Diagnostic device and method for diagnosing support structure of gear device

Abstract

To provide a diagnostic device for a support structure of a gear device.SOLUTION: The diagnostic device for a support structure of a gear device includes: a first sensor for detecting vibration of a support structure that supports the gear device; and a processing circuit for processing a detection result of the first sensor, the processing circuit executing calculating the difference between first vibration data and second vibration data at the same meshing frequency and performing diagnosis of the state of the support structure on the basis of the difference, the first vibration data being data indicating vibration of the support structure at the meshing frequency during a first period in which the support structure is in a normal state, the second vibration data being data indicating vibration of the support structure at the meshing frequency, the second vibration data being processed from the detection result of the first sensor during a second period later than the first period, the meshing frequency being a frequency at which a plurality of teeth of a gear included in the gear device mesh with an engagement target.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a diagnostic device and method for a support structure of a gear device. [Background technology]

[0002] Patent Document 1 discloses a device for detecting the condition of bearings in gear devices that make up a bogie of a railway vehicle. The device detects the actual state of damage to the bearings based on information including parameters related to bearing vibrations measured before the railway vehicle begins actual operation. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2015-111113 Summary of the Invention [Problem to be solved by the invention]

[0004] The device in Patent Document 1 detects abnormalities in the state of a gear device. However, since the support structure that supports the gear device is subject to various loads and vibrations, abnormalities may also occur in the state of the support structure.

[0005] Therefore, one aspect of the present disclosure aims to provide a diagnostic device and diagnostic method for a support structure of a gear device.

[0006] A diagnostic device for a support structure of a gear device according to one embodiment of the present disclosure is a diagnostic device for a support structure of a gear device, comprising a first sensor that detects vibrations of the support structure that supports the gear device, and a processing circuit that processes the detection results of the first sensor, wherein the processing circuit calculates the difference between first vibration data and second vibration data at the same meshing frequency, and diagnoses the condition of the support structure based on the difference, wherein the first vibration data is data that indicates the vibration of the support structure at the meshing frequency during a first period in which the support structure is in a normal state, and the second vibration data is data that indicates the vibration of the support structure at the meshing frequency, processed from the detection results of the first sensor during a second period that is later than the first period, and the meshing frequency is the frequency at which multiple teeth of a gear included in the gear device mesh with an engaging object. [Brief explanation of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram illustrating an example of a configuration of a diagnostic system according to an embodiment. [Figure 2] FIG. 2 is a flowchart showing an example of the operation of the diagnostic device according to the embodiment. [Figure 3] FIG. 3 is a flowchart showing the details of step S2 in the flowchart of FIG. [Figure 4] FIG. 4 is a diagram showing an example of a frequency analysis result of a detection signal of the first sensor for a time period regarding the first data and the second data. [Figure 5] FIG. 5 is a diagram showing an example of a frequency analysis result of the detection signal of the second sensor for the first data and the second data during a time period. [Figure 6] FIG. 6 is a flowchart showing the details of step S6 in the flowchart of FIG. [Figure 7] FIG. 7 is a diagram showing an example of time-series data of the difference in vibration transmission magnification at one meshing frequency. [Figure 8] FIG. 8 is a diagram illustrating an example of the configuration of a diagnostic system according to the first modification. [Figure 9]FIG. 9 is a flowchart showing an example of the operation of the diagnostic device according to the first modification. [Figure 10] FIG. 10 is a flowchart showing the details of step S2A in the flowchart of FIG. [Figure 11] FIG. 11 is a flowchart showing the details of step S6A in the flowchart of FIG. [Figure 12] FIG. 12 is a diagram illustrating an example of the configuration of a diagnostic system according to the second modification. [Figure 13] FIG. 13 is a front view showing an application example of the diagnostic system. [Figure 14] FIG. 14 is a side view showing an application example of the diagnostic system. [Figure 15] FIG. 15 is a side view showing an application example of the diagnostic system. DETAILED DESCRIPTION OF THE INVENTION

[0008] Hereinafter, exemplary embodiments of the present disclosure will be described with reference to the drawings. The embodiments described below are all comprehensive or specific examples. Among the components in the following embodiments, components that are not recited in the independent claims showing the highest concepts will be described as optional components. Each figure in the accompanying drawings is a schematic diagram and is not necessarily an exact drawing. In each figure, substantially identical components are assigned the same reference numerals, and duplicated descriptions may be omitted or simplified. In this specification and claims, the term "device" may refer not only to one device but also to a system including multiple devices.

[0009] A diagnostic system 100 according to an exemplary embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of the configuration of the diagnostic system 100 according to the embodiment. The diagnostic system 100 includes a diagnostic device 30 and a first sensor 40 that detects vibrations of a support structure 20 that supports a gear train 10. In this embodiment, the diagnostic system 100 further includes, but is not limited to, a second sensor 50 that detects vibrations of the gear train 10.

[0010] The gear device 10 transmits a driving force of a driving source D to a driven object T. FIG. 1 shows the interior of the gear device 10. The gear device 10 includes a plurality of gears 11, at least two of which are gear-engaged. In this embodiment, the gear device 10 includes two shafts 12 and 13, each having one or more gears 11 attached thereto, and a housing 14. The housing 14 houses the plurality of gears 11 and the shafts 12 and 13. The gear 11 on the first shaft 12 and the gear 11 on the second shaft 13 are directly gear-engaged, but may also be indirectly gear-engaged via another gear 11. For example, the first shaft 12 is connected to a driving source D so as to be able to transmit a driving force, and the second shaft 13 is connected to a driven object T so as to be able to transmit a driving force.

[0011] For example, the gear device 10 may have a structure that reduces or increases the rotational driving speed of the driving source D and transmits the driving force to the driven object T. The gear device 10 may have a structure that changes the direction of the driving force of the driving source D and transmits the driving force to the driven object T. The gear device 10 may have a structure that changes the rotation direction of the rotational driving force, or may have a structure that converts the rotational driving force into a linear driving force or vice versa. The gear device 10 may have a structure that branches the driving force of the driving source D and transmits it to multiple driven objects T. Examples of the driving source D may include an internal combustion engine, an electric motor, a compressor, a pump, a hydraulic or pneumatic cylinder, a turbine or a rotor of a generator, and other linear or rotary actuators.

[0012] In this embodiment, the diagnostic system 100 includes, but is not limited to, a rotation sensor 60 that detects the rotation speed of the shaft 12 or 13. The rotation sensor 60 is arranged to detect the rotation speed of the second shaft 13 and outputs a signal indicating the detection result to the diagnostic device 30. Examples of the rotation sensor 60 may include an encoder, a Hall sensor, and an optical sensor. The rotation sensor 60 may be arranged in the driving source D or the driven object T. The rotation sensor 60 may also be arranged to detect the rotation speed of another component that can transmit rotational driving force to the shaft 12 or 13. The rotation sensor 60 may be a sensor provided in the mounting object E that mounts the gear device 10, the driving source D, and the driven object T.

[0013] The support structure 20 supports the gear device 10 on the base B of the mounting object E. The support structure 20 may support the gear device 10 from any direction, such as above, below, or side. The support structure 20 may have a structure for attaching the gear device 10 to the base B. The support structure 20 may have a structure for connecting the gear device 10 to the base B. The support structure 20 may have a structure for placing the gear device 10 on the base B, a structure for fastening the gear device 10 to the base B, or a structure for suspending the gear device 10 from the base B. In this embodiment, although not limited thereto, the support structure 20 extends laterally from the base B to cantilever the housing 14 of the gear device 10, thereby attaching the housing 14 to the base B.

[0014] The support structure 20 is attached to the base B. The base B supports the support structure 20 and bears the load of the gear device 10 and the support structure 20. The base B may be a part of the mounted object E, for example, a part of the skeleton of the mounted object E. The skeleton may be a skeleton that forms the entire mounted object E, a skeleton that supports the driving source D, a skeleton that supports the driven object T, or a skeleton that supports another part. The base B may be a part of the driving source D, the driven object T, or any of these.

[0015] The first sensor 40 is disposed on the support structure 20 or the base B. The second sensor 50 is disposed on the gear device 10 or the support structure 20. The gear device 10 generates vibrations due to the rotation of the meshing gears 11. The vibrations are transmitted to the support structure 20 and further transmitted to the base B via the support structure 20.

[0016] When the first sensor 40 is disposed on the base B, it is disposed so as to be able to detect vibrations transmitted from the support structure 20 to the base B. For example, the first sensor 40 is disposed at or near the connection portion between the base B and the support structure 20.

[0017] When the first sensor 40 is disposed on the support structure 20, it is disposed so as to be able to detect vibrations transmitted within the support structure 20. For example, the first sensor 40 is disposed at a position closer to the connection between the base B and the support structure 20 than the second sensor 50. The first sensor 40 can detect vibrations transmitted within the support structure 20.

[0018] When the second sensor 50 is disposed on the support structure 20, it is disposed so as to be able to detect vibrations transmitted from the gear device 10 to the support structure 20. For example, the second sensor 50 is disposed at a position closer to the connection between the gear device 10 and the support structure 20 than the first sensor 40. For example, the second sensor 50 is disposed at or near the connection between the gear device 10 and the support structure 20.

[0019] When the second sensor 50 is disposed in the gear device 10, it is positioned so as to be able to directly or indirectly detect vibrations generated by the gear 11. For example, the second sensor 50 may detect vibrations directly by being positioned to detect vibrations of the bearings of one or both of the shafts 12 and 13, or by being positioned to detect vibrations of the support portions of the bearings. The second sensor 50 may also detect vibrations indirectly by being positioned in the housing 14.

[0020] The sensors 40 and 50 output detection signals indicating the detection results to the diagnostic device 30. For example, the sensors 40 and 50 may detect vibrations at predetermined sampling intervals and output detection signals. The sensors 40 and 50 may be any sensors that can detect vibrations and output detection signals.

[0021] Although not limited thereto, in this embodiment, sensors 40 and 50 are acceleration sensors that detect vibration intensity as acceleration. Specifically, sensors 40 and 50 are triaxial acceleration sensors that detect acceleration in three mutually intersecting axial directions, specifically, acceleration in the mutually orthogonal X-axis, Y-axis, and Z-axis directions. Furthermore, sensors 40 and 50 are arranged so that the X-axis, Y-axis, and Z-axis are oriented in the same direction, but this is not limiting.

[0022] Either or both of the sensors 40 and 50 may be a uniaxial acceleration sensor that detects acceleration in one axis direction, or a 2-axis acceleration sensor that detects acceleration in two intersecting axis directions. Examples of the acceleration sensor include a servo type acceleration sensor, a piezoelectric type acceleration sensor, a strain gauge type acceleration sensor such as a piezoresistive type, a capacitance type acceleration sensor, and a frequency change type acceleration sensor.

[0023] The diagnostic device 30 processes the detection results of the sensors 40 and 50 to diagnose the condition of the support structure 20. In this embodiment, the diagnostic device 30 may be mounted on the mounting target E and connected to the sensors 40 and 50 via wired communication, but is not limited to this. However, the diagnostic device 30 may be located at a location remote from the mounting target E. In this case, the diagnostic device 30 may be connected to the sensors 40 and 50 via wireless communication, or may be connected via wireless communication to a relay device that is connected to the sensors 40 and 50 and mounted on the mounting target E. The diagnostic device 30 may receive the detection results of the sensors 40 and 50 from the relay device via a recording medium.

