation speed acquisition unit 13 detects a peak in the vibration magnitude of the spectrum data in a frequency band ΔF2 that includes the second estimated rotation speed Fa2 calculated by the second estimated rotation speed acquisition unit 16, and acquires the frequency Fe corresponding to the peak detected within the frequency band ΔF2 as the rotation speed of the electric motor 91.

[0047] The frequency band ΔF2 including the second approximate rotation speed Fa2 is, for example, a frequency band having the second approximate rotation speed Fa2 as its center frequency. The bandwidth of the frequency band ΔF2 is determined according to the possible values ​​of the error between the second approximate rotation speed Fa2 and the actual rotation speed of the electric motor 91. The error between the second approximate rotation speed Fa2 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 ΔF2 is a frequency range estimated to include the second approximate rotation speed Fa2 and the actual rotation speed of the electric motor 91 based on the error between the second approximate rotation speed Fa2 and the actual rotation speed of the electric motor 91. For example, the frequency band ΔF2 is a band having the second approximate rotation speed Fa2 as its center frequency and including a range of 5% above and below the center frequency. Specifically, when the second approximate rotation speed Fa2 is 10 Hz, the frequency band ΔF2 is in the range of ±0.5 Hz centered around 10 Hz, in other words, in the range of 9.5 Hz or more and 10.5 Hz or less.

[0048] When no peak exists in the frequency band ΔF2, the rotation speed acquisition unit 13 acquires the second approximate rotation speed Fa2 as the rotation speed of the electric motor 91.

[0049] The rotation speed acquisition unit 13 outputs the rotation speed of the electric motor 91 to the diagnosis unit 14. In detail, when the electric motor 91 is energized, the rotation speed acquisition unit 13 outputs the frequency corresponding to the peak in the frequency band ΔF1 as the rotation speed of the electric motor 91 to the diagnosis unit 14, and when the electric motor 91 is not energized, the rotation speed acquisition unit 13 outputs the frequency corresponding to the peak in the frequency band ΔF2 as the rotation speed of the electric motor 91 to the diagnosis unit 14.

[0050] The operation of the diagnosing unit 14 is the same as in the first embodiment, in that it detects peaks in the vibration magnitude of spectrum data in a frequency band including a diagnosis target frequency that varies depending on the rotation speed acquired from the rotation speed acquiring unit 13, and diagnoses the state of the target device based on the detected peaks. In detail, the processes of steps S16 and S17 in Fig. 9 are the same as the processes performed by the diagnosing device 1 shown in Fig. 5. After completing the process of step S17, the diagnosing device 2 repeats the above-mentioned processes from step S11.

[0051] As described above, when the electric motor 91 is not energized, the diagnostic device 2 according to the second embodiment determines the rotation speed of the electric motor 91 from the second approximate rotation speed according to the speed of the railway vehicle, and therefore, it is possible to determine the rotation speed of the electric motor 91 even when the electric motor 91 is not energized. As a result, the diagnostic device 2 can accurately diagnose the condition of the electric motor 91.

[0052] The present disclosure is not limited to the above-described embodiment. The data generator 11 is not limited to the above-described embodiment, and may perform any signal processing necessary to generate spectral data. As an example, the data generator 11 included in the diagnostic device 2 may generate spectral 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.

[0053] The method by which the first approximate rotation number obtaining unit 12 obtains the drive power supply frequency is not limited to the above example. As an example, the first approximate rotation number obtaining unit 12 may obtain the frequency corresponding to the sharpest peak in the detected spectrum as the drive power supply frequency. The degree of sharpness of the peak is determined by the difference between the peak value and the spectral value at a frequency near the frequency corresponding to the peak, for example, a frequency of ±1 Hz. For example, the first approximate rotation number obtaining unit 12 may determine that the peak having the largest difference between the peak value and the spectral value at a frequency near the frequency corresponding to the peak is the sharpest.

[0054] The rotation speed obtaining unit 13 may use a frequency band ΔF1 whose bandwidth changes depending on the load on the electric motor 91. Specifically, the rotation speed obtaining unit 13 may obtain the first approximate rotation speed using the frequency band ΔF1 whose bandwidth becomes wider as the load on the electric motor 91 increases.

[0055] As an example, the rotation speed acquisition unit 13 acquires information about the vehicle weight from a load-varying detector that detects the vehicle weight based on changes in the internal pressure of the air spring 46. The rotation speed acquisition unit 13 calculates the rotation speed of the electric motor 91 using a frequency band ΔF1 having a bandwidth that increases as the vehicle weight increases.

