JP6173530B1 - Air conditioner failure sign detection device - Google Patents

Abstract

The present invention provides an air conditioner failure sign detection device capable of improving the accuracy of detecting a compressor abnormality. A failure symptom detection device according to the present invention includes a compressor including a motor and a drive device. The drive device 12 outputs a three-phase current to the motor 11. The failure sign detection device 5 includes a conversion unit 51 and an abnormality detection unit 52. The conversion unit 51 calculates the q-axis current Iq of the motor 11 from the measured value of the three-phase current and the rotation angle θ of the rotor of the motor 11. The abnormality detection unit 52 detects an abnormality of the compressor 1 by comparing an evaluation value calculated by performing frequency analysis on the q-axis current Iq and a reference value. [Selection] Figure 2

Description

  The present invention relates to a failure sign detection device for an air conditioner.

  Conventionally, an apparatus for detecting an abnormality of an air conditioner is known. For example, in Japanese Patent Application Laid-Open No. 2007-170411 (Patent Document 1), in a compressor used in an air conditioner, an internal state of the compressor is determined by analyzing a harmonic component of a three-phase current applied to a motor coil. A compressor internal state estimation device for estimation is disclosed. This internal state estimation device estimates the action of an impact load such as a bearing abnormality, thereby predicting or diagnosing a compressor failure in real time.

JP 2007-170411 A

  The internal state of the compressor can be estimated to some extent by analyzing the magnitude and phase of each phase of the three-phase current output to the compressor motor and estimating the motor torque or rotational speed, for example. .

  However, it is known that the three-phase current output to the motor may be distorted under the influence of, for example, electrical noise caused by the power supply frequency or electrical noise caused by the inverter drive voltage.

  Therefore, according to the internal state estimation using the analysis of the three-phase current as disclosed in JP 2007-170411 A (Patent Document 1), it may be difficult to detect the compressor abnormality with high accuracy. is there.

  The present invention has been made to solve the above-described problems, and an object of the present invention is to provide a failure sign detection device for an air conditioner that can improve the detection accuracy of a compressor abnormality. It is.

  The failure symptom detection device according to the present invention is a failure symptom detection device for an air conditioner including a compressor including a motor and a drive device. The drive device is configured to output a three-phase current to the motor. The failure sign detection apparatus includes a conversion unit and an abnormality detection unit. The conversion unit is configured to calculate the q-axis current of the motor from the measured value of the three-phase current and the rotation angle of the rotor of the motor. The abnormality detection unit is configured to detect an abnormality of the compressor by comparing an evaluation value calculated by performing frequency analysis on the q-axis current and a reference value.

  According to the present invention, the internal state of the compressor can be accurately estimated by analyzing the q-axis current that is not easily affected by electrical noise. As a result, the abnormality detection accuracy of the compressor can be improved.

It is a block diagram of the air conditioner which concerns on embodiment. It is a figure which shows the function structure of the drive device of FIG. 1, and a control apparatus. It is a figure which shows together the mode of the time change of the U-phase current in a single rotary compressor, and the time change of the q-axis current of dq-axis current. It is a figure which shows the torque fluctuation rate at the time of normal of a single rotary compressor. It is a spectrum figure which shows the FFT analysis result by the FFT analysis part of FIG. It is a figure which shows the torque fluctuation rate in 1 rotation in the normal time for every compression format of a compressor.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals and description thereof will not be repeated.

  FIG. 1 is a configuration diagram of an air conditioner 100 according to an embodiment. As shown in FIG. 1, the air conditioner 100 includes a compressor 1, a condenser 2, an expansion valve 3, an evaporator 4, a control device 5, and a drive device 12.

  The air conditioner 100 operates as a refrigeration cycle apparatus. In the air conditioner 100, the refrigerant circulates in the order of the compressor 1, the condenser 2, the expansion valve 3, and the evaporator 4.

  The compressor 1 compresses and discharges the gas refrigerant. The compressor 1 uses the driving force of the motor 11 to compress the sucked gas refrigerant. The motor 11 is, for example, a direct current brushless motor. The motor 11 includes, for example, a permanent magnet synchronous motor (PMSM), a brushless direct current motor (BLDCM), a reluctance motor (RM), and a synchronous reluctance motor (SyRM). Motor) or a switched reluctance motor (SRM). The motor 11 is connected to a compression mechanism (not shown) that compresses the gas refrigerant in the refrigeration cycle.

