Diagnostic device and diagnostic method

Abstract

To provide a technology capable of easily performing diagnosis related to the condition of a bearing.SOLUTION: A monitoring device 200 according to an embodiment of the present disclosure includes an acquisition unit 2001 that acquires measurement data of a rotational speed of an electric motor 100, a calculation unit 2003 that extracts a component of a monitoring frequency of the rotational speed of the electric motor 100 on the basis of the measurement data of the rotational speed of the electric motor 100 acquired by the acquisition unit 2001, and a diagnosis unit 2004 that performs diagnosis regarding the condition of a bearing 104 of the electric motor 100 on the basis of the component of the monitoring frequency extracted by the calculation unit 2003.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present disclosure relates to a diagnostic device and the like.

Background Art

[0002] Conventionally, techniques for diagnosing the state of bearings have been known (see Patent Documents 1 and 2).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, for example, in Patent Document 1, a vibration sensor is required. Therefore, a high-precision vibration sensor is required to accurately detect vibrations in the high-frequency band where bearing vibrations occur, or depending on the installation location, such as when a rotating device is installed at a high place or in water, it may be difficult or impossible to install the vibration sensor itself. Further, for example, in Patent Document 2, bearing damage is estimated by focusing on the mutual inductance of an electric motor. Therefore, setting of criteria according to the electrical characteristics of the electric motor is required, and as a result, the algorithm may become complicated.

[0005] Therefore, in view of the above problems, an object is to provide a technique capable of easily performing diagnosis regarding the state of a bearing.

Means for Solving the Problems

[0006] To achieve the above object, in one embodiment of the present disclosure, Obtain measurement data of the rotational speed of a rotating device, and based on the obtained measurement data of the rotational speed, diagnose the state of the bearing of the rotating device. A diagnostic device is provided.

[0007] Also, in another embodiment of the present disclosure, The diagnostic device obtains measurement data of the rotational speed of a rotating device, and based on the obtained measurement data of the rotational speed, diagnoses the state of the bearing of the rotating device. A diagnostic method is provided.

Advantages of the Invention

[0008] According to the above-described embodiment, it is possible to easily perform a diagnosis regarding the state of the bearing.

Brief Description of the Drawings

[0009]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Embodiments for Carrying Out the Invention

[0010] Hereinafter, embodiments will be described with reference to the drawings.

[0011] [First Example of Monitoring System] With reference to FIGS. 1 to 3, a first example of the monitoring system 1 according to the present embodiment will be described.

[0012] FIG. 1 is a diagram showing an example of the monitoring system 1. FIG. 2 is a diagram showing an example of the structure of the bearing 104x. FIG. 3 is a diagram showing an example of the configuration of the monitoring device 200.

[0013] The monitoring system 1 monitors the state of the bearing 104 that rotatably supports the rotating shaft 103 of the electric motor 100.

[0014] As shown in FIG. 1, the monitoring system 1 includes a rotary electric motor 100, a load device 110, a speed detector 120, a monitoring device 200, and an external device 300.

[0015] The electric motor 100 rotationally drives the load device 110. The electric motor 100 is, for example, an induction motor. Also, the electric motor 100 may be a synchronous motor. The electric motor 100 includes a rotor 101 disposed at the radial center, a stator 102 disposed to face the rotor 101 on the outer side in the radial direction of the rotor 101, a rotating shaft 103, and a bearing 104.

[0016] The rotating shaft 103 includes a rotating shaft portion 103a at one end connected to the load device 110 and a rotating shaft portion 103b at the other end on the opposite side in the axial direction of the electric motor 100.

[0017] The bearing 104 supports the rotating shaft 103 rotatably on the housing of the fixed part of the motor 100. The bearing 104 includes a bearing 104a that supports the rotating shaft portion 103a and a bearing 104b that supports the rotating shaft portion 103b. Hereinafter, any one of the bearings 104a and 104b may be generically referred to as the bearing 104x.

[0018] As shown in FIG. 2, the bearing 104x includes an outer ring 1041, an inner ring 1042, rolling elements 1043, and a cage 1044.

[0019] Note that in FIG. 2, a deep groove ball bearing is illustrated as the bearing 104x, but other types of bearings such as tapered roller bearings may also be used.

[0020] The load device 110 is driven by the motor 100. The load device 110 is, for example, factory machinery and production equipment.

[0021] The speed detector 120 detects the rotational speed of the motor 100 and outputs a signal (rotational speed signal) 130 representing the rotational speed. The speed detector 120 is, for example, a rotary encoder or a resolver. The rotational speed signal 130 is taken into the monitoring device 200 through a predetermined communication line. The predetermined communication line is, for example, a one-to-one communication line or a local area network (LAN) in a factory.

[0022] The monitoring device 200 monitors the state of the bearing 104 based on the rotational speed signal 130 taken in from the speed detector 120.

[0023] The monitoring device 200 is, for example, a terminal device, a PLC (Programmable Logic Controller), an edge controller, an edge server, etc. installed inside a factory where the motor 100 and the load device 110 are installed or within the same site. Further, the monitoring device 200 may be built into a power conversion device such as an inverter device or a servo amplifier that supplies power to and drives the motor 100. In this case, the function of the monitoring device 200 may be integrated into a control circuit that controls the power conversion device, or may be built into the power conversion device separately from the control circuit. Also, the monitoring device 200 may be an on-premises server or a cloud server of a monitoring center installed at a location separate from the site of the factory where the motor 100 and the load device 110 are installed.

[0024] The function of the monitoring device 200 is realized by arbitrary hardware, or an arbitrary combination of hardware and software. For example, as shown in FIG. 3, the monitoring device 200 includes an external interface 201, an auxiliary storage device 202, a memory device 203, a CPU 204, a high-speed arithmetic device 205, a communication interface 206, an input device 207, a display device 208, and a sound output device 209. These components are connected by a bus BS2.

[0025] The external interface 201 functions as an interface for reading data from the recording medium 201A and writing data to the recording medium 201A. The recording medium 201A includes, for example, a flexible disk, a CD (Compact Disc), a DVD (Digital Versatile Disc), a BD (Blu-ray (registered trademark) Disc), an SD memory card, a USB memory, etc. Thereby, the monitoring device 200 can read various data used in processing through the recording medium 201A, store it in the auxiliary storage device 202, or install a program for realizing various functions.