[0056] As another example, the rotation speed acquisition unit 13 acquires the position information of the railway vehicle from a GPS receiver, and calculates the gradient of the running position from the correspondence between the position information of the railway vehicle and the gradient information. The rotation speed acquisition unit 13 is assumed to store the correspondence between the position information of the railway vehicle and the gradient information in advance. The rotation speed acquisition unit 13 calculates the rotation speed of the electric motor 91 using a frequency band ΔF1 having a bandwidth that increases as the gradient increases.

[0057] The bandwidth of the frequency band ΔF2 used by the rotation speed acquisition unit 13 may be a constant value, for example, 2 Hz, regardless of the second approximate rotation speed.

[0058] The rotation speed acquisition unit 13 included in the diagnosis device 2 may calculate the rotation speed of the electric motor 91 from a spectral peak in a frequency band having the first approximate rotation speed calculated by the first approximate rotation speed acquisition unit 12 as an upper limit value and a peak of the spectral data in a frequency band including the second approximate rotation speed. In detail, the rotation speed acquisition unit 13 detects a peak in the magnitude of vibration of the spectral data in a range where a frequency band ΔF1 having the first approximate rotation speed Fa1 calculated by the first approximate rotation speed acquisition unit 12 as an upper limit value and a frequency band ΔF2 including the second approximate rotation speed Fa2 calculated by the second approximate rotation speed acquisition unit 16 overlap, and acquires, as the rotation speed of the electric motor 91, a frequency Fe corresponding to the peak detected in the range where the frequency bands ΔF1 and ΔF2 overlap.

[0059] 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.

[0060] When there is no peak in either of the frequency bands ΔF1 and ΔF2, the rotation speed acquisition unit 13 acquires the first approximate rotation speed Fa1 or the second approximate rotation speed Fa2 as the rotation speed of the electric motor 91.

[0061] The diagnosis of the state of the target device performed by the diagnoser 14 is not limited to determining whether or not there is an abnormality in the motor 91, and may also include estimating the load (unit: N m) of the motor 91. The diagnoser 14 substitutes the rotation speed of the motor 91 obtained by the rotation speed acquirer 13, the drive power supply frequency obtained by the first approximate rotation speed acquirer 12, and the number of poles of the motor 91 into the above equation (1) to obtain the slip s of the motor 91. The diagnoser 14 estimates the load of the motor 91 from the relationship between the slip and the load of the motor 91. It is assumed that the diagnoser 14 stores the relationship between the slip and the load of the motor 91 in advance.

[0062] The method by which the energization determination unit 15 determines whether or not a current is flowing through the electric motor 91 is not limited to the above example. As one example, the energization determination 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. As another example, the energization determination unit 15 may acquire current information indicating the value of the current flowing through the electric motor 91 from a train control device that controls the operation of the railway vehicle, and determine whether or not a current is flowing through the electric motor 91 based on the current information.

[0063] The method by which the second approximate rotation speed acquisition unit 16 calculates the second approximate rotation speed is not limited to the above example. As an example, FIG. 11 shows a diagnostic device 3 that calculates the railway vehicle's speed from a vibration sensor signal and calculates the second approximate rotation speed from the railway vehicle. The second approximate rotation speed acquisition unit 16 included in the diagnostic device 3 shown in FIG. 11 may extract a DC component indicating static acceleration from the vibration sensor signal and integrate the extracted DC component to calculate the railway vehicle's speed. In this case, the vibration sensor 92 is an acceleration sensor that measures static acceleration and dynamic vibration. The vibration sensor 92 is oriented 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, and the other measurement axis indicates the direction of travel of the moving body on which the target device is mounted, i.e., the railway vehicle. For example, the vibration sensor 92 is a triaxial acceleration sensor, and its measurement axes are oriented so that they coincide with the X-axis, Y-axis, and Z-axis. By providing the vibration sensor 92 as described above, the vibration sensor 92 can measure changes in acceleration according to the acceleration and deceleration of the railway vehicle.

[0064] The second approximate rotation speed acquisition unit 16 extracts a DC component indicating static acceleration from the vibration sensor signal, specifically, the vibration sensor signal corresponding to a 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's speed. Specifically, the second approximate rotation speed acquisition unit 16 includes an LPF (Low Pass Filter) and an integrating circuit. The cutoff frequency of the LPF is set to a frequency sufficiently low enough to extract the DC component from the vibration sensor signal, e.g., 1 Hz. The second approximate rotation speed acquisition unit 16 processes the vibration sensor signal that has passed through the LPF using the integrating circuit to integrate the acceleration and determine the railway vehicle's speed. The first approximate rotation speed acquisition unit 12 calculates a second approximate rotation speed, which is an approximate value of the rotation speed of the electric motor 91, from the calculated railway vehicle speed based on the gear ratio of the gear unit 44 and the diameter of the wheels 42.

