State estimation method and state estimation program

Abstract

To prevent an erroneous estimation of the state of an apparatus.SOLUTION: In estimation processing, a control unit (31) estimates the state of an apparatus (70) based on a specific frequency component (C1) of a physical quantity which is obtained from the apparatus (70). In restriction processing, the control unit (31) restricts, when a noise frequency component (Cn) included in the physical quantity and the specific frequency component (C1) satisfy a predetermined relationship, the estimation processing or operation of a motor (50). When a carrier frequency is fc, a frequency for sampling the physical quantity is fs, and an electric angular frequency is f0, the frequency of the noise frequency component (Cn) is represented by one of specific formulas if the physical quantity is a DC signal.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to state estimation techniques. [Background technology]

[0002] Patent Document 1 discloses an abnormality diagnosis device that diagnoses abnormalities in an electric motor driven by pulse width modulation control of a power conversion device. This abnormality diagnosis device includes a detection unit, an analysis unit, a judgment unit, and a frequency setting unit. The detection unit detects a current flowing through the electric motor. The analysis unit performs frequency analysis on the current detected by the detection unit and outputs the analysis result. The judgment unit judges an abnormality in the electric motor based on the spectrum peak of at least one sideband wave component of the modulated wave obtained from the analysis result. The frequency setting unit sets a noise frequency in the current in advance.

[0003] The frequency setting unit calculates the greatest common divisor of two or more frequencies including the modulating wave frequency among the three frequencies used in pulse width modulation control, namely, the modulating wave frequency, the carrier wave frequency, and the sampling frequency for sampling the modulating wave, and sets the greatest common divisor and its integer multiple as the noise frequency. The determination unit estimates the presence or absence of noise interference at the spectrum peak of the sideband wave component based on the frequency of the sideband wave component and the set noise frequency, and determines an abnormality in the motor. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 6824494 Summary of the Invention [Problem to be solved by the invention]

[0005] A state estimation device (a device that estimates the state of an equipment) such as the abnormality diagnosis device of Patent Document 1 can only detect noise frequency components of the above greatest common divisor (greatest common divisor of 2 or more) and its integer multiples, and therefore cannot take into account the influence of noise frequency components of other frequencies than the above greatest common divisor and its integer multiples. Therefore, it is difficult to appropriately suppress erroneous estimation of the state of the equipment. [Means for solving the problem]

[0006] A first aspect of the present disclosure relates to a state estimation method for estimating a state of an equipment (70) equipped with a motor (50), the state estimation method comprising: an estimation step of estimating a state of the equipment (70) based on a magnitude of a specific frequency component (C1) of a signal indicating a physical quantity obtained from the equipment (70); and a limiting step of limiting the estimation step or limiting operation of the motor (50) based on a magnitude of a periodic component included in a variable calculated based on the magnitude of the specific frequency component (C1), the limiting step being a first limiting step of limiting the estimation step so that a predetermined estimation result is output, or a second limiting step of limiting the operation of the motor (50) so that erroneous estimation is not performed in the estimation step.

[0007] A second aspect of the present disclosure relates to a state estimation program that causes a computer to execute the state estimation method of the first aspect. [Brief description of the drawings]