[0026] Note that the monitoring device 200 may acquire various data and programs used in processing from an external device (for example, the external device 300) through the communication interface 206.

[0027] The auxiliary storage device 202 stores various installed programs and also stores files, data, etc. necessary for various processes. The auxiliary storage device 202 includes, for example, an HDD (Hard Disc Drive), an SSD (Solid State Disc), a flash memory, and the like.

[0028] When there is an instruction to start a program, the memory device 203 reads and stores the program from the auxiliary storage device 202. The memory device 203 includes, for example, a DRAM (Dynamic Random Access Memory) and an SRAM (Static Random Access Memory).

[0029] The CPU 204 executes various programs loaded from the auxiliary storage device 202 to the memory device 203 and realizes various functions related to the monitoring device 200 according to the programs.

[0030] The high-speed arithmetic device 205 operates in conjunction with the CPU 204 and performs arithmetic processing at a relatively high speed. The high-speed arithmetic device 205 includes, for example, a GPU (Graphics Processing Unit), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), and the like.

[0031] Note that the high-speed arithmetic device 205 may be omitted depending on the speed of the necessary arithmetic processing.

[0032] The communication interface 206 is used as an interface for communicably connecting to an external device. Thereby, the monitoring device 200 can communicate with devices external to the monitoring device 200, such as the speed detector 120 and the external device 300, through the communication interface 206. Further, the communication interface 206 may have a plurality of types of communication interfaces depending on the communication method with the connected device and the like.

[0033] The input device 207 receives various inputs from the user.

[0034] The input device 207 includes, for example, an input device (hereinafter, "mechanical input device") in a form that receives mechanical operation inputs from the user. The mechanical input device includes, for example, buttons, toggles, levers, keyboards, mice, touch panels mounted on the display device 208, touch pads provided separately from the display device 208, and the like.

[0035] Further, the input device 207 may include a voice input device capable of receiving voice inputs from the user. The voice input device includes, for example, a microphone capable of collecting the user's voice.

[0036] Further, the input device 207 may include a gesture input device capable of receiving gesture inputs from the user. The gesture input device includes, for example, a camera capable of imaging the state of the user's gestures.

[0037] Further, the input device 207 may include a biological input device capable of receiving biological inputs from the user. The biological input device includes, for example, a camera capable of acquiring image data containing information about the user's fingerprint or iris.

[0038] The display device 208 displays an information screen or an operation screen for the user of the monitoring device 200. The display device 208 is, for example, a liquid crystal display, an organic EL (Electroluminescence) display, or the like.

[0039] The sound output device 209 conveys various information to the user of the monitoring device 200 by sound. The sound output device 209 is, for example, a buzzer, an alarm, a speaker, or the like.

[0040] The external device 300 is provided separately from the monitoring device 200 and is communicably connected to the monitoring device 200 through a predetermined communication line. The external device 300 is, for example, a management terminal device or a server device that manages the electric motors 100 distributed and arranged in a plurality of factories.

[0041] The external device 300 transmits, for example, information (external information 310) necessary for the monitoring device 200 to monitor the state of the bearing 104 to the monitoring device 200.

[0042] The external information 310 includes information on the specifications of the bearing 104x (bearing specification information). For example, the specifications of the bearing 104x include, for example, the diameter (rolling element diameter) d of the rolling element 1043, the pitch circle diameter D of the rolling element 1043 disposed between the outer ring 1041 and the inner ring 1042, the contact angle α of the rolling element 1043, and the number (number of rolling elements) Z of the rolling elements 1043. Further, the external information 310 includes information on criteria for diagnosing the state of the bearing 104 (diagnostic criterion information). The information on the criteria for determining the state of the bearing 104 includes, for example, information on thresholds for diagnosing the presence or absence of abnormalities in the bearing 104.

[0043] Note that the function of the external device 300 may be integrated into the monitoring device 200. That is, the information corresponding to the external information 310 may be registered in the monitoring device 200 in advance. In this case, the external device 300 may be omitted.

[0044] [First Example of Functional Configuration of Monitoring Device] Next, with reference to FIGS. 4 to 6, a first example of the functional configuration of the monitoring device 200 according to the present embodiment will be described.

[0045] FIG. 4 is a functional block diagram showing a first example of the functional configuration of the monitoring device 200. FIG. 5 is a diagram for explaining an example of the vibration and the change in the rotational speed that occur in the electric motor 100 due to the damage of the bearing 104x. Specifically, FIG. 5 is a diagram for explaining the vibration and the change in the rotational speed that occur in the electric motor 100 when damage DP such as scratches or peeling occurs in a part of the circumferential direction of the contact surface between the inner ring 1042 of the bearing 104x and the rolling elements 1043. FIG. 5 includes FIGS. 5A to 5C. FIG. 5A schematically shows the operation of the bearing 104x as the electric motor 100 rotates, FIG. 5B shows the time change of the vibration state of the electric motor 100 accompanying the operation of the bearing 104x, and FIG. 5C shows the time change of the rotational speed of the electric motor 100 accompanying the operation of the bearing 104x. FIG. 6 is a diagram showing a specific example of the result of the frequency analysis of the rotational speed of the electric motor 100. FIG. 6 includes FIGS. 6A to 6C. FIG. 6A shows an example of the frequency spectrum of the rotational speed of the electric motor 100 when the bearing 104 is normal. FIG. 6B shows an example of the frequency spectrum of the rotational speed of the electric motor 100 when damage occurs in a part of the circumferential direction of the contact surface between the inner ring 1042 of the bearing 104x and the rolling elements 1043. FIG. 6C shows an example of the frequency spectrum of the rotational speed of the electric motor 100 when damage occurs in a part of the circumferential direction of the contact surface between the outer ring 1041 of the bearing 104x and the rolling elements 1043.

[0046] As shown in FIG. 4, the monitoring device 200 includes, as functional units, an acquisition unit 2001, a storage unit 2002, a calculation unit 2003, a diagnosis unit 2004, and a notification unit 2005. The functions of the acquisition unit 2001, the calculation unit 2003, the diagnosis unit 2004, and the notification unit 2005 are realized, for example, by loading a program installed in the auxiliary storage device 202 into the memory device 203 and executing it on the CPU 204. Further, the function of the storage unit 2002 is realized, for example, by a storage area defined in the auxiliary storage device 202 or a storage device connected to the monitoring device 200.

