WO2022003758A1 - Dispositif de diagnostic d'anomalie, dispositif de conversion de puissance et procédé de diagnostic d'anomalie - Google Patents

Dispositif de diagnostic d'anomalie, dispositif de conversion de puissance et procédé de diagnostic d'anomalie Download PDF

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Publication number
WO2022003758A1
WO2022003758A1 PCT/JP2020/025464 JP2020025464W WO2022003758A1 WO 2022003758 A1 WO2022003758 A1 WO 2022003758A1 JP 2020025464 W JP2020025464 W JP 2020025464W WO 2022003758 A1 WO2022003758 A1 WO 2022003758A1
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WIPO (PCT)
Prior art keywords
frequency
noise
abnormality
unit
power
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PCT/JP2020/025464
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English (en)
Japanese (ja)
Inventor
俊彦 宮内
将仁 三好
健 開田
壮太 佐野
烈 菅原
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三菱電機株式会社
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Application filed by 三菱電機株式会社 filed Critical 三菱電機株式会社
Priority to DE112020007369.6T priority Critical patent/DE112020007369T5/de
Priority to PCT/JP2020/025464 priority patent/WO2022003758A1/fr
Priority to JP2020560425A priority patent/JP6824494B1/ja
Priority to CN202080102292.3A priority patent/CN115885469A/zh
Priority to KR1020227043657A priority patent/KR20230010708A/ko
Publication of WO2022003758A1 publication Critical patent/WO2022003758A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/34—Testing dynamo-electric machines
    • G01R31/343—Testing dynamo-electric machines in operation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M7/00—Conversion of ac power input into dc power output; Conversion of dc power input into ac power output
    • H02M7/42—Conversion of dc power input into ac power output without possibility of reversal
    • H02M7/44—Conversion of dc power input into ac power output without possibility of reversal by static converters
    • H02M7/48—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode
    • H02M7/53—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal
    • H02M7/537—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters
    • H02M7/539—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters with automatic control of output wave form or frequency
    • H02M7/5395—Conversion of dc power input into ac power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters with automatic control of output wave form or frequency by pulse-width modulation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/005—Circuits for comparing several input signals and for indicating the result of this comparison, e.g. equal, different, greater, smaller (comparing phase or frequency of 2 mutually independent oscillations in demodulators)
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/02—Arrangements for measuring frequency, e.g. pulse repetition rate; Arrangements for measuring period of current or voltage
    • G01R23/12—Arrangements for measuring frequency, e.g. pulse repetition rate; Arrangements for measuring period of current or voltage by converting frequency into phase shift
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/02—Arrangements for measuring frequency, e.g. pulse repetition rate; Arrangements for measuring period of current or voltage
    • G01R23/15—Indicating that frequency of pulses is either above or below a predetermined value or within or outside a predetermined range of values, by making use of non-linear or digital elements (indicating that pulse width is above or below a certain limit)
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
    • G01R23/16—Spectrum analysis; Fourier analysis
    • G01R23/165—Spectrum analysis; Fourier analysis using filters
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/185—Electrical failure alarms
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M1/00—Details of apparatus for conversion
    • H02M1/32—Means for protecting converters other than automatic disconnection
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02M—APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF
    • H02M1/00—Details of apparatus for conversion
    • H02M1/44—Circuits or arrangements for compensating for electromagnetic interference in converters or inverters
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P27/00—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage
    • H02P27/04—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage
    • H02P27/06—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters
    • H02P27/08—Arrangements or methods for the control of AC motors characterised by the kind of supply voltage using variable-frequency supply voltage, e.g. inverter or converter supply voltage using dc to ac converters or inverters with pulse width modulation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P29/00—Arrangements for regulating or controlling electric motors, appropriate for both AC and DC motors
    • H02P29/02—Providing protection against overload without automatic interruption of supply
    • H02P29/024—Detecting a fault condition, e.g. short circuit, locked rotor, open circuit or loss of load

Definitions

  • the present application relates to an abnormality diagnosing device for diagnosing an abnormality in an electric motor, a power conversion device equipped with the abnormality diagnosing device to drive the electric motor, and a method for diagnosing an abnormality in the electric motor.
  • the frequency analysis is performed on the current flowing through the motor, and the abnormality is diagnosed from the frequency component appearing as a sideband wave of the power supply frequency component. Then, in the current flowing through the motor, the noise component is canceled by subtracting the waveforms of two periods having the same phase, and the pulsating component that appears when the rotor is abnormal is extracted to perform abnormality diagnosis. ..
  • the induction motor is driven by the PWM (pulse width modulation) control of the inverter, and the noise component generated in the vibration spectrum is removed and the noise component is removed.
  • the spectrum is inverse Fourier transformed, and the vibration acceleration waveform collected by the induction motor is obtained with the noise component removed.
  • the present application discloses a technique for solving the above-mentioned problems, and prevents an abnormality of a motor driven by pulse width modulation control of a power converter from the influence of noise including a low frequency region. It is an object of the present invention to provide an abnormality diagnosis device for reliable diagnosis. Another object of the present invention is to provide a power conversion device provided with such an abnormality diagnosis device, which can reliably diagnose an abnormality of an electric motor and drive the electric motor. Further, it is an object of the present invention to provide an abnormality diagnosis method for reliably diagnosing an abnormality of an electric motor driven by pulse width modulation control of a power converter by preventing the influence of noise including a low frequency region.
  • the abnormality diagnosis device disclosed in the present application diagnoses an abnormality of an electric motor driven by pulse width modulation control of a power conversion device.
  • the abnormality diagnosis device includes a detection unit that detects a current flowing through the motor, an analysis unit that frequency-analyzes the current detected by the detection unit, and outputs an analysis result.
