CN115885469A

CN115885469A - Abnormality diagnosis device, power conversion device, and abnormality diagnosis method

Info

Publication number: CN115885469A
Application number: CN202080102292.3A
Authority: CN
Inventors: 宫内俊彦; 三好将仁; 开田健; 佐野壮太; 菅原烈
Original assignee: Mitsubishi Electric Corp
Current assignee: Mitsubishi Electric Corp
Priority date: 2020-06-29
Filing date: 2020-06-29
Publication date: 2023-03-31
Also published as: JPWO2022003758A1; WO2022003758A1; JP6824494B1; DE112020007369T5; KR20230010708A

Abstract

An abnormality diagnosis device (30) detects a current flowing through a motor (2) driven by pulse width modulation control of a power conversion device (100) and performs frequency analysis, and a determination unit (34) determines an abnormality of the motor (2) based on a spectral peak of at least one sideband component of a modulation wave obtained from the analysis result. The abnormality diagnosis device (30) is provided with a frequency setting unit (33), wherein the frequency setting unit (33) sets a noise frequency (fn alpha) in the current in advance, and a determination unit (34) estimates whether or not there is noise interference in the spectral peak of the sideband component based on the frequency of the sideband component and the set noise frequency (fn alpha), thereby performing abnormality determination.

Description

Abnormality diagnosis device, power conversion device, and abnormality diagnosis method

Technical Field

The present invention relates to an abnormality diagnostic device for diagnosing an abnormality of a motor, a power conversion device that drives the motor and includes the abnormality diagnostic device, and an abnormality diagnostic method for the motor.

Background

In order to diagnose an abnormality of the motor during operation, for example, in the conventional method described in patent document 1, a frequency analysis is performed on a current flowing through the motor, and the abnormality is diagnosed from a frequency component appearing as a sideband of a power supply frequency component. Then, in the current flowing through the motor, by subtracting waveforms of two cycles having the same phase from each other, the noise component is cancelled and the pulsation component occurring when the rotor is abnormal is extracted, thereby performing the abnormality diagnosis.

Further, in the conventional method described in patent document 2, in the case of driving the induction motor by PWM (pulse width modulation) control of the inverter, a noise component generated in a frequency spectrum of vibration is removed, and the frequency spectrum from which the noise component is removed is subjected to inverse fourier transform to obtain a vibration acceleration waveform picked up by the induction motor in the form of removing the noise component.

Documents of the prior art

Patent document

Patent document 1: japanese patent laid-open No. 2003-274691

Patent document 2: japanese patent laid-open No. 2016-116251

Disclosure of Invention

Technical problem to be solved by the invention

In the conventional abnormality diagnosis described in patent document 1, only noise components having the same phase and the same magnitude can be canceled out in each cycle in a current flowing through the motor. However, the noise components are different depending on the driving conditions or abnormal states of the motor, and the noise components that cannot be reduced remain, and it is difficult to extract the frequency components for abnormality diagnosis with high reliability.

In the conventional abnormality diagnosis described in patent document 2, since a noise signal, which is an acceleration component due to a carrier frequency, is avoided, other noise components, particularly noise components in a low frequency region, remain, and it is difficult to perform abnormality diagnosis with high reliability.

The present application discloses a technique for solving the above-described problem, and an object thereof is to provide an abnormality diagnosis device that diagnoses an abnormality of a motor driven by pulse width modulation control of a power conversion device with high reliability by preventing the influence of noise including a low frequency region.

Further, an object of the present application is to provide a power conversion apparatus including such an abnormality diagnostic apparatus, diagnosing an abnormality of a motor and driving the motor with high reliability.

Further, an object of the present invention is to provide an abnormality diagnosis method for diagnosing an abnormality of a motor driven by pulse width modulation control of a power conversion device with high reliability by preventing an influence of noise including a low frequency region.

Means for solving the problems

The abnormality diagnostic device disclosed in the present application diagnoses an abnormality of a motor driven by pulse width modulation control of a power conversion device. The abnormality diagnostic device includes: a detection unit for detecting a current flowing through the motor; an analysis section for performing frequency analysis on the current detected by the detection section and outputting an analysis result;

a determination unit that determines an abnormality of the motor based on a spectral peak of at least one sideband component of the modulation wave obtained from the analysis result; and a frequency setting unit for setting a noise frequency in the current in advance. The determination unit estimates the presence or absence of noise interference in the spectral peak of the sideband component based on the frequency of the sideband component and the set noise frequency, and determines an abnormality of the motor.

Further, the power conversion device disclosed in the present application includes a power conversion portion that converts direct current into alternating current and supplies power to the motor, and a control device that performs output control of the power conversion portion by the pulse width modulation control, and the control device includes the abnormality diagnostic device to diagnose an abnormality of the motor.

Further, an abnormality diagnostic method disclosed in the present application is a method of diagnosing an abnormality of a motor driven by pulse width modulation control of a power conversion apparatus, including: a first step of calculating a greatest common divisor of two or more frequencies including a modulation wave frequency among three frequencies used for pulse width modulation control, that is, the modulation wave frequency, a carrier frequency, and a sampling frequency at which the modulation wave is sampled, and setting a frequency of an integral multiple of the greatest common divisor as a noise frequency; a second step of detecting a current flowing through the motor and performing frequency analysis; and a third step of determining an abnormality of the motor based on a spectral peak of a sideband component of the modulation wave obtained from the analysis result of the second step. Then, in the third step, it is estimated whether or not there is noise interference in the spectral peak of the sideband component based on the frequency of the sideband component and the noise frequency set in the first step.

Further, an abnormality diagnostic method disclosed in the present application is a method of diagnosing an abnormality of a motor driven by pulse width modulation control of a power conversion apparatus, including: a first step of setting, as a noise frequency, a frequency that is shifted from a modulation wave frequency for pulse width modulation control by an integral multiple of a frequency of an alternating-current power supply to which the power conversion device is connected; a second step of detecting a current flowing through the motor and performing frequency analysis; a third step of determining an abnormality of the motor based on a spectral peak of a sideband component of the modulated wave obtained from the analysis result of the second step. Then, in the third step, the presence or absence of noise interference in the spectral peak of the sideband component is estimated based on the frequency of the sideband component and the noise frequency set in the first step.

Effects of the invention

According to the abnormality diagnostic device disclosed in the present application, it is possible to diagnose an abnormality of the motor driven by the pulse width modulation control of the power conversion device with high reliability while preventing the influence of noise including a low frequency region.

Further, according to the power conversion device disclosed in the present application, it is possible to prevent the influence of noise including a low frequency region and diagnose abnormality of the motor driven by the pulse width modulation control of the power conversion device with high reliability.