[0047] The acquisition unit 2001 acquires information necessary for monitoring the state of the bearing 104.

[0048] For example, the acquisition unit 2001 acquires external information 310 received from an external device 300 through the communication interface 206.

[0049] Also, the acquisition unit 2001 acquires measurement data (rotation speed data) of the rotation speed of the electric motor 100 based on the rotation speed signal received from the speed detector 120 through the communication interface 206.

[0050] The storage unit 2002 stores external information 310 for diagnosing the state of the bearing 104.

[0051] The calculation unit 2003 performs various calculations based on the rotation speed data of the electric motor 100 acquired by the acquisition unit 2001, and outputs a feature quantity related to the state of the bearing 104.

[0052] For example, the calculation unit 2003 includes an average rotation speed calculation unit 2003A, a monitoring frequency calculation unit 2003B, a frequency analysis unit 2003C, and a monitoring frequency component extraction unit 2003D.

[0053] The average rotation speed calculation unit 2003A calculates the average rotation speed of the electric motor 100 during that period based on the rotation speed data for a certain period acquired by the acquisition unit 2001.

[0054] The monitoring frequency calculation unit 2003B calculates a frequency to be monitored (monitoring frequency) of the rotation speed of the electric motor 100 for diagnosing the state of the bearing 104.

[0055] For example, as shown in FIG. 5A, when there is a damage DP in a part of the circumferential direction of the contact surface with the rolling element 1043 in the inner ring 1042, as the inner ring 1042 rotates and the rolling element 1043 revolves in accordance with the rotation of the rotary shaft 103, the rolling element 1043 passes through the damaged part DP. As a result, as shown in FIG. 5B, vibration occurs, and due to the influence of the vibration, the rotational speed of the motor 100 fluctuates. The period during which the rolling element 1043 passes through the damaged part of the inner ring 1042, that is, the period during which the rotational speed of the motor 100 fluctuates due to the damage DP of the inner ring 1042, is determined by the rotational speed of the motor 100 and the specifications related to the structure of the bearing 104x. The frequency (inner ring damage passing frequency) f corresponding to this period inner is the rotational frequency f of the motor 100 r , and is expressed by the following formula (1) using the rolling element diameter d, pitch circle diameter D, contact angle α, and number of rolling pairs Z of the bearing 104x.

[0056]

Equation

[0057] Further, when there are damages such as scratches and peeling in a part of the circumferential direction of the contact surface with the rolling element 1043 in the outer ring 1041, as the outer ring 1041 rotates and the rolling element 1043 revolves in accordance with the rotation of the rotary shaft 103, the rolling element 1043 passes through the damaged part. As a result, vibration occurs, and due to the influence thereof, the rotational speed of the motor 100 fluctuates. The period during which the rolling element 1043 passes through the damaged part of the outer ring 1041, that is, the period during which the rotational speed of the motor 100 fluctuates due to the damage of the outer ring 1041, is determined by the rotational speed of the motor 100 and the specifications related to the structure of the bearing 104x. The frequency (outer ring damage passing frequency) f corresponding to this period outer is the rotational frequency f of the motor 100 r , and is expressed by the following formula (2) using the rolling element diameter d, pitch circle diameter D, contact angle α, and number of rolling pairs Z of the bearing 104x.

[0058]

Equation

[0059] Also, when there are damages such as scratches or peeling on the rolling element 1043, as the rotating shaft 103 rotates, the rolling element 1043 rotates on its own, and the damaged part of the rolling element 1043 passes through the outer ring 1041 and the inner ring 1042. As a result, vibration occurs, and due to this influence, the rotational speed of the motor 100 fluctuates. The period during which the damaged part of the rolling element 1043 passes through the outer ring 1041 and the inner ring 1042, that is, the period during which the rotational speed of the motor 100 fluctuates due to the damage of the rolling element 1043, is determined by the rotational speed of the motor 100 and the specifications related to the structure of the bearing 104. The frequency (rolling element damage passing frequency) f corresponding to this period ball is the rotational frequency f of the motor 100 r and is expressed by the following formula (3) using the rolling element diameter d, pitch circle diameter D, contact angle α, and number of rolling pairs Z of the bearing 104x.

[0060]

Equation

[0061] Also, when there are damages such as scratches or defects on the cage 1044, as the rotating shaft 103 rotates, the cage 1044 rotates (revolves), and the rolling element 1043 passes through the damaged part of the cage. As a result, vibration occurs, and due to this influence, the rotational speed of the motor 100 fluctuates. The period during which the damaged part of the cage 1044 passes through the rolling element 1043, that is, the period during which the rotational speed of the motor 100 fluctuates due to the damage of the cage 1044, is determined by the rotational speed of the motor 100 and the specifications related to the structure of the bearing 104. The frequency (cage damage passing frequency) f corresponding to this period cage is the rotational frequency f of the motor 100 r and is expressed by the following formula (4) using the rolling element diameter d, pitch circle diameter D, contact angle α, and number of rolling pairs Z of the bearing 104x.

[0062]

Equation

[0063] Hereinafter, the inner ring defect passing frequency f inner , the outer ring defect passing frequency f outer , the rolling element defect passing frequency f ball , and the cage defect passing frequency f cage may be collectively referred to as the "defect passing frequency".

[0064] When damage occurs on the contact surface between the rolling element 1043 and the inner ring 1042, for the rotational speed of the motor 100, a peak may occur in the n-fold component (n: positive integer) of the inner ring defect passing frequency f inner . For example, as shown in FIGS. 6A and 6B, in this example, peaks appear in the 1-fold component 601 and the 2-fold component 602 of the inner ring defect passing frequency f inner .

[0065] Also, when damage occurs on the contact surface between the rolling element 1043 and the inner ring 1042, for the rotational speed of the motor 100, a peak may occur in the upper sideband component or the lower sideband component shifted by the rotational frequency f inner with respect to the n-fold component of the inner ring defect passing frequency component f r . For example, as shown in FIGS. 6A and 6B, in this example, peaks appear in the upper sideband component 603 and the lower sideband component 604 shifted by the rotational frequency f inner from the 1-fold component 601 of the inner ring defect passing frequency f r .

[0066] Also, when damage occurs on the contact surface between the rolling element 1043 and the outer ring 1041, for the rotational speed of the motor 100, a peak may occur in the n-fold component of the outer ring defect passing frequency f outer . For example, as shown in FIGS. 6A and 6C, in this example, a peak occurs in the 2-fold component 605 of the outer ring defect passing frequency f outer .