  The condenser 2 condenses the gas refrigerant discharged from the compressor 1 and discharges the liquid refrigerant. The opening degree of the expansion valve 3 is controlled by the control device 5, and the refrigerant from the condenser 2 is expanded to reduce the pressure. The evaporator 4 evaporates the liquid refrigerant (liquid refrigerant) discharged from the expansion valve 3 and discharges the gas refrigerant (gas refrigerant).

  The control device 5 controls the drive frequency of the compressor 1 via the drive device 12. The control device 5 adjusts the opening degree of the expansion valve 3 so that the degree of superheat at the pipe outlet of the evaporator 4 approaches the target value based on, for example, the pressure on the low pressure side and the temperature of the pipe outlet of the evaporator 4 ( Superheat control).

  FIG. 2 is a diagram showing a functional configuration of the driving device 12 and the control device 5 of FIG. As shown in FIG. 2, drive device 12 includes a converter 121 and an inverter 122.

  Converter 121 receives an alternating current from power supply 6, converts the alternating current into a direct current, and outputs the direct current to inverter 122. The frequency of the power source 6 is, for example, 50 Hz or 60 Hz.

Inverter 122 includes an inverter main circuit (all not shown) including a plurality of switching elements. The inverter 122 outputs a three-phase (UVW phase) current to the motor 11 included in the compressor 1 by receiving a PWM (Pulse Width Modulation) signal from the control device 5 and switching the switching element on and off. The U-phase current I _U and the V-phase current I _V output to the motor 11 are measured by the current sensors 111 and 112, respectively, and output to the control device 5.

  The control device 5 includes an inverter control unit 51, an abnormality detection unit 52, and a memory 53. The control device 5 corresponds to the failure symptom detection device in the present invention.

  The inverter control unit 51 outputs a PWM signal to the inverter 122 to perform vector control. Inverter controller 51 includes a phase current calculator 511, a Clark converter 512, a park converter 513, a voltage command value calculator 514, an output voltage vector calculator 515, and a PWM signal generator 516. The phase current calculation unit 511, the Clark conversion unit 512, the park conversion unit 513, the voltage command value calculation unit 514, the output voltage vector calculation unit 515, and the PWM signal generation unit 516 are obtained by a computer such as a CPU (Central Processing Unit). It may be realized by executing a program stored in the memory 53, or may be realized by dedicated hardware.

Phase current calculation section 511 receives the U-phase current _{I U} and V-phase current _{I V,} respectively from the current sensors 111 and 112, calculates the W-phase current _{I W.} The phase current calculation unit 511 outputs each phase current (I _U , I _V , I _W ) to the Clark conversion unit 512. Each phase current (I _U , I _V , I _W ) changes with a change in the rotation angle θ (mechanical angle) of the rotor of the motor 11. In the following description, the rotation angle θ is described as a value measured by the angle sensor 113, but the angle sensor 113 is not an essential component of the present invention, and the rotation angle θ may be calculated by other methods. For example, as in the position sensorless control, the rotation angle θ may be calculated from each phase current (I _U , I _V , I _W ) and the voltage command value.

The Clark conversion unit 512 converts each phase current (I _U , I _V , I _W ) into a two-phase (αβ phase) current (Iα, Iβ), and outputs the current to the park conversion unit 513.

The park conversion unit 513 receives the rotation angle θ of the rotor of the motor 11 from the angle sensor 113, and converts the αβ phase current (Iα, Iβ) corresponding to the coordinates of the stationary coordinate system into the rotation coordinate system (dq coordinate system). Is converted into a dq-axis current (I _d , I _q ) corresponding to the coordinates of and is output to the voltage command value calculation unit 514. The d-axis current I _d is an exciting current component and causes the motor 11 to generate a rotating magnetic field. The q-axis current I _q is a torque current component and generates the torque of the motor 11. The dq-axis current (I _d , I _q ) corresponds to a value obtained by measuring the αβ phase current (Iα, Iβ) rotating at the rotation angle θ in the stationary coordinate system in the rotating coordinate system following the rotation. The change of the angle θ does not appear.