[0024] The diagnostic device 30 includes a processing circuit. Specifically, the diagnostic device 30 includes a processor P and a memory M. The memory M may include a volatile memory such as a random access memory (RAM) and a non-volatile memory such as a read-only memory (ROM). The memory M may further include a hard disk drive (HDD) or a solid state drive (SSD). The memory M stores a control program for the diagnostic device 30, as well as detection results of the sensors 40 and 50. The diagnostic device 30 may be configured to execute each process under centralized control by a single device, or may be configured to execute each process under distributed control through cooperation between multiple devices.

[0025] Some or all of the functions of the diagnostic device 30 may be realized by the processor P executing a program recorded in the ROM using the RAM as a working memory. Some or all of the functions of the diagnostic device 30 may be realized by a dedicated hardware circuit such as an electronic circuit or an integrated circuit. Some or all of the functions of the diagnostic device 30 may be realized by a combination of the above software functions and hardware circuits.

[0026] For example, the processor P may include, but is not limited to, a CPU (Central Processing Unit), an MPU (Micro Processing Unit), a GPU (Graphics Processing Unit), a microprocessor, a processor core, a multiprocessor, an ASIC (Application-Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), etc. The processor P may implement each process by a logic circuit or a dedicated circuit formed on an IC (Integrated Circuit) chip, an LSI (Large Scale Integration), etc. Multiple processes may be implemented by one or multiple integrated circuits, or may be implemented by a single integrated circuit.

[0027] The diagnostic device 30 may be an electronic circuit board, an electronic control unit, a microcomputer, a personal computer, a workstation, a smart device such as a smartphone or tablet, or other electronic device. The diagnostic device 30 may be a standalone device or may be incorporated into some other device. The diagnostic device 30 may be incorporated into the device as an electronic circuit board, an electronic control unit, or a microcomputer, or may be incorporated as a program to realize its functions.

[0028] The operation of the diagnostic device 30 according to the embodiment will be described with reference to Fig. 2. Fig. 2 is a flowchart showing an example of the operation of the diagnostic device 30 according to the embodiment. First, in step S1, the diagnostic device 30 acquires detection results from the first sensor 40 and the second sensor 50 over a first period in which the support structure 20 is in a normal state, and stores the detection results in the memory M as first data. The diagnostic device 30 associates the detection results of the rotation sensor 60 of the gear device 10 with the detection results of the sensors 40 and 50 based on the detection times, and stores the association results in the memory M as first data. The first data includes data on the detection signals of the sensors 40 and 50 and data on the detection signal of the rotation sensor 60.

[0029] Although not limited thereto, in this embodiment, the first period is a predetermined period from when the support structure 20 is new, or a predetermined period from immediately after the support structure 20 has undergone maintenance. The first period is set to a period during which the support structure 20 can be considered to be in a normal state. For example, the first period may be set based on a maintenance period, which is the interval between timings at which the support structure 20 undergoes maintenance. The first period may be set to a period that is a predetermined percentage of the maintenance period.

[0030] Next, in step S2, the diagnostic device 30 performs frequency analysis processing on each of the detection results of the sensors 40 and 50 for the first data acquired within the first period, and stores the processing results in the memory M. The diagnostic device 30 may process all of the first data and store the results in the memory M, or may process a portion of the first data and store the results in the memory M.

[0031] Next, in step S3, the diagnostic device 30 uses the processing result of step S2 to determine a set value of the vibration transmission magnification for diagnosing the state of the support structure 20. The vibration transmission magnification will be described later.

[0032] Next, in step S4, after the first period has elapsed, the diagnostic device 30 acquires detection results from the sensors 40 and 50 while the drive source D is operating, and stores the detection results in the memory M as second data. The diagnostic device 30 associates the detection results of the rotation sensor 60 with the detection results of the sensors 40 and 50 based on the detection times, and stores the second data in the memory M. The diagnostic device 30 may also store results detected after the most recent diagnosis timing in the memory M. The second data includes data on the detection signals of the sensors 40 and 50 and data on the detection signal of the rotation sensor 60.

[0033] Next, if the current time has reached the diagnosis timing (Yes in step S5), the diagnostic device 30 proceeds to step S6, and if the current time has not yet reached the diagnosis timing (No in step S5), the diagnostic device 30 returns to step S4. For example, the diagnosis timing may be a preset date and time, a preset periodic timing, or a timing commanded by the operator of the diagnostic device 30. For example, the periodic timing may be determined from every few seconds, every few minutes, every tens of minutes, every few hours, every few days, every few weeks, every tens of days, every few months, or every predetermined percentage of the maintenance period. The diagnostic device 30 can perform the processes from step S6 onwards continuously or intermittently.

[0034] In step S6, the diagnostic device 30 performs frequency analysis processing on the second data acquired during a second period up to the current diagnostic timing, for each of the detection results of the sensors 40 and 50. The second period may be the period from after the first period has elapsed until the current diagnostic timing, the period from the previous diagnostic timing to the current diagnostic timing, or any period shorter than the period between diagnostic timings.

[0035] Next, in step S7, the diagnostic device 30 calculates a vibration transmission magnification for diagnosing the state of the support structure 20 using the processing result in step S6.

[0036] Next, in step S8, the diagnostic device 30 diagnoses the condition of the support structure 20 by comparing the processing result of the second data with the set value determined in step S3.

[0037] Next, in step S9, the diagnostic device 30 presents the diagnostic result to the operator of the diagnostic device 30. For example, the diagnostic device 30 may display the diagnostic result on a display or an indicator lamp such as a warning lamp connected to the diagnostic device 30. The diagnostic device 30 may present the diagnostic result only when an abnormality in the support structure 20 is detected.

[0038] Details of step S2 will be described with reference to Fig. 3. Fig. 3 is a flowchart showing details of step S2 in the flowchart of Fig. 2. First, in step S201, diagnostic device 30 classifies the detection result of first sensor 40 included in the first data based on the rotation speed of second shaft 13 detected by rotation sensor 60. For the rotation speed of second shaft 13, a range of rotation speed from 0 to an upper limit value is previously divided into m speed ranges V, and classification information for the m speed ranges V is stored in memory M. The upper limit value is a preset upper limit value of the rotation speed, and m is a natural number equal to or greater than 2.

[0039] Based on the correspondence between the detection signals of the first sensor 40 and the detection signals of the rotation sensor 60, the diagnostic device 30 extracts data of the detection signals of the first sensor 40 corresponding to each speed range V from data of all the detection signals of the first sensor 40. In this way, for each speed range V, the diagnostic device 30 extracts data of the detection signals of the first sensor 40 that are detected when the second shaft 13 is rotating within that speed range V.

[0040] Although not limited thereto, in this embodiment, among the m speed ranges V, there is a speed range that does not include the rotation speed detected by the rotation sensor 60. For this reason, the diagnosis device 30 extracts data of the detection signal of the first sensor 40 corresponding to each of the ma speed ranges Vk (k=1, 2, . . . , ma) that include the rotation speed detected by the rotation sensor 60. ma is a natural number less than m.

[0041] Next, in step S202, the diagnostic device 30 performs frequency analysis on the detection result of the first sensor 40 corresponding to each of the ma speed ranges Vk. The diagnostic device 30 can obtain data representing the distribution of frequency components of the detection signal of the first sensor 40 through frequency analysis. In this embodiment, the frequency analysis method is based on Fourier transform, although not limited thereto. Examples of Fourier transform include discrete Fourier transform (DFT) and fast Fourier transform (FFT). In this embodiment, the diagnostic device 30 uses fast Fourier transform, which is an algorithm for quickly calculating discrete Fourier transform on a computer.

[0042] The diagnostic device 30 extracts data of the detection signal of the first sensor 40 within the speed range Vk for a predetermined time period tp and performs frequency analysis on the extracted data. In the frequency analysis, a frequency band including the entire detection signal included in the time period tp is divided into n portions at a constant sampling frequency fs, where n is a natural number equal to or greater than 2. The data after the frequency analysis includes, for each frequency band at each sampling frequency fs, the amount of signal included in the frequency band as frequency power. Frequency power is an example of vibration intensity. For example, the diagnostic device 30 obtains frequency power data for each frequency band, which represents the relationship shown in data D1a in FIG. 4, through the frequency analysis. FIG. 4 is a diagram showing an example of the frequency analysis results of the detection signal of the first sensor 40 for the time period tp for the first data and the second data. The horizontal axis represents frequency F, and the vertical axis represents frequency power P.

[0043] The diagnostic device 30 extracts data of the detection signal for one or more time periods tp, performs frequency analysis on the extracted data, and obtains frequency analysis data including the results of the frequency analysis. In this embodiment, the diagnostic device 30 extracts data of the detection signal for multiple time periods tp, and performs frequency analysis on each of the extracted data. As a result, the diagnostic device 30 obtains frequency analysis data including time-series data of the results of the frequency analysis at times corresponding to each of the time periods tp.

[0044] Since the first sensor 40 is a three-axis acceleration sensor, the diagnostic device 30 performs frequency analysis processing on the data of the detected values ​​of the X-axis acceleration, Y-axis acceleration, and Z-axis acceleration of the first sensor 40 corresponding to the speed range Vk, individually. As a result, the diagnostic device 30 can obtain frequency analysis data of the X-axis acceleration, Y-axis acceleration, and Z-axis acceleration for each speed range Vk.

[0045] Hereinafter, "frequency analysis data of acceleration in the X-axis direction," "frequency analysis data of acceleration in the Y-axis direction," and "frequency analysis data of acceleration in the Z-axis direction" may be referred to as "X-axis analysis data," "Y-axis analysis data," and "Z-axis analysis data," respectively. Furthermore, when "X-axis analysis data," "Y-axis analysis data," and "Z-axis analysis data" are collectively expressed or expressed without distinction, they may be expressed as "analysis data." In this embodiment, the diagnostic device 30 can obtain analysis data as time-series data.

[0046] Next, in step S203, the diagnosing device 30 extracts the analysis result at the meshing frequency corresponding to the speed range Vk from the frequency analysis result for each speed range Vk.

[0047] The meshing frequency is the number of times per second that the teeth of the gear 11 on the second shaft 13 mesh with the teeth of another gear 11. The meshing frequency is obtained by multiplying the number of teeth of the gear 11 on the second shaft 13 by the number of rotations per second of the second shaft 13. Since this meshing frequency varies depending on the rotational speed of the second shaft 13, there may be multiple meshing frequencies. Because the meshing frequency indicates how often the gears 11 mesh with each other, the acceleration at the meshing frequency can accurately represent the characteristics of the acceleration of the vibration generated by the gear device 10. The gear device 10 may generate particularly large vibrations at the meshing frequency. Note that the gear device 10 may generate particularly large vibrations at frequencies that are integer multiples of the meshing frequency. For example, in the case of Figure 4, in the frequency band Fk that includes the meshing frequency fk, the frequency power takes on the maximum value Pka, and in the frequency band Fk' that includes the frequency fk' that is twice the meshing frequency fk, the frequency power takes on the second maximum value Pka'.