Further, according to the abnormality diagnosis method disclosed in the present application, it is possible to prevent the influence of noise including a low frequency region and diagnose the abnormality of the motor driven by the pulse width modulation control of the power conversion device with high reliability.

Drawings

Fig. 1 is a diagram showing the configurations of a power conversion device and an abnormality diagnosis device according to embodiment 1.

Fig. 2 is a block diagram showing a schematic configuration of the abnormality diagnostic device according to embodiment 1.

Fig. 3 is a block diagram showing a hardware configuration of a part of the abnormality diagnosis device according to embodiment 1.

Fig. 4 is a diagram illustrating a spectrum waveform of a current in the abnormality diagnostic device according to embodiment 1.

Fig. 5 is a waveform diagram illustrating pulse width modulation control of the power conversion device according to embodiment 1.

Fig. 6 is a flowchart for explaining the operation of the abnormality diagnostic device according to embodiment 1.

Fig. 7 is a block diagram showing a schematic configuration of the abnormality diagnostic device according to embodiment 2.

Fig. 8 is a block diagram showing a schematic configuration of the abnormality diagnostic device according to embodiment 3.

Fig. 9 is a diagram showing the configurations of a power conversion device and an abnormality diagnosis device according to embodiment 4.

Fig. 10 is a block diagram showing a schematic configuration of the abnormality diagnostic device according to embodiment 4.

Fig. 11 is a waveform of a spectrum of a current for explaining a noise frequency according to embodiment 4.

Fig. 12 is a flowchart for explaining the operation of the abnormality diagnostic device according to embodiment 4.

Fig. 13 is a diagram showing the configurations of a power conversion device and an abnormality diagnosis device according to embodiment 5.

Fig. 14 is a diagram showing a carrier wave according to another example of embodiment 5.

Fig. 15 is a schematic diagram of a current spectrum waveform for explaining the effect according to embodiment 6.

Detailed Description

Embodiment 1.

As shown in fig. 1, the power conversion device 100 is connected between an ac power supply 1, which is a commercial power supply, and a motor 2, and controls driving of the motor 2. The power conversion apparatus 100 includes a power conversion unit 10 and a control device 20 that controls the output of the power conversion unit 10.

Further, a current i flowing from the power conversion unit 10 to the motor 2 is detected by the current sensor 3, and the abnormality diagnosis device 30 diagnoses an abnormality of the motor 2 based on the current i. The current sensors 3 may be built in the power conversion device 100 or may be externally mounted, and the number and positions of the current sensors 3 are not limited to those shown in the drawings.

The power conversion unit 10 includes a converter unit 10A, an inverter unit 10B, and a smoothing capacitor 10C, which are connected via a dc bus. The converter unit 10A converts ac power from the ac power supply 1 into dc power and outputs the dc power to the smoothing capacitor 10C, and the inverter unit 10B converts the dc power of the smoothing capacitor 10C into ac power and supplies the ac power to the motor 2.

In this case, the ac power supply 1, the motor 2, and the power conversion device 100 have a three-phase configuration, but are not limited thereto.

The converter unit 10A is configured by a three-phase bridge circuit including six diodes Da, and the input/output line of each phase is connected to the ac power supply 1. The inverter unit 10B is configured by a three-phase bridge circuit including six switching elements Q each having a diode Db connected in inverse parallel thereto, and the input/output line of each phase is connected to the motor 2. For the switching element Q, for example, an IGBT (Insulated Gate Bipolar Transistor), a MOSFET (Metal-oxide-semiconductor Field Effect Transistor), or the like is used.

The ac power from the ac power supply 1 is rectified by the converter unit 10A, converted into dc power, and output to the smoothing capacitor 10C. The control device 20 generates a gate signal G to each switching element Q of the inverter unit 10B by pulse width modulation control (PWM control), and controls the switching elements Q to be turned on and off, thereby outputting desired electric power from the power conversion unit 10 to the motor 2. Thereby, the power conversion device 100 drives the motor 2.

The configurations of the converter unit 10A and the inverter unit 10B are not limited to those shown in the drawings. In this case, although the power conversion unit 10 is provided with the converter unit 10A and connected to the ac power supply 1, the converter unit 10A may be omitted as long as the inverter unit 10B that converts dc power into ac power and supplies the ac power to the motor 2 is provided.

The abnormality diagnostic device 30 acquires the frequencies of the modulation wave (fundamental wave), the carrier wave, and the clock signal (CLK) for sampling, that is, the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs, which are used by the control device 20 in the PWM control of the power conversion unit 10. Then, abnormality diagnosis apparatus 30 performs frequency analysis on current i flowing from power conversion unit 10 to motor 2, and diagnoses an abnormality of motor 2.

Fig. 2 is a block diagram showing a schematic configuration of the abnormality diagnostic device 30. As shown in fig. 2, the abnormality diagnostic device 30 includes a detection unit 31 for detecting a current i flowing through the motor 2, an analysis unit 32 for performing frequency analysis on the current i, a frequency setting unit 33 for setting in advance a frequency of noise in the current i (noise frequency fn α), and a determination unit 34 for determining an abnormality of the motor 2.

The detection unit 31 acquires the output of the current sensor 3 and detects the waveform of the current of at least one phase current i flowing through the motor 2. The analysis unit 32 performs frequency analysis based on the detected current i, and derives an analysis result 32a including a spectrum waveform. The frequency setting unit 33 acquires the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs, calculates the greatest common divisor GCD thereof, and sets the greatest common divisor GCD and its integer multiple as the noise frequency fn α.

The determination unit 34 acquires the spectral peak of the sideband component of the modulated wave from the analysis result 32a of the analysis unit 32, determines an abnormality of the motor 2 based on the spectral peak, and outputs a determination result 34a. At this time, the presence or absence of noise interference in the spectral peak of the sideband component of the modulated wave is estimated based on the noise frequency fn α, and the sideband component estimated to have noise interference is excluded from the abnormality determination.

In addition, the hardware constituting the abnormality diagnostic device 30 may use a known dedicated device for frequency analysis in combination with, for example, the processor 5 and the storage device 6 shown in fig. 3.

The processor 5 executes a control program input from the storage device 6. The storage device 6 includes a secondary storage device and a volatile storage device. The control program is input from the secondary storage device to the processor 5 via the volatile storage device. The processor 5 outputs data such as the operation result to the volatile storage device of the storage device 6, and stores the data in the auxiliary storage device via the volatile storage device as necessary.

When the motor 2 has a sign of abnormality, the sideband component of the modulation wave as a specific frequency component is added to the current i. For example, if the rotational frequency of the rotor is fr due to vibration caused by dynamic eccentricity or abnormality of the rotor, the sideband component of | k1 · f0 ± k2 · fr | increases based on the frequency (f 0 ± fr). Here, k1 and k2 are positive integers, respectively.