The voltage command value calculation unit 514 performs proportional-integral control so that the dq axis current (I _d , I _q ) approaches a preset target current value (I _dref , I _qref ), and outputs an output voltage command value (V _{d *} , _{Vq *} ) is calculated. The voltage command value calculation unit 514 outputs the output voltage command value (V _{d *} , V _{q *} ) in the dq coordinate system to the output voltage vector calculation unit 515.

The output voltage vector calculation unit 515 converts the output voltage command value (V _{d *} , V _{q *} ) into the output voltage command value in the stationary coordinate system, and then performs space vector conversion to calculate the output voltage vector V _{X *.} And output to the PWM signal generator 516.

The PWM signal generation unit 516 generates a PWM signal using the comparison between the output voltage vector V _{X *} and the carrier signal, and outputs the PWM signal to the inverter 122.

The abnormality detection unit 52 detects an abnormality that has occurred in the compressor 1. For example, as a method for detecting an abnormality occurring in the compressor 1, the magnitude and phase of each phase current (I _U , I _V , I _W ) output to the motor 11 of the compressor is analyzed to analyze the torque of the motor 11. And a method of detecting an abnormality by estimating the internal state of the compressor 1 by estimating the rotation speed.

Since each phase current (I _U , I _V , I _W ) is a measured value from the stationary coordinate system, a change in the rotation angle θ of the rotor of the motor 11 appears. Therefore, if the rotation angle θ changes due to the influence of electrical noise, the influence may appear in each phase current (I _U , I _V , I _W ). As the electrical noise, for example, electrical noise caused by the frequency of the power supply 6 or electrical noise caused by the drive voltage of the inverter 122 can be cited.

On the other hand, as described above, even if the rotation angle θ changes under the influence of electrical noise, the change does not appear in the dq axis current (I _d , I _q ). The q-axis current I _q changes in magnitude according to the torque output from the motor 11. Therefore, by analyzing the q-axis current _Iq , it is possible to analyze the fluctuation of the torque output from the motor 11 without being affected by the electric noise.

  Therefore, in the embodiment, an abnormality occurring in the compressor 1 is detected by analyzing torque fluctuations in the compressor 1 using the q-axis current. As a result, torque fluctuations in the compressor 1 can be analyzed without being affected by electrical noise, and the accuracy of abnormality detection can be increased.

Figure 3 is a diagram showing together an example of how the time variation of the time change, and q-axis current I _q of U-phase current in the single rotary compressor. In FIG. 3, a solid line C1 represents a change in the U-phase current, and a broken line C2 represents a change in the q-axis current _Iq , both of which are currents corresponding to four revolutions of the rotor of the motor 11 at a compressor drive frequency of 38 Hz. The waveform is shown.

  As shown in FIG. 3, the waveform of the U-phase current is greatly distorted due to the influence of, for example, electrical noise caused by the power supply frequency or electrical noise caused by the inverter drive voltage. On the other hand, in the waveform of the q-axis current, the distortion that appears in the waveform of the U-phase current hardly appears.

FIG. 4 is a diagram showing a torque fluctuation rate when the single rotary compressor is normal. FIG. 4 shows torque fluctuations when the rotation angle θ of the rotor of the motor 11 changes from 0 to 2π, that is, when the rotor makes one revolution. The variation of the q-axis current I _q for one rotation of the rotor shown in FIG. 3 is substantially the same as the variation of the torque for one rotation of the rotor shown in FIG. Therefore, by analyzing the q-axis current I _q , torque fluctuations in the compressor 1 can be analyzed without being affected by electrical noise.

  Referring again to FIG. 2, abnormality detection unit 52 includes an FFT analysis unit 521, a comparison unit 522, an estimation unit 523, a notification unit 524, and a setting unit 525. The FFT analysis unit 521, the comparison unit 522, the estimation unit 523, the notification unit 524, and the setting unit 525 are realized by executing a program stored in the memory 53 by a computer such as a CPU (Central Processing Unit). Alternatively, it may be realized by dedicated hardware.