[0008] [Figure 1] FIG. 1 is a circuit diagram illustrating the configuration of a drive system according to the first embodiment. [Diagram 2] FIG. 2 is a schematic diagram illustrating the flow of the control process. [Diagram 3] FIG. 3 is a graph illustrating a specific frequency component and a noise frequency component. [Figure 4] FIG. 4 is a graph illustrating an example of a waveform of a specific frequency component that varies due to a noise frequency component. [Diagram 5] FIG. 5 is a graph illustrating an example of a waveform of a specific frequency component when the frequency difference between the noise frequency component and the specific frequency component is relatively large. [Figure 6] FIG. 6 is a graph illustrating an example of a waveform of a specific frequency component when the frequency difference between the noise frequency component and the specific frequency component is relatively small. [Figure 7] FIG. 7 is a graph illustrating the relationship between the frequency difference between the noise frequency component and the specific frequency component and the fluctuation range of the specific frequency component. [Figure 8] FIG. 8 is a flowchart illustrating a process flow by the control unit of the first embodiment. [Figure 9]FIG. 9 is a graph showing specific examples of specific frequency components and noise frequency components. [Figure 10] FIG. 10 is a graph illustrating a specific frequency band based on the frequency of a specific frequency component. [Figure 11] FIG. 11 is a flowchart illustrating the first estimation process. [Figure 12] FIG. 12 is a flowchart illustrating the second estimation process. [Figure 13] FIG. 13 is a timing chart illustrating the second estimation process. [Figure 14] FIG. 14 is a flowchart illustrating the third estimation process. [Figure 15] FIG. 15 is a timing chart illustrating the third estimation process. [Figure 16] FIG. 16 is a flowchart illustrating the fourth estimation process. [Figure 17] FIG. 17 is a timing chart illustrating the fourth estimation process. [Figure 18] FIG. 18 is a flowchart illustrating a restriction process according to the first modification of the first embodiment. [Figure 19] FIG. 19 is a flowchart illustrating a process flow by the control unit of the second embodiment. [Figure 20] FIG. 20 is a graph for explaining the average value of the amount of change of a specific frequency component within a predetermined time period. [Figure 21] FIG. 21 is a graph illustrating a periodic component extracted from a specific frequency component. [Figure 22] FIG. 22 is a graph for explaining the standard deviation of a specific frequency component within a predetermined time. [Figure 23] FIG. 23 is a graph for explaining the kurtosis of the distribution of a specific frequency component within a predetermined time. [Figure 24] FIG. 24 is a graph for explaining the cumulative value of the absolute value of the difference between a specific frequency component and the average value within a predetermined time period. [Diagram 25]FIG. 25 is a graph for explaining the magnitude of the spectrum energy of the periodic component of a specific frequency component. [Figure 26] FIG. 26 is a graph for explaining the difference between the maximum value and the minimum value of a specific frequency component within a predetermined time period. [Figure 27] FIG. 27 is a schematic diagram illustrating the configuration of a refrigeration system. [Figure 28] FIG. 28 is a schematic diagram illustrating the configuration of a fan system. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0009] Hereinafter, the embodiments will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are designated by the same reference characters and their description will not be repeated.

[0010] (Embodiment 1) FIG. 1 illustrates an example of the configuration of a drive system (10) of the first embodiment. The drive system (10) drives a motor (50) by using power supplied from a power source (60). The motor (50) is mounted on a device (70). For example, the motor (50) is an interior permanent magnet motor (IPM motor). In this example, the power source (60) is an AC power source, and the motor (50) is a three-phase AC motor. The drive system (10) is mounted on a device (70). For example, the device (70) is an outdoor unit of an air conditioner. The drive system (10) includes a motor drive device (20) and a control device (30).

[0011] [Motor drive device] The motor drive device (20) drives the motor (50). Specifically, the motor drive device (20) converts power supplied from a power source (60) into output AC power (in this example, three-phase AC power) having a predetermined frequency and voltage, and supplies the output AC power to the motor (50). In this example, the motor drive device (20) has a converter (21), a DC unit (22), and an inverter (23).

[0012] The converter (21) rectifies the power supplied from the power source (60). In this example, the converter (21) full-wave rectifies the AC power supplied from the power source (60). For example, the converter (21) is formed of a diode bridge circuit in which a plurality of rectifier diodes are connected in a bridge shape.

[0013] The DC unit (22) generates DC power according to the power supply power supplied from the power supply (60). In this example, the DC unit (22) has a capacitor and smoothes the output of the converter (21).

[0014] The inverter (23) has a plurality of switching elements, and converts the output of the DC section (22) into output AC power (three-phase AC power) having a predetermined frequency and voltage by switching operations of the plurality of switching elements.

[0015] In this example, the inverter (23) has six bridge-connected switching elements and six free wheel diodes connected in anti-parallel to each of the six switching elements. More specifically, the inverter (23) has three switching legs, each of which has two switching elements connected in series. The midpoints of the three switching legs (specifically, the connection points between the switching elements on the upper arm side and the switching elements on the lower arm side) are connected to the three windings (U-phase, V-phase, and W-phase windings) of the motor (50), respectively.