[0067] Also, when damage occurs on the contact surface between the rolling element 1043 and the outer ring 1041, for the rotational speed of the motor 100, with respect to the n-fold component of the outer ring defect passing frequency f outer , a peak may occur in the upper sideband component or the lower sideband component shifted by the rotational frequency f rPeaks may occur in the upper sideband component or the lower sideband component that is shifted by that amount. For example, as shown in FIGS. 6A and 6C, in this example, from the double component 605 of the outer ring defect passing frequency f outer to the upper sideband component 606 and the lower sideband component 607 that are shifted by only the rotational frequency f r peaks appear.

[0068] Also, when damage occurs to the rolling element 1043, peaks may occur in the n-fold component of the rolling element defect passing frequency f ball with respect to the rotational speed of the motor 100. Further, when damage occurs to the rolling element 1043, peaks may occur in the upper sideband component or the lower sideband component that is shifted by the rotational frequency f ball by the amount of the rotational frequency f r with respect to the n-fold component of the rolling element defect passing frequency f

[0069] Also, when damage occurs to the cage 1044, peaks may occur in the n-fold component of the cage defect passing frequency f cage with respect to the rotational speed of the motor 100. Further, when damage occurs to the cage 1044, peaks may occur in the upper sideband component or the lower sideband component that is shifted by the rotational frequency f cage by the amount of the rotational frequency f r with respect to the n-fold component of the cage defect passing frequency f

[0070] Thus, when damage occurs to the bearing 104x, the influence of the damage appears in the n-fold component of the defect passing frequency and the sideband component that is shifted by the rotational frequency f r by the amount of the defect passing frequency's n-fold component. Therefore, for example, the monitoring frequency calculation unit 2003B calculates, as the monitoring frequency, at least one of the n-fold component of the defect passing frequency in the range of N1 ≦ n ≦ N2 and the sideband component that is shifted by the rotational frequency f r by the amount of that component. The constants N1 and N2 are positive integers with the relationship N1 < N2.

[0071] Specifically, the monitoring frequency calculation unit 2003B calculates the rotational frequency f r from the average rotational speed of the motor 100 over a certain period, which is calculated by the average rotational speed calculation unit 2003A.Calculate it. Then, the monitoring frequency calculation unit 2003B uses the calculated rotational frequency f r and the bearing specifications information, and uses the above formulas (1) to (4) to calculate, as the monitoring frequency, the n-fold component of the fault passing frequency and the sideband component shifted by the amount of the rotational frequency f r from that component.

[0072] The monitoring frequency calculation unit 2003B calculates, for example, the monitoring frequencies for all of the inner ring fault passing frequency f inner , the outer ring fault passing frequency f outer , the rolling element fault passing frequency f ball , and the cage fault passing frequency f cage . Also, the monitoring frequency calculation unit 2003B may calculate the monitoring frequencies for only some of the inner ring fault passing frequency f inner , the outer ring fault passing frequency f outer , the rolling element fault passing frequency f ball , and the cage fault passing frequency f cage .

[0073] Also, when the bearing specifications information of the bearings 104a and 104b is different from each other, the monitoring frequency calculation unit 2003B may calculate the monitoring frequencies for each of the bearings 104a and 104b, or may calculate the monitoring frequencies for only one of them.

[0074] The frequency analysis unit 2003C performs a frequency analysis of the rotational speed data for a certain period acquired by the acquisition unit 2001, and outputs, as an analysis result, data on the frequency spectrum distribution of the rotational speed of the motor 100. For example, the frequency analysis unit 2003C performs an FFT (Fast Fourier Transform) analysis on the rotational speed data for a certain period, and outputs, as an analysis result, data on the frequency spectrum distribution of the rotational speed of the motor 100.

[0075] The monitoring frequency component extraction unit 2003D extracts the components of the monitoring frequency from the frequency spectrum distribution of the analysis result of the frequency analysis unit 2003C.

[0076] The diagnosis unit 2004 diagnoses the state of the bearing 104 based on the output of the calculation unit 2003, specifically, the components of the monitoring frequency extracted by the monitoring frequency component extraction unit 2003D and the diagnosis reference information.

[0077] The diagnosis regarding the state of the bearing 104 includes, for example, the diagnosis regarding the abnormality of the bearing 104. The abnormality of the bearing 104 includes not only the abnormality that occurs suddenly but also the deterioration that progresses relatively slowly. The diagnosis regarding the abnormality of the bearing 104 includes, for example, the diagnosis of the presence or absence of the abnormality of the bearing 104. Further, the diagnosis regarding the abnormality of the bearing 104 may include the diagnosis of the degree of abnormality (abnormality degree) of the bearing 104.

[0078] The notification unit 2005 notifies the user of the diagnosis result of the diagnosis unit 2004.

[0079] The notification unit 2005 may notify the user of the diagnosis result regardless of the content of the diagnosis result, or may notify the user of the diagnosis result only when the diagnosis result indicates an inappropriate state of the bearing 104. The case where the diagnosis result indicates an inappropriate state of the bearing 104 means, for example, the case where the diagnosis result indicates that there is an abnormality in the bearing 104, the case where the diagnosis result indicates that the abnormality degree of the bearing 104 is relatively high with respect to a predetermined standard, or the case where the diagnosis result indicates that there are signs of abnormality in the bearing 104.

[0080] The notification unit 2005 notifies the user of the diagnosis result through, for example, the display device 208 and the sound output device 209. Further, the notification unit 2005 may notify the user of the diagnosis result through an indicator or the like associated with the load device 110 or the electric motor 100. In this case, the notification unit 2005 outputs a notification command including the diagnosis result to the indicator or the like of the load device 110 or the electric motor 100 through the communication interface 206. Further, the notification unit 2005 may output the diagnosis result outside the monitoring device 200 so that the user can confirm the diagnosis result on the terminal device (user terminal) used by the user. For example, the notification unit 2005 transmits the diagnosis result to the mobile terminal (for example, a smartphone or a tablet terminal) used by the user by push notification through the communication interface 206. Further, the notification unit 2005 may transmit the diagnosis result to the user's email address or SNS (Social Networking Service) account through the communication interface 206.