  The FFT analysis unit 521 receives the q-axis current from the inverter control unit 51. The FFT analysis unit 521 performs analysis by a fast Fourier transform (FFT) on the q-axis current. The FFT analysis unit 521 outputs, for example, spectrum diagram data to the memory 53 and the comparison unit 522 as a result of the FFT analysis.

The comparison unit 522 is based on the FFT analysis result from the FFT analysis unit 521, for example, the driving frequency of the compressor 1 in the spectrum diagram, or a value indicating the strength of the n-order component of the driving frequency (hereinafter also simply referred to as “strength”). And the reference value L _th stored in the memory 53, and the comparison result is output to the estimation unit 523.

  The estimation unit 523 estimates an abnormality that has occurred in the compressor 1 based on the comparison result received from the comparison unit 522. For example, the estimation unit 523 estimates an abnormality that has occurred in the compressor 1 based on whether the intensity exceeding the reference value corresponds to the drive frequency component or the n-order component of the drive frequency. The estimation unit 523 outputs the abnormality estimation result to the notification unit 524.

  The notification unit 524 notifies the user that an abnormality has occurred in the compressor based on the estimation result received from the estimation unit 523. Examples of the notification method include a method of displaying a warning message on a monitor (not shown), a method of emitting a warning sound or a warning message from a speaker (not shown), and a method of lighting a lamp (not shown).

The setting unit 525 sets the reference value L _th based on the history of the result of the FFT analysis of the q-axis current stored in the memory 53. For example, setting unit 525 sets the average value of the results of FFT analysis of a given period, or a maximum value as the reference value L _th.

  FIG. 5 is a spectrum diagram showing an FFT analysis result by the FFT analysis unit 521 in FIG. The spectrum diagram shown in FIG. 5 is a spectrum diagram when the drive frequency is 78 Hz.

The intensities L1 and L2 corresponding to 78 Hz, which is the driving frequency of the compressor 1, and 156 Hz, which is the secondary component thereof, are analysis results of the q-axis current _Iq , and thus are hardly affected by electrical noise. Therefore, as shown in FIG. 5, by determining whether the intensity L1 and L2 exceeds the reference value L _th, it is possible to improve the detection accuracy of the compressor 1 abnormality.

Also, when analyzing the shape of the U-phase current waveform to detect an abnormality in the compressor 1, the U-phase current in which a change in mechanical angle appears as a change in electrical angle eliminates the influence of electrical noise. Analyzing is often difficult. However, if the FFT analysis of the q-axis current I _{q which is} not easily affected by electrical noise, a detailed analysis for each frequency component is possible. For example, in FIG. 5, maximum values of intensity are also generated at frequencies of 50 Hz, 100 Hz, and 200 Hz. These are maximum values corresponding to the frequency of the power source 6 and the n-order component of the frequency. As shown in FIG. 5, the frequency of the power source 6 and the n-order component of the frequency are determined in advance if the frequency of the power source 6 is known in advance. It can be processed separately from the components. As a result, it is possible to analyze the driving frequency of the compressor 1 and the n-order component of the driving frequency.

  Examples of the failure of the air conditioner 100 include stopping of the compressor 1 due to lack of lubricating oil in the compressor 1. The shortage of lubricating oil in the compressor 1 may occur due to the lubricating oil moving to other parts constituting the refrigeration cycle. When the lubricating oil in the compressor 1 is insufficient, metal parts often come into direct contact with each other at the sliding portion of the compressor 1. As a result, the frictional resistance between the metal parts increases to generate frictional heat, and the metal parts may adhere to each other. If the metal parts of the sliding part adhere to each other, it will cause the compressor 1 to stop.

  Abnormalities in the sliding portion of the compressor 1 have a relatively large influence on the torque fluctuation of the compressor 1. In the embodiment, since the q-axis current that is hardly affected by electric noise and changes according to the torque fluctuation in the compressor is analyzed, the accuracy of detecting an abnormality occurring in the sliding portion of the compressor 1 is improved. Can be made.