[0048] For each speed range Vk, the diagnostic device 30 determines a representative rotational speed vk from the rotational speeds included in the speed range Vk, and calculates the meshing frequency fk at the representative rotational speed vk. The representative rotational speed vk may be any of the rotational speeds included in the speed range Vk that are actually detected by the rotation sensor 60, or a statistical value thereof, or may be a statistical value of the rotational speeds included in the speed range Vk. Examples of the statistical value may include a maximum value, a minimum value, a median value, a mode value, and an average value.

[0049] For the speed range Vk, the diagnostic device 30 determines a frequency band Fk that includes a meshing frequency fk at the representative rotational speed vk from among the n frequency bands for each sampling frequency fs, and extracts the analysis data of the frequency band Fk as the analysis data corresponding to the meshing frequency fk. For example, in the case of Fig. 4, the diagnostic device 30 extracts the power Pka of the frequency in the frequency band Fk.

[0050] In this embodiment, the diagnostic device 30 extracts X-axis analysis data, Y-axis analysis data, and Z-axis analysis data for the frequency band Fk and stores them in the memory M. Then, for each speed range Vk, the diagnostic device 30 extracts X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fk and stores them in the memory M. In this way, analysis data from which noise other than vibration caused by the meshing of the gears 11 has been removed can be obtained.

[0051] In this embodiment, the X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fk are time-series data including the processing results of data for the time period tp that coincides with the time period tp that is the target of the frequency analysis processing in step S202. The X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fk for each speed range Vk are an example of first vibration data.

[0052] Next, in step S204, similar to step S201, the diagnostic device 30 classifies the detection results of the second sensor 50 included in the first data based on the rotation speed detected by the rotation sensor 60. The diagnostic device 30 extracts data of the detection signal of the second sensor 50 corresponding to each of the ma speed ranges Vk.

[0053] Next, in step S205, the diagnostic device 30 performs frequency analysis on the detection results of the second sensor 50 corresponding to each of the ma speed ranges Vk, as in step S202. The diagnostic device 30 obtains X-axis analysis data, Y-axis analysis data, and Z-axis analysis data for each speed range Vk. For example, the diagnostic device 30 obtains frequency power data for each frequency band, which represents the relationship shown in data D1b in FIG. 5, through frequency analysis. FIG. 5 is a diagram showing an example of the frequency analysis results of the detection signals of the second sensor 50 for the first data and the second data. FIG. 5 shows data for the same speed range Vk and the same time period tp as in FIG. 4. The horizontal axis represents frequency F, and the vertical axis represents frequency power P. In this embodiment, the diagnostic device 30 uses the detection signal data for the time period tp at the same time as the time period tp targeted for the frequency analysis in step S202 in the frequency analysis to obtain analysis data as time-series data.

[0054] Next, in step S206, similar to step S203, the diagnostic device 30 extracts the analysis result at the meshing frequency corresponding to each speed range Vk from the frequency analysis result for that speed range Vk. For example, in the case of Fig. 5, in the frequency band Fk that includes the meshing frequency fk, the frequency power takes the maximum value Pkb, and in the frequency band Fk' that includes the frequency fk' that is twice the meshing frequency fk, the frequency power takes the second maximum value Pkb'. The diagnostic device 30 extracts the frequency power Pkb in the frequency band Fk.

[0055] The diagnosis device 30 extracts X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fk for each speed range Vk and stores them in the memory M. The X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fk are time-series data including the processing results of data for the time period tp that is the same as the time period tp targeted for the frequency analysis processing in step S202. The X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fk for each speed range Vk are an example of third vibration data.

[0056] Step S3 will now be described in detail. The diagnostic device 30 calculates a vibration transmission magnification factor Tk using the analysis data for the first sensor 40 and the analysis data for the second sensor 50 corresponding to each meshing frequency fk calculated in steps S203 and S206 described above. The vibration transmission magnification factor Tk is the ratio of the analysis data for the first sensor 40 and the analysis data for the second sensor 50 corresponding to the same meshing frequency fk. The vibration transmission magnification factor Tk is obtained by dividing the frequency power in the first sensor 40 at the meshing frequency fk by the frequency power in the second sensor 50 at the meshing frequency fk, and is expressed as "frequency power of the first sensor 40 / frequency power of the second sensor 50." The vibration transmission magnification factor Tk represents the transmissibility of vibration from the position of the second sensor 50 to the position of the first sensor 40. The larger the vibration transmission magnification factor Tk, the higher the transmissibility.

[0057] Since there are multiple meshing frequencies, the diagnostic device 30 calculates the vibration transmission magnification Tk for one or more of the multiple meshing frequencies fk, and in this embodiment, calculates the vibration transmission magnification Tk for each of the meshing frequencies fk. The vibration transmission magnification Tk is an example of a first vibration magnification.

[0058] For one meshing frequency fk, the diagnostic device 30 calculates the vibration transmission magnifications Tki (i=1, . . . , 6) for each of six combinations of the X-axis analysis data, Y-axis analysis data, and Z-axis analysis data of the first sensor 40 and the X-axis analysis data, Y-axis analysis data, and Z-axis analysis data of the second sensor 50. This is because the vibration direction may change in the process of vibration transmission from the second sensor 50 to the first sensor 40.

[0059] The vibration transmission magnification Tk1 is the vibration transmission magnification between the X-axis analysis data of the first sensor 40 and the X-axis analysis data of the second sensor 50. The vibration transmission magnification Tk2 is the vibration transmission magnification between the X-axis analysis data of the first sensor 40 and the Y-axis analysis data of the second sensor 50. The vibration transmission magnification Tk3 is the vibration transmission magnification between the X-axis analysis data of the first sensor 40 and the Z-axis analysis data of the second sensor 50. The vibration transmission magnification Tk4 is the vibration transmission magnification between the Y-axis analysis data of the first sensor 40 and the Y-axis analysis data of the second sensor 50. The vibration transmission magnification Tk5 is the vibration transmission magnification between the Y-axis analysis data of the first sensor 40 and the Z-axis analysis data of the second sensor 50. The vibration transmission magnification Tk6 is the vibration transmission magnification between the Z-axis analysis data of the first sensor 40 and the Z-axis analysis data of the second sensor 50.

[0060] The diagnostic device 30 determines six vibration transmission magnifications Tki as set values ​​for the vibration transmission magnifications. In this embodiment, the diagnostic device 30 obtains time-series data of the vibration transmission magnifications Tki in order to calculate, for each time period tp, the vibration transmission magnifications of two frequency powers that are the same at the same time during the time period tp that is the target of frequency analysis processing between two pieces of analysis data that make up the vibration transmission magnification Tki. The diagnostic device 30 calculates the time-series data of the six vibration transmission magnifications Tki for each meshing frequency fk and stores the data in the memory M.

[0061] Furthermore, the diagnostic device 30 uses the time-series data of the vibration transmission magnification factor Tki to determine a set vibration transmission magnification factor Tkai (i = 1,...,6), which is a set value of the vibration transmission magnification factor for each meshing frequency fk. The diagnostic device 30 determines the statistical value of multiple vibration transmission magnification factors included in the time-series data of the vibration transmission magnification factor Tki as the set vibration transmission magnification factor Tkai. Examples of the statistical value may include a maximum value, a minimum value, a median value, a mode value, and an average value. The diagnostic device 30 determines the set vibration transmission magnification factor Tkai for each of the six vibration transmission magnification factors Tki for each meshing frequency fk.

[0062] Details of step S6 will be described with reference to Fig. 6. Fig. 6 is a flowchart showing details of step S6 in the flowchart of Fig. 2. First, in step S601, similar to step S201 described above, diagnostic device 30 classifies the detection results of first sensor 40 included in the second data based on the rotation speed detected by rotation sensor 60, and extracts data of the detection signal of first sensor 40 corresponding to each of mb speed ranges Vj (j == 1, 2, . . . , mb). mb is a natural number equal to or less than m.

[0063] Next, in step S602, similar to step S202 described above, the diagnostic device 30 performs frequency analysis on the detection results of the first sensor 40 corresponding to each of the mb speed ranges Vj to obtain X-axis analysis data, Y-axis analysis data, and Z-axis analysis data for each speed range Vj. For example, the diagnostic device 30 performs frequency analysis to obtain frequency power data for each frequency band that represents the relationship shown in data D2a in FIG. 4. FIG. 4 shows the results of frequency analysis of the detection results of the first sensor 40 corresponding to the same speed range Vj as the speed range Vk. Therefore, the meshing frequency fk and the frequency band Fk of the meshing frequency fk corresponding to the speed range Vk are the same as the meshing frequency fj and the frequency band Fj of the meshing frequency fj corresponding to the speed range Vj.

[0064] The diagnostic device 30 uses detection signal data for one or more time periods tp for frequency analysis processing, and in this embodiment, detection signal data for multiple time periods tp is used. The diagnostic device 30 uses detection signal data for multiple time periods tp included in the second time period to obtain multiple sets of X-axis analysis data, Y-axis analysis data, and Z-axis analysis data for each speed range Vj.

[0065] Next, in step S603, similar to step S203 described above, the diagnostic device 30 extracts the analysis result at the meshing frequency fj corresponding to the speed range Vj from the frequency analysis result for each speed range Vj. For example, in the case of Fig. 4, in the frequency band Fj that includes the meshing frequency fj, the frequency power takes on the maximum value Pja, and in the frequency band Fj' that includes the frequency fj' that is twice the meshing frequency fj, the frequency power takes on the second maximum value Pja'. The diagnostic device 30 extracts the frequency power Pja in the frequency band Fj.

[0066] The diagnostic device 30 extracts X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fj for each speed range Vj and stores the data in the memory M. The diagnostic device 30 extracts multiple sets of X-axis analysis data, Y-axis analysis data, and Z-axis analysis data for one meshing frequency fj, thereby obtaining time-series data including frequency power values ​​at times corresponding to each of multiple time periods tp as analysis data. The X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fj for each speed range Vj is an example of second vibration data.

[0067] Next, in steps S604 to S606, similar to steps S204 to S206 described above, the diagnostic device 30 calculates X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fj for each speed range Vj from the detection results of the second sensor 50 included in the second data, and stores the data in the memory M. For example, the diagnostic device 30 obtains frequency power data for each frequency band, which represents the relationship shown in data D2b in FIG. 5, by frequency analysis processing. FIG. 5 shows the frequency analysis results of the detection results of the first sensor 40 corresponding to the same speed range Vj as the speed range Vk. Therefore, the meshing frequency fk and the frequency band Fk of the meshing frequency fk corresponding to the speed range Vk are the same as the meshing frequency fj and the frequency band Fj of the meshing frequency fj corresponding to the speed range Vj. The X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fj for each speed range Vj are an example of fourth vibration data.

[0068] In step S605, the diagnostic device 30 uses the data of the detection signal for the time period tp at the same time as the time period tp that is the target of the frequency analysis in step S602 in the frequency analysis process to obtain analysis data as time-series data.

[0069] In step S606, the X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to meshing frequency fj are time-series data containing the processing results of data for time period tp that coincides with the time period tp targeted for frequency analysis in step S602. In the case of Fig. 5, in the frequency band Fj that includes meshing frequency fj, the frequency power takes on the maximum value Pjb, and in the frequency band Fj' that includes frequency fj' that is twice the meshing frequency fj, the frequency power takes on the second maximum value Pjb'. The diagnostic device 30 extracts the frequency power Pjb in the frequency band Fj.