When the conductor bars of the cage rotor are damaged, if the slip is s, the sideband component of the frequency ((1 ± 2 s) · f 0) increases.

In addition, when a scratch is formed on the bearing, the sideband component deviating from the modulated wave frequency f0 is increased only by the characteristic frequency determined by the position of the scratch and the shape of the bearing. For example, the characteristic frequency of damage to the outer ring of the bearing is N · fr (1-dcos θ/D)/2.

Wherein N, D, D, theta are the number of balls in the bearing, the diameter of the balls, the pitch diameter and the contact angle respectively.

Hereinafter, simply referred to as a sideband or a sideband component means a sideband of a modulated wave or a sideband component of a modulated wave.

Fig. 4 is a diagram illustrating a spectrum waveform of the current i in the abnormality diagnostic device 30 when there is an abnormality in the motor 2.

As shown in fig. 4, a plurality of

frequency spectrums

41, 42 appear on both sides of the frequency spectrum 40 of the modulated wave frequency f 0. In this case, at frequencies (f 0 ± fr) shifted from the rotation frequency fr on both sides of the modulated wave frequency f0, a spectrum 41 of the sideband component of the modulated wave appears, and a spectrum 42 of the noise component caused by the switching operation of the inverter unit 10B also appears.

In fig. 4, the spectrum 41 of the sideband component and the spectrum 42 of the noise component are neither close to nor overlap, and the spectrum 41 of the sideband component showing a sign of abnormality can be identified and detected separately from the spectrum 42 of the noise component. When the conditions change, the spectrum 42 of the noise component may approach the spectrum 41 of the sideband component indicating a sign of an abnormality, and noise interference (not shown) may occur at a peak of the spectrum.

In this case, although only spectrum 41 is shown in the case where k1= k2=1 in frequencies | k1 · f0 ± k2 · fr | described above, if a spectrum having a small peak is included, spectrum 41 of a combination other than k1= k2=1 may appear in general.

Fig. 5 is a waveform diagram illustrating PWM control of the power conversion apparatus 100.

As shown in fig. 5, in the PWM control, the modulated wave M is compared with the carrier wave Cr to generate the gate signal G. At this time, the modulated wave M is sampled at the timing of the clock signal (CLK), the value of the modulated wave M is temporarily stored, and compared with the carrier wave Cr.

If the carrier frequency fc or the sampling frequency fs is not a multiple of the modulation wave frequency f0, a spectrum 42 of a noise component caused by the switching operation of the inverter section 10B is generated at a frequency of the greatest common divisor of the values thereof and an integral multiple thereof.

Therefore, by calculating the greatest common divisor of the two frequencies, or all three frequencies, the carrier frequency fc or the sampling frequency fs and the modulated wave frequency f0, it is possible to grasp in advance which frequency may cause noise.

In this case, the frequency setting unit 33 acquires the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs, calculates the greatest common divisor GCD of these frequencies, and sets the greatest common divisor GCD and its integer multiple as the noise frequency fn α. When the greatest common divisor GCD is the modulation frequency f0, the noise frequency fn α is not set.

Next, the operation of the abnormality diagnostic device 30 will be described based on the flowchart shown in fig. 6.

First, abnormality diagnostic device 30 detects, by detecting unit 31, the current waveform of current i of at least one phase of currents i flowing from power converting unit 10 of power converting device 100 to motor 2. In this case, the detection unit 31 detects current waveforms of three phases. The current sensor 3 may detect each phase current i of three phases, or may detect the amount of two phases and obtain the current of the remaining phase by calculation (step S1).

Next, the analysis unit 32 performs frequency analysis based on the detected current i, and derives an analysis result 32a including a spectrum waveform (step S2).

On the other hand, the frequency setting unit 33 acquires the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs from the control device 20 of the power conversion device 100 (step S3). Then, the frequency setting unit 33 calculates the greatest common divisor GCD of the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs, and further calculates an integer multiple of the greatest common divisor GCD (step S4).

When the greatest common divisor GCD is not the modulation wave frequency f0, the calculated greatest common divisor GCD and its integer multiple are set as the noise frequency fn α. In addition, the noise frequency fn α is set within a range not exceeding the measurable region.

The greatest common divisor GCD is a value below fc/2. Further, under the normal control condition of the power conversion apparatus 100, the greatest common divisor GCD becomes a value lower than (fc-4 f 0). Therefore, the set noise frequency fn α includes a frequency of a frequency domain lower than fc/2, and is usually set to include a frequency lower than (fc-4 f 0) (step S5).

The determination unit 34 estimates the presence or absence of noise interference in the spectral peak of the sideband component of the modulated wave based on the analysis result 32a derived in step S2 and the noise frequency fn α set in step S5. Specifically, it is determined whether or not the frequency of the sideband component (spectrum 41) of the modulated wave overlaps or is close to the noise frequency fn α to estimate that there is noise interference.

Since the sideband component (spectrum 41) of the modulated wave, which increases due to the abnormality sign of the motor 2, is the frequency component specified as described above, the determination unit 34 determines that the particular frequency component is overlapped with or close to the noise frequency fn α by comparing the frequency with the noise frequency fn α to be monitored, and when the difference is smaller than the set value. The set value is set to a few Hz, for example 2Hz. When the difference is equal to or greater than the set value, the peak of the spectrum 41 is not affected by the noise component, and thus noise interference is not generated (step S6).

If the sideband component estimated to be noisy exists in step S6, the determination unit 34 excludes the sideband component from the object of the abnormality diagnosis (step S7), determines the abnormality of the motor 2 from the other sideband components, and outputs the determination result 34a. At this time, if the spectral peak of the sideband component exceeds a preset reference value, it is determined to be abnormal. The reference value is set based on, for example, the spectral peak of the modulated wave frequency f0 (step S8).

In step S5, when the greatest common divisor GCD is the modulation wave frequency f0, the frequency setting unit 33 does not set the noise frequency fn α, and the process proceeds to step S8. Then, the determination unit 34 determines an abnormality of the motor 2 based on the spectral peak of the sideband component.

As described above, the abnormality diagnostic device 30 according to this embodiment sets the frequency of the noise component (noise frequency fn α) in the current i flowing through the motor 2 in advance, and diagnoses an abnormality of the sideband component of the modulated wave obtained by frequency analyzing the current i. Then, at the time of abnormality diagnosis, the presence or absence of noise interference in the spectral peak of the sideband component is estimated from the frequency of the sideband component and the noise frequency fn α, the sideband component estimated to have noise interference is excluded, and abnormality is determined from the spectral peak of the remaining sideband component.

Therefore, it is possible to prevent erroneous diagnosis caused by the influence of noise including the low frequency region, and to perform abnormality diagnosis of the motor 2 with high reliability.