[0016] [Various sensors] The motor drive device (20) is provided with various sensors such as a phase current detector (41) and an electrical angular frequency detector (42). Various pieces of information detected by the various sensors are transmitted to the control device (30). Specifically, detection signals of the various sensors are transmitted to a control unit (31) which will be described later.

[0017] The phase current detection unit (41) detects three-phase currents (U-phase current (iu), V-phase current (iv), and W-phase current (iw)) flowing through three windings (not shown) of the motor (50). For example, the phase current detection unit (41) may detect all of the three-phase currents (iu, iv, iw), or may detect two of the three-phase currents (iu, iv, iw) and derive the remaining phase current based on the detected two-phase currents. Furthermore, the phase current detection unit (41) may derive the three-phase currents (iu, iv, iw) from the DC current detected by a shunt resistor (not shown) provided in the DC unit (22) and the switching pattern.

[0018] The electrical angular frequency detection unit (42) detects the electrical angular frequency (ω) of the motor (50). Note that the electrical angular frequency detection unit (42) is not an essential component, and the electrical angular frequency (ω) of the motor (50) may be calculated by another method or estimated in a sensorless manner.

[0019] [Control device (state estimation device)] The control device (30) estimates a state of the equipment (70). The control device (30) is an example of a state estimation device that estimates a state of the equipment (70) equipped with the motor (50). The processing in the control device (30) (processing related to estimating the state of the equipment (70)) is an example of a state estimation method that estimates the state of the equipment (70) equipped with the motor (50).

[0020] In this example, the control device (30) estimates the presence or absence of an abnormality in the device (70) and takes measures against the abnormality in the device (70). The control device (30) also controls the motor (50). Specifically, the control device (30) controls the motor (50) by controlling the motor drive device (20).

[0021] [Control Unit] The control device (30) includes a control unit (31). The control unit (31) performs various processes. Specifically, the control unit (31) acquires information and data from each part of the device (70) and performs various processes based on the information and data. The processes performed by the control unit (31) will be described in detail later.

[0022] For example, the control unit (31) includes a processor and a memory electrically connected to the processor and storing a program for operating the processor. The processor executes the program to realize various functions of the control unit (31). The control unit (31) is an example of a computer, and the program is an example of a state estimation program.

[0023] [Processing by the control unit] In this example, the control unit (31) performs a control process, a calculation process, an estimation process, and a countermeasure process. Note that these various processes are examples of various steps. For example, the estimation process is an example of an estimation step.

[0024] [Control Processing] In the control process, the control unit (31) controls the motor drive device (20) to control the motor (50). Specifically, the control unit (31) receives as input a target command value, such as a command value for the electrical angular frequency (ω) of the motor (50), detection signals of various sensors provided in the motor drive device (20), and the like. Based on the target command value, the detection signals of the various sensors, and the like, the control unit (31) controls the switching operation of the inverter (23) to control the AC power supplied from the inverter (23) to the motor (50).

[0025] In this example, the control unit (31) receives a carrier signal indicating a carrier wave and a sampling clock. The carrier wave is a wave whose amplitude fluctuates at a predetermined frequency (carrier frequency). The sampling clock is a signal indicating the timing of sampling.

[0026] As shown in Fig. 2, the control unit (31) generates a modulated wave signal indicative of a modulated wave. The modulated wave is a wave that corresponds to the waveform of an output AC voltage having a predetermined frequency and voltage. The control unit (31) samples an instantaneous value of the modulated wave signal in synchronization with a sampling clock, and compares the instantaneous value of the modulated wave signal obtained by sampling with a carrier signal.

[0027] Then, based on the result of the comparison, the control unit (31) generates a PWM signal that controls the switching operation of the inverter (23). Specifically, when the instantaneous value of the sampled modulated wave signal is higher than the signal level (amplitude value) of the carrier wave signal, the signal level of the PWM signal becomes high, and when the instantaneous value of the sampled modulated wave signal is lower than the signal level of the carrier wave signal, the signal level of the PWM signal becomes low (e.g., zero).

[0028] The PWM signal generated by the control unit (31) is supplied to a plurality of switching elements included in the inverter (23). The plurality of switching elements included in the inverter (23) are turned on and off in response to the PWM signal, thereby generating output AC power having a predetermined frequency and voltage.