[0081] As described above, in this example, the monitoring device 200 can perform a diagnosis regarding the state of the bearing 104 based on the rotational speed data of the electric motor 100. Thereby, for example, it is not necessary to add a dedicated vibration sensor or the like for diagnosing the state of the bearing 104, and the speed detector 120 used for controlling the electric motor 100 can be used in combination. Therefore, the monitoring system 1 can easily perform a diagnosis regarding the state of the bearing 104, and as a result, the cost for the diagnosis function can be reduced.

[0082] Further, since the rotational speed of the electric motor 100 fluctuates every time vibration due to an abnormality of the bearing 104 occurs, in this example, the monitoring system 1 can achieve the detection sensitivity of the change in the state of the bearing 104 at the same level as when using a vibration sensor.

[0083] Also, for example, when diagnosing the state of the bearing 104 using a vibration sensor, the accuracy of the diagnosis may decrease due to the influence of external vibration or resonance. Also, for example, there is an existing technique for diagnosing the state of the bearing 104 by using the electrical characteristic quantities of the electric motor 100, but the accuracy of the diagnosis may decrease due to the influence of the current harmonic noise of the inverter, etc.

[0084] In contrast, in this example, without being affected by external vibration, resonance, or harmonic noise, the monitoring system 1 can more appropriately diagnose the state of the bearing 104.

[0085] Also, for example, when diagnosing the state of the bearing 104 by using the electrical characteristic quantities of the electric motor 100, it is necessary to set parameters and diagnostic criteria (for example, threshold values) for diagnosis according to the electrical characteristics of the electric motor 100, and the algorithm may become complicated.

[0086] In contrast, in this example, only the specifications related to the structure of the bearing 104 need to be considered, and the setting of the diagnostic criteria can be simplified. Therefore, also from this perspective, the monitoring system 1 can easily perform the diagnosis regarding the state of the bearing 104.

[0087] [First Example of Diagnostic Method for Bearing State] Next, with reference to FIG. 7, a first example of a diagnostic method for the state of the bearing 104 will be described.

[0088] FIG. 7 is a flowchart schematically showing a first example of a diagnostic method for the state of the bearing 104.

[0089] This flowchart is executed, for example, at each predetermined processing cycle during the operation of the electric motor 100.

[0090] As shown in FIG. 7, in step S102, the acquisition unit 2001 acquires the rotational speed data of the electric motor 100 based on the latest rotational speed signal 130 for a certain period taken in from the speed detector 120.

[0091] When the process of step S102 is completed, the monitoring device 200 proceeds to step S104.

[0092] In step S104, the average rotation speed calculation unit 2003A calculates the average rotation speed of the motor 100 in the latest fixed period based on the rotation speed data of the latest fixed period obtained in the process of step S102.

[0093] When the process of step S104 is completed, the monitoring device 200 proceeds to step S106.

[0094] In step S106, the monitoring frequency calculation unit 2003B calculates the monitoring frequency based on the calculation result of the process of step S104 and the bearing specifications information of the storage unit 2002.

[0095] When the process of step S106 is completed, the monitoring device 200 proceeds to step S108.

[0096] In step S108, the frequency analysis unit 2003C performs a frequency analysis on the rotation speed data of the latest fixed period obtained in step S102 and outputs the data of the frequency spectrum.

[0097] When the process of step S108 is completed, the monitoring device 200 proceeds to step S110.

[0098] In step S110, the monitoring frequency component extraction unit 2003D extracts the components of the monitoring frequency from the data of the frequency spectrum distribution of the analysis result of step S108 based on the calculation result of step S106.

[0099] When the process of step S110 is completed, the monitoring device 200 proceeds to step S112.

[0100] In step S112, the diagnosis unit 2004 calculates the total value SUM of the amplitude values of the components of all the monitoring frequencies extracted in step S110.

[0101] When the process of step S112 is completed, the monitoring device 200 proceeds to step S114.

[0102] In step S114, the diagnosis unit 2004 determines whether the total value SUM calculated in step S112 is greater than or equal to the threshold value SUMth. The threshold value SUMth is pre-stored in the storage unit 2002 as diagnosis criterion information. When the total value SUM is greater than or equal to the threshold value SUMth, the diagnosis unit 2004 diagnoses that there is an abnormality in the bearing 104 and proceeds to step S116. Otherwise, the diagnosis unit 2004 diagnoses that there is no abnormality in the bearing 104 and ends the current flowchart.

[0103] In step S116, the notification unit 2005 notifies the user that there is an abnormality in the bearing 104.

[0104] When the process of step S116 is completed, the monitoring device 200 ends the process of the current flowchart.

[0105] [Second Example of Diagnosis Method for Bearing Condition] Next, with reference to FIG. 8, a second example of the diagnosis method for the condition of the bearing 104 will be described.

[0106] In this example, the description will be centered on the parts different from the above-described first example, and the description of the same or corresponding content as the above-described first example may be omitted.

[0107] FIG. 8 is a flowchart schematically showing a second example of the diagnosis method for the condition of the bearing 104.

[0108] This flowchart is executed, for example, at each predetermined processing cycle during the operation of the motor 100.

[0109] The processes of steps S202, S204, S206, S208, and S210 are the same as the processes of steps S102, S104, S106, S108, and S110 in FIG. 7 described above, and thus the description thereof will be omitted.

[0110] When the process of step S210 is completed, the monitoring device 200 proceeds to step S212.

[0111] In step S212, the diagnosis unit 2004 initializes the counter C to "0".

[0112] When the process of step S212 is completed, the monitoring device 200 proceeds to step S214.

[0113] The series of processes in steps S214, S216, and S218 are performed in a predetermined order for each component of the plurality of monitoring frequencies extracted in the process of step S210.

[0114] In step S214, the diagnosis unit 2004 determines whether the amplitude A corresponding to the spectrum value of the component of the target monitoring frequency is equal to or greater than the threshold value Ath. The threshold value Ath is stored in advance in the storage unit 2002 as diagnosis reference information. The threshold value Ath may be the same for all components of the plurality of monitoring frequencies, or may be different from each other in at least a part thereof. When the amplitude A of the component of the target monitoring frequency is equal to or greater than the threshold value Ath, the diagnosis unit 2004 proceeds to step S216, and in other cases, proceeds to step S218.

[0115] In step S216, the diagnosis unit 2004 increments the counter C by "1" (C = C + 1).