Further, since the frequency of the noise frequency fn α is set to the greatest common divisor GCD of the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs for PWM control and an integral multiple thereof, it is possible to reliably prevent the influence of noise components including a low frequency region.

Further, when the difference between the frequency of the sideband component and the set noise frequency fn α is smaller than the set value and the two are close to each other, the sideband component is estimated as having noise interference, and therefore the noise interference can be estimated with high reliability.

Although noise frequency fn α is set within a range not exceeding the measurable range, it may be set only within a frequency range lower than 1/2 of carrier frequency fc.

Further, when the greatest common divisor GCD calculated by the frequency setting unit 33 is the modulated wave frequency f0, the noise frequency fn α is not set, but there is no problem even if the modulated wave frequency f0 and its integral multiple are set as the noise frequency fn α as they are, because it is not a frequency component close to the sideband component of the modulated wave.

Further, although carrier Cr based on a triangular wave is illustrated as the PWM control of power conversion device 100, carrier Cr is not limited to a triangular wave, and a sinusoidal wave may be used.

In addition, in order to improve the voltage use efficiency, a third harmonic may be superimposed on the modulated wave M, and in this case, the value of the greatest common divisor GCD does not change, and the noise frequency fn α may be set similarly.

Embodiment 2.

Fig. 7 is a block diagram showing a schematic configuration of an abnormality diagnostic device 30A according to embodiment 2.

As shown in fig. 7, the abnormality diagnostic device 30A includes a detection unit 31, an analysis unit 32, a frequency setting unit 33, a determination unit 34, and a notification unit 35, as in embodiment 1.

When there is a sideband component estimated to be noisy, the determination unit 34 excludes the sideband component from the object of the abnormality diagnosis (see step S7 in fig. 6), and outputs a notification command 34b to the notification unit 35. Then, the notification unit 35 outputs a notification signal 35a for notifying the outside of the presence of noise interference. The other structures and operations are the same as those of embodiment 1.

In this embodiment, as in embodiment 1, it is possible to prevent erroneous diagnosis due to the influence of noise components including the low frequency region, and to perform abnormality diagnosis of the motor 2 with high reliability. In addition, at the time of diagnosis, the user is notified of the estimation of noise interference, and therefore, convenience is improved.

Even if there is a sideband component estimated to be noisy, the sideband component may be output only from the notification unit 35 without being excluded from the object of abnormality diagnosis. In this case, the user is notified to promote the attention, and the user can consider the influence of the noise component with respect to the determination result 34a from the abnormality diagnostic device 30A, and as a result, the erroneous diagnosis can be prevented.

Embodiment 3.

Fig. 8 is a block diagram showing a schematic configuration of an abnormality diagnostic device 30B according to embodiment 3.

As shown in fig. 8, the abnormality diagnostic device 30B includes a detection unit 31, an analysis unit 32, a frequency setting unit 33, a determination unit 36, a noise detection unit 37, a storage unit 38, and a switch 39, as in embodiment 1. The configuration and operation of the judgment unit 36, the noise detection unit 37, the storage unit 38, and the switch 39 are the same as those of embodiment 1.

As in embodiment 1, the detection unit 31 acquires the output of the current sensor 3 and detects the current waveform of the current i flowing through at least one phase of the motor 2. The analysis unit 32 performs frequency analysis based on the detected current i, and derives an analysis result 32a including a spectrum waveform. The frequency setting unit 33 acquires the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs, calculates the greatest common divisor GCD thereof, and sets the greatest common divisor GCD and its integer multiple as the noise frequency fn α in a range exceeding the measurable region.

Then, when the motor 2 is normally operated, the noise detection unit 37 detects the magnitude of noise at the noise frequency fn α of the current i, for example, the value of the peak of the frequency spectrum of the noise component from the analysis result 32a of the analysis unit 32, and stores the detection result in the storage unit 38. The noise detection in the noise detection portion 37 is performed in advance during the normal operation of the motor 2 before the abnormality diagnosis of the motor 2.

The switch 39 selectively switches the output destination of the analysis result 32a of the analysis section 32 to one of the noise detection section 37 and the determination section 36. When the motor 2 is diagnosed for an abnormality, the selection determination unit 36 selects the noise detection unit 37 when noise is detected in advance during a normal operation of the motor 2.

The determination unit 36 acquires the spectral peak of the sideband component of the modulated wave from the analysis result 32a of the analysis unit 32, determines an abnormality of the motor 2 based on the spectral peak, and outputs the determination result 36a. At this time, the presence or absence of noise interference in the spectral peak of the sideband component of the modulated wave is estimated based on the noise frequency fn α. Specifically, as in embodiment 1, when the difference between the frequency of the sideband component of the modulated wave and the noise frequency fn α is smaller than a set value, it is determined that the frequency of the sideband component overlaps or is close to the noise frequency fn α, and it is estimated that there is noise interference.

Next, the determination unit 36 extracts the magnitude of noise at the noise frequency fn α, which is a noise interference source, from the storage unit 38. Then, regarding the sideband component of the noise interference destination, an abnormality of the motor 2 is determined based on the spectral peak of the sideband component and the magnitude of the extracted noise. Specifically, for example, if a value obtained by subtracting the spectral peak of the noise component from the value of the spectral peak of the sideband component exceeds a preset reference value, it is determined that the noise component is abnormal. The reference value is set based on, for example, the spectral peak of the modulated wave frequency f 0.

As described above, the abnormality diagnostic device 30B according to this embodiment sets the frequency of the noise component (noise frequency fn α) in the current i flowing through the motor 2 in advance, and performs abnormality diagnosis on the sideband component of the modulated wave obtained by frequency-analyzing the current i. Before the abnormality diagnosis, the abnormality diagnostic device 30B detects the magnitude of noise at the noise frequency fn α of the current i from the analysis result 32a of the analyzer 32 during the normal operation of the motor 2, and stores the detection result. Then, at the time of abnormality diagnosis, the presence or absence of noise interference in the spectral peak of the sideband component is estimated based on the frequency of the sideband component and the noise frequency fn α, and the spectral peak of the sideband component estimated to have noise interference is used for abnormality determination in consideration of the magnitude of noise.

Therefore, as in embodiment 1, it is possible to prevent erroneous diagnosis due to the influence of noise components including the low frequency region, and to perform abnormality diagnosis of the motor 2 with high reliability. Further, since the sideband component estimated to be noisy is also used for abnormality diagnosis without being excluded, it is possible to reliably monitor the sideband component of the monitoring target used for abnormality diagnosis and to reliably diagnose an abnormality of the motor 2.