[0070] Step S7 will now be described in detail. As in step S3 described above, the diagnostic device 30 calculates the vibration transmission magnification Tj using the analysis data of the first sensor 40 and the analysis data of the second sensor 50 corresponding to the meshing frequencies fj calculated in steps S603 and S606 described above. The diagnostic device 30 calculates the vibration transmission magnifications Tji (i=1, . . . , 6) of six combinations of the analysis data for each axis and stores them in the memory M. The vibration transmission magnifications Tji are an example of a first vibration magnification.

[0071] In this embodiment, the analysis data of the first sensor 40 and the analysis data of the second sensor 50 corresponding to one meshing frequency fj are both time-series data of frequency power values. Between the two analysis data constituting the vibration transmission magnification Tji, the diagnostic device 30 calculates, for each time period tp, the vibration transmission magnifications of two frequency powers that are the same at the same time during the time period tp that is the target of the frequency analysis process, to obtain time-series data of the vibration transmission magnification Tji.

[0072] The vibration transmission magnification Tj1 is the vibration transmission magnification between the X-axis analysis data of the first sensor 40 and the X-axis analysis data of the second sensor 50. The vibration transmission magnification Tj2 is the vibration transmission magnification between the X-axis analysis data of the first sensor 40 and the Y-axis analysis data of the second sensor 50. The vibration transmission magnification Tj3 is the vibration transmission magnification between the X-axis analysis data of the first sensor 40 and the Z-axis analysis data of the second sensor 50. The vibration transmission magnification Tj4 is the vibration transmission magnification between the Y-axis analysis data of the first sensor 40 and the Y-axis analysis data of the second sensor 50. The vibration transmission magnification Tj5 is the vibration transmission magnification between the Y-axis analysis data of the first sensor 40 and the Z-axis analysis data of the second sensor 50. The vibration transmission magnification Tj6 is the vibration transmission magnification between the Z-axis analysis data of the first sensor 40 and the Z-axis analysis data of the second sensor 50.

[0073] Step S8 will now be described in detail. The diagnosis device 30 calculates the difference between the time-series data of the vibration transmission magnification factor Tji for each meshing frequency fj obtained from the second data and the set vibration transmission magnification factor Tkai for each meshing frequency fk obtained from the first data.

[0074] Specifically, for combinations of vibration transmission magnifications in which the meshing frequencies fj and fk are the same, the diagnostic device 30 calculates the difference obtained by subtracting the vibration transmission magnification Tji from the set vibration transmission magnification Tkai. The diagnostic device 30 calculates the difference Dj1 between each value in the time-series data of the vibration transmission magnification Tj1 and the set vibration transmission magnification Tka1, the difference Dj2 between each value in the time-series data of the vibration transmission magnification Tj2 and the set vibration transmission magnification Tka2, the difference Dj3 between each value in the time-series data of the vibration transmission magnification Tj3 and the set vibration transmission magnification Tka3, the difference Dj4 between each value in the time-series data of the vibration transmission magnification Tj4 and the set vibration transmission magnification Tka4, the difference Dj5 between each value in the time-series data of the vibration transmission magnification Tj5 and the set vibration transmission magnification Tka5, and the difference Dj6 between each value in the time-series data of the vibration transmission magnification Tj6 and the set vibration transmission magnification Tka6. As a result, the diagnostic device 30 obtains time-series data for each of the differences Dj1 to Dj6 for each meshing frequency fj. The differences Dj1 to Dj6 are examples of vibration magnification differences.

[0075] The diagnostic device 30 uses the time-series data of the differences Dj1 to Dj6 for each meshing frequency fj to diagnose the condition of the support structure 20. The diagnostic device 30 determines that there is an abnormality in the support structure 20 based on the state of the time-series data of the differences Dj1 to Dj6.

[0076] For example, Fig. 7 is a diagram showing an example of time-series data of the difference Dj1 in vibration transmission magnification at one meshing frequency fj. As shown in Fig. 7, the difference Dj1 exists intermittently depending on the rotational speed of the second shaft 13 of the gear device 10.

[0077] The diagnostic device 30 detects one or more of the time range Rj1 of the peak of the waveform formed by the difference Dj1, the quantity Aj1 of the peak of the waveform formed by the difference Dj1, and the magnitude Mj1 of the difference Dj1 at the peak formed by the difference Dj1, and in this embodiment detects all of them.

[0078] As with the difference Dj1, the diagnostic device 30 detects the peak time ranges Rj2 to Rj6 of the differences Dj2 to Dj6, the peak quantities Aj2 to Aj6 of the differences Dj2 to Dj6, and the peak magnitudes Mj2 to Mj6 of the differences Dj2 to Dj6, respectively.

[0079] Although not limited thereto, in this embodiment, the diagnostic device 30 determines representative values ​​of the time range of the peaks, the number of peaks, and the magnitude of the peaks using statistical values. For example, the diagnostic device 30 may determine the maximum, minimum, median, mode, or average of the time range Rj1 to Rj6 as the representative value Rjr of the time range. The diagnostic device 30 may determine the maximum, minimum, median, mode, or average of the quantities Aj1 to Aj6 as the representative value Ajr of the quantities. The diagnostic device 30 may determine the maximum, minimum, median, mode, or average of the magnitudes Mj1 to Mj6 as the representative value Mjr of the magnitudes.

[0080] The diagnostic device 30 determines that there is a possibility of an abnormality in the support structure 20 when one or more of the representative value Rjr of the peak time range, the representative value Ajr of the peak quantity, and the representative value Mjr of the peak magnitude exceed their respective thresholds. For example, the diagnostic device 30 may set a judgment point P, and when there is one or more representative values ​​that exceed the threshold, the diagnostic device 30 may determine the judgment point P to be "1", or may determine the judgment point P to be the number of representative values ​​that exceed the threshold. In determining the judgment point P, weighting may be applied depending on the representative values ​​that exceed the threshold.

[0081] The diagnostic device 30 also determines judgment points P for other meshing frequencies fj. The diagnostic device 30 may determine that there is an abnormality in the support structure 20 when any of the judgment points P, the average value of the judgment points P, or a predetermined number or more of the judgment points P exceed a threshold. The diagnostic device 30 may also determine that there is an abnormality in the support structure 20 when the sum of the judgment points P for all meshing frequencies fj exceeds a threshold.

[0082] The diagnostic device 30 may detect the quantity at which the time ranges Rj1 to Rj6 of the peaks of the differences Dj1 to Dj6 exceed a threshold value without using the representative value. The diagnostic device 30 may set a judgment point P and determine the judgment point P to be the above quantity, or may determine the judgment point P to be "1" if the quantity exceeds the threshold. The diagnostic device 30 also determines judgment points P for other meshing frequencies fj.

[0083] Similarly, the diagnostic device 30 may detect the quantity at which the peak quantities Aj1 to Aj6 of the differences Dj1 to Dj6 exceed a threshold. The diagnostic device 30 may set a judgment point P and determine the judgment point P to be the above quantity, or may determine the judgment point P to be "1" if the quantity exceeds the threshold. The diagnostic device 30 also determines judgment points P for other meshing frequencies fj.

[0084] Similarly, the diagnostic device 30 may detect the quantity at which the magnitudes Mj1 to Mj6 of the peaks of the differences Dj1 to Dj6 exceed a threshold. The diagnostic device 30 may set a judgment point P and determine the judgment point P to be the above quantity, or may determine the judgment point P to be "1" if the quantity exceeds the threshold. The diagnostic device 30 also determines judgment points P for other meshing frequencies fj.

[0085] The diagnostic device 30 may determine that there is an abnormality in the support structure 20 if any of the decision points P, the average value of the decision points P, or a predetermined number or more of the decision points P exceed a threshold for each of the time range of the peaks, the number of peaks, and the magnitude of the peaks. In this case, the decision points P for some of the meshing frequencies fj may be targeted, or the decision points P for all of the meshing frequencies fj may be targeted. The diagnostic device 30 may determine that there is an abnormality in the support structure 20 based on one or more of the determination results for the time range of the peaks, the number of peaks, and the magnitude of the peaks.

[0086] The diagnostic device 30 may determine a decision point P for each meshing frequency fj, and may determine that there is an abnormality in the support structure 20 based on the behavior of the decision point P in response to changes in the meshing frequency fj. For example, the diagnostic device 30 may determine that there is an abnormality in the support structure 20 based on one or more of the range and distribution of frequencies at which the decision point P forms a peak, the number of frequencies at which the decision point P forms a peak, and the magnitude of the decision point P at which the peak forms.

[0087] The diagnostic device 30 according to the embodiment described above diagnoses the condition of the support structure 20 based on the difference in vibration transmission magnification at the meshing frequency between a first period in which the support structure 20 is normal and a second period following the first period.

[0088] (Variation 1) The diagnostic system 100A according to the first modification differs from the embodiment in that it does not include the second sensor 50. Below, the modification will be described focusing on the differences from the embodiment, and the description of the similarities with the embodiment will be omitted as appropriate.

[0089] Fig. 8 is a diagram showing an example of the configuration of a diagnostic system 100A according to Modification 1. As shown in Fig. 8, the diagnostic system 100A differs from the diagnostic system 100 according to the embodiment in that it does not include a second sensor 50. The diagnostic system 100A includes a diagnostic device 30A.

[0090] The operation of the diagnostic device 30A according to the modified example will be described with reference to Fig. 9. Fig. 9 is a flowchart showing an example of the operation of the diagnostic device 30A according to the modified example 1. First, in step S1A, the diagnostic device 30A acquires detection results from the first sensor 40 and the rotation sensor 60 over a first period, associates the results with each other based on the detection times, and stores the results in the memory M as first data.

[0091] Next, in step S2A, similar to step S2 in the embodiment, diagnostic device 30A performs frequency analysis processing on the detection result of first sensor 40 for the first data acquired within the first period, and stores the processing result in memory M. Diagnostic device 30A executes step S2A in accordance with the flowchart shown in FIG.

[0092] Fig. 10 is a flowchart showing the details of step S2A in the flowchart of Fig. 9. Diagnostic device 30A executes steps S201A to S203A in the same manner as steps S201 to S203 in the embodiment, respectively.

[0093] In step S201A, diagnostic device 30A classifies the detection results of first sensor 40 included in the first data based on the rotational speed detected by rotation sensor 60, and extracts data of the detection signal of first sensor 40 corresponding to each of ma speed ranges Vk.

[0094] In step S202A, the diagnostic device 30A performs frequency analysis on the detection results of the first sensor 40 corresponding to each speed range Vk to obtain X-axis analysis data, Y-axis analysis data, and Z-axis analysis data for each speed range Vk. The diagnostic device 30A uses data of the detection signals for one or more time periods tp for the frequency analysis, but in this modification, data of the detection signals for multiple time periods tp is used. The diagnostic device 30A obtains frequency analysis data including time-series data of the frequency analysis results at times corresponding to each time period tp.

[0095] In step S203A, the diagnostic device 30A extracts the analysis result at the meshing frequency fk corresponding to the speed range Vk from the frequency analysis result for each speed range Vk. The diagnostic device 30A extracts the X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fk and stores them in the memory M. In this modification, the X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fk are time-series data including the processing results of data for the time period tp that is the same as the time period tp targeted for the frequency analysis processing in step S202A. The X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequency fk for each speed range Vk are an example of first vibration data.