[0116] When the process of step S216 is completed, the monitoring device 200 proceeds to step S218.

[0117] In step S218, the diagnosis unit 2004 determines whether the determination in step S214 for all components of the monitoring frequencies has been completed. When the determination for all components of the monitoring frequencies has been completed, the diagnosis unit 2004 proceeds to step S220, and when it has not been completed, returns to step S214, and performs the processes after step S214 for the next target component of the monitoring frequency.

[0118] In step S220, the diagnosis unit 2004 determines whether the counter C is equal to or greater than the threshold value Cth. The threshold value Cth is pre-stored in the storage unit 2002 as diagnosis reference information. When the counter C is equal to or greater than the threshold value Cth, the diagnosis unit 2004 diagnoses that there is an abnormality in the bearing 104 and proceeds to step S222. Otherwise, the diagnosis unit 2004 diagnoses that there is no abnormality in the bearing 104 and ends the current flowchart.

[0119] Since the process of step S222 is the same as the process of step S116 in FIG. 7 described above, the description thereof is omitted.

[0120] When the process of step S222 is completed, the monitoring device 200 ends the current flowchart.

[0121] [Second Example of Monitoring System] Next, with reference to FIG. 9, a second example of the monitoring system 1 will be described.

[0122] In this example, the same or corresponding components as those in the above-described first example (FIG. 1) are denoted by the same reference numerals, and the description will be centered on the parts different from the above-described first example.

[0123] As shown in FIG. 9, this example is different from the above-described first example in that the monitoring frequency component data (monitoring frequency component data) 320 of the rotation speed data is transmitted from the monitoring device 200 to the external device 300.

[0124] The monitoring device 200 transmits the monitoring frequency component data 320 to the external device 300 every time it extracts the spectral value (amplitude value) of the component of the monitoring frequency for the rotation speed of the motor 100 based on, for example, the rotation speed data for the latest fixed period.

[0125] The external device 300 accumulates, for example, the history of the monitoring frequency component data 320. Thereby, the external device 300 can analyze the time-series change of the components of the monitoring frequency and predict future changes. For example, the external device 300 applies a known statistical method to generate a prediction model of the change of the components of the monitoring frequency based on the history of the data of the components of the monitoring frequency for a number of electric motors 100. Further, the external device 300 may perform supervised learning using the history of the data of the components of the monitoring frequency for a number of electric motors 100 as teacher data to generate a learned model for predicting the change of the components of the monitoring frequency. Therefore, the external device 300 can, for example, distribute a prediction model for predicting the change of the components of the monitoring frequency as external information 310, or distribute the prediction result of the future change of the components of the monitoring frequency to the monitoring device 200 as external information 310.

[0126] [Second Example of the Functional Configuration of the Monitoring Device] Next, with reference to FIGS. 10 and 11, a second example of the functional configuration of the monitoring device 200 according to the present embodiment will be described.

[0127] In this example, the same or corresponding components as those in the above-described first example (FIG. 4) are denoted by the same reference numerals, and the description will be centered on the parts different from the above-described first example.

[0128] FIG. 10 is a functional block diagram showing a second example of the functional configuration of the monitoring device 200. FIG. 11 is a diagram showing an example of the prediction result of the time change of the components of the monitoring frequency of the rotational speed of the electric motor.

[0129] As shown in FIG. 10, in this example, the monitoring device 200 is different from the above-described first example in that it includes a storage unit 2006, a transmission unit 2007, and a diagnostic criterion setting unit 2008 as functional units.

[0130] In the storage unit 2006, the data of the components of the monitoring frequency extracted by the monitoring frequency component extraction unit 2003D is stored in a form accumulated in time series.

[0131] The transmission unit 2007 transmits, through the communication interface 206, the data of the monitored frequency components stored in the storage unit 2006 to the external device 300. Each time new data of the monitored frequency components is stored in the storage unit 2006, the transmission unit 2007 may transmit the data to the external device 300, or may transmit, by batch processing, data that is newer than the previously transmitted data to the external device 300.

[0132] The diagnostic criterion setting unit 2008 sets diagnostic criteria for diagnosing the state of the bearing 104 by the diagnostic unit 2004.

[0133] For example, the diagnostic criterion setting unit 2008 sets thresholds (for example, the above-mentioned threshold SUMth and threshold Ath) for diagnosing the presence or absence of abnormalities in the bearing 104 based on the data of the monitored frequency components in the initial state of the motor 100 stored in the storage unit 2006. The initial state means, for example, the first operation after the motor 100 is shipped from the factory. Thereby, the diagnostic unit 2004 can set diagnostic criteria such as thresholds according to the mechanical characteristics of each motor 100.

[0134] The acquisition unit 2001 acquires, for example, as the external information 310, information on the prediction result of the change in the monitored frequency components regarding the rotational speed of the motor 100 (prediction result information). Further, the acquisition unit 2001 may acquire, as the external information 310, a prediction model of the change in the monitored frequency components regarding the rotational speed of the motor 100 from the external device 300.

[0135] The prediction result information or the prediction model is stored in the storage unit 2002.

[0136] The diagnostic unit 2004 diagnoses, for example, the presence or absence and degree of abnormality of the bearing 104 in the same manner as in the first example above.

[0137] Also, in this example, the diagnostic unit 2004 may diagnose the remaining life of the bearing 104 or the presence or absence of signs of abnormality of the bearing 104 using the prediction result information and the prediction model.

[0138] For example, as shown in FIG. 11, in this example, based on the time-series measurement data 1101 of the sum value SUM of the amplitude values of the components at all monitoring frequencies up to the present (time Tc), prediction data 1102 of the time change of the sum value SUM after the present has been obtained.

[0139] The diagnosis unit 2004 can calculate the timing (time Td) at which the threshold value SUMth reaches the threshold value SUMth from the relationship between the prediction data 1102 and the threshold value SUMth. Therefore, the diagnosis unit 2004 can estimate the remaining life of the bearing 104 as the difference between the times Td and Tc.

[0140] Also, similar to the second example (FIG. 9) of the above-described diagnosis method, the diagnosis unit 2004 may predict the remaining life based on the prediction data of the amplitude A for each component of the monitoring frequency. For example, the diagnosis unit 2004 predicts the remaining life for each component of the monitoring frequency, and adopts the average value, minimum value, etc. thereof as the remaining life of the bearing 104.