The noise detection in the noise detection unit 37 is obtained from the analysis result 32a of the current i during the normal operation of the motor 2, but may be obtained from a result obtained by detecting the output voltage to the motor 2 and performing frequency analysis. In this case, it is not necessary to detect the voltage particularly at the time of normal operation of the motor 2, and the magnitude corresponding to the noise at the normal operation can be calculated from the frequency analysis result of the detected voltage at the noise frequency fn α of the current i. The calculation result may be used by the determination unit 36 without being stored in the storage unit 38, or the storage unit 38 may be omitted.

The determination unit 36 may use both the frequency analysis result of the detected voltage and the noise detection result obtained from the analysis result 32a of the current i when the motor 2 is operating normally, thereby improving the accuracy of the abnormality determination.

Further, in embodiment 3, the above-described embodiment 2 may be applied to the installation notification unit 35 to notify the user of the estimation of the presence of noise interference.

Embodiment 4.

Fig. 9 is a configuration diagram illustrating a power conversion device 100 and an abnormality diagnosis device 30C according to embodiment 4.

As shown in fig. 9, the power converter 100 is configured in the same manner as in embodiment 1, and includes a power converter 10 and a controller 20 that controls the output of the power converter 10. Further, a current i flowing from the power conversion unit 10 to the motor 2 is detected by the current sensor 3, and the abnormality diagnosis device 30 diagnoses an abnormality of the motor 2 based on the current i.

The power conversion unit 10 includes a converter unit 10A, an inverter unit 10B, and a smoothing capacitor 10C, which are connected via a dc bus. In this embodiment, the converter unit 10A cannot be omitted, and converts the ac power from the ac power supply 1 into dc power and outputs the dc power to the smoothing capacitor 10C. The inverter unit 10B converts the dc power of the smoothing capacitor 10C into ac power and supplies the ac power to the motor 2.

In this case, in the power conversion unit 10, the ac power supply 1, the motor 2, and the power conversion device 100 have a three-phase configuration, but the configuration is not limited to this.

The ac power from the ac power supply 1 is rectified by the converter unit 10A, converted into dc power, and output to the smoothing capacitor 10C. Control device 20 generates gate signal G to each switching element Q of inverter unit 10B by PWM control, and controls switching elements Q to be turned on and off, thereby outputting desired power from power conversion unit 10 to motor 2.

Thereby, the power conversion device 100 drives the motor 2. Then, the dc voltage of the smoothing capacitor 10C and the ac voltage output to the motor 2 fluctuate slightly at the frequency of the ac power supply 1 and its integral multiple, and a sideband component (noise component) deviating from the modulation wave frequency f0 is generated in the current i.

Abnormality diagnostic device 30C acquires the frequency of the modulated wave (modulated wave frequency f 0) used by control device 20 for PWM control of power conversion unit 10 and the frequency of ac power supply 1 (ac power supply frequency fac). Then, abnormality diagnostic device 30C performs frequency analysis on current i flowing from power conversion unit 10 to motor 2 to diagnose abnormality of motor 2.

Fig. 10 is a block diagram showing a schematic configuration of the abnormality diagnostic device 30C. As shown in fig. 10, the abnormality diagnostic device 30C includes a detection unit 31 for detecting a current i flowing through the motor 2, an analysis unit 32 for performing frequency analysis on the current i, a frequency setting unit 33A for setting in advance a frequency of noise in the current i (noise frequency fn β), and a determination unit 34 for determining an abnormality of the motor 2.

The detection unit 31 and the analysis unit 32 operate in the same manner as in the above-described embodiment 1.

The frequency setting unit 33A acquires the modulated wave frequency f0 and the ac power supply frequency fac, and calculates the following frequency to set the noise frequency fn β. Wherein m and n are positive integers respectively.

|m·fac±n·f0|

That is, noise frequency fn β is an absolute value of a value obtained by deviating from an integer multiple of modulation wave frequency f0 by an integer multiple of ac power supply frequency fac.

The determination unit 34 acquires the spectral peak of the sideband component of the modulated wave from the analysis result 32a of the analysis unit 32, determines an abnormality of the motor 2 based on the spectral peak, and outputs a determination result 34a. At this time, the presence or absence of noise interference in the spectral peak of the sideband component of the modulated wave is estimated based on the noise frequency fn β, and the sideband component estimated to have noise interference is excluded from the abnormality determination.

Fig. 11 is a spectrum waveform of a current i for explaining a noise frequency.

As shown in fig. 11, when the modulated wave frequency f0 and the ac power frequency fac are 50Hz and 60Hz, respectively, a frequency spectrum of a noise component appears at frequencies that are multiples of the modulated wave frequency f0 (100hz, 150hz, 200hz) and at frequencies 10hz,70hz,110hz, and 170hz other than the frequencies. If the frequencies of noise components other than the multiples of the modulated wave frequency f0 are expressed by the modulated wave frequency f0 (50 Hz) and the AC power frequency fac (60 Hz), respectively

10Hz＝fac-f0

70Hz＝2·fac-f0

110Hz＝fac+f0

170Hz＝2·fac+f0

And satisfies the above-mentioned operational expression of the noise frequency fn beta.

Next, the operation of the abnormality diagnostic device 30C will be described based on the flowchart shown in fig. 12.

First, in the abnormality diagnosis device 30C, as in the above-described embodiment 1, the detection unit 31 detects the current waveform of the current i of at least one phase of the currents i flowing from the power conversion unit 10 of the power conversion device 100 to the motor 2 (step S1), and the analysis unit 32 performs frequency analysis based on the detected current i to derive the analysis result 32a including the spectrum waveform (step S2).

On the other hand, frequency setting unit 33A acquires modulated wave frequency f0 and ac power supply frequency fac (step SS 3).

Then, the frequency setting unit 33A performs the following calculation as described above (step SS 4),

|m·fac±f0|

and set it as the noise frequency fn β. In addition, the noise frequency fn β includes a case where m = n =1, and is set within a range not exceeding the measurable region.

When m = n =1, i.e. (fac ± f 0) is a value lower than fc/2. Further, under the normal control condition of the power conversion apparatus 100, (fac ± f 0) becomes a value lower than (fc-4 f 0). Therefore, the set noise frequency fn β contains a frequency of a frequency domain lower than fc/2, and is usually set to contain a frequency lower than (fc-4 f 0) (step S5).

The determination unit 34 estimates the presence or absence of noise interference in the spectral peak of the sideband component of the modulated wave based on the analysis result 32a derived in step S2 and the noise frequency fn β set in step S5. Specifically, it is determined whether or not the frequency of the sideband component (spectrum 41) of the modulated wave overlaps or is close to the noise frequency fn β, and it is estimated that there is noise interference. In this case, as in embodiment 1, the determination unit 34 determines that there is noise interference by comparing the frequency of the specific frequency component (sideband component) that increases due to the abnormality sign to the noise frequency fn β, and determining that the frequency component overlaps or approaches when the difference is smaller than a set value. In this case, the set value is set to several Hz, for example, 2Hz (step S6).

