Rotary machine abnormality diagnosing device and abnormality diagnosing method

Abstract

This abnormality diagnosing device comprises: a capacitance calculating unit that calculates a winding capacitance, which is the capacitance of a winding of a rotary machine, on the basis of a winding current flowing through the winding; an environmental information acquiring unit that acquires environmental information relating to the region in which the rotary machine is installed; a rotary machine information storage unit that stores a characteristic change in the winding capacitance with respect to a change in the environmental information; a winding state estimating unit that acquires the environmental information when the rotary machine is operating from the environmental information acquiring unit, if the environmental information has changed, acquires the characteristic change from the rotary machine information storage unit and estimates an estimated winding capacitance corresponding to the changed environmental information; and a diagnosing unit that acquires, from the capacitance calculating unit, the winding capacitance after the environmental information has changed, and diagnoses an abnormality of the rotary machine by comparing the winding capacitance with the estimated winding capacitance.

Description

Rotating machine abnormality diagnosis device and abnormality diagnosis method

[0001] The present invention relates to an abnormality diagnosis device and an abnormality diagnosis method for a rotating machine such as a motor or a generator.

[0002] When a motor or generator stops, it can cause significant damage. In particular, a sudden motor failure in an electric aircraft can have a significant impact on the system and passenger safety. Therefore, there is a growing need to perform highly accurate predictive failure diagnosis while the motor is in use in a real environment, and to prevent sudden motor failures.

[0003] In response to such needs, Patent Document 1 below describes a technology for diagnosing abnormalities in rotating machines. Specifically, Patent Document 1 discloses a method for measuring the capacitance of an insulating member to detect deterioration of the insulating material with high sensitivity. However, this technology has a problem in that it may lead to erroneous diagnosis when the coating of the insulating material absorbs moisture due to changes in atmospheric pressure, temperature, or humidity, causing a change in the relative dielectric constant and resulting in a change in capacitance.

[0004] Patent No. 7184706 specification

[0005] When the humidity around a rotating machine increases, the temperature decreases, or the air pressure rises, the insulating coating contained in the windings of the rotating machine absorbs moisture, increasing its dielectric constant and resulting in an increase in capacitance. On the other hand, when the humidity decreases, the temperature increases, or the air pressure drops, the insulating coating releases moisture, decreasing its dielectric constant and resulting in a decrease in capacitance. In this way, changes in capacitance due to moisture absorption and release by the insulating coating are reversible. On the other hand, when the insulating coating becomes contaminated or deteriorates due to changes in air pressure, humidity, temperature, or the external environment, the dielectric constant of the insulating coating increases, increasing the winding capacitance. Such changes in capacitance due to contamination or deterioration of the insulating coating are irreversible.

[0006] As mentioned above, there is a method of monitoring the capacitance of insulating members when diagnosing abnormalities in rotating machines, but with conventional technology, it was not possible to determine whether a change in capacitance was reversible or irreversible.

[0007] The present invention has been made in consideration of the above-mentioned circumstances, and aims to provide an abnormality diagnosis device that can detect abnormalities caused by contamination or deterioration of an insulating coating in an environment where the capacitance changes due to moisture absorption and release of the insulating coating.

[0008] In order to solve the above-mentioned problems, the abnormality diagnosis device for a rotating machine of the present invention is characterized by comprising: a capacitance calculation unit that calculates a winding capacitance, which is the electrostatic capacitance of the windings, based on a winding current flowing through the windings of the rotating machine; an environmental information acquisition unit that acquires environmental information of an area in which the rotating machine is installed; a rotating machine information storage unit that stores characteristic changes in the winding capacitance in response to changes in the environmental information; a winding state estimating unit that acquires environmental information while the rotating machine is operating from the environmental information acquisition unit, acquires the characteristic changes from the rotating machine information storage unit when the environmental information changes, and estimates an estimated winding capacitance corresponding to the changed environmental information; and a diagnosis unit that acquires the winding capacitance after the environmental information has changed from the capacitance calculation unit, and diagnoses an abnormality in the rotating machine by comparing the winding capacitance with the estimated winding capacitance.