[0096] Returning to FIG. 9, in step S3A, the diagnostic device 30A determines setting values ​​for the X-axis analysis data, Y-axis analysis data, and Z-axis analysis data for each of the meshing frequencies fk, using the X-axis analysis data, Y-axis analysis data, and Z-axis analysis data corresponding to the meshing frequencies fk extracted in step S2A.

[0097] The diagnostic device 30A determines the statistical values ​​of the data included in the analysis data for each axis as analysis set values, which are set values ​​for the analysis data for each axis at the meshing frequency fk. Examples of statistical values ​​may include maximum, minimum, median, mode, and average. The diagnostic device 30A determines, for each meshing frequency fk, an X-axis analysis set value Akax for the X-axis analysis data, a Y-axis analysis set value Akay for the Y-axis analysis data, and a Z-axis analysis set value Akaz for the Z-axis analysis data.

[0098] Next, in step S4A, after the first period has elapsed, the diagnostic device 30A acquires detection results from the first sensor 40 and the rotation sensor 60 while the drive source D is operating, associates the detection results with each other based on the detection times, and stores the results as second data in the memory M. The diagnostic device 30 may store in the memory M the results detected after the most recent diagnosis timing.

[0099] Next, if the current time has reached the diagnosis timing (Yes in step S5A), diagnostic device 30A proceeds to step S6A, and if the current time has not yet reached the diagnosis timing (No in step S5A), returns to step S4A.

[0100] In step S6A, diagnostic device 30A performs frequency analysis processing on the detection result of first sensor 40 for the second data acquired during a second period up to the current diagnosis timing, and stores the processing result in memory M. Diagnostic device 30A executes step S6A in accordance with the flowchart shown in FIG.

[0101] Fig. 11 is a flowchart showing the details of step S6A in the flowchart of Fig. 9. Diagnostic device 30A executes steps S601A to S603A in the same manner as steps S601 to S603 in the embodiment, respectively.

[0102] In step S601A, diagnostic device 30A classifies the detection results of first sensor 40 included in the second data based on the rotation speed detected by rotation sensor 60, and extracts data of the detection signal of first sensor 40 corresponding to each of mb speed ranges Vj.

[0103] In step S602A, the diagnostic device 30A performs frequency analysis on the detection results of the first sensor 40 corresponding to each speed range Vj, and obtains X-axis analysis data, Y-axis analysis data, and Z-axis analysis data for each speed range Vj. In this modification, the diagnostic device 30A obtains multiple sets of X-axis analysis data, Y-axis analysis data, and Z-axis analysis data for each speed range Vj, using data of the detection signals for multiple time periods tp included in the second time period.

[0104] In step S603A, the diagnostic device 30A extracts the analysis results at the meshing frequency fj corresponding to each speed range Vj from the frequency analysis results for that speed range Vj. The diagnostic device 30A extracts the X-axis analysis data Ajx, Y-axis analysis data Ajy, and Z-axis analysis data Ajz corresponding to the meshing frequency fj and stores them in the memory M. In this modification, the X-axis analysis data Ajx, Y-axis analysis data Ajy, and Z-axis analysis data Ajz are time-series data including the processing results of data for the time period tp that is the same as the time period tp targeted for the frequency analysis processing in step S602A. The X-axis analysis data Ajx, Y-axis analysis data Ajy, and Z-axis analysis data Ajz corresponding to the meshing frequency fj for each speed range Vj are an example of second vibration data.

[0105] 9, in step S7A, the diagnostic device 30A compares the processing results of the second data with the set values ​​determined in step S3A to diagnose the condition of the support structure 20. The diagnostic device 30A calculates the differences between the analysis data Ajx, Ajy, and Ajz for each meshing frequency fj obtained from the second data and the analysis set values ​​Akax, Akay, and Akaz for each meshing frequency fk obtained from the first data.

[0106] Specifically, the diagnostic device 30A calculates the differences DAj1 to DAj6 between the analysis data Ajx, Ajy, and Ajz and the analysis set values ​​Akax, Akay, and Akaz for combinations of analysis data and analysis set values ​​in which the meshing frequencies fj and fk are the same.

[0107] The difference DAj1 is the difference between each data value included in the time series data of the X-axis analysis data Ajx and the X-axis analysis set value Akax. The difference DAj2 is the difference between each data value included in the time series data of the X-axis analysis data Ajx and the Y-axis analysis set value Akay. The difference DAj3 is the difference between each data value included in the time series data of the X-axis analysis data Ajx and the Z-axis analysis set value Akaz. The difference DAj4 is the difference between each data value included in the time series data of the Y-axis analysis data Ajy and the Y-axis analysis set value Akay. The difference DAj5 is the difference between each data value included in the time series data of the Y-axis analysis data Ajy and the Z-axis analysis set value Akaz. The difference DAj6 is the difference between each data value included in the time series data of the Z-axis analysis data Ajz and the Z-axis analysis set value Akaz. Therefore, the diagnostic device 30A calculates the time series data of the differences DAj1 to DAj6. The differences DAj1 to DAj6 are examples of the differences between the first vibration data and the second vibration data.

[0108] The diagnostic device 30A uses the time-series data of the differences DAj1 to DAj6 for each meshing frequency fj to diagnose the condition of the support structure 20. The diagnostic device 30A determines that there is an abnormality in the support structure 20 based on the state of the time-series data of the differences DAj1 to DAj6.

[0109] The diagnostic device 30A detects, for each meshing frequency fj, one or more of the time range of the peaks of the waveforms formed by the differences DAj1 to DAj6, the number of peaks of the waveforms formed by the differences DAj1 to DAj6, and the magnitude of the difference between the peaks formed by the differences DAj1 to DAj6, and uses these to determine that there is an abnormality in the support structure 20.

[0110] The diagnostic device 30A may determine that there is an abnormality in the support structure 20 by using a process similar to any of the processes in which the diagnostic device 30 diagnoses the condition of the support structure 20 using time-series data of the differences Dj1 to Dj6 of each of the meshing frequencies fj, as described above in the embodiment.

[0111] In step S8A, diagnostic device 30A presents the diagnostic results to the operator of diagnostic device 30A.

[0112] The diagnostic device 30A according to the modified example described above diagnoses the condition of the support structure 20 based on the difference in vibration of the support structure 20 at the meshing frequency between a first period in which the support structure 20 is normal and a second period after the first period.

[0113] (Variation 2) A diagnostic system 100B according to Modification 2 differs from the embodiment and Modification 1 in that a diagnostic device 30B is connected to a plurality of first sensors 40 via a communication network. Below, this modification will be described, focusing on the differences from the embodiment and Modification 1, and descriptions of the same points as the embodiment or Modification 1 will be omitted as appropriate.

[0114] Fig. 12 is a diagram showing an example of the configuration of a diagnostic system 100B according to Modification 2. As shown in Fig. 12, diagnostic system 100B differs from the embodiment and Modification 1 in that a diagnostic device 30B is connected to relay devices 80 mounted on a plurality of mounting targets E via a communication network N.

[0115] The diagnostic system 100B includes a diagnostic device 30B. The processing circuit of the diagnostic device 30B is an example of a remote processing circuit. The diagnostic device 30B according to this modification may have at least some of the functions of the diagnostic device 30 according to the embodiment or at least some of the functions of the diagnostic device 30A according to the first modification. Thus, the diagnostic device 30B may function as the diagnostic device 30 or 30A, or may implement some of the functions of the diagnostic device 30 or 30A. The diagnostic device 30B may have a function of accumulating information received from the relay device 80 of multiple mounting targets E. Each of the multiple mounting targets E includes a drive source D, a driven target T, a gear device 10, a support structure 20, a first sensor 40, a rotation sensor 60, and the relay device 80. Although not limited thereto, in this modification, each of the multiple mounting targets E also includes a second sensor 50.

[0116] The relay device 80 includes a communicator 80a connected to the communication network N via wired communication or wireless communication to enable data communication. The communicator 80a includes a communication circuit. The relay device 80 includes a processing circuit, which is an example of a sensor processing circuit. Such a relay device 80 may include a processor and a memory. The relay device 80 may have the functions of the diagnostic device 30 or 30A excluding the functions of the diagnostic device 30B. The relay device 80 may transmit detection signals of the first sensor 40, the second sensor 50, and the rotation sensor 60 to the diagnostic device 30B via the communication network N. The relay device 80 may process the detection signals of the first sensor 40, the second sensor 50, and the rotation sensor 60 using the functions of the diagnostic device 30 or 30A included in the relay device 80, and transmit the processing results to the diagnostic device 30B. The relay device 80 may execute at least a part of the processing from obtaining the first data and the second data to diagnosing the state of the support structure 20 using the function of the diagnostic device 30 or 30A included in the relay device 80, and may transmit the processing results to the diagnostic device 30B. The relay device 80 may be equipped with a display or an indicator lamp such as a warning lamp, and may have a function of presenting the diagnostic results of the diagnostic device 30B to the operator of the mounting object E, etc.

[0117] For example, the relay device 80 may have at least some of the functions of processing first data from the first sensor 40 and the second sensor 50 in the diagnostic device 30 or 30A. In this case, the relay device 80 may have the function of executing at least some of steps S1 to S3 of FIG. 2 and the function of executing at least some of steps S1A to S3A of FIG. 9. The relay device 80 may have at least some of the functions of processing second data from the first sensor 40 and the second sensor 50 in the diagnostic device 30 or 30A. In this case, the relay device 80 may have the function of executing at least some of steps S4 to S6 of FIG. 2 and the function of executing at least some of steps S4A to S6A of FIG. 9. The relay device 80 may have at least some of the functions of diagnosing the support structure 20 in the diagnostic device 30 or 30A. In this case, the relay device 80 may have the function of executing at least some of steps S7 to S9 of FIG. 2 and the function of executing at least some of steps S7A to S8A of FIG. 9.

[0118] The diagnostic device 30B is located remotely from the multiple mounting targets E. In this modification, the diagnostic device 30B functions as a server, for example, a cloud server, although not limited thereto. The diagnostic device 30B can communicate data with the relay devices 80 of the multiple mounting targets E via the communication network N. For example, the diagnostic device 30B may receive detection signals of the first sensor 40, the second sensor 50, and the rotation sensor 60 or processing results of the relay device 80 from the relay device 80 of the mounting target E, diagnose the condition of the support structure 20 of the mounting target E using the received information, and transmit the diagnosis result to the relay device 80. The relay device 80 of the mounting target E may diagnose the condition of the support structure 20 of the relay device 80, and the diagnostic device 30B may receive the diagnosis result from the relay device 80. The relay device 80 of the mounting target E and the diagnostic device 30B may share the processing from acquiring the first data and the second data to diagnosing the state of the support structure 20 of the relay device 80, and the relay device 80 and the diagnostic device 30B may diagnose the state of the support structure 20 while sending and receiving necessary information and processing results to each other. The diagnostic device 30B may store and accumulate the diagnostic results of the support structures 20 of multiple mounting targets E.

[0119] The diagnostic device 30B includes a communication device 30Ba that is connected to the communication network N via wired or wireless communication so as to be able to perform data communication with the communication network N. The communication device 30Ba includes a communication circuit.