If the sideband component estimated to be noisy exists in step S6, the determination unit 34 excludes the sideband component from the object of the abnormality diagnosis (step S7), and determines the abnormality of the motor 2 from the other sideband components. At this time, if the spectral peak of the sideband component exceeds a preset reference value, it is determined to be abnormal. The reference value is set based on, for example, the spectral peak of the modulated wave frequency f0 (step S8).

As described above, the abnormality diagnostic device 30C according to this embodiment sets the frequency of the noise component (noise frequency fn β) in the current i flowing through the motor 2 in advance, and diagnoses an abnormality of the sideband component of the modulated wave obtained by frequency analyzing the current i. Then, at the time of abnormality diagnosis, the presence or absence of noise interference in the spectral peak of the sideband component is estimated from the frequency of the sideband component and the noise frequency fn β, the sideband component estimated to have noise interference is excluded, and abnormality is determined from the spectral peak of the remaining sideband component.

Therefore, it is possible to prevent erroneous diagnosis due to the influence of noise components including noise components in the low frequency region, that is, the modulation wave frequency f0 and the ac power supply frequency fac in this case, and to perform abnormality diagnosis of the motor 2 with high reliability.

Further, when the difference between the frequency of the sideband component and the set noise frequency fn β is smaller than the set value and the two are close to each other, it is estimated that the sideband component has noise interference, and therefore, the noise interference can be estimated with high reliability.

In embodiment 4, the above-described embodiment 2 may be applied to the installation notification unit 35 to notify the user of the estimation of the presence of noise interference.

Further, the above-described embodiment 3 can be applied to this embodiment 4. In this case, the noise detection unit 37, the storage unit 38, and the switch 39 are provided, and the magnitude of the noise at the noise frequency fn β of the current i is detected and stored in advance before the abnormality diagnosis and during the normal operation of the motor 2. Then, at the time of abnormality diagnosis, the presence or absence of noise interference in the spectral peak of the sideband component is estimated based on the frequency of the sideband component and the noise frequency fn β, and the spectral peak of the sideband component estimated to have noise interference is used for abnormality determination in consideration of the magnitude of noise.

This makes it possible to reliably monitor the sideband component of the monitoring target for the abnormality diagnosis and to reliably diagnose the abnormality of the motor 2.

In the case of applying embodiment 3 described above, the detection of the noise by the noise detection unit 37 may be obtained from the result of frequency analysis performed by detecting the line-to-line voltage output to the motor 2 or the dc voltage of the smoothing capacitor 10C. In this case, it is not necessary to detect the voltage particularly at the time of normal operation of the motor 2, and the magnitude of the noise corresponding to the noise at the normal operation can be calculated from the frequency analysis result of the detected voltage at the noise frequency fn β of the current i. The calculation result may not be stored in the storage unit 38 and may be used, or the storage unit 38 may be omitted.

Further, both the frequency analysis result of the detected voltage and the detection result of the noise obtained from the analysis result 32a of the current i when the motor 2 is normally operated may be used, thereby improving the accuracy of the abnormality determination.

In embodiment 4, the frequency setting unit 33A acquires the modulated wave frequency f0 and the ac power supply frequency fac and sets the noise frequency fn β, but the noise frequency fn α shown in embodiment 1 may be set at the same time. In this case, the frequency setting unit 33A acquires the modulated wave frequency f0, the carrier frequency fc, the sampling frequency fs, and the ac power supply frequency fac, calculates and sets the noise frequency fn α and the noise frequency fn β. Thereby, the influence of the noise component can be widely suppressed and the erroneous diagnosis can be prevented, and the abnormality diagnosis of the motor 2 can be further performed with high reliability.

Further, although the abnormality

diagnostic devices

30, 30A to 30C according to embodiments 1 to 4 are described as being located outside the power converter 100, they may be located inside the control device 20 of the power converter 100, and the same effects can be obtained, and transmission and reception of information necessary for setting the noise frequencies fn α and fn β are facilitated.

Embodiment 5.

Fig. 13 is a diagram showing the configuration of a power conversion device 100A according to embodiment 5.

As shown in fig. 13, power converter 100A is configured in the same manner as in embodiment 1, and includes power converter 10 and controller 20A that controls output of power converter 10. Control device 20A includes an inverter control unit 21 for output-controlling power conversion unit 10 and an abnormality diagnosis device 30D.

Further, a current i flowing from the power conversion unit 10 to the motor 2 is detected by the current sensor 3, and the abnormality diagnosis device 30 diagnoses an abnormality of the motor 2 based on the current i.

In control device 20A, inverter control unit 21 generates gate signals G to switching elements Q of inverter unit 10B by PWM control, and controls switching elements Q to be turned on and off, thereby outputting desired power from power conversion unit 10 to motor 2. Thereby, the power conversion device 100A drives the motor 2.

The abnormality diagnostic device 30D acquires the frequencies of the modulation wave (fundamental wave), the carrier wave, and the clock signal (CLK) for sampling, that is, the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs, which are used by the inverter control unit 21 in the PWM control. Then, abnormality diagnostic device 30D performs frequency analysis on current i flowing from power conversion unit 10 to motor 2 to diagnose an abnormality of motor 2.

The abnormality diagnostic device 30D includes a detection unit 31, an analysis unit 32, a frequency setting unit 33, and a determination unit 34, as in the abnormality diagnostic device 30 of embodiment 1, and the detection unit 31, the analysis unit 32, and the frequency setting unit 33 operate as in embodiment 1. The determination unit 34 estimates the presence or absence of noise interference in the spectral peak of the sideband component of the modulated wave based on the frequency of the sideband component and the noise frequency fn α, as in embodiment 1.

When there is no noise interference, the determination unit 34 diagnoses an abnormality of the motor 2 based on the spectral peak of the sideband component, as in embodiment 1. When there is noise interference, the determination unit 34 interrupts the abnormality diagnosis and transmits the notification signal SS1 to the inverter control unit 21.

Upon receiving the notification signal SS1 notifying the interruption of the abnormality diagnosis from the abnormality diagnostic device 30D, the inverter control unit 21 changes the carrier frequency fc, controls the output of the power conversion unit 10 by PWM control using the changed carrier frequency fc, and drives the motor 2. The carrier frequency fc can be easily changed without directly affecting the output of the power conversion portion 10.

In the abnormality diagnostic device 30D, each part operates again to continue the abnormality diagnosis. When the carrier frequency fc is changed, the noise frequency fn α changes, and thus the presence or absence of noise interference at the spectral peak of the sideband component also changes. Thus, the determination unit 34 can derive the estimation of the noise-free disturbance and diagnose the abnormality of the motor 2 based on the spectral peak of the sideband component.