  • a determination unit for determining an abnormality of the motor based on a spectral peak of at least one sideband wave component of the modulated wave obtained from the analysis result, and a frequency setting unit for presetting a noise frequency in the current are provided. .. Then, the determination unit estimates the presence or absence of noise interference in the spectrum peak of the sideband wave component based on the frequency of the sideband wave component and the set noise frequency, and determines the abnormality of the motor. ..
  • the power conversion device disclosed in the present application includes a power conversion unit that converts DC power into AC power and supplies power to the electric motor, and a control device that outputs and controls the power conversion unit by the pulse width modulation control.
  • the control device includes the abnormality diagnosis device and diagnoses an abnormality of the electric power.
  • the abnormality diagnosis method disclosed in the present application is a method for diagnosing an abnormality in an electric motor driven by pulse width modulation control of a power conversion device, and is a modulated wave having three frequencies used for the pulse width modulation control.
  • the maximum promise number of two or more frequencies including the modulated wave frequency is calculated, and the frequency that is an integral multiple of the maximum promise number is set as the noise frequency.
  • the third step the presence or absence of noise interference in the spectrum peak of the sideband wave component is estimated based on the frequency of the sideband wave component and the noise frequency set in the first step.
  • the abnormality diagnosis method disclosed in the present application is a method of diagnosing an abnormality of an electric motor driven by pulse width modulation control of a power conversion device, and the power is obtained from a modulated wave frequency used for the pulse width modulation control.
  • the first step of setting the frequency deviated by an integral multiple of the frequency of the AC power supply to which the converter is connected as the noise frequency the second step of detecting the current flowing through the electric motor and analyzing the frequency, and the second step of the second step.
  • the present invention includes a third step of determining an abnormality of the electric motor based on the spectral peak of the sideband wave component of the modulated wave obtained from the analysis result of the above. Then, in the third step, the presence or absence of noise interference in the spectrum peak of the sideband wave component is estimated based on the frequency of the sideband wave component and the noise frequency set in the first step.
  • the abnormality diagnosis device disclosed in the present application it is possible to reliably diagnose an abnormality of an electric motor driven by pulse width modulation control of a power conversion device by preventing the influence of noise including a low frequency region. Obviously, it is possible to reliably diagnose an abnormality of an electric motor driven by pulse width modulation control of a power conversion device by preventing the influence of noise including a low frequency region. Obviously, it is possible to reliably diagnose an abnormality of an electric motor driven by pulse width modulation control of a power conversion device by preventing the influence of noise including a low frequency region. Become.
  • an abnormality of the motor driven by the pulse width modulation control of the power conversion device can be reliably diagnosed by preventing the influence of noise including a low frequency region. Will be possible.
  • the abnormality diagnosis method disclosed in the present application it is possible to reliably diagnose an abnormality of a motor driven by pulse width modulation control of a power converter by preventing the influence of noise including a low frequency region. It will be possible.
  • FIG. It is a figure which shows the structure of the power conversion apparatus and the abnormality diagnosis apparatus by Embodiment 1.
  • FIG. It is a block diagram which shows the schematic structure of the abnormality diagnosis apparatus by Embodiment 1.
  • FIG. It is a block diagram which shows the hardware structure of a part of the abnormality diagnosis apparatus by Embodiment 1.
  • FIG. It is a figure explaining the frequency spectrum waveform of the electric current in the abnormality diagnosis apparatus by Embodiment 1.
  • FIG. It is a waveform diagram explaining the pulse width modulation control of the power conversion apparatus by Embodiment 1.
  • FIG. It is a flowchart explaining the operation of the abnormality diagnosis apparatus by Embodiment 1.
  • FIG. It is a block diagram which shows the schematic structure of the abnormality diagnosis apparatus by Embodiment 2.
  • FIG. 9 is a frequency spectrum waveform of a current for explaining the noise frequency according to the fourth embodiment. It is a flowchart explaining the operation of the abnormality diagnosis apparatus according to Embodiment 4. It is a figure which shows the structure of the power conversion apparatus and the abnormality diagnosis apparatus according to Embodiment 5. It is a figure which shows the carrier wave by another example of Embodiment 5. It is a schematic diagram of the frequency spectrum waveform of the current for demonstrating the effect by Embodiment 6.
  • FIG. 1 is a diagram showing a configuration of a power conversion device and an abnormality diagnosis device according to the first embodiment.
  • the power conversion device 100 is connected between an AC power supply 1 composed of, for example, a commercial power source and an electric motor 2, and drives and controls the electric motor 2.
  • the power conversion device 100 includes a power conversion unit 10 and a control device 20 that outputs and controls the power conversion unit 10. Further, the current i flowing from the power conversion unit 10 to the electric motor 2 is detected by the current sensor 3, and the abnormality diagnosis device 30 diagnoses the abnormality of the electric motor 2 based on the current i.
  • the current sensor 3 may be built in the power conversion device 100 or may be externally attached, and the number and position thereof are not limited to those shown in the figure.
  • 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 the AC power from the AC power supply 1 into DC power and outputs it to the smoothing capacitor 10C
  • the inverter unit 10B converts the DC power of the smoothing capacitor 10C into AC power and supplies power to the electric motor 2. ..
  • the AC power supply 1, the electric motor 2, and the power conversion device 100 show a three-phase configuration, but the present invention is not limited to this.
  • the converter unit 10A is composed of a three-phase bridge circuit including six diodes Da, and the input / output lines of each phase are connected to the AC power supply 1.
  • the inverter unit 10B is composed of a three-phase bridge circuit including six switching elements Q in which diodes Db are connected in antiparallel to each other, and input / output lines of each phase are connected to the motor 2.
  • the switching element Q for example, an IGBT (Insulated Gate Bipolar Transistor) or a MOSFET (metric-axis-semiconductor 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 turns the switching element Q on and off to control the switching element Q from the power conversion unit 10 to the electric motor 2. Output the desired power.