[0009] According to the present invention, it is possible to provide an abnormality diagnosis device capable of detecting abnormalities caused by contamination or deterioration of an insulating coating in an environment in which the capacitance changes due to moisture absorption and release of the insulating coating. Further features related to the present invention will become apparent from the description of this specification and the accompanying drawings. In addition, the problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments.

[0010] 1 is a diagram showing an example of the configuration of a rotating machine system 100 according to a first embodiment. FIG. 2 is a functional block diagram showing an example of the configuration of an abnormality diagnosis device 30 according to a first embodiment. FIG. 3 is an example of a flowchart showing processing executed by the abnormality diagnosis device 30 according to a first embodiment. FIG. 4 is an example of time change in winding capacitance in response to time change in environmental information according to a first embodiment. FIG. 5 is an example of time change in winding capacitance and estimated winding capacitance in response to time change in environmental information according to a first embodiment. FIG. 6 is an example of operation of a winding state estimation unit, a capacitance calculation unit, and a diagnosis unit while a rotating machine is operating in an environment where environmental information changes over time according to a first embodiment. FIG. 7 is an example of a computer according to a first embodiment.

[0011] [Example 1] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. The embodiment is an example for explaining the present invention, and appropriate omissions and simplifications have been made for clarity of explanation. Furthermore, not all of the elements and combinations thereof described in the embodiment are necessarily essential to the solution of the invention. When there are multiple components having the same or similar functions, they may be described using the same reference numeral with different subscripts. Furthermore, when it is not necessary to distinguish between these multiple components, the subscripts may be omitted in the description.

[0012] FIG. 1 is a diagram illustrating an example of the configuration of a rotating machine system 100 according to a first embodiment. As illustrated in FIG. 1 , the rotating machine system 100 includes a battery 1, an inverter 2, a rotating machine 3, a current sensor 4, a control device 5, an abnormality diagnosis device 30, a temperature sensor 6, a humidity sensor 7, and an air pressure sensor 8. The inverter 2 converts a DC voltage input from the battery 1 into an AC voltage. The rotating machine 3 is driven and rotated based on the AC voltage input from the inverter 2. The control device 5 controls the driving of the rotating machine by passing a current through the windings, and uses, for example, a detection value from the current sensor 4 for control. The temperature sensor 6, the humidity sensor 7, and the air pressure sensor 8 measure the temperature, humidity, and air pressure around the rotating machine 3, respectively, and output the measured values ​​to the control device 5. The abnormality diagnosis device 30 includes a capacitance calculation unit 301, an environmental information acquisition unit 302, a rotating machine information storage unit 303, a winding state estimation unit 304, and a diagnosis unit 305.

[0013] [Fault diagnosis device 30] Fig. 2 is a functional block diagram showing an example of the configuration of the fault diagnosis device 30. In Fig. 2, a capacitance calculation unit 301 acquires data relating to current ringing in response to application of a voltage pulse from a current sensor 4 using, for example, the method disclosed in Patent Document 1, and calculates a winding capacitance proportional to the relative dielectric constant of the sensor insulating material.

[0014] The environmental information acquisition unit 302 acquires environmental information (temperature, humidity, and atmospheric pressure) around the rotating machine 3 from various sensors (temperature sensor 6, humidity sensor 7, and atmospheric pressure sensor 8) and outputs the environmental information to the rotating machine information storage unit 303 and the winding state estimation unit 304. The rotating machine information storage unit 303 acquires and stores environmental information at multiple points in time from the environmental information acquisition unit 302 and acquires and stores winding capacitance environmental information at multiple points in time from the capacitance calculation unit 301. Based on this data at multiple points in time, the rotating machine information storage unit 303 generates and stores characteristic changes in winding capacitance with respect to changes in the environmental information and outputs the characteristic changes in winding capacitance to the winding state estimation unit 304. Note that in this embodiment, the characteristic changes in winding capacitance with respect to changes in the environmental information refer to, but are not limited to, winding capacitance change delay, which indicates a delay in the change in winding capacitance, and / or winding capacitance change rate, which indicates the rate at which the winding capacitance changes. Furthermore, with regard to the winding capacitance change delay information and the winding capacitance change rate information, both or either of these pieces of information may be used. The same applies to the other functional units.