  For example, when the strength of the drive frequency component of the compressor 1 is increased as a result of the FFT analysis, it can be estimated that the sliding portion inside the compressor 1 is damaged and the frictional resistance is increased. Specifically, the intensity of the driving frequency component of the compressor 1 is continuously recorded, and when the intensity of the driving frequency component of the compressor 1 exceeds the threshold, or the rate of increase per predetermined time exceeds the threshold. In this case, the abnormality of the compressor 1 can be detected.

  Further, as a result of the FFT analysis, when the driving frequency of the compressor 1 or the strength of the n-th order component of the driving frequency exceeds the reference value, an abnormality that affects the torque fluctuation of the compressor 1 may cause a slip of the compressor. It can be estimated that it occurred in the moving part. For example, when a plurality of minute scratches are generated in the sliding portion of the compressor 1, frictional resistance due to the minute scratches occurs a plurality of times during one rotation. Therefore, when the intensity of the n-order component of the driving frequency of the compressor 1 exceeds the reference value in the spectrum diagram, it can be estimated that a minute scratch is generated in the sliding portion of the compressor 1.

  According to the embodiment, it may be possible to detect an abnormality other than the abnormality related to the sliding portion of the compressor 1. For example, since the refrigerant circulates at a substantially constant speed in the air conditioner 100, a phenomenon that the liquid refrigerant is mixed with the refrigerant sucked by the compressor 1 may periodically occur. In such a case, in the spectrum diagram, the strength of the driving frequency component of the compressor 1 often varies every several rotations. Therefore, when the intensity of the drive frequency component of the compressor 1 varies every several revolutions in the spectrum diagram, it can be estimated that the liquid refrigerant is mixed with the refrigerant sucked by the compressor 1. Specifically, for example, the ratio of the average of the driving frequency components generated during 10 revolutions of the compressor 1 and the maximum value of the driving frequency components during 10 revolutions is recorded. When this ratio exceeds the reference value, an abnormality that the liquid refrigerant is mixed with the refrigerant sucked by the compressor 1 can be detected.

  The reference value used for detecting the abnormality of the compressor 1 causes the air conditioner 100 to perform a pseudo operation (learning operation) for the purpose of measuring the q-axis current under various parameter settings related to the refrigeration cycle. Thus, it may be set based on the q-axis current measured during the learning operation. In this case, the air conditioner 100 can switch between a normal operation mode in which normal air conditioning is performed and a learning operation mode in which a learning operation is performed. The parameters included in the parameter setting relating to the refrigeration cycle in the learning operation include, for example, the drive number frequency of the compressor 1, the condensation temperature of the condenser 2, the evaporation temperature of the evaporator 4, or the overheating of the gas refrigerant sucked into the compressor 1. Degrees can be mentioned.

  Further, the compressor 1 may be tested in a state where it is not installed in the air conditioner 100, and the reference value may be set in advance based on the q-axis current measured during the test operation. Alternatively, the reference value may be set in advance to a value calculated from information related to the performance of the compressor 1. Thus, by setting the reference value so as to correspond to the characteristics of the compressor 1, it is possible to detect the abnormality of the compressor 1 with higher accuracy.

When the driving frequency of the compressor 1 is constant, the frequency of the q-axis current I _q is smaller than the frequency of the U-phase current. For example, if the motor 11 is a three-phase six-pole motor, the frequency of the q-axis current is about one-third of the frequency of the U-phase current I _U. When the frequency band that can be analyzed by the FFT analysis unit 521 is limited, the analysis can be performed up to higher-order frequency components when the q-axis current is analyzed than when the U-phase current is analyzed. As a result, the compressor abnormality can be detected with high accuracy.

  As described above, according to the embodiment, it is possible to improve the abnormality detection accuracy of the compressor 1 by analyzing the q-axis current that is hardly affected by the electrical noise.

  The embodiment can be applied regardless of the compression format of the compressor 1. The embodiment can be applied to, for example, a reciprocating compressor, a single rotary compressor, a twin rotary compressor, a scroll compressor, and a helical compressor.