  • PWM control pulse width modulation control
  • the power conversion device 100 drives the electric motor 2.
  • the configurations of the converter unit 10A and the inverter unit 10B are not limited to those shown in the figure.
  • the power conversion unit 10 is provided with a converter unit 10A and is connected to the AC power supply 1, but there is an inverter unit 10B that converts DC power into AC power and supplies power to the motor 2.
  • the converter unit 10A may be omitted.
  • the abnormality diagnosis device 30 has a modulated wave frequency f0 and a carrier frequency fc, which are frequencies of the modulated wave (fundamental wave), the carrier wave, and the clock signal (CLK) for sampling used by the control device 20 in the PWM control of the power conversion unit 10. ,
  • the sampling frequency fs is acquired. Then, the abnormality diagnosis device 30 performs frequency analysis on the current i flowing from the power conversion unit 10 to the electric motor 2, and diagnoses the abnormality of the electric motor 2.
  • FIG. 2 is a block diagram showing a schematic configuration of the abnormality diagnosis device 30.
  • the abnormality diagnosis device 30 includes a detection unit 31 for detecting the current i flowing in the motor 2, an analysis unit 32 for frequency analysis of the current i, and a noise frequency (noise frequency fn ⁇ ) in the current i.
  • a frequency setting unit 33 for presetting the above and a determination unit 34 for determining an abnormality of the electric motor 2 are provided.
  • the detection unit 31 acquires the output of the current sensor 3 and detects the current waveform in the current i of at least one phase flowing through the motor 2.
  • the analysis unit 32 performs frequency analysis based on the detected current i, and derives the analysis result 32a including the frequency spectrum waveform.
  • the frequency setting unit 33 acquires the modulated 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 integral multiple as the noise frequency fn ⁇ .
  • the determination unit 34 acquires the spectrum peak of the sideband wave component of the modulated wave from the analysis result 32a by the analysis unit 32, determines the abnormality of the motor 2 based on the spectrum peak, and outputs the determination result 34a. At that time, the presence or absence of noise interference in the spectral peak of the sideband wave component of the modulated wave is estimated based on the noise frequency fn ⁇ , and the sideband wave component presumed to have noise interference is excluded from the abnormality determination.
  • the processor 5 executes the control program input from the storage device 6.
  • the storage device 6 includes an auxiliary storage device and a volatile storage device.
  • a control program is input to the processor 5 from the auxiliary storage device via the volatile storage device.
  • the processor 5 outputs data such as calculation results to the volatile storage device of the storage device 6, and stores these data in the auxiliary storage device via the volatile storage device as needed.
  • the sideband wave component of the modulated wave which is a specific frequency component, increases in the current i.
  • the rotation frequency of the rotor is fr due to the dynamic eccentricity of the rotor or vibration caused by an abnormality
  • increases based on the frequency (f0 ⁇ fr).
  • k1 and k2 are positive integers, respectively.
  • the conductor bar of the cage rotor is damaged, the sideband wave component of the frequency ((1 ⁇ 2s) ⁇ f0) increases when the slip is s.
  • the sideband wave component deviated from the modulated wave frequency f0 increases by a characteristic frequency determined by the location of the scratch and the shape of the bearing.
  • the characteristic frequency is N ⁇ fr (1-dcos ⁇ / D) / 2 Will be.
  • N, d, D, and ⁇ are the number of balls, the diameter of the balls, the pitch diameter, and the contact angle in the bearing, respectively.
  • sideband wave or sideband wave component refers to the sideband wave of the modulated wave or the sideband wave component of the modulated wave.
  • FIG. 4 is a diagram illustrating a frequency spectrum waveform of the current i in the abnormality diagnosis device 30 when there is an abnormality in the electric motor 2.
  • a plurality of spectra 41 and 42 appear on both sides of the spectrum 40 having the modulated wave frequency f0.
  • the spectrum 41 of the sideband wave component of the modulated wave appears at a frequency (f0 ⁇ fr) deviated by the rotation frequency fr on both sides of the modulated wave frequency f0, and further, the noise component caused by the switching operation of the inverter unit 10B.
  • the spectrum 42 appears.
  • FIG. 5 is a waveform diagram illustrating PWM control of the power conversion device 100.
  • the modulated wave M is compared with the carrier wave Cr to generate a gate signal G.
  • 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 the value is compared with the carrier wave Cr.
  • the carrier frequency fc or the sampling frequency fs is not a multiple of the modulated wave frequency f0
  • the spectrum 42 of the noise component caused by the switching operation of the inverter unit 10B is displayed at the greatest common divisor of those values and an integral multiple thereof. Occurs.
  • the frequency setting unit 33 acquires the modulated 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 integral multiple as the noise frequency fn ⁇ . .. When the greatest common divisor GCD is the modulated wave frequency f0, the noise frequency fn ⁇ is not set.
  • the abnormality diagnosis device 30 detects the current waveform of at least one phase of the current i of each phase current i flowing from the power conversion unit 10 of the power conversion device 100 to the electric motor 2 by the detection unit 31.
  • the detection unit 31 shall detect the current waveforms for three phases.
  • the current sensor 3 may detect each phase current i of the three phases, or may detect two phases and obtain the current of the remaining phases by calculation (step S1).
  • the analysis unit 32 performs frequency analysis based on the detected current i, and derives the analysis result 32a including the frequency spectrum waveform (step S2).
  • the frequency setting unit 33 acquires the modulated wave frequency f0, the carrier wave 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 modulated wave frequency f0, the carrier frequency fc, and the sampling frequency fs, and further calculates an integral multiple of the greatest common divisor GCD (step S4).
  • the noise frequency fn ⁇ is set within a range that does not exceed the measurable range.
  • the greatest common divisor GCD is a value lower than fc / 2.