The change of carrier frequency fc is preferably to derive the estimation of noise-free interference in determining unit 34 by a single change, but may be changed a plurality of times.

As described above, in the power conversion device 100A according to the present embodiment, the abnormality diagnostic device 30D in the control device 20A estimates the presence or absence of noise interference at the spectral peak of the sideband component based on the frequency of the sideband component and the noise frequency fn α at the time of abnormality diagnosis, and changes the carrier frequency fc if it is estimated that noise interference is present. Thereby, the greatest common divisor GCD of the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs is changed, and the frequency itself of the noise component caused by the PWM control is changed. Therefore, noise interference at the spectral peak of the sideband component can be eliminated, thereby reliably performing abnormality diagnosis. This prevents an erroneous diagnosis due to the influence of the noise component, and thus makes it possible to perform an abnormality diagnosis of the motor 2 with high reliability.

Although embodiment 5 has been described as changing the carrier frequency fc, it is sufficient to change at least one of the modulated wave frequency f0, the carrier frequency fc, and the sampling frequency fs, and the frequency used for calculating the greatest common divisor GCD.

When the carrier frequency fc is changed, the carrier frequency fc may be changed over time as shown in fig. 14. In this case, the carrier Cr is changed alternately repeating two frequencies (1/t 1), (1/t 2) based on two different periods t1, t 2. Not only the change per one cycle but also 3 or more kinds of frequencies can be changed in time. Further, the frequency may be varied discontinuously in a discrete manner.

When the carrier frequency fc or the sampling frequency fs is varied in time as described above, the frequency spectrum of the greatest common divisor GCD and its integral multiple frequency components is dispersed in a plurality of frequency domains. This makes it possible to reduce the spectral peak of the noise component, eliminate or suppress noise interference in the spectral peak of the sideband component, and diagnose an abnormality with high reliability.

Embodiment 6.

In embodiment 5, it is shown that, when the abnormality diagnosis is performed by the abnormality diagnosis device 30D, if it is estimated that there is noise interference at the spectral peak of the sideband component, at least one of the frequencies used for the calculation of the greatest common divisor GCD is changed.

In this embodiment, in the case of embodiment 5 described above, at least one of the frequencies used for the calculation of the greatest common divisor GCD is further changed so that the greatest common divisor GCD coincides with the modulated wave frequency f0, or so that the greatest common divisor GCD is 10Hz or less, preferably several Hz or less.

Fig. 15 is a schematic diagram of a current spectrum waveform for explaining the effect according to embodiment 6. Fig. 15 illustrates noise components in both cases where the greatest common divisor GCD of the modulated wave frequency f0, the carrier frequency fc, and the sampling frequency fs is several Hz and in the case of the comparative example exceeding 10 Hz.

As shown in fig. 15, in addition to the frequency spectrum 40 of the modulation wave frequency f0,

frequency spectra

42A and 42B of noise components caused by the switching operation of the inverter section 10B appear. Spectrum 42A is a comparative example in which the greatest common divisor GCD exceeds 10Hz, and spectrum 42B is a case in which the greatest common divisor GCD is several Hz. Spectrum 42B has a greater number of occurrences, but has lower spectral peaks, than spectrum 42A.

Thus, by reducing the greatest common divisor GCD to several Hz, the number of occurrences of the spectrum of the noise component increases, but the spectrum can be dispersed over a plurality of frequency domains, and the spectral peak can be reduced. Thus, noise interference at the spectral peak of the sideband component of the modulated wave can be eliminated or suppressed, and abnormality diagnosis can be performed with high reliability.

In embodiment 6, when at least one of the frequencies used for calculating the greatest common divisor GCD is changed so that the greatest common divisor GCD matches the modulated wave frequency f0, noise components assumed by the abnormality diagnostic device 30D are eliminated, and therefore it is possible to reliably diagnose an abnormality with high reliability.

Embodiment 7.

In this embodiment, an abnormality diagnostic device 30C shown in embodiment 4 is applied to an abnormality diagnostic device 30D in a power conversion device 100A shown in embodiment 5. In this case, abnormality diagnostic device 30C is provided in control device 20A of power conversion device 100A.

The abnormality diagnostic device 30C includes a detection unit 31, an analysis unit 32, a frequency setting unit 33A, and a determination unit 34, as in embodiment 4, and the detection unit 31, the analysis unit 32, and the frequency setting unit 33A operate as in embodiment 4.

The determination unit 34 estimates the presence or absence of noise interference in the spectral peak of the sideband component of the modulated wave based on the frequency of the sideband component and the noise frequency fn β, as in embodiment 4.

When there is no noise interference, the determination unit 34 performs an abnormality diagnosis of the motor 2 based on the spectral peak of the sideband component, as in embodiment 4. When there is noise interference, the determination unit 34 interrupts the abnormality diagnosis and transmits the notification signal SS1 to the inverter control unit 21.

When receiving a notification signal SS1 for notifying the interruption of the abnormality diagnosis from the abnormality diagnosis device 30C, the inverter control unit 21 changes the modulation wave frequency f0, and drives the motor 2 by performing output control on the power conversion unit 10 by PWM control using the changed modulation wave frequency f 0.

In the abnormality diagnostic device 30C, each part operates again to continue the abnormality diagnosis. When the carrier frequency fc is changed, the noise frequency fn β changes, and thus the presence or absence of noise interference at the spectral peak of the sideband component also changes. Thus, the determination unit 34 can derive an estimate of the noise-free disturbance and diagnose the abnormality of the motor 2 based on the spectral peak of the sideband component.

As described above, in the power conversion device 100A according to the present embodiment, when the abnormality diagnosis device 30C in the control device 20A performs the abnormality diagnosis, the presence or absence of noise interference at the spectral peak of the sideband component is estimated based on the frequency of the sideband component and the noise frequency fn β, and if the presence of noise interference is estimated, the modulated wave frequency f0 is changed.

Thereby, the frequency of the noise component itself is changed by the fluctuation of the voltage (the dc voltage of the smoothing capacitor 10C and the ac voltage output to the motor 2) corresponding to the ac power supply frequency fac. Therefore, noise interference at the spectral peak of the sideband component can be eliminated, thereby reliably performing abnormality diagnosis. This prevents an erroneous diagnosis due to the influence of the noise component, and thus makes it possible to perform an abnormality diagnosis of the motor 2 with high reliability.

In addition, although embodiments 5 to 7 described above have shown that the frequency related to the noise frequency is changed when it is estimated that there is noise interference, it is also possible to operate the power conversion device 100A by initially removing or suppressing the assumed noise interference.