[0120] The communication network N is not particularly limited and may include, for example, a local area network (LAN), a wide area network (WAN), the Internet, or a combination of two or more of these. The communication network N may be configured to use short-range wireless communication such as Bluetooth (registered trademark) and ZigBee (registered trademark), a network dedicated line, a dedicated line of a communication carrier, a public switched telephone network (PSTN), a mobile communication network, the Internet network, satellite communication, or a combination of two or more of these. The mobile communication network may use a fourth-generation mobile communication system, a fifth-generation mobile communication system, or the like. The communication network N may include one or more communication networks.

[0121] The diagnostic device 30B as described above can centrally manage the status of one or more support structures 20 that are remote from the diagnostic device 30B.

[0122] (Application example) An example of application of the diagnostic systems 100, 100A, and 100B will now be described. The diagnostic systems 100, 100A, and 100B can be applied to any device, machine, or installation that includes a gear device and its supporting structure.

[0123] For example, the diagnostic systems 100, 100A, and 100B can be applied to vehicles. An example of an application of a vehicle is a railway vehicle. FIG. 13 is a front view showing an example of an application of the diagnostic systems 100, 100A, and 100B. As shown in FIG. 13, a bogie 1100 of the railway vehicle 1000 includes a bogie frame 1110, an electric motor 1120, an axle 1130, wheels 1140, and a gear set 10.

[0124] The railway vehicle 1000 is a mounted object E, and the axle 1130 and wheels 1140 are a driven object T. The bogie frame 1110 supports the carbody 1200 of the railway vehicle 1000. The electric motor 1120 is a driving source D and is fixed to the bogie frame 1110. A rotating shaft 1121 of the electric motor 1120 is connected to the first shaft 12 of the gear set 10 via a coupling 1122 so as to be able to transmit driving force. The wheels 1140 are connected coaxially to the second shaft 13 of the gear set 10. The two wheels 1140 are connected to each other by the axle 1130. Bearings 1131 at both ends of the axle 1130 are connected to the bogie frame 1110 via axle springs 1150. The axle springs 1150 function as a suspension for the bogie frame 1110 and are, for example, coil springs.

[0125] The gear device 10 is attached to the bogie frame 1110 so as to be suspended from the bogie frame 1110. A buffer member 1160 that reduces the transmission of vibrations is arranged between the gear device 10 and the bogie frame 1110. Examples of the buffer member 1160 are vibration-isolating rubber and springs. The buffer member 1160 functions as the support structure 20. For example, the second sensor 50 is arranged in a bearing of the shaft 12 or 13 of the gear device 10, and the first sensor 40 is arranged in a portion of the bogie frame 1110 that is connected to the buffer member 1160. The diagnostic device is arranged inside or outside the carbody 1200, and can diagnose the condition of the buffer member 1160 based on the detection signals received from the sensors 40 and 50.

[0126] Another application example of a vehicle is a watercraft. Fig. 14 is a side view showing an application example of the diagnostic systems 100, 100A, and 100B. As shown in Fig. 14, the watercraft 2000 includes a hull 2100, an internal combustion engine 2200, a propeller shaft 2300, a propeller 2400, and a gear train 10. The watercraft 2000 is an installation object E, and the propeller shaft 2300 and the propeller 2400 are a driving object T. The propeller 2400 is attached to the tip of the propeller shaft 2300 so as to rotate integrally with the propeller shaft 2300. The internal combustion engine 2200 is a driving source D and is fixed to the hull 2100. The gear train 10 is a marine gear including a clutch and a gear. The housing 14 of the gear device 10 is attached to a housing 2210, such as a crankcase of the internal combustion engine 2200, by fastening bolts 2500, and is also fixed to the hull 2100. The bolts 2500 and the fasteners that fix the housing 14 to the hull 2100 function as the support structure 20. The first shaft 12 of the gear device 10 is connected to the output shaft of the internal combustion engine 2200, and the second shaft 13 is connected to the propeller shaft 2300.

[0127] For example, the second sensor 50 is disposed on a bearing of the shaft 12 or 13 of the gear device 10, and the first sensor 40 is disposed on a portion of the housing 2210 of the internal combustion engine 2200 that is connected to the housing 14 of the gear device 10, or on a portion of the hull 2100 that is connected to a fastener. The diagnostic device is disposed inside or outside the hull 2100, and can diagnose the condition of the bolt 2500 and the fastener based on the detection signals received from the sensors 40 and 50.

[0128] Other examples of vehicle applications include automobiles and motorcycles. The gear device 10 of an automobile may be a transmission or a differential of the automobile. For example, the transmission and the differential are connected to the body of the automobile via a metal member and a rubber bushing. The member and the rubber bushing function as a support structure 20. The first shaft 12 of the gear device 10 as a transmission is connected to an output shaft of an internal combustion engine, and the second shaft 13 is connected to a shaft connecting the transmission and the differential. The first shaft 12 of the gear device 10 as a differential is connected to a shaft connecting the transmission and the differential, and the second shaft 13 is connected to a shaft connecting the differential and the wheels. For example, the second sensor 50 is disposed on a bearing of the shaft 12 or 13 of the gear device 10, and the first sensor 40 is disposed on a portion of the vehicle body connected to the member.

[0129] The gear device 10 for a motorcycle may be a transmission for the motorcycle. For example, the gear device 10 is connected to a frame of the motorcycle via a rubber bushing. The rubber bushing functions as the support structure 20. A first shaft 12 of the gear device 10 is connected to an output shaft of an internal combustion engine, and a second shaft 13 is connected to a sprocket that is connected to a wheel via a transmission member such as a chain. For example, the second sensor 50 is disposed in a bearing of the shaft 12 or 13 of the gear device 10, and the first sensor 40 is disposed in a portion of the frame that is connected to the rubber bushing. The diagnostic device is mounted on the automobile or motorcycle and can diagnose the condition of the support structure 20 based on detection signals received from the sensors 40 and 50.

[0130] For example, the diagnostic systems 100, 100A, and 100B can be applied to an industrial robot, which is an example of a machine. FIG. 15 is a side view showing an application example of the diagnostic systems 100, 100A, and 100B. As shown in FIG. 15, a robot arm 3000 is exemplified as an industrial robot. The robot arm 3000 includes a plurality of joints 3100, a plurality of links 3200 connecting the joints 3100, an electric motor 3300 arranged at each of the joints 3100, and a gear device 10 arranged at each of the joints 3100.

[0131] The robot arm 3000 is a mounting object E, and the link 3200 is a driven object T. The electric motor 3300 is a driving source D and is fixed to the link 3200. The gear device 10 is a reducer that transmits the driving force of the electric motor 3300 to the link 3200 and is fixed to the link 3200. A fixture that fixes the gear device 10 to the link 3200 functions as the support structure 20. The first shaft 12 of the gear device 10 is connected to the output shaft of the electric motor 3300, and the second shaft 13 is connected to the link 3200. For example, the second sensor 50 is disposed in a bearing of the shaft 12 or 13 of the gear device 10, and the first sensor 40 is disposed in a portion of the link 3200 that is connected to the fixture. A diagnostic device is disposed outside the robot arm 3000 and can diagnose the condition of the support structure 20 based on detection signals received from the sensors 40 and 50.

[0132] Although exemplary embodiments and modifications of the present disclosure have been described above, the present disclosure is not limited to the above-described embodiments and modifications. In other words, various modifications and improvements are possible within the scope of the present disclosure. For example, various modifications made to the embodiments or modifications, and forms constructed by combining components of different embodiments and modifications, are also included within the scope of the present disclosure.

[0133] For example, the diagnostic device 30 according to the embodiment acquires detection results from the first sensor 40 and the second sensor 50 over a first period in which the support structure 20 is in a normal state, and stores the detection results in the memory M as first data of the support structure 20 in a normal state. The diagnostic device 30A according to the first modification acquires detection results from the first sensor 40 over a first period in which the support structure 20 is in a normal state, and stores the detection results in the memory M as first data of the support structure 20 in a normal state. However, the first data acquired by the diagnostic device is not limited to the above. The above first data is data acquired during the operation stage in which the mounting target E is being operated, but the first data may also be data acquired during the pre-operation stage before the mounting target E is put into operation.

[0134] The pre-operation stage may be a stage before the mounted object E is shipped from the manufacturer as a product, a stage before the gear device 10 is mounted on the mounted object E, or a stage before the gear device 10 is shipped from the manufacturer as a product. The first data in the pre-operation stage may be acquired during the course of inspection, testing, or experimentation on the combination of the gear device 10 and the support structure 20, the gear device, or the mounted object E.

[0135] The sensors used to detect the first data in the pre-operational stage may be the first sensor 40 and the second sensor 50 mounted on the mounted target E, or may be sensors different from the first sensor 40 and the second sensor 50. When acquiring the first data in the pre-operational stage, the gear device 10 and the support structure 20 may be mounted on the mounted target E, or may not be mounted on the mounted target E. In the latter case, the gear device 10 may be supported by the support structure 20 or another support structure in an environment that is the same as or similar to the environment on the mounted target E. The other support structure may have the same or similar structure as the support structure 20.

[0136] The gear device or support structure from which the first data is acquired may be different from the gear device 10 or support structure 20 mounted on the mounted object E. Such a gear device may have the same or similar structure as the gear device 10. The environment in which the gear device is placed may be the same or similar to the environment of the gear device 10 on the mounted object E. The support structure may have the same or similar structure as the support structure 20. The environment in which the support structure is placed may be the same or similar to the environment of the support structure 20 on the mounted object E.

[0137] The first data may be simulation data. For example, the first data may be calculated by a computer program that designs or simulates the gear train 10, the support structure 20, or both. The first data may be data obtained by running virtual models of the gear train 10 and the support structure 20 to be mounted on the mounting target E on a computer. These virtual models may be realized by using digital twin technology or the like to construct a virtual space representing the environment in which the gear train 10 and the support structure 20 are placed.

[0138] Therefore, the first data may be actual data obtained from the gear train 10 and support structure 20 mounted on the mounting object E, or index data obtained from a combination of a gear train 10, support structure 20, another gear train, and another support structure that are not mounted on the mounting object E, or may be simulation data.

[0139] The diagnostic device may then acquire the first data as described above and perform frequency analysis processing on the acquired first data to acquire vibration data indicative of vibration at the meshing frequency. Alternatively, the diagnostic device may acquire a result of performing frequency analysis processing on the first data as described above and process the acquired processing result to acquire vibration data indicative of vibration at the meshing frequency. Alternatively, the diagnostic device may acquire the vibration data itself indicative of vibration at the meshing frequency, which is obtained from the result of performing frequency analysis processing on the first data as described above.

[0140] The diagnostic device according to the embodiment and the modification obtains frequency power data at the meshing frequency for each of the first data and the second data from the results of frequency analysis processing based on Fourier transform on the first data and the second data as vibration data indicating the vibration at the meshing frequency. However, the vibration data indicating the vibration at the meshing frequency is not limited to this and may be data obtained using any frequency analysis that can obtain data indicating the vibration characteristics for each frequency band. The diagnostic device can obtain such vibration data indicating the vibration at the meshing frequency from the first data and second data exemplified in the embodiment and the modification, as well as from various variations of the first data as described above.