[0015] The winding state estimating unit 304 acquires winding capacitance change delay information and / or winding capacitance change rate information from the environmental information acquiring unit 302, and estimates an estimated winding capacitance, which is the winding capacitance, based on this data. Note that the winding capacitance estimated by the winding state estimating unit 304 is defined as an "estimated winding capacitance" to distinguish it from the "winding capacitance" calculated by the capacitance calculating unit 301. The diagnosing unit 305 compares the "winding capacitance" calculated by the capacitance calculating unit 301 with the "estimated winding capacitance" estimated by the winding state estimating unit 304, and diagnoses an abnormality in the rotating machine.

[0016] [Flow of the Abnormality Diagnosis Device 30] FIG. 3 is a diagram showing an example of a flowchart illustrating processing executed by the abnormality diagnosis device 30. As shown in FIG.

[0017] In step S101, when the rotating machine is normal, the winding capacitance is calculated by the capacitance calculation unit 301, and the process proceeds to step S102.

[0018] In step S102, when the rotating machine is normal, environmental information (barometric pressure, humidity, temperature) is acquired by the environmental information acquisition unit 302. Steps S101 and S102 are performed at multiple times, and the information is stored in association with the time information in the rotating machine information storage unit 303. After repeating steps S101 and S102 a predetermined number of times, the process proceeds to step S103.

[0019] In step S103, the relationship between the delay and the rate of change in the winding capacitance relative to changes in the environmental information is modeled using time-series data of the environmental information (air pressure, humidity, and temperature) when the rotating machine is normal and time-series data of the winding capacitance, and the model is stored in the rotating machine information storage unit 303. Here, steps S101 to S103 are performed when the rotating machine is normal. For example, in the case of an electric aircraft, a pre-test may be performed under conditions of changed humidity and temperature before operation when the rotating machine is normal (immediately after the rotating machine is manufactured), or a model may be created based on data when the rotating machine is normal during operation between the Nth regular inspection and the N+1th regular inspection (N is a natural number), and the model may be stored in the rotating machine information storage unit 303.

[0020] Although it is possible to store environmental information data obtained in advance by simulation or the like, it is preferable to obtain the environmental information by directly operating the actual rotating machine when it is normal, as in this embodiment. This is because, when the rotating machine is used in an electric aircraft as described above, the aircraft flies in the air where environmental information is prone to change suddenly, and by obtaining and updating environmental information in real time, it becomes possible to respond to such suddenly changing environmental information.

[0021] In step S104, the winding state estimating unit 304 constructs the winding state estimating unit 304 so that it can estimate an estimated winding capacitance without using data from the capacitance calculating unit 301, based on the information stored in the rotating machine information storing unit 303 and the environmental information acquired by the environmental information acquiring unit 302. In step S105, when the rotating machine 3 is operating, the capacitance calculating unit 301 calculates the winding capacitance, and the winding state estimating unit 304 estimates the estimated winding capacitance and outputs it to the diagnosing unit 305.

[0022] In step S106, the diagnosis unit 305 compares the winding capacitance calculated by the capacitance calculation unit 301 with the estimated winding capacitance estimated by the winding state estimation unit 304 to determine whether there is an abnormality in the rotating machine 3. If the degree of abnormality is high (if the degree of agreement is low), the process proceeds to step S108. If the degree of abnormality is low (if the degree of agreement is high), the process proceeds to step S107.

[0023] In step S107, it is determined that the rotating machine 3 is normal, and the process ends. The fact that the rotating machine 3 is normal may be displayed on a display device not shown in FIG. 1. In step S108, abnormality information is issued, and the process ends. The abnormality information may be displayed on a display device in the same manner as above. Alternatively, the abnormality information may be output to the control device 5, and the output of the rotating machine 3 may be suppressed so that the abnormality in the rotating machine 3 does not progress.

[0024] [Details of Rotating Machine Information Storage Unit and Winding State Estimation Unit] The rotating machine information storage unit 303 and the winding state estimation unit 304 will be described in detail with reference to Figs. 4 and 5. Fig. 4 is a diagram showing an example of the time change in winding capacitance in response to the time change in environmental information. The environmental information is, for example, the temperature, humidity, or atmospheric pressure around the windings. The environmental information is estimated using, for example, the temperature around the rotating machine 3 detected by a temperature sensor, the humidity around the rotating machine 3 detected by a humidity sensor, and the atmospheric pressure around the rotating machine 3 detected by an atmospheric pressure sensor.