In this case, the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs are determined so that the difference between the frequency of the sideband component to be monitored and the assumed noise frequency is equal to or greater than a set value, and the power conversion device 100A is operated. Alternatively, the modulation wave frequency f0, the carrier frequency fc, and the sampling frequency fs are determined so that the greatest common divisor GCD is reduced to several Hz, and the power conversion device 100A is operated.

While various exemplary embodiments and examples are described herein, the various features, aspects, and functions described in one or more embodiments are not limited in their application to a particular embodiment, but may be applied to embodiments alone or in various combinations.

Therefore, countless modifications not shown by way of example can be conceived within the technical scope disclosed in the present application. For example, the present invention includes a case where at least one of the components is modified, added, or omitted, and a case where at least one of the components is extracted and combined with the components of the other embodiments.

Description of the reference symbols

1 ac power supply, 2 motor, 10 power conversion unit, 10A converter unit, 10B inverter unit, 10C filter capacitor, 20A control device, 30A to 30D abnormality diagnosis device, 31 detection unit, 32 analysis unit, 32a analysis result, 33A frequency setting unit, 34 determination unit, 35 notification unit, 36 determination unit, 37 noise detection unit, 38 storage unit, 100A power conversion device, f0 modulation wave frequency, fac ac power supply frequency, fc carrier frequency, fs sampling frequency, fn α, fn β noise frequency, M modulation wave.

Claims

1. An abnormality diagnostic device for diagnosing an abnormality of a motor driven by pulse width modulation control of a power conversion device, comprising:

a detection unit that detects a current flowing through the motor;

an analysis unit that performs frequency analysis on the current detected by the detection unit and outputs an analysis result;

a determination section that determines an abnormality of the motor based on a spectral peak of at least one sideband component of the modulation wave obtained from the analysis result; and

a frequency setting unit that sets a noise frequency in the current in advance,

the determination unit estimates the presence or absence of noise interference at the peak of the frequency spectrum of the sideband component based on the frequency of the sideband component and the set noise frequency, and determines an abnormality of the motor.

2. The abnormality diagnostic device according to claim 1,

the noise frequency set by the frequency setting unit includes a frequency lower than 1/2 of a carrier frequency.

3. The abnormality diagnostic device according to claim 1 or 2,

the frequency setting unit calculates a greatest common divisor of two or more frequencies including a modulated wave frequency among three frequencies used for the pulse width modulation control, that is, a modulated wave frequency, a carrier frequency, and a sampling frequency at which the modulated wave is sampled, and sets the greatest common divisor and an integer multiple thereof as the noise frequency.

4. The abnormality diagnostic device according to claim 1 or 2,

the frequency setting unit sets, as the noise frequency, an absolute value of a value that is offset from an integer multiple of a modulation wave frequency used for the pulse width modulation control by an integer multiple of a frequency of an ac power supply to which the power conversion device is connected.

5. The abnormality diagnostic device according to any one of claims 1 to 4, wherein the determination section estimates that the noise disturbance is present for the sideband component when the difference between the frequency of the sideband component and the noise frequency is smaller than a set value and the two are close to each other.

6. The abnormality diagnostic device according to claim 5,

the determination unit removes a sideband component estimated to have the noise disturbance, and determines an abnormality of the motor.

7. The abnormality diagnostic device according to claim 5,

a noise detection unit for detecting the noise level at the noise frequency of the current when the motor is operating normally; and a storage unit for storing a detection result of the noise detection unit, wherein the determination unit determines an abnormality of the motor based on the spectral peak of the sideband component and the detection result in the storage unit, with respect to the sideband component estimated to have the noise interference.

8. The abnormality diagnostic device according to any one of claims 1 to 7, comprising a notification unit configured to notify the outside of the presence or absence of the noise interference.

9. A power conversion apparatus, comprising:

a power conversion unit that converts direct current power into alternating current power and supplies the alternating current power to the motor; and

a control device for controlling the output of the power conversion unit by the pulse width modulation control,

the control device includes the abnormality diagnostic device according to any one of claims 1 to 8 to diagnose an abnormality of the motor.

10. A power conversion apparatus, comprising:

the control device includes an abnormality diagnostic device according to claim 3 to diagnose an abnormality of the motor,

the control device performs the pulse width modulation control by changing at least one of the two or more frequencies for calculating the greatest common divisor when a difference between the frequency of the sideband component and the noise frequency is smaller than a set value and the two frequencies are close to each other,

the abnormality diagnosis device diagnoses an abnormality of the motor based on the changed frequency.

11. The power conversion apparatus of claim 10,

the change of the frequency means that the frequency is changed in time.

12. The power conversion apparatus of claim 10,

when the difference between the frequency of the sideband component and the noise frequency is smaller than a set value and the two frequencies are close to each other, the control device changes at least one of the two or more frequencies so that the greatest common divisor coincides with the modulation wave frequency or becomes 10Hz or less.

13. The power conversion apparatus according to any one of claims 10 to 12, wherein the change of the frequency is a change of the carrier frequency as the frequency.

14. A power conversion apparatus, comprising:

a power conversion unit including a converter unit that converts alternating current power from an alternating current power supply into direct current power, a smoothing capacitor, and an inverter unit that converts the direct current power of the smoothing capacitor into alternating current power and supplies the alternating current power to the motor; and

the control device includes the abnormality diagnostic device according to claim 4 to diagnose an abnormality of the motor.

15. The power conversion apparatus of claim 14,

the control device changes the modulation wave frequency to perform the pulse width modulation control when the difference between the frequency of the sideband component and the noise frequency is smaller than a set value and the two frequencies are close to each other,

the abnormality diagnosis device diagnoses an abnormality of the motor based on the changed modulated wave frequency.

16. An abnormality diagnostic method for diagnosing an abnormality of a motor driven by pulse width modulation control of a power conversion apparatus, characterized by comprising:

a first step of calculating a greatest common divisor including two or more frequencies of the modulation wave frequencies among modulation wave frequencies, carrier frequencies, and sampling frequencies at which the modulation waves are sampled, the modulation wave frequencies being three frequencies used for the pulse width modulation control, and setting frequencies that are integer multiples of the greatest common divisor as noise frequencies;

a second step of detecting a current flowing through the motor and performing frequency analysis; and

a third step of determining abnormality of the motor based on a spectral peak of a sideband component of the modulated wave obtained from the analysis result in the second step,

in the third step, it is estimated whether or not there is noise interference in the spectral peak of the sideband component based on the frequency of the sideband component and the noise frequency set in the first step.

17. An abnormality diagnostic method for diagnosing an abnormality of a motor driven by pulse width modulation control of a power conversion apparatus, characterized by comprising:

a first step of setting, as a noise frequency, a frequency that is offset from a modulation wave frequency used for the pulse width modulation control by an integral multiple of a frequency of an ac power supply to which the power conversion device is connected;

a second step of detecting a current flowing through the motor and performing a frequency analysis; and