[0141] For example, the frequency analysis may be frequency analysis using a wavelet transform. In this case, the diagnostic device performs frequency analysis processing using a wavelet transform on the first data and the second data, thereby obtaining, for each of the first data and the second data, time series data indicating changes over time in the amplitude of vibration in each of n frequency bands at a certain sampling frequency. For each of the first data and the second data, the diagnostic device can obtain, as vibration data indicating vibration at the meshing frequency, time series data in a frequency band corresponding to the meshing frequency among the n frequency bands. The diagnostic device can diagnose the support structure 20 using the obtained time series data.

[0142] The diagnostic devices according to the embodiments and modifications extract, for each speed range V, analytical data corresponding to the meshing frequency of the representative rotational speed of that speed range, and diagnose the condition of the support structure 20 using the extracted analytical data, but are not limited to this. For example, the diagnostic device may extract, for the speed range V, analytical data corresponding to frequencies that are integer multiples of the meshing frequency. For example, in the cases of FIGS. 4 and 5, the diagnostic device may extract analytical data corresponding to frequency bands Fk' and Fj'. The diagnostic device may diagnose the condition of the support structure 20 using analytical data corresponding to frequencies that are integer multiples of the meshing frequency, in addition to or instead of the analytical data corresponding to the meshing frequency. The diagnostic device may process the analytical data corresponding to frequencies that are integer multiples of the meshing frequency in the same way as the analytical data corresponding to the meshing frequency.

[0143] The diagnostic device 30 according to the embodiment calculates a statistical value of the time-series data of the vibration transmission magnification for the first data and determines the statistical value as the set value of the vibration transmission magnification, but is not limited to this. For example, the diagnostic device 30 may calculate a statistical value of data values ​​in the same frequency band in the analysis data as time-series data after frequency analysis processing, and generate analysis data that is non-time-series data that includes the statistical value as an element. The diagnostic device 30 may determine the vibration transmission magnification calculated using such analysis data as the set value of the vibration transmission magnification.

[0144] The diagnostic device 30A according to the first modification calculates, for the first data, statistical values ​​of the data values ​​of the analytical data as time-series data corresponding to the meshing frequency fk, and determines the statistical values ​​as the set value of the analytical data, but is not limited to this. For example, the diagnostic device 30A may calculate statistical values ​​of data values ​​in the same frequency band for the analytical data as time-series data after frequency analysis processing, and generate analytical data that is non-time-series data that includes the statistical values ​​as elements. The diagnostic device 30A may use such analytical data to determine the set value of the analytical data that corresponds to the meshing frequency fk.

[0145] Examples of aspects of the technology of the present disclosure are as follows: A diagnostic device according to a first aspect of the present disclosure is a diagnostic device for a support structure of a gear device, comprising: a first sensor that detects vibrations of the support structure that supports the gear device; and a processing circuit that processes the detection results of the first sensor, wherein the processing circuit calculates a difference between first vibration data and second vibration data at the same meshing frequency and diagnoses the condition of the support structure based on the difference, wherein the first vibration data is data indicative of vibrations of the support structure at the meshing frequency in a first period in which the support structure is in a normal state, and the second vibration data is data indicative of vibrations of the support structure at the meshing frequency processed from the detection results of the first sensor in a second period after the first period, wherein the meshing frequency is a frequency at which multiple teeth of a gear included in the gear device mesh with a mating target.

[0146] In the first aspect, the meshing frequency is a frequency correlated with the number of teeth and rotational speed of the gears in the gear device. The first vibration data and the second vibration data relate to vibrations transmitted from the gear device to the support structure. The first period may be any period during which the support structure is in a normal state or during which the support structure can be considered to be in a normal state. The second period may be any period after the first period.

[0147] The second vibration data is data obtained from the detection result of the first sensor, and may be data obtained during operation of the gear device, for example. The first vibration data may be data obtained from the detection result of the first sensor, or may be data obtained from the detection result of a sensor different from the first sensor. The first vibration data may be data stored in advance, or may be data obtained either during operation of the gear device or before operation. For example, the first vibration data may be data obtained by inspection, testing, experimentation, calculation, or simulation before operation of the gear device. The first vibration data may be data obtained in a gear device and a support structure having the same or similar configuration as the gear device and support structure. All of the first vibration data exemplified above are data obtained during a period in which the support structure is in a normal state or a period in which the support structure can be considered to be in a normal state.

[0148] The difference between the first vibration data and the second vibration data represents the fluctuation in vibration transmitted from the gear device to the support structure between them, and is related to the change in the state in which the support structure supports the gear device. Therefore, the diagnostic device can diagnose the state of the support structure of the gear device. By detecting vibration data at the meshing frequency, where vibration intensity is high, the influence of disturbance vibration can be mitigated and the support structure can be diagnosed, improving diagnostic accuracy.

[0149] In the first aspect above, in a diagnostic device according to a second aspect of the present disclosure, the meshing frequencies include a plurality of meshing frequencies based on a plurality of rotational speeds of the gears of the gear device, the first vibration data is a plurality of data indicating vibration of the support structure at each of the plurality of meshing frequencies, and the second vibration data is a plurality of data indicating vibration of the support structure at each of the plurality of meshing frequencies from the detection results of the first sensor, and the processing circuit may calculate the difference between the first vibration data and the second vibration data, which have the same meshing frequency, for a plurality of meshing frequencies, and perform the condition diagnosis based on the plurality of differences for the plurality of meshing frequencies.

[0150] According to the second aspect, the diagnostic device calculates a plurality of differences according to a plurality of meshing frequencies corresponding to a plurality of rotational speeds of the gears that change in the gear device. The diagnostic device then diagnoses the condition of the support structure based on the plurality of differences according to the plurality of rotational speeds of the gears of the gear device. Thus, the diagnostic device can diagnose the condition of the support structure for various cases where the gear rotational speeds are different, thereby improving diagnostic accuracy.

[0151] In the second aspect above, in a diagnostic device according to a third aspect of the present disclosure, the processing circuit may diagnose the condition based on one or more of the frequency range of the peaks formed by the multiple differences, the number of peaks formed by the multiple differences, and the magnitude of vibration intensity at the peaks formed by the multiple differences.

[0152] According to the third aspect, the diagnostic device diagnoses the state of the support structure based on the state of the peak formed by the plurality of differences. The diagnostic device can diagnose the support structure while excluding states that accidentally occur in the support structure due to disturbances, etc., thereby improving diagnostic accuracy.

[0153] In any of the first to third aspects, a diagnostic device according to a fourth aspect of the present disclosure may further include a second sensor disposed on the gear device and detecting vibrations of the gear device, wherein the processing circuit further calculates a first vibration magnification which is a ratio of vibration intensities between the first vibration data and third vibration data at the same meshing frequency, and a second vibration magnification which is a ratio of vibration intensities between the second vibration data and fourth vibration data at the same meshing frequency, and the processing circuit performs the condition diagnosis based on a vibration magnification difference which is a difference between the first vibration magnification and the second vibration magnification, wherein the third vibration data is data indicative of vibrations of the gear device at the meshing frequency during the first period, and the fourth vibration data is data indicative of vibrations of the gear device at the meshing frequency during the second period, processed from the detection result of the second sensor.

[0154] According to the fourth aspect, the first vibration magnification and the second vibration magnification both represent the rate at which vibrations generated in the gear device are transmitted to the support structure. The difference between the first vibration magnification and the second vibration magnification is related to the difference in the support state of the gear device by the support structure. For example, if there is a large difference between the vibration transmission rate associated with the second vibration data and the fourth vibration data and the vibration transmission rate associated with the first vibration data and the third vibration data, it can be determined that the support state of the gear device by the support structure has deteriorated. Therefore, the diagnostic device can improve the accuracy of diagnosing the state in which the support structure supports the gear device.

[0155] In the second or third aspect described above, a diagnostic device according to a fifth aspect of the present disclosure further includes a second sensor disposed on the gear device and detecting vibrations of the gear device, wherein the processing circuit further executes the steps of: calculating, for a plurality of meshing frequencies, a first vibration magnification which is a ratio of vibration intensity between the first vibration data and third vibration data, the meshing frequencies of which are the same; and calculating, for a plurality of meshing frequencies, a second vibration magnification which is a ratio of vibration intensity between the second vibration data and fourth vibration data, the meshing frequencies being processed from the detection results of the second sensor; the processing circuit calculates, for a plurality of meshing frequencies, a vibration magnification difference which is a difference between the first vibration magnification and the second vibration magnification, the meshing frequencies being the same; and diagnosing the condition based on the plurality of vibration magnification differences; wherein the third vibration data may be a plurality of data indicative of vibration of the gear device at a plurality of meshing frequencies based on a plurality of rotational speeds of the gears of the gear device; and the fourth vibration data may be a plurality of data indicative of vibration of the gear device at a plurality of meshing frequencies based on a plurality of rotational speeds of the gears of the gear device.

[0156] According to the fifth aspect, the diagnostic device calculates a plurality of vibration magnification differences corresponding to a plurality of meshing frequencies corresponding to a plurality of rotational speeds of the gears that change in the gear device.The diagnostic device then diagnoses the condition of the support structure based on the plurality of vibration magnification differences corresponding to the plurality of rotational speeds of the gears of the gear device.As a result, the diagnostic device can diagnose the condition of the support structure for various cases where the gear rotational speeds are different, thereby improving diagnostic accuracy.

[0157] In the fifth aspect above, in a diagnostic device according to a sixth aspect of the present disclosure, the processing circuit may diagnose the condition based on one or more of the frequency range of peaks formed by the plurality of vibration magnification differences, the number of peaks formed by the plurality of vibration magnification differences, and the magnitude of the vibration magnification at the peaks formed by the plurality of vibration magnification differences.

[0158] According to the sixth aspect, the diagnostic device diagnoses the state of the support structure based on the state of peaks formed by multiple vibration magnification differences. The diagnostic device can diagnose the support structure while excluding states that accidentally occur in the support structure due to disturbances, etc., thereby improving diagnostic accuracy.

[0159] In any of the above fourth to sixth aspects, in a diagnostic device according to a seventh aspect of the present disclosure, the first sensor detects vibrations in the direction of one detection axis or in the directions of two or more detection axes that intersect with each other, the second sensor detects vibrations in the direction of one detection axis or in the directions of two or more detection axes that intersect with each other, and the processing circuit may detect a plurality of the vibration magnification differences corresponding to a plurality of combinations of the detection axis of the first sensor and the detection axis of the second sensor, and perform the condition diagnosis based on the plurality of vibration magnification differences.

[0160] According to the seventh aspect, vibrations from the gear device may be transmitted to the support structure while changing direction. The diagnostic device diagnoses the condition of the support structure based on multiple vibration magnification differences corresponding to multiple combinations of the direction of vibration detected in the gear device and the direction of vibration detected in the support structure. This improves the diagnostic accuracy of the diagnostic device.

[0161] In any of the first to seventh aspects above, in a diagnostic device according to an eighth aspect of the present disclosure, the processing circuit may acquire data indicating vibrations of the support structure or data indicating vibrations of the gear device and perform frequency analysis to acquire data indicating vibration characteristics of the support structure or the gear device for multiple frequency bands as at least one of the vibration data indicating vibrations at meshing frequencies.