  • the noise frequency fn ⁇ to be set includes a frequency in the frequency domain lower than fc / 2, and is generally set to include a frequency lower than (fc-4f0) (step S5).
  • the determination unit 34 estimates the presence or absence of noise interference at the spectral peak of the sideband wave component of the modulated wave based on the analysis result 32a derived in step S2 and the noise frequency fn ⁇ set in step S5. Specifically, it is determined whether the frequency of the sideband wave component (spectrum 41) of the modulated wave overlaps or is close to the noise frequency fn ⁇ , and it is estimated that there is noise interference. Since the sideband wave component (spectrum 41) of the modulated wave that increases due to the abnormal sign of the motor 2 is a specific frequency component as described above, the determination unit 34 monitors the specific frequency component and sets the frequency.
  • the set value is set to several Hz, for example, 2 Hz.
  • 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 noise interference does not occur (step S6).
  • the determination unit 34 excludes the sideband wave component from the target of abnormality diagnosis (step S7), and the motor 2 is based on the other sideband wave components.
  • the abnormality is determined and the determination result 34a is output.
  • the spectral peak of the sideband wave component exceeds a preset reference value, it is determined to be abnormal.
  • the reference value is set, for example, based on the spectral peak of the modulated wave frequency f0 (step S8).
  • the frequency setting unit 33 does not set the noise frequency fn ⁇ and proceeds to step S8. Then, the determination unit 34 determines the abnormality of the motor 2 based on the spectral peak of the sideband wave component.
  • the abnormality diagnosis device 30 sets the frequency (noise frequency fn ⁇ ) of the noise component in the current i flowing through the motor 2 in advance, and analyzes the current i by the frequency of the modulated wave. Abnormal diagnosis is performed for the lateral band component. Then, at the time of abnormality diagnosis, the presence or absence of noise interference in the spectral peak of the sideband wave component is estimated based on the frequency of the sideband wave component and the noise frequency fn ⁇ , and the sideband wave component presumed to have noise interference is excluded. The anomaly is determined based on the spectral peaks of the remaining sideband components. Therefore, erroneous diagnosis due to the influence of noise including a low frequency region can be prevented, and abnormality diagnosis of the motor 2 can be performed with high reliability.
  • the noise frequency fn ⁇ is set to a frequency of the maximum promised GCD of the modulated wave frequency f0, the carrier wave frequency fc, and the sampling frequency fs used for PWM control, and an integral multiple thereof, so that noise including a low frequency region is included.
  • the influence of the ingredients can be reliably prevented.
  • the sideband wave component is estimated to have noise interference, so that noise interference can be estimated with high reliability.
  • the noise frequency fn ⁇ is set within a range that does not exceed the measurable range, it may be set only in a frequency region lower than 1/2 of the carrier frequency fc.
  • the maximum promise number GCD calculated by the frequency setting unit 33 is the modulated wave frequency f0
  • the noise frequency fn ⁇ is not set, but the modulated wave frequency f0 and its integral multiple are set as the noise frequency fn ⁇ as it is.
  • the frequency component is not close to the side band component of the modulated wave.
  • the carrier wave Cr by the triangular wave is shown for the PWM control of the power conversion device 100, the carrier wave Cr is not limited to the triangular wave, and a sine wave may be used. Further, in order to improve the voltage utilization rate, a third harmonic may be superimposed on the modulated wave M. In that case, the value of the greatest common divisor GCD does not change, and the noise frequency fn ⁇ can be set in the same manner.
  • FIG. 7 is a block diagram showing a schematic configuration of the abnormality diagnosis device 30A according to the second embodiment.
  • the abnormality diagnosis device 30A includes a detection unit 31, an analysis unit 32, a frequency setting unit 33, and a determination unit 34, and further includes a notification unit 35, as in the first embodiment. If there is a sideband wave component presumed to have noise interference, the determination unit 34 excludes the sideband wave component from the target of abnormality diagnosis (see step S7 in FIG. 6), and outputs a notification command 34b to the notification unit 35. do. Then, the notification unit 35 outputs a notification signal 35a that notifies the outside that there is noise interference. Other configurations and operations are the same as those in the first embodiment.
  • the sideband wave component may not be excluded from the target of abnormality diagnosis, and the notification signal 35a may only be output from the notification unit 35. In that case, the user is notified to call attention, and the user can consider the influence of the noise component on the determination result 34a from the abnormality diagnosis device 30A, and as a result, erroneous diagnosis can be prevented.
  • FIG. 8 is a block diagram showing a schematic configuration of the abnormality diagnosis device 30B according to the third embodiment.
  • the abnormality diagnosis 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, and a storage unit, as in the first embodiment.
  • a unit 38 and a switch 39 are provided.
  • the configuration and operation other than the determination unit 36, the noise detection unit 37, the storage unit 38, and the switch 39 are the same as those in the first embodiment.
  • the detection unit 31 acquires the output of the current sensor 3 and detects the current waveform in the current i of at least one phase flowing through the motor 2.
  • the analysis unit 32 performs frequency analysis based on the detected current i, and derives the analysis result 32a including the frequency spectrum waveform.
  • the frequency setting unit 33 acquires the modulated 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 integral multiple within a range not exceeding the measurable range. Set as the noise frequency fn ⁇ .
  • the noise detection unit 37 detects the magnitude of noise at the noise frequency fn ⁇ of the current i, for example, the value of the spectral peak of the noise component from the analysis result 32a by the analysis unit 32 during the normal operation of the electric motor 2.
  • the detection result is stored in the storage unit 38.
  • the noise detection by the noise detection unit 37 is performed in advance during the normal operation of the motor 2 prior to the abnormality diagnosis of the motor 2.
  • the switch 39 selectively switches the output destination of the analysis result 32a of the analysis unit 32 to one of the noise detection unit 37 and the determination unit 36.