[0025] Furthermore, if the temperature sensor is located near the rotating machine 3 and cannot directly measure the temperature around the windings, the winding temperature can be estimated using a physical model based on the motor structure that further uses the current detection value detected by the current sensor to estimate the winding temperature based on the heat generated in the windings due to Joule loss in the winding current, the temperature detected by the temperature sensor, and the positional relationship between the windings and the temperature sensor, thereby enabling more accurate detection of environmental information about the windings. Furthermore, if the humidity sensor cannot directly detect the humidity around the windings, the humidity around the windings can be estimated using a physical model based on the motor structure or materials that uses the humidity detected by the humidity sensor and the positional relationship between the windings and the humidity sensor, thereby enabling more accurate detection of environmental information about the windings.

[0026] As an example, a change in humidity, which is one of the environmental information, is used for explanation in Figure 4. Note that even when there are changes in multiple elements of the environmental information, the same function can be realized by calculating the contribution of each element change to the change in winding capacitance, for example, by machine learning.

[0027] 4(a) shows an example of the change in winding capacitance over time in response to an increase in humidity, and Fig. 4(b) shows an example of the change in winding capacitance over time in response to a decrease in humidity. This is because there is a delay in changes in physical phenomena such as moisture absorption and release relative to changes in environmental information over time, and there is a delay in the change in winding capacitance over time relative to changes in environmental information over time.

[0028] When the rotating machine 3 is operating normally, the winding state estimator 304 models the moisture absorption / desorption phenomenon of the windings in response to changes in environmental information and the change in winding capacitance associated with the moisture absorption / desorption phenomenon. This modeling corresponds to "construction of a winding state estimator" shown in step S104 of Fig. 3. If an abnormality is detected in the rotating machine 3 at this point, the modeling is stopped and measures such as replacing or repairing the rotating machine 3 are taken.

[0029] FIG. 5 is a diagram showing an example of time changes in winding capacitance and estimated winding capacitance relative to time changes in environmental information. The winding state estimator 304 and the rotating machine information storage unit 303 perform modeling based on physical phenomena related to moisture absorption or desorption of the windings so that the winding state estimator 304 can estimate the estimated winding capacitance without using information on the winding capacitance calculated by the capacitance calculator 301. Then, parameters related to delay and rate of change are calculated using the winding capacitance calculated by the capacitance calculator 301 and actual data. A winding state model is constructed using data including time changes in the winding capacitance when the rotating machine 3 is normal, and the data in the rotating machine information storage unit 303 is learned to calculate the estimated winding capacitance without using the winding capacitance. Finally, as shown in FIGS. 5( a) and 5(b), the parameters of the winding state estimator 304 are adjusted so that the estimated winding capacitance matches the winding capacitance.

[0030] As described above, this embodiment models the moisture absorption / desorption phenomenon of the windings in response to changes in environmental information when the rotating machine 3 is operating normally, and the change in winding capacitance that accompanies this moisture absorption / desorption phenomenon. That is, the created model includes reversible changes in winding capacitance that accompany moisture absorption / desorption of the windings. Therefore, if the capacitance actually measured while the rotating machine 3 is operating significantly deviates from the value estimated based on this model, it can be determined that the deviation is due to an irreversible change in capacitance caused by contamination or deterioration of the windings.

[0031] FIG. 6 is a diagram illustrating an example of the operation of the winding state estimator 304, capacitance calculator 301, and diagnoser 305 while the rotating machine 3 is operating in an environment where environmental information changes over time. The capacitance calculator 301 calculates the winding capacitance based on the ringing of the current. The winding state estimator 304 estimates the estimated winding capacitance based on the environmental information and data from the rotating machine information storage unit 303. When the rotating machine 3 operates in an environment where environmental information changes over time, the winding capacitance and the estimated winding capacitance change over time as shown in FIG. 6( a). The diagnoser 305 compares the winding capacitance with the estimated winding capacitance to diagnose an abnormality in the winding. If the two match or there is a small discrepancy, the winding is considered to be normal. On the other hand, if the degree of agreement between the two is low and the winding capacitance is greater than the estimated winding capacitance, it is determined that an increase in capacitance has occurred due to a winding abnormality (such as thermal deterioration of the winding) other than moisture absorption or release, and the time when the degree of abnormality (the difference between the winding capacitance and the estimated winding capacitance) exceeds the reference value Th (Time ≥ t １ ) outputs winding abnormality information.