[0065] As another example, second approximate rotation speed acquisition unit 16 may acquire railway vehicle speed information from a train control device that controls operation of the railway vehicle, and calculate the second approximate rotation speed of electric motor 91 from the railway vehicle speed indicated by the speed information, based on the gear ratio of gear unit 44 and the diameter of wheels 42. As another example, the railway vehicle speed may be calculated 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 second approximate rotation speed may be calculated from the calculated railway vehicle speed.

[0066] The diagnostic device 1-3 can diagnose the condition of the rotating mechanism that 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 1 obtains the rotation speed of the rotating mechanism from a peak in a frequency band having the first approximate rotation speed of the electric motor 91 as an upper limit value, and diagnoses the condition of the rotating mechanism based on the spectrum value at the diagnosis target frequency corresponding to the rotation speed.

[0067] The diagnostic devices 2 and 3 calculate the rotation speed of the rotating mechanism from a peak in a frequency band having the first approximate rotation speed of the electric motor 91 as an upper limit value or a frequency band including the second approximate rotation speed of the electric motor 91, and diagnose the state of the rotating mechanism based on the spectral value at the frequency to be diagnosed corresponding to the rotation speed.

[0068] 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. The diagnostic device 1 is not limited to being mounted on a moving body, but may also be installed in ground equipment, such as a train operation control center.

[0069] 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.

[0070] The measurement axes 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 the 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.

[0071] The above hardware configuration and flowchart are merely examples and can be changed and modified as desired.

[0072] As an example, a modified example of the hardware configuration of the diagnostic device 1 is shown in Fig. 12. The diagnostic device 1 may be realized by a processing circuit 84 as shown in Fig. 12. The same applies to the diagnostic devices 2 and 3. The processing circuit 84 included in the diagnostic device 1 shown in Fig. 12 is connected to a vibration sensor 92 and a current sensor 93 via an interface circuit 85.

[0073] 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.

[0074] 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. 12, and the first approximate 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. 4 reading and executing programs stored in a memory 82.

[0075] 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.

[0076] 1, 2, 3 Diagnostic device, 11 Data generation unit, 12 First approximate rotation speed acquisition unit, 13 Rotation speed acquisition unit, 14 Diagnosis unit, 15 Power supply determination unit, 16 Second approximate rotation speed acquisition unit, 41 Bogie, 42 Wheel, 43 Joint, 44 Gear device, 45 Axle, 46 Air spring, 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 which is an electric motor which rotates upon receiving a supply of AC power or a rotating mechanism which rotates upon receiving rotational force from the electric motor, comprising: a data generation unit which generates spectral data which indicates a distribution of the vibration magnitude of the target device for each frequency from a vibration sensor signal output by a vibration sensor which measures the vibration magnitude of the target device; a first approximate rotation speed acquisition unit which detects a peak in the vibration magnitude of the spectral data and calculates a first approximate rotation speed which is an approximate value of the rotation speed of the motor from a drive power frequency which is a frequency corresponding to the detected peak; a rotation speed acquisition unit which detects a peak in the vibration magnitude of the spectral data in a frequency band which has an upper limit value for the first approximate rotation speed and acquires the frequency corresponding to the detected peak in the frequency band which has an upper limit value for the first approximate rotation speed as the rotation speed of the motor; and a diagnostic unit which uses a diagnosis target frequency which is determined based on the rotation speed of the electric motor acquired by the rotation speed acquisition unit to detect a peak in the vibration magnitude of the spectral data in a frequency band which 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 which includes the diagnosis target frequency. A diagnostic device comprising:

2. The diagnostic device according to claim 1, further comprising a current flow determination unit that determines whether or not a current is flowing through the electric motor, wherein the first approximate rotation speed acquisition unit detects a peak in the vibration magnitude of the spectrum data generated from the vibration sensor signal output during a period in which it is determined by the current flow determination unit that a current is flowing through the electric motor.

3. The diagnostic device according to claim 2, wherein the current flow determination unit acquires current information indicating the value of the current flowing through the motor from a control device that controls the operation of a mobile body on which the motor is mounted, and determines whether or not current is flowing through the motor based on the current information.