  • the determination unit 36 is selected when the abnormality of the motor 2 is diagnosed, and the noise detection unit 37 is selected when the noise is detected in advance during the normal operation of the motor 2.
  • the determination unit 36 acquires the spectrum peak of the sideband wave component of the modulated wave from the analysis result 32a by the analysis unit 32, determines the abnormality of the motor 2 based on the spectrum peak, and outputs the determination result 36a. At that time, the presence or absence of noise interference in the spectral peak of the sideband wave component of the modulated wave is estimated based on the noise frequency fn ⁇ . Specifically, as in the first embodiment, when the difference between the frequency of the sideband wave component of the modulated wave and the noise frequency fn ⁇ is less than the set value, the frequency of the sideband wave component and the noise frequency fn ⁇ overlap or are close to each other. It is presumed that there is noise interference.
  • the determination unit 36 extracts the magnitude of the noise of the noise frequency fn ⁇ , which is the noise interference source, from the storage unit 38. Then, with respect to the sideband wave component of the noise interference destination, the abnormality of the electric motor 2 is determined based on the spectral peak of the sideband wave component and the magnitude of the extracted noise. Specifically, for example, when the value obtained by subtracting the spectral peak value of the noise component from the spectral peak value of the sideband wave component exceeds a preset reference value, it is determined to be abnormal.
  • the reference value is set, for example, based on the spectral peak of the modulated wave frequency f0.
  • the abnormality diagnosis device 30B sets the frequency (noise frequency fn ⁇ ) of the noise component in the current i flowing through the motor 2 in advance, and analyzes the current i by the frequency of the modulated wave. Abnormal diagnosis is performed for the lateral band component. Further, prior to the abnormality diagnosis, the abnormality diagnosis device 30B detects the magnitude of noise at the noise frequency fn ⁇ of the current i from the analysis result 32a by the analysis unit 32 during the normal operation of the electric motor 2, and the detection result.
  • the presence or absence of noise interference in the spectrum peak of the sideband wave component is estimated based on the frequency of the sideband wave component and the noise frequency fn ⁇ , and the spectrum peak of the sideband wave component estimated to have noise interference is obtained. , Used for abnormality judgment in consideration of the magnitude of noise.
  • the sideband wave component presumed to have noise interference is also used for the abnormality diagnosis without removing it, the sideband wave component to be monitored for the abnormality diagnosis can be reliably monitored and the abnormality diagnosis of the motor 2 can be surely performed. ..
  • the noise detection by the noise detection unit 37 is obtained from the analysis result 32a of the current i during normal operation of the motor 2, but is obtained from the result of frequency analysis by detecting the output voltage to the motor 2. You can also do things. In that case, it is not particularly necessary to detect it during normal operation of the motor 2, and the magnitude of noise corresponding to normal operation at the noise frequency fn ⁇ of the current i can be calculated from the result of the frequency analysis of the detected voltage.
  • the calculation result can be used by the determination unit 36 without being stored in the storage unit 38, and the storage unit 38 may be omitted.
  • both the result of the frequency analysis of the detected voltage and the detection result of the noise obtained from the analysis result 32a of the current i during the normal operation of the electric motor 2 can be used by the determination unit 36, and the abnormality determination can be made. Accuracy is improved.
  • the notification unit 35 may be provided by applying the second embodiment to notify the user that there is an estimation of noise interference.
  • FIG. 9 is a diagram showing the configuration of the power conversion device 100 and the abnormality diagnosis device 30C according to the fourth embodiment.
  • the power conversion device 100 is configured in the same manner as in the first embodiment, and includes a power conversion unit 10 and a control device 20 that outputs and controls the power conversion unit 10. Further, the current i flowing from the power conversion unit 10 to the electric motor 2 is detected by the current sensor 3, and the abnormality diagnosis device 30 diagnoses the abnormality of the electric 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.
  • the converter unit 10A cannot be omitted, and the AC power from the AC power supply 1 is converted into DC power and output to the smoothing capacitor 10C.
  • the inverter unit 10B converts the DC power of the smoothing capacitor 10C into AC power and supplies power to the motor 2.
  • the power conversion unit 10 indicates that the AC power supply 1, the electric motor 2, and the power conversion device 100 have a three-phase configuration, but the present invention 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.
  • the control device 20 generates a gate signal G to each switching element Q of the inverter unit 10B by PWM control, controls the switching element Q on and off, and outputs desired power from the power conversion unit 10 to the electric motor 2. .. In this way, the power conversion device 100 drives the electric motor 2.
  • the DC voltage of the smoothing capacitor 10C and the AC voltage output to the electric motor 2 slightly fluctuate at the frequency of the AC power supply 1 and a frequency that is an integral multiple of the frequency, and the sideband wave deviates from the modulated wave frequency f0 by that value.
  • a component (noise component) is generated in the current i.
  • the abnormality diagnosis device 30C acquires the frequency of the modulated wave (modulated wave frequency f0) used by the control device 20 in the PWM control of the power conversion unit 10 and the frequency of the AC power supply 1 (AC power supply frequency fac). Then, the abnormality diagnosis device 30C performs frequency analysis on the current i flowing from the power conversion unit 10 to the electric motor 2, and diagnoses the abnormality of the electric motor 2.
  • FIG. 10 is a block diagram showing a schematic configuration of the abnormality diagnosis device 30C.
  • the abnormality diagnosis device 30C includes a detection unit 31 for detecting the current i flowing in the motor 2, an analysis unit 32 for frequency analysis of the current i, and a noise frequency (noise frequency fn ⁇ ) in the current i.
  • the frequency setting unit 33A is provided in advance, and the determination unit 34 for determining an abnormality of the electric motor 2 is provided.
  • the detection unit 31 and the analysis unit 32 operate in the same manner as in the first embodiment.