[0141] Also, the diagnosis unit 2004 may diagnose the presence or absence of signs of abnormality of the bearing 104 based on the rising slope of the prediction data 1102 of the time change of the sum value SUM. Specifically, this is because when the rising slope of the prediction data 1102 of the time change of the sum value SUM becomes relatively large with respect to a predetermined standard, the diagnosis unit 2004 can surely assume that the sum value SUM exceeds the threshold value SUMth.

[0142] Also, similar to the second example (FIG. 9) of the above-described diagnosis method, the diagnosis unit 2004 may diagnose the presence or absence of signs of abnormality of the bearing 104 based on the prediction data of the amplitude A for each component of the monitoring frequency. For example, the diagnosis unit 2004 diagnoses the presence or absence of signs of abnormality of the bearing 104 using the average value, maximum value, etc. of the rising slopes of the prediction data of the amplitude A for each component of the monitoring frequency.

[0143] Thus, in this example, the monitoring system 1 can record data on the components of the monitoring frequency of the rotational speed of the electric motor 100. Therefore, for example, the monitoring device 200 can set diagnostic criteria for diagnosing the state of the bearing 104 using the data on the initial state of the electric motor 100, and as a result, can set the diagnostic criteria according to the individual mechanical characteristics of the electric motor 100.

[0144] Also, in this example, the monitoring system 1 can predict the future temporal change of the components of the monitoring frequency based on the history of the data on the components of the monitoring frequency of the rotational speed of the electric motor 100. Therefore, the monitoring system 1 can diagnose the remaining life of the bearing 104 or diagnose the presence or absence of signs of abnormality in the bearing 104.

[0145] [Other Embodiments] Next, other embodiments will be described.

[0146] The above-described embodiments may be appropriately modified or changed.

[0147] For example, in the above-described embodiment, instead of the total value SUM of the amplitudes A of the components of the monitoring frequency of the rotational speed of the electric motor 100, the diagnostic unit 2004 may perform a diagnosis regarding the state of the bearing 104 based on the maximum value, average value, etc. of the amplitude A.

[0148] Also, in the above-described embodiments and examples of their modifications and changes, the functions of the external device 300 may be integrated into the monitoring device 200.

[0149] Also, in the above-described embodiments and examples of their modifications and changes, the monitoring device 200 may extract the components of the monitoring frequency of the rotational speed of the electric motor 100 by using a filter that extracts the components of the monitoring frequency of the rotational speed of the electric motor 100 instead of frequency analysis.

[0150] Further, in the above-described embodiments and examples of their modifications and changes, the monitoring device 200 may perform a diagnosis regarding the state of the bearing 104 by using a known analysis method such as waveform counting based on time-series waveform data instead of the frequency component of the rotational speed of the electric motor 100.

[0151] Further, in the above-described embodiments and examples of their modifications and changes, the monitoring device 200 may perform a diagnosis regarding the state of the bearing of the load device 110 instead of, or in addition to, the bearing 104 of the electric motor 100.

[0152] Also, a diagnostic method similar to the above-described embodiments and examples of their modifications and changes may be adopted for diagnosing the state of the bearing of another type of rotating device different from the electric motor 100 and the load device 110.

[0153] [Operation] Next, the operation of the diagnostic device, diagnostic method, and program according to the present embodiment will be described.

[0154] In the first aspect of the present embodiment, the diagnostic device acquires measurement data of the rotational speed of the rotating device, and based on the acquired measurement data of the rotational speed, performs a diagnosis regarding the state of the bearing of the rotating device. The diagnostic device is, for example, the above-described monitoring device 200. The rotating device is, for example, the above-described electric motor 100. The bearing is, for example, the above-described bearing 104.

[0155] Also, in the first aspect of the present embodiment, the diagnostic device may execute a diagnostic method of acquiring measurement data of the rotational speed of the rotating device and performing a diagnosis regarding the state of the bearing of the rotating device based on the acquired measurement data of the rotational speed.

[0156] Also, in the first aspect of the present embodiment, a program may be adopted that causes an information processing device to acquire measurement data of the rotational speed of the rotating device and perform a diagnosis regarding the state of the bearing of the rotating device based on the acquired measurement data of the rotational speed. The information processing device is, for example, the above-described monitoring device 200.

[0157] As a result, a diagnostic device, an information processing device (hereinafter referred to as "diagnostic device etc.") can easily diagnose the state of the bearing of the rotating device by using the measurement data of the rotational speed of the rotating device.

[0158] Also, in the second aspect of the present embodiment, on the premise of the above-described first aspect, the diagnostic device etc. may perform a diagnosis regarding the state of the bearing based on the frequency components of the acquired measurement data of the rotational speed.

[0159] As a result, the diagnostic device etc. can perform a diagnosis regarding the state of the bearing of the rotating device based on the frequency components of the measurement data of the rotational speed.

[0160] Also, in the third aspect of the present embodiment, on the premise of the above-described second aspect, the diagnostic device etc. may perform a diagnosis regarding the state of the bearing based on the result of the frequency analysis of the acquired measurement data of the rotational speed.

[0161] As a result, the diagnostic device etc. can perform a diagnosis regarding the state of the bearing of the rotating device based on the frequency components of the measurement data of the rotational speed obtained from the result of the frequency analysis of the measurement data of the rotational speed.

[0162] Also, in the fourth aspect of the present embodiment, on the premise of the above-described second or third aspect, the diagnostic device etc. may perform a diagnosis regarding the state of the bearing based on the frequency components of the monitoring target related to a specific frequency representing the damage of the bearing. The frequency components of the monitoring target are, for example, the components of the above-described monitoring frequency.

[0163] As a result, the diagnostic device etc. can perform a diagnosis regarding the state of the bearing by paying attention to the damage that may occur in the bearing of the rotating device.

[0164] Further, in the fifth aspect of the present embodiment, on the premise of the above-described fourth aspect, the specific frequency may include at least one of a first frequency corresponding to vibrations generated in the rotating device due to damage occurring in the inner ring of the bearing, a second frequency of vibrations generated in the rotating device due to damage occurring in the outer ring of the bearing, a third frequency corresponding to vibrations generated in the rotating device due to damage occurring in the rolling elements of the bearing, and a fourth frequency corresponding to vibrations generated in the rotating device due to damage occurring in the cage of the bearing. The first frequency is, for example, the inner ring defect passing frequency f inner as described above. The second frequency is, for example, the outer ring defect passing frequency f outer as described above. The third frequency is, for example, the rolling element defect passing frequency f ball as described above. Also, the fourth frequency is, for example, the cage defect passing frequency f cageである。

[0165] Thereby, a diagnostic device or the like can focus on damage that may occur in at least one of the inner ring, outer ring, rolling elements, and cage of the bearing of the rotating device, and diagnose the state of the bearing.