4. The diagnostic device according to claim 2 or 3, wherein the data generation unit generates the spectrum data from the vibration sensor signal output by the vibration sensor that is mounted on a moving body and measures the magnitude of vibration of the target equipment, which is the electric motor that generates the propulsive force of the moving body or the rotating mechanism that rotates by receiving rotational force from the electric motor, and further comprises a second approximate rotation speed acquisition unit that calculates a second approximate rotation speed that is an approximate value of the rotation speed of the electric motor from the speed of the moving body, and the rotation speed acquisition unit detects peaks in the magnitude of vibration of the spectrum data in a frequency band that has the first approximate rotation speed as an upper limit value and a frequency band that includes the second approximate rotation speed, and acquires the frequency corresponding to the peak detected in the frequency band that has the first approximate rotation speed as an upper limit value and the frequency band that includes the second approximate rotation speed as the rotation speed of the electric motor.

5. The diagnostic device according to claim 4, 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 having the first approximate rotation speed as an upper limit value and a frequency band including the second approximate rotation speed overlap, and acquires the frequency corresponding to the peak detected in the range where the frequency band having the first approximate rotation speed as an upper limit value and a frequency band including the second approximate rotation speed overlap as the rotation speed of the electric motor.

6. The diagnostic device according to claim 4, wherein the rotation speed acquisition unit detects a peak in the magnitude of vibration of the spectrum data generated from the vibration sensor signal output during a period in which the energization determination unit determines that current is flowing through the electric motor in a frequency band having the first approximate rotation speed as an upper limit value, and detects a peak in the magnitude of vibration of the spectrum data generated from the vibration sensor signal output during a period in which the energization determination unit determines that current is not flowing through the electric motor in a frequency band including the second approximate rotation speed.

7. A diagnostic device as claimed in any one of claims 1 to 6, wherein the data generation unit generates the spectrum data from the vibration sensor signal output by the vibration sensor that is mounted on a railway vehicle and measures the magnitude of vibration 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.

8. A diagnostic device according to any one of claims 1 to 7, wherein the first approximate rotation speed acquisition unit detects a peak in the magnitude of vibration of the spectrum data in a frequency band having an upper limit value equal to a maximum drive power supply frequency, which is the drive power supply frequency when the rotation speed of the electric motor reaches its maximum rotation speed.

9. A diagnostic device according to any one of claims 1 to 8, wherein the first approximate rotation speed acquisition unit detects peaks in the vibration magnitude of the spectrum data, acquires the frequency corresponding to the largest peak among the detected peaks as the drive power supply frequency, and determines the first approximate rotation speed from the acquired drive power supply frequency.

10. A diagnostic device according to any one of claims 1 to 9, wherein the first approximate rotation speed acquisition unit detects peaks in the vibration magnitude of the spectrum data, acquires the frequency corresponding to the sharpest peak among the detected peaks as the drive power supply frequency, and determines the first approximate rotation speed from the acquired drive power supply frequency.

11. A diagnostic device as described in any one of claims 1 to 10, wherein the first approximate rotation speed acquisition unit determines the rotation speed of the motor in a state where no slip occurs in the motor from the drive power supply frequency and the number of poles of the motor, and acquires the determined rotation speed as the first approximate rotation speed.

12. A diagnostic device according to any one of claims 1 to 11, wherein the rotation speed acquisition unit detects a peak in the magnitude of vibration of the spectrum data in the frequency band whose bandwidth changes according to the load on the motor, with the first approximate rotation speed as an upper limit value.

13. A diagnostic device according to any one of claims 1 to 12, wherein the diagnostic unit determines the slip of the motor from the rotational speed, the drive power supply frequency, and the number of poles of the motor, and estimates the load of the motor from the determined slip of the motor based on the relationship between the slip of the motor and the load.

14. A diagnostic method performed by a diagnostic device that diagnoses the condition of a target device that is an electric motor that rotates when supplied with AC power or a rotating mechanism that rotates when rotational force is transmitted from the electric motor, the method comprising: generating spectral data that indicates 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; detecting a peak in the vibration magnitude of the spectral data; determining a first approximate rotation speed that is an approximate value of the rotation speed of the motor from the drive power frequency that is the frequency corresponding to the detected peak; detecting a peak in the vibration magnitude of the spectral data in a frequency band having an upper limit for the first approximate rotation speed; obtaining the frequency corresponding to the detected peak in the frequency band having an upper limit for the first approximate rotation speed as the rotation speed of the motor; using a diagnosis target frequency that is determined based on the obtained rotation speed of the motor, detecting a peak in 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 peak detected in the frequency band that includes the diagnosis target frequency.

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