[0032] [Computer] Fig. 7 is a block diagram of the computer 980. The control device 5 and the abnormality diagnosis device 30 shown in Fig. 1 each include one or more computers 980 shown in Fig. 7 .

[0033] 7, a computer 980 includes a CPU 981, a storage unit 982, a communication I / F (interface) 983, an input / output I / F 984, and a media I / F 985. Here, the storage unit 982 includes a RAM 982a, a ROM 982b, and an HDD 982c. The communication I / F 983 is connected to a communication circuit 986. The input / output I / F 984 is connected to an input / output device 987. The media I / F 985 reads and writes data from a recording medium 988.

[0034] The ROM 982b stores an IPL (Initial Program Loader) executed by the CPU, etc. The HDD 982c stores control programs, various data, etc. The CPU 981 executes the control programs, etc. loaded from the HDD 982c to the RAM 982a, thereby realizing various functions. The interior of the abnormality diagnosis device 30, etc. shown in FIG. 2 is shown as blocks representing functions realized by the control programs, etc.

[0035] As described above, the present invention makes it possible to correctly detect an abnormality due to contamination or deterioration of the insulating coating without falsely detecting an abnormality when a change in capacitance occurs due to moisture absorption and release by the insulating coating, even in an environment where environmental information changes over time.

[0036] [Modifications] The present invention is not limited to the above-described embodiment, and various modifications are possible. The above-described embodiment is provided as an example to facilitate understanding of the present invention, and is not necessarily limited to an embodiment including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to delete part of the configuration of each embodiment, or to add or replace other configurations. Furthermore, the control lines and information lines shown in the figures are those considered necessary for explanation, and do not necessarily represent all control lines and information lines necessary for the product. In reality, it is possible to consider that almost all components are interconnected. Possible modifications of the above-described embodiment include, for example, the following.

[0037] (1) The hardware of the anomaly determiner in the above embodiment can be realized by a general computer. Therefore, the processes corresponding to the above-described block diagrams and flowcharts, as well as programs for executing the various processes described above, may be stored in a storage medium (a computer-readable storage medium on which a program is recorded) or distributed via a transmission path.

[0038] (2) In the above embodiment, the processes corresponding to the block diagrams and flowcharts, and the programs that execute the various processes described above have been described as software-based processes using programs. However, some or all of these processes may be replaced with hardware-based processes using an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array), etc.

[0039] (3) The various processes executed in the above embodiment may be executed by a server computer via a network (not shown), and the various data stored in the above embodiment may also be stored in the server computer.

[0040] The above-described embodiment of the present invention provides the following advantageous effects.

[0041] (1) An abnormality diagnosis device according to the present invention includes a capacitance calculation unit that calculates a winding capacitance, which is the electrostatic capacitance of the windings, based on a winding current flowing through the windings of a rotating machine; an environmental information acquisition unit that acquires environmental information of an area in which the rotating machine is installed; a rotating machine information storage unit that stores characteristic changes in the winding capacitance in response to changes in the environmental information; a winding state estimation unit that acquires environmental information from the environmental information acquisition unit while the rotating machine is operating, acquires the characteristic changes from the rotating machine information storage unit when the environmental information changes, and estimates an estimated winding capacitance corresponding to the changed environmental information; and a diagnosis unit that acquires the winding capacitance after the change in environmental information from the capacitance calculation unit and diagnoses an abnormality in the rotating machine by comparing the winding capacitance with the estimated winding capacitance.

[0042] With the above configuration, even in an environment where environmental information changes over time, if a change in capacitance occurs due to moisture absorption and release in the insulating coating, it is possible to correctly detect an abnormality due to contamination or deterioration of the insulating coating without falsely detecting an abnormality.

[0043] (2) The environmental information is the temperature, humidity, or atmospheric pressure around the winding. It is necessary to consider these factors that affect the change in capacitance of the insulating member.