  • the frequency setting unit 33A acquires the modulated wave frequency f0 and the AC power supply frequency fac, and calculates and sets the following frequencies as the noise frequency fn ⁇ .
  • m and n are positive integers, respectively.
  • the determination unit 34 acquires the spectrum peak of the sideband wave component of the modulated wave from the analysis result 32a by the analysis unit 32, determines the abnormality of the motor 2 based on the spectrum peak, and outputs the determination result 34a. At that time, the presence or absence of noise interference in the spectral peak of the sideband wave component of the modulated wave is estimated based on the noise frequency fn ⁇ , and the sideband wave component presumed to have noise interference is excluded from the abnormality determination.
  • FIG. 11 is a frequency spectrum waveform of the current i for explaining the noise frequency.
  • the modulated wave frequency f0 and the AC power supply frequency fac are 50 Hz and 60 Hz, respectively, the frequency is a multiple of the modulated wave frequency f0 (100 Hz, 150 Hz, 200 Hz), and the frequencies are 10 Hz and 70 Hz separately. , 110 Hz, 170 Hz, the spectrum of the noise component appears.
  • the abnormality diagnosis device 30C detects the current waveform of the current i for at least one phase among the phase currents i flowing from the power conversion unit 10 of the power conversion device 100 to the electric motor 2 as in the first embodiment. Detected by the unit 31 (step S1), the analysis unit 32 performs frequency analysis based on the detected current i, and derives the analysis result 32a including the frequency spectrum waveform (step S2).
  • the frequency setting unit 33A acquires the modulated wave frequency f0 and the AC power supply frequency fac (step SS3). Then, as described above, the frequency setting unit 33A has the frequency setting unit 33A.
  • the determination unit 34 estimates the presence or absence of noise interference at the spectral peak of the sideband wave component of the modulated wave based on the analysis result 32a derived in step S2 and the noise frequency fn ⁇ set in step S5. Specifically, it is determined whether the frequency of the sideband wave component (spectrum 41) of the modulated wave overlaps or is close to the noise frequency fn ⁇ , and it is estimated that there is noise interference. In this case as well, as in the first embodiment, the determination unit 34 compares a specific frequency component (sideband wave component) that increases due to an abnormality sign with the noise frequency fn ⁇ , and makes a difference. If it is less than the set value, it is judged that they are duplicated or close to each other, and it is estimated that there is noise interference. Also in this case, the set value is set to several Hz, for example, 2 Hz (step S6).
  • the determination unit 34 excludes the sideband wave component from the target of abnormality diagnosis (step S7), and the motor 2 is based on the other sideband wave components. Judge the abnormality of. At that time, if the spectral peak of the sideband wave component exceeds a preset reference value, it is determined to be abnormal.
  • the reference value is set, for example, based on the spectral peak of the modulated wave frequency f0 (step S8).
  • the abnormality diagnosis device 30C sets the frequency (noise frequency fn ⁇ ) of the noise component in the current i flowing through the motor 2 in advance, and the current i is frequency-analyzed to obtain the modulated wave. Abnormal diagnosis is performed for the lateral band component. Then, at the time of abnormality diagnosis, the presence or absence of noise interference in the spectral peak of the sideband wave component is estimated based on the frequency of the sideband wave component and the noise frequency fn ⁇ , and the sideband wave component presumed to have noise interference is excluded. The anomaly is determined based on the spectral peaks of the remaining sideband components.
  • the noise component including the low frequency region in this case, the noise component caused by the modulated wave frequency f0 and the AC power frequency fac, and the abnormality diagnosis of the motor 2 can be performed with high reliability.
  • the sideband wave component is estimated to have noise interference, so that noise interference can be estimated with high reliability.
  • the noise frequency fn ⁇ is set within a range that does not exceed the measurable range, it may be set only in a frequency region lower than 1/2 of the carrier frequency fc.
  • the notification unit 35 may be provided by applying the above-described second embodiment to the fourth embodiment to notify the user that the presence or absence of noise interference has been estimated.
  • the third embodiment may be applied to the fourth embodiment.
  • a noise detection unit 37, a storage unit 38, and a switch 39 are provided to detect and store the magnitude of noise at the noise frequency fn ⁇ of the current i during normal operation of the motor 2 prior to the abnormality diagnosis. Keep it. Then, at the time of abnormality diagnosis, the presence or absence of noise interference in the spectrum peak of the sideband wave component is estimated based on the frequency of the sideband wave component and the noise frequency fn ⁇ , and the spectrum peak of the sideband wave component estimated to have noise interference is obtained. , Used for abnormality judgment in consideration of the magnitude of noise. As a result, the sideband wave component to be monitored for the abnormality diagnosis can be reliably monitored, and the abnormality diagnosis of the motor 2 can be reliably performed.
  • the noise detection by the noise detection unit 37 is obtained from the result of frequency analysis by detecting the line voltage output to the motor 2 or the DC voltage of the smoothing capacitor 10C. You can also. In that case, it is not particularly necessary to detect it during normal operation of the motor 2, and the magnitude of noise corresponding to normal operation at the noise frequency fn ⁇ of the current i can be calculated from the result of the frequency analysis of the detected voltage. The calculation result can be used without being stored in the storage unit 38, and the storage unit 38 may be omitted. Further, both the result of the frequency analysis of the detected voltage and the detection result of the noise obtained from the analysis result 32a of the current i during the normal operation of the motor 2 can be used, and the accuracy of the abnormality determination is improved. ..
  • the frequency setting unit 33A acquires the modulated wave frequency f0 and the AC power supply frequency fac to set the above-mentioned noise frequency fn ⁇ , which was shown in the first embodiment.
  • the noise frequency fn ⁇ may also be set.
  • the frequency setting unit 33A acquires the modulated wave frequency f0, the carrier wave frequency fc, the sampling frequency fs, and the AC power supply frequency fac, and calculates and sets the noise frequency fn ⁇ and the noise frequency fn ⁇ .