[0162] According to the eighth aspect, the diagnostic device performs frequency analysis on data indicating vibrations of the support structure or data indicating vibrations of the gear train to obtain data indicating vibration characteristics of the support structure or the gear train for each of a plurality of frequency bands. The diagnostic device can obtain data indicating vibration characteristics at the meshing frequency as vibration data from data indicating vibration characteristics for each frequency band. Note that the at least one vibration data may be at least one of one or more first vibration data and one or more second vibration data, or at least one of one or more first vibration data to one or more fourth vibration data. The data indicating vibrations of the support structure and the data indicating vibrations of the gear train can be obtained from the first data and second data exemplified in the embodiment and modified examples, as well as from the various variations exemplified for the first data. Examples of frequency analysis may include frequency analysis based on Fourier transform and frequency analysis based on wavelet transform.

[0163] In any of the above first to eighth aspects, a diagnostic device according to a ninth aspect of the present disclosure may further include a sensor processing circuit connected to at least the first sensor of the first sensor and a second sensor arranged in the gear device and detecting vibrations of the gear device, and acquiring a detection result from the connected sensor; a remote processing circuit having at least some of the functions of the processing circuit and arranged remotely from the first sensor and the sensor processing circuit; a first communicator connecting the sensor processing circuit to a communication network so as to be able to communicate data; and a second communicator connecting the remote processing circuit to the communication network so as to be able to communicate data, wherein the sensor processing circuit has functions of the processing circuit excluding the functions of the remote processing circuit, and may transmit information used for diagnosing the condition of the support structure to the remote processing circuit via the communication network, and the remote processing circuit may perform the condition diagnosis of the support structure using the information received from the sensor processing circuit.

[0164] According to the above ninth aspect, the remote processing circuit can diagnose the condition of the support structure of the gear device that is remote from the remote processing circuit.

[0165] In the above-mentioned ninth aspect, a diagnostic device according to a tenth aspect of the present disclosure includes a plurality of first sensors that detect vibrations of each of a plurality of support structures that support each of a plurality of gear devices, a plurality of sensor processing circuits that are connected to at least each of the plurality of first sensors among the plurality of first sensors and a plurality of second sensors that are arranged on the plurality of gear devices and detect vibrations of each of the plurality of gear devices, and acquire detection results from the connected sensors, and a plurality of first communicators that connect each of the plurality of sensor processing circuits to the communication network so that data communication is possible, and the remote processing circuit may diagnose the condition of the plurality of support structures using information received from the plurality of sensor processing circuits.

[0166] According to the tenth aspect, the remote processing circuit is connected to a plurality of sensor processing circuits via a communication network, thereby enabling centralized management of the states of a plurality of support structures.

[0167] A method for diagnosing a support structure of a gear device according to an eleventh aspect of the present disclosure calculates the difference between first vibration data and second vibration data at the same meshing frequency, and diagnoses the condition of the support structure based on the difference, wherein the first vibration data is data indicating the vibration of the support structure supporting the gear device at a meshing frequency in a first period, the second vibration data is data indicating the vibration of the support structure at a meshing frequency in a second period after the first period, and the meshing frequency is the frequency at which multiple teeth of a gear included in the gear device mesh with an engaging object.

[0168] According to the eleventh aspect, the same effects as those of the diagnostic device according to each aspect of the present disclosure can be obtained. A part or all of the method of the present disclosure may be realized, for example, by a CPU, a circuit such as an LSI, an IC card, or a standalone module. Multiple elements included in the method of the present disclosure may be realized by a single device, or may be realized by two or more devices sharing the same functions.

[0169] The present disclosure may also be a computer program that causes a computer to execute a method according to each aspect of the present disclosure. Such a computer program can achieve the same effects as the method according to each aspect of the present disclosure. The computer program may, for example, be a program recorded on a non-transitory computer-readable recording medium and may be configured to be read from the recording medium using a recording medium drive device and installed on a computer. The computer program may, for example, be a program that can be distributed via a transmission medium such as the Internet and may be configured to be downloaded and installed on a computer.

[0170] The functions of the elements disclosed herein can be performed using circuits or processing circuitry, including general-purpose processors, special-purpose processors, integrated circuits, ASICs, conventional circuits, and / or combinations thereof, configured or programmed to perform the disclosed functions. A processor is considered a processing circuit or circuitry because it includes transistors and other circuitry. In this disclosure, a circuit, unit, or means is hardware that performs the recited functions or hardware that is programmed to perform the recited functions. The hardware may be hardware disclosed herein or other known hardware that is programmed or configured to perform the recited functions. Where the hardware is a processor, which is considered a type of circuit, the circuit, means, or unit is a combination of hardware and software, and the software is used to configure the hardware and / or processor.

[0171] All numbers such as ordinal numbers and quantities used in this specification are provided as examples to specifically explain the technology of the present disclosure, and the present disclosure is not limited to the illustrated numbers. The connection relationships between components are provided as examples to specifically explain the technology of the present disclosure, and the connection relationships that realize the functions of the present disclosure are not limited to these.

[0172] Because the present disclosure may be embodied in various forms without departing from the scope of its essential characteristics, the scope of the present disclosure is defined by the appended claims rather than the description in the specification, and therefore the exemplary embodiments and modifications are intended to be illustrative and not limiting. All modifications within the scope of the claims and their equivalents are intended to be embraced by the claims. [Explanation of symbols]

[0173] 10 Gearing 20 Support structure 30, 30A, 30B Diagnostic equipment 30Ba communication device (1st communication device) 40 First Sensor 50 Second sensor 80 Relay Device 80a Communication device (second communication device)

Claims

1. A diagnostic device for a support structure of a gear device, comprising: a first sensor for detecting vibrations of a support structure that supports the gear device; a processing circuit for processing a detection result of the first sensor; The processing circuitry Calculating a difference between the first vibration data and the second vibration data at the same meshing frequency; and performing a condition diagnosis of the support structure based on the difference. the first vibration data is data indicative of vibration of the support structure at a meshing frequency during a first period in which the support structure is in a normal state; the second vibration data is data indicating vibration of the support structure at a meshing frequency, the data being processed from a detection result of the first sensor in a second time period that is later than the first time period; The meshing frequency is the frequency at which multiple teeth of a gear included in the gear device mesh with an engaging object. Diagnostic equipment.

2. the meshing frequencies include a plurality of meshing frequencies based on a plurality of rotational speeds of the gears of the gearing; the first vibration data is a plurality of data representing vibrations of the support structure at each of the plurality of meshing frequencies, the second vibration data is a plurality of data representing vibrations of the support structure at each of the plurality of meshing frequencies based on the detection results of the first sensor, The processing circuitry calculating a difference between the first vibration data and the second vibration data having the same meshing frequency for a plurality of meshing frequencies; and performing the condition diagnosis based on the plurality of differences for a plurality of meshing frequencies. The diagnostic device of claim 1 .

3. The processing circuit diagnoses the condition based on one or more of a frequency range of peaks formed by the plurality of differences, a number of peaks formed by the plurality of differences, and a magnitude of vibration intensity at the peaks formed by the plurality of differences. The diagnostic device of claim 2 .

4. a second sensor disposed on the gear device and detecting vibrations of the gear device; The processing circuitry Calculating a first vibration magnification, which is a ratio of vibration intensity between the first vibration data and the third vibration data at the same meshing frequency; calculating a second vibration magnification ratio, which is a ratio of vibration intensity between the second vibration data and the fourth vibration data at the same meshing frequency; the processing circuit executes the condition diagnosis based on a vibration magnification difference that is a difference between the first vibration magnification and the second vibration magnification; the third vibration data is data indicative of vibration of the gear device at a meshing frequency during the first time period, the fourth vibration data is data indicating vibration of the gear device at a meshing frequency, the data being processed from the detection result of the second sensor during the second time period; The diagnostic device of claim 1 .

5. a second sensor disposed on the gear device and detecting vibrations of the gear device; The processing circuitry calculating a first vibration magnification, which is a ratio of vibration intensity between the first vibration data and the third vibration data, for a plurality of meshing frequencies, the first vibration magnification being a ratio of vibration intensity between the first vibration data and the third vibration data, the first vibration data and the third vibration data being the same meshing frequency; calculating, for a plurality of meshing frequencies, a second vibration magnification, which is a ratio of vibration intensity between the second vibration data and the fourth vibration data, which are processed from the detection result of the second sensor and have the same meshing frequency; the processing circuit calculates a vibration magnification difference, which is a difference between the first vibration magnification and the second vibration magnification, for a plurality of meshing frequencies, and performs the condition diagnosis based on the plurality of vibration magnification differences; the third vibration data is a plurality of data representing vibrations of the gear device at a plurality of meshing frequencies based on a plurality of rotational speeds of the gears of the gear device, the fourth vibration data is a plurality of data representing vibrations of the gear device at a plurality of meshing frequencies based on a plurality of rotational speeds of the gears of the gear device, The diagnostic device of claim 2 .

6. The processing circuit diagnoses the condition based on one or more of the frequency range of the peaks formed by the plurality of vibration magnification differences, the number of peaks formed by the plurality of vibration magnification differences, and the magnitude of the vibration magnification at the peaks formed by the plurality of vibration magnification differences. The diagnostic device according to claim 5.

7. the first sensor detects vibrations in a direction of one detection axis or in directions of two or more detection axes that intersect with each other; the second sensor detects vibrations in a direction of one detection axis or in directions of two or more detection axes that intersect with each other; The processing circuit detects a plurality of the vibration magnification differences corresponding to a plurality of combinations of the detection axis of the first sensor and the detection axis of the second sensor, and performs the condition diagnosis based on the plurality of vibration magnification differences. The diagnostic device of claim 4.

8. a sensor processing circuit connected to at least the first sensor of the first sensor and a second sensor disposed in the gear device and detecting vibration of the gear device, and configured to acquire a detection result from the connected sensor; a remote processing circuit having at least some of the functionality of the processing circuit and located remotely from the first sensor and the sensor processing circuit; a first communicator that connects the sensor processing circuit to a communication network so as to be able to communicate data; a second communicator connecting the remote processing circuit to the communication network for data communication; the sensor processing circuit has functions of the processing circuit excluding the functions of the remote processing circuit, and transmits information used for diagnosing the condition of the support structure to the remote processing circuit via the communication network; The remote processing circuitry uses the information received from the sensor processing circuitry to diagnose the condition of the support structure. The diagnostic device of claim 1 .

9. a plurality of first sensors that detect vibrations of a plurality of support structures that support a plurality of gear devices, respectively; a plurality of sensor processing circuits connected to at least the plurality of first sensors out of the plurality of first sensors and a plurality of second sensors disposed on the plurality of gear devices and detecting vibrations of the plurality of gear devices, respectively, and configured to acquire detection results from the connected sensors; a plurality of first communicators that connect the plurality of sensor processing circuits to the communication network so as to be able to communicate data therewith, The remote processing circuitry uses information received from the plurality of sensor processing circuits to diagnose the condition of the plurality of support structures. The diagnostic device of claim 8.

10. 1. A method for diagnosing a support structure for a gear device, comprising: Calculating a difference between the first vibration data and the second vibration data at the same meshing frequency; and performing a condition diagnosis of the support structure based on the difference. the first vibration data is data indicative of vibrations of a support structure supporting the gear device at a meshing frequency during a first time period; the second vibration data is data indicating vibration of the support structure at a meshing frequency during a second time period that is later than the first time period, The meshing frequency is the frequency at which multiple teeth of a gear included in the gear device mesh with an engaging object. Diagnostic methods.

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