  FIG. 6 is a diagram also showing the torque fluctuation rate during one rotation at the normal time for each compressor type. In FIG. 6, curves R, Sy, T, Sc, and H represent torque fluctuation rates of a reciprocating compressor, a single rotary compressor, a twin rotary compressor, a scroll compressor, and a helical compressor, respectively. As shown in FIG. 6, the amplitude of the torque fluctuation rate of the twin rotary compressor (curve T), the scroll compressor (curve Sc), and the helical compressor (curve H) is the same as that of the reciprocating compressor (curve R) and the single. It is smaller than the amplitude of the torque fluctuation rate of the rotary compressor (curve Sy). Therefore, in the twin rotary compressor, the scroll compressor, and the helical compressor, when an abnormality occurs in the torque fluctuation and the torque of the compressor changes greatly, the torque fluctuation appears more remarkably than in the normal state. Therefore, for example, an abnormality can be easily detected by visually observing the waveform shape. According to the embodiment, in the compression formats of the twin rotary compressor, scroll compressor, and helical compressor, an abnormality occurring in the compressor 1 can be detected more easily than other compression formats.

  The embodiment disclosed this time should be considered as illustrative in all points and not restrictive. The scope of the present invention is defined by the terms of the claims, rather than the description above, and is intended to include any modifications within the scope and meaning equivalent to the terms of the claims.

DESCRIPTION OF SYMBOLS 1 Compressor, 2 Condenser, 3 Expansion valve, 4 Evaporator, 5 Control apparatus, 6 Power supply, 11 Motor, 12 Drive apparatus, 51 Inverter control part, 52 Abnormality detection part, 53 Memory, 100 Air conditioner, 111,112 Current sensor, 113 angle sensor, 121 converter, 122 inverter, 511 phase current calculation unit, 512 Clark conversion unit, 513 park conversion unit, 514 voltage command value calculation unit, 515 output voltage vector calculation unit, 516 signal generation unit, 521 analysis Unit, 522 comparison unit, 523 estimation unit, 524 notification unit, 525 setting unit, I _U , I _V , I _W phase current, I d d axis current, I q q axis current.

Claims (8)

A failure symptom detection device for an air conditioner comprising a compressor including a motor and a drive device configured to output a three-phase current to the motor,
The failure sign detection device is
A converter configured to calculate the q-axis current of the motor from the measured value of the three-phase current and the rotation angle of the rotor of the motor;
By comparing each evaluation value corresponding to the driving frequency of the compressor and harmonics of the driving frequency, which is calculated by performing frequency analysis on the q-axis current, with a reference value, the compressor A failure symptom detection apparatus comprising: an abnormality detection unit configured to detect an abnormality. The abnormality detection unit is configured to perform a fast Fourier transform as the frequency analysis,
The failure symptom detection apparatus according to claim 1, wherein the evaluation value is a value indicating an intensity of a predetermined frequency component in a spectrum obtained by performing the fast Fourier transform.   The failure symptom detection apparatus according to claim 1, wherein the abnormality detection unit is configured to notify a user when an abnormality of the compressor is detected.   The failure symptom detection device according to claim 3, wherein the abnormality detection unit is configured to notify that an abnormality has occurred in the sliding portion of the compressor. A storage unit;
The abnormality detection unit is configured to store a history of the evaluation value in the storage unit and use a value calculated from the evaluation value stored in the history as the reference value. Failure sign detection device. The air conditioner is configured to operate by switching between a normal operation mode and a learning operation mode,
In the learning operation mode, the compressor is driven at each of a plurality of driving frequencies stored in advance in the storage unit,
In the learning operation mode, the abnormality detection unit records each of the plurality of drive frequencies in the history in association with the evaluation value calculated when the compressor is driven at the drive frequency. The fault symptom detection device according to claim 5, configured as described above.   The failure symptom detection apparatus according to claim 5, wherein the reference value is stored in the storage unit in advance as a value corresponding to a characteristic of the compressor. A failure symptom detection device for an air conditioner comprising a compressor including a motor and a drive device configured to output a three-phase current to the motor,
The failure sign detection device is
A converter configured to calculate the q-axis current of the motor from the measured value of the three-phase current and the rotation angle of the rotor of the motor;
An abnormality detection unit configured to detect an abnormality of the compressor by comparing an evaluation value calculated by performing frequency analysis on the q-axis current and a reference value;
The abnormality detection unit is configured to notify that an abnormality has occurred in a sliding portion of the compressor, and is a failure symptom detection device.