  • the influence of the noise component can be widely suppressed to prevent erroneous diagnosis, and the abnormality diagnosis of the motor 2 can be performed more reliably.
  • abnormality diagnosis devices 30 and 30A to 30C are shown to be outside the power conversion device 100, they may be inside the control device 20 of the power conversion device 100. , The same effect can be obtained, and the exchange of information necessary for setting the noise frequencies fn ⁇ and fn ⁇ becomes easy.
  • FIG. 13 is a diagram showing the configuration of the power conversion device 100A according to the fifth embodiment.
  • the power conversion device 100A includes a power conversion unit 10 configured in the same manner as in the first embodiment, and a control device 20A that outputs and controls the power conversion unit 10.
  • the control device 20A includes an inverter control unit 21 for controlling the output of the power conversion unit 10 and an abnormality diagnosis device 30D. Further, the current i flowing from the power conversion unit 10 to the electric motor 2 is detected by the current sensor 3, and the abnormality diagnosis device 30D diagnoses the abnormality of the electric motor 2 based on the current i.
  • the inverter control unit 21 In the control device 20A, the inverter control unit 21 generates a gate signal G to each switching element Q of the inverter unit 10B by PWM control, and controls the switching element Q on and off to control the switching element Q from the power conversion unit 10 to the electric motor 2. Output the desired power. As a result, the power conversion device 100A drives the electric motor 2.
  • the abnormality diagnosis device 30D has a modulated wave frequency f0, a carrier wave frequency fc, and a sampling frequency fs, which are frequencies of a modulated wave (fundamental wave), a carrier wave, and a clock signal (CLK) for sampling used by the inverter control unit 21 in PWM control. To get. Then, the abnormality diagnosis device 30D performs frequency analysis on the current i flowing from the power conversion unit 10 to the electric motor 2, and diagnoses the abnormality of the electric motor 2.
  • the abnormality diagnosis 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 diagnosis device 30 shown in the first embodiment, and includes the detection unit 31, the analysis unit 32, and the abnormality diagnosis device 30.
  • the frequency setting unit 33 operates in the same manner as in the first embodiment.
  • the determination unit 34 estimates the presence or absence of noise interference in the spectral peak of the sideband wave component of the modulated wave based on the frequency of the sideband wave component and the noise frequency fn ⁇ . When there is no noise interference, the determination unit 34 makes an abnormality diagnosis of the motor 2 based on the spectral peak of the sideband wave component, as in the first embodiment. Then, 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.
  • the inverter control unit 21 When the inverter control unit 21 receives the notification signal SS1 notifying the interruption of the abnormality diagnosis from the abnormality diagnosis device 30D, the inverter control unit 21 changes the carrier frequency fc and outputs the power conversion unit 10 by PWM control using the changed carrier frequency fc. It controls and drives the electric motor 2.
  • the carrier frequency fc can be easily changed without directly affecting the output of the power conversion unit 10.
  • each part operates again to continue the abnormality diagnosis. Since the noise frequency fn ⁇ changes when the carrier frequency fc is changed, the presence or absence of noise interference at the spectral peak of the sideband wave component also changes. As a result, the determination unit 34 can derive an estimation without noise interference, and makes an abnormality diagnosis of the motor 2 based on the spectral peak of the sideband wave component.
  • the determination unit 34 derives the estimation without noise interference by changing it once, but it is possible to change it multiple times.
  • the abnormality diagnosis device 30D in the control device 20A determines the sideband wave component based on the frequency of the sideband wave component and the noise frequency fn ⁇ at the time of abnormality diagnosis.
  • the presence or absence of noise interference at the spectrum peak is estimated, and if it is estimated that there is noise interference, the carrier frequency fc is changed.
  • the greatest common divisor GCD of the modulated wave frequency f0, the carrier wave 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, it is possible to remove noise interference at the spectral peak of the sideband wave component, and it is possible to reliably perform an abnormality diagnosis. In this way, erroneous diagnosis due to the influence of the noise component can be prevented, and abnormality diagnosis of the electric motor 2 can be performed with high reliability.
  • the carrier frequency fc is changed, but at least one of the modulated wave frequency f0, the carrier frequency fc, and the sampling frequency fs, which is used for the calculation of the greatest common divisor GCD. Just change one.
  • the carrier frequency fc when the carrier frequency fc is changed, the carrier frequency fc may be changed with time as shown in FIG.
  • the carrier wave Cr changes by alternately repeating two kinds of frequencies (1 / t1) and (1 / t2) with two kinds of different periods t1 and t2.
  • the change is not limited to each cycle, and may be changed over time to three or more kinds of frequencies. Further, the frequency may be changed continuously instead of discretely.
  • the carrier frequency fc or the sampling frequency fs changes with time as described above, the spectrum of the greatest common divisor GCD and its integral multiple frequency components is dispersed in a plurality of frequency ranges. As a result, the spectral peak of the noise component can be reduced, the noise interference at the spectral peak of the sideband wave component can be removed or suppressed, and the abnormality diagnosis can be performed with high reliability.
  • Embodiment 6 when it is estimated that there is noise interference at the spectral peak of the sideband wave component during the abnormality diagnosis by the abnormality diagnosis device 30D, at least one of the frequencies used for the calculation of the greatest common divisor GCD is used. Shown what to change.
  • the greatest common divisor GCD is further such that the greatest common divisor GCD matches the modulated wave frequency f0 or is 10 Hz or less, preferably several Hz or less. Change at least one of the frequencies used in the calculation of.
  • FIG. 15 is a schematic diagram of a frequency spectrum waveform of a current for explaining the effect of the sixth embodiment.
  • noise components are shown in two 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 the comparative example exceeding 10 Hz.