[0166] Further, in the sixth aspect of the present embodiment, on the premise of the above-described fifth aspect, the first frequency, the second frequency, the third frequency, and the fourth frequency may be defined based on the rotational frequency of the rotating device and the dimensional specifications of the bearing.

[0167] Thereby, a diagnostic device or the like can easily identify a specific frequency representing damage to the bearing, and as a result, can easily diagnose the state of the bearing based on the frequency components to be monitored.

[0168] Further, in the seventh aspect of the present embodiment, on the premise of any one of the above-described fourth to sixth aspects, the frequency components to be monitored may include at least one of a multiple component of the specific frequency and a sideband component shifted by the rotational frequency of the rotating device with respect to the multiple component of the specific frequency.

[0169] As a result, a diagnostic device or the like can diagnose the state of the bearing based on changes that appear in a multiple component of a specific frequency representing damage to the bearing or a sideband component shifted by the rotational frequency from the multiple component.

[0170] Further, in the eighth aspect of the present embodiment, on the premise of any one of the fourth to seventh aspects described above, a diagnostic device or the like may diagnose an abnormality of the bearing based on the amplitude value of the frequency component of the monitoring target.

[0171] As a result, a diagnostic device or the like can diagnose the state of the bearing of the rotating device based on the amplitude value (spectrum value) of the frequency component of the monitoring target.

[0172] Further, in the ninth aspect of the present embodiment, on the premise of the eighth aspect described above, when the amplitude value of the frequency component of the monitoring target is relatively higher than a predetermined standard, the diagnostic device or the like may diagnose that there is an abnormality in the bearing. The predetermined standard is, for example, the above-described threshold value Ath or threshold value SUMth.

[0173] As a result, a diagnostic device or the like can diagnose the presence or absence of an abnormality in the bearing of the rotating device.

[0174] Further, in the tenth aspect of the present embodiment, on the premise of the eighth aspect described above, a diagnosis regarding the remaining life or signs of abnormality of the bearing may be made based on the history of the amplitude value of the frequency component of the monitoring target.

[0175] As a result, a diagnostic device or the like can diagnose the remaining life and signs of abnormality of the bearing of the rotating device.

[0176] Further, in the eleventh aspect of the present embodiment, on the premise of any one of the first to tenth aspects described above, a diagnostic device or the like may notify a user of a diagnostic result regarding the state of the bearing.

[0177] As a result, a diagnostic device or the like can notify a user of a diagnostic result regarding the state of the bearing of the rotating device.

[0178] Although the embodiments have been described in detail above, the present disclosure is not limited to such specific embodiments, and various modifications and changes are possible within the scope of the gist described in the claims.

Explanation of Reference Numerals

[0179] 1 Monitoring system 100 Electric motor 103 Rotating shaft 103a, 103b Rotating shaft portions 104 Bearing 104a, 104b Bearings 110 Load device 120 Speed detector 200 Monitoring device 300 External device 1041 Outer ring 1042 Inner ring 1043 Rolling element 1044 Cage 2001 Acquisition unit 2002 Storage unit 2003 Calculation unit 2003A Average rotation speed calculation unit 2003B Monitoring frequency calculation unit 2003C Frequency analysis unit 2003D Monitoring frequency component extraction unit 2004 Diagnosis unit 2005 Notification unit 2006 Storage unit 2007 Transmission unit 2008 Diagnosis criterion setting unit f ball Rolling element defect passing frequency f cage Cage defect passing frequency f inner Inner ring defect passing frequency f outer Outer ring defect passing frequency f r Rotation frequency

Claims

1. A diagnostic device that acquires measurement data of the rotational speed of a rotating device and performs a diagnosis regarding the state of a bearing of the rotating device based on the acquired measurement data of the rotational speed.

2. A diagnostic device according to claim 1, wherein a diagnosis regarding the state of the bearing is performed based on a frequency component of the acquired measurement data of the rotational speed.

3. A diagnostic device according to claim 2, wherein a diagnosis regarding the state of the bearing is performed based on a result of frequency analysis of the acquired measurement data of the rotational speed.

4. A diagnostic device according to claim 2 or 3, wherein a diagnosis regarding the state of the bearing is performed based on a frequency component to be monitored related to a specific frequency representing damage to the bearing.

5. The specific frequency includes at least one of a first frequency corresponding to vibration generated in the rotating device due to damage occurring in an inner ring of the bearing, a second frequency of vibration generated in the rotating device due to damage occurring in an outer ring of the bearing, a third frequency corresponding to vibration generated in the rotating device due to damage occurring in a rolling element of the bearing, and a fourth frequency corresponding to vibration generated in the rotating device due to damage occurring in a cage of the bearing.

6. A diagnostic device according to claim 5, wherein the first frequency, the second frequency, the third frequency, and the fourth frequency are defined based on a rotational frequency of the rotating device and dimensional specifications of the bearing.

7. A diagnostic device according to claim 4, wherein the frequency component to be monitored includes at least one of a multiple component of the specific frequency and a sideband component shifted by a rotational frequency of the rotating device with respect to the multiple component of the specific frequency.

8. A diagnostic device according to claim 4, wherein a diagnosis regarding an abnormality of the bearing is performed based on an amplitude value of the frequency component to be monitored.

9. A diagnostic device according to claim 8, wherein when the amplitude value of the frequency component to be monitored is relatively higher than a predetermined standard, it is diagnosed that there is an abnormality in the bearing.

10. A diagnostic device according to claim 8, wherein a diagnosis regarding a remaining life or a sign of an abnormality of the bearing is performed based on a history of the amplitude value of the frequency component to be monitored.

11. A diagnostic device according to any one of claims 1 to 3, which notifies a user of a diagnosis result regarding the state of the bearing.

12. ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ ​ A diagnostic device acquires measurement data of the rotational speed of a rotating device, and based on the acquired measurement data of the rotational speed, diagnoses the state of the bearing of the rotating device. Diagnostic method.

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