[0044] (3) The rotating machine information storage unit estimates the humidity around the windings using the detected humidity value around the windings and information about the structure or material of the rotating machine. Alternatively, it estimates the temperature around the windings using the detected temperature value around the windings, the winding current flowing through the windings of the rotating machine, and information about the structure or material of the rotating machine. Even if it is not possible to directly measure the humidity or temperature around the windings, it is possible to obtain the necessary data by measuring it indirectly in this way.

[0045] (4) The rotating machine information storage unit calculates physical phenomena related to moisture absorption or desorption of the windings using the environmental information, which makes it possible to construct a winding state estimation unit that can estimate the estimated winding capacitance.

[0046] (5) The winding state estimator estimates the winding capacitance based on a model that includes reversible changes in winding capacitance due to moisture absorption and desorption phenomena in the windings. This makes it possible to determine that if the actually measured capacitance significantly deviates from the estimated value, this is due to an irreversible change in capacitance.

[0047] (6) The characteristic change is winding capacitance change delay information indicating the delay in the change of the winding capacitance and / or winding capacitance change rate information indicating the rate at which the winding capacitance changes. By using these data on the winding capacitance, it is possible to estimate the winding capacitance in detail.

[0048] (7) The abnormality diagnosis method according to the present invention also provides the same effects as the abnormality diagnosis device described above.

[0049] 3 Rotating machine, 6 Temperature sensor, 7 Humidity sensor, 8 Barometric pressure sensor 30 Abnormality diagnosis device, 301 Capacitance calculation unit, 302 Environmental information acquisition unit, 303 Rotating machine information storage unit, 304 Winding state estimation unit, 305 Diagnosis unit

Claims

1. An abnormality diagnosis device for a rotating machine comprising: a capacitance calculation unit that calculates a winding capacitance, which is the electrostatic capacitance of a winding of a rotating machine, based on a winding current flowing through the winding; an environmental information acquisition unit that acquires environmental information of an area in which the rotating machine is installed; a rotating machine information storage unit that stores characteristic changes in the winding capacitance in response to changes in the environmental information; a winding state estimation unit that acquires the environmental information when the rotating machine is operating from the environmental information acquisition unit, acquires the characteristic change from the rotating machine information storage unit when the environmental information changes, and estimates an estimated winding capacitance corresponding to the changed environmental information; and a diagnosis unit that acquires the winding capacitance after the environmental information has changed from the capacitance calculation unit, and diagnoses an abnormality in the rotating machine by comparing the winding capacitance with the estimated winding capacitance.

2. An abnormality diagnosis device according to claim 1, wherein the environmental information is any one of the temperature, humidity, or atmospheric pressure around the winding.

3. An abnormality diagnosis device as claimed in claim 2, characterized in that the rotating machine information storage unit estimates the humidity around the winding using the humidity detection value around the winding and information about the structure or material of the rotating machine.

4. An abnormality diagnosis device as claimed in claim 2, characterized in that the rotating machine information storage unit estimates the temperature around the winding using the temperature detection value around the winding, the winding current flowing through the winding of the rotating machine, and information relating to the structure or material of the rotating machine.

5. An abnormality diagnosis device according to claim 2, characterized in that the rotating machine information storage unit calculates physical phenomena relating to moisture absorption or release of the windings using the environmental information.

6. An abnormality diagnosis device as claimed in claim 2, characterized in that the winding state estimation unit estimates the estimated winding capacitance based on a model including a reversible change in the winding capacitance associated with moisture absorption and release phenomena of the winding.

7. An abnormality diagnosis device as claimed in claim 2, characterized in that the characteristic change is winding capacitance change delay information indicating a delay in the change in the winding capacitance and / or winding capacitance change rate information indicating the rate of change in the winding capacitance.

8. A method for diagnosing an abnormality in a rotating machine, comprising: calculating a winding capacitance, which is the electrostatic capacitance of a winding of a rotating machine, based on a winding current flowing through the winding; acquiring environmental information of an area in which the rotating machine is installed; storing characteristic changes in the winding capacitance in response to changes in the environmental information; acquiring the environmental information while the rotating machine is operating, acquiring the characteristic changes when the environmental information changes, and estimating an estimated winding capacitance corresponding to the changed environmental information; acquiring the winding capacitance after the environmental information has changed, and diagnosing an abnormality in the rotating machine by comparing the winding capacitance with the estimated winding capacitance.

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