  • the spectra 42A and 42B of the noise component caused by the switching operation of the inverter unit 10B appear apart from the spectrum 40 of the modulated wave frequency f0.
  • the spectrum 42A is a case where the greatest common divisor GCD exceeds 10 Hz
  • the spectrum 42B is a case where the greatest common divisor GCD is several Hz.
  • the spectrum 42B has a larger number of appearances but a lower spectrum peak than the spectrum 42A.
  • the abnormality diagnosis device 30D when at least one of the frequencies used in the calculation of the greatest common divisor GCD is changed so that the greatest common divisor GCD matches the modulated wave frequency f0, the abnormality diagnosis device 30D is used. Since the noise component assumed by the above is removed, the abnormality diagnosis can be performed reliably and reliably.
  • Embodiment 7 the abnormality diagnosis device 30C shown in the fourth embodiment is applied to the abnormality diagnosis device 30D in the power conversion device 100A shown in the fifth embodiment.
  • the abnormality diagnosis device 30C is provided in the control device 20A of the power conversion device 100A.
  • the abnormality diagnosis device 30C includes a detection unit 31, an analysis unit 32, a frequency setting unit 33A, and a determination unit 34, as in the fourth embodiment, and the detection unit 31, analysis unit 32, and frequency setting unit 33A are described above. It operates in the same manner as in the fourth embodiment.
  • the determination unit 34 estimates the presence or absence of noise interference in the spectral peak of the sideband wave component of the modulated wave based on the frequency of the sideband wave component and the noise frequency fn ⁇ . When there is no noise interference, the determination unit 34 makes an abnormality diagnosis of the motor 2 based on the spectral peak of the sideband wave component, as in the fourth embodiment. Then, 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.
  • the inverter control unit 21 When the inverter control unit 21 receives the notification signal SS1 notifying the interruption of the abnormality diagnosis from the abnormality diagnosis device 30C, the inverter control unit 21 changes the modulated wave frequency f0 and PWM-controls the power conversion unit 10 using the changed modulated wave frequency f0. The output is controlled by the above to drive the electric motor 2. In the abnormality diagnosis device 30C, each part operates again to continue the abnormality diagnosis. Since the noise frequency fn ⁇ changes when the modulated wave frequency f0 is changed, the presence or absence of noise interference at the spectral peak of the sideband wave component also changes. As a result, the determination unit 34 can derive an estimation without noise interference, and makes an abnormality diagnosis of the motor 2 based on the spectral peak of the sideband wave component.
  • the abnormality diagnosis device 30C in the control device 20A determines the sideband wave component based on the frequency of the sideband wave component and the noise frequency fn ⁇ at the time of abnormality diagnosis.
  • the presence or absence of noise interference at the spectrum peak is estimated, and if it is estimated that there is noise interference, the modulated wave frequency f0 is changed.
  • the frequency itself of the noise component caused by the fluctuation of the voltage (DC voltage of the smoothing capacitor 10C and the AC voltage output to the electric motor 2) according to the AC power supply frequency fac is changed. Therefore, it is possible to remove noise interference at the spectral peak of the sideband wave component, and it is possible to reliably perform an abnormality diagnosis. In this way, erroneous diagnosis due to the influence of the noise component can be prevented, and abnormality diagnosis of the electric motor 2 can be performed with high reliability.
  • the frequency related to the noise frequency is changed.
  • the assumed noise interference is removed or suppressed from the beginning for power conversion.
  • the device 100A can also be operated.
  • the modulation wave frequency f0, the carrier wave frequency fc, and the sampling frequency fs are determined so that the difference between the frequency of the sideband wave component to be monitored and the assumed noise frequency becomes equal to or more than the set value, and the power conversion device 100A is used. drive.
  • the power conversion device 100A is operated by determining the modulated wave frequency f0, the carrier wave frequency fc, and the sampling frequency fs so as to reduce the greatest common divisor GCD to several Hz.

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Abstract

Dispositif de diagnostic d'anomalie (30) détectant un courant circulant à travers un moteur électrique (2) entraîné par commande de modulation de largeur d'impulsion d'un dispositif de conversion de puissance (100) pour analyser la fréquence du courant, et comprenant une unité de détermination (34) qui détermine une anomalie du moteur électrique (2) sur la base d'un pic de spectre d'au moins une composante de bande latérale d'une onde modulée, qui est obtenue à partir du résultat de l'analyse de fréquence. Le dispositif de diagnostic d'anomalie (30) comprend une unité de réglage de fréquence (33) pour prédéfinir une fréquence de bruit (fnα) dans le courant. L'unité de détermination (34) détermine l'anomalie par estimation de la présence ou de l'absence d'une interférence de bruit au pic de spectre de la composante de bande latérale sur la base de la fréquence de la composante de bande latérale et de la fréquence de bruit définie (fnα).
PCT/JP2020/025464 2020-06-29 2020-06-29 Dispositif de diagnostic d'anomalie, dispositif de conversion de puissance et procédé de diagnostic d'anomalie WO2022003758A1 (fr)

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PCT/JP2020/025464 WO2022003758A1 (fr) 2020-06-29 2020-06-29 Dispositif de diagnostic d'anomalie, dispositif de conversion de puissance et procédé de diagnostic d'anomalie
JP2020560425A JP6824494B1 (ja) 2020-06-29 2020-06-29 異常診断装置、電力変換装置および異常診断方法
CN202080102292.3A CN115885469A (zh) 2020-06-29 2020-06-29 异常诊断装置、功率转换装置及异常诊断方法
KR1020227043657A KR20230010708A (ko) 2020-06-29 2020-06-29 이상 진단 장치, 전력 변환 장치 및 이상 진단 방법

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JP2016116251A (ja) * 2014-12-10 2016-06-23 旭化成エンジニアリング株式会社 インバータノイズ除去方法、およびインバータ等を含む設備の診断方法
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