[0029] The frequency of the carrier signal corresponds to the "carrier frequency of the inverter (23)." The inverse of the period for sampling the instantaneous value of the modulated wave signal corresponds to the "frequency for sampling the modulated wave used to control the inverter (23)."

[0030] [Calculation process] In the calculation process, the control unit (31) calculates a specific frequency component (C1) from a physical quantity obtained from the device (70). Specifically, the control unit (31) samples an instantaneous value of the physical quantity at a predetermined sampling period, and calculates the specific frequency component (C1) based on the sampled instantaneous value of the physical quantity. The sampling period is the "period for sampling the physical quantity", and its reciprocal is the "sampling frequency".

[0031] In this example, the control unit 31 derives a specific frequency component C1 of a signal based on the current or voltage of the motor 50. The signal based on the current or voltage of the motor 50 is an example of a physical quantity obtained from the device 70. Specific examples of the signal and the specific frequency component C1 will be described in detail later.

[0032] [Estimation process] In the estimation process, the control unit (31) estimates the state of the equipment (70) based on the specific frequency component (C1) calculated by the calculation process (the specific frequency component (C1) of the physical quantity obtained from the equipment (70)). Then, the control unit (31) outputs the estimation result. In this example, the control unit (31) estimates the presence or absence of an abnormality in the equipment (70) in the estimation process. Also, in the estimation process, the control unit (31) estimates the state of the equipment (70) based on the specific frequency component (C1) of a signal based on the current or voltage of the motor (50). A specific example of the estimation process will be described in detail later.

[0033] [Restriction processing] In the limiting process, the control unit (31) limits the estimation process or the operation of the motor (50) when a noise frequency component (Cn) and a specific frequency component (C1) included in the physical quantity satisfy a predetermined relationship. The limiting process is a first limiting process that limits the estimation process so that a predetermined estimation result is output, or a second limiting process that limits the operation of the motor (50) so that erroneous estimation is not performed in the estimation process. The first limiting process and the second limiting process will be described in detail later.

[0034] In this example (an example in which the presence or absence of an abnormality in the equipment 70 is estimated in the estimation process), the predetermined estimation result is an estimation result that does not indicate that the equipment 70 is abnormal. Examples of the predetermined estimation result include an estimation result that indicates that the equipment 70 is normal, an estimation result that indicates that the state of the equipment 70 is unknown, an estimation result that indicates that the estimation process is prohibited (stopped), an estimation result that was output before the estimation process was restricted (for example, immediately before), and the like.

[0035] [Noise frequency components] Here, the noise frequency component (C1) will be described. Hereinafter, the carrier frequency of the inverter (23) is defined as "f c ” and the sampling frequency, which is the inverse of the period for sampling the physical quantity, is “f s ", and the electrical angular frequency of the motor (50) is "f0."

[0036] When the physical quantity is a DC signal, the noise frequency component (C1) is a frequency represented by any one of the following formulas 1, 2, and 3. When the physical quantity is an AC signal, the noise frequency component (C1) is a frequency represented by any one of the following formulas 4, 5, and 6, under a condition where there is no greatest common divisor of two or more frequencies, including the electrical angular frequency of the motor (50), among the electrical angular frequency of the motor (50), the carrier frequency of the inverter (23), and the frequency for sampling a modulated wave used to control the inverter (23).

[0037]

number

[0038] [Countermeasures] In the estimation process, when the control unit (31) estimates that the state of the device (70) is an “abnormal state”, the control unit (31) performs a countermeasure process. The countermeasure process is a process for dealing with the abnormality of the device (70). For example, the countermeasure process is an output process for outputting first information indicating that the state of the device (70) is an abnormal state.

[0039] Examples of the output process include the following first output process, second output process, third output process, and combinations of these. The first output process is a process of outputting the first information to a display device (not shown) provided on a remote controller or the like, thereby causing the display device to display the first information. The second output process is a process of outputting the first information to a control unit (not shown) that controls the operation of the device (70), thereby causing the control unit to perform an operation to deal with an abnormal state. The third output process is a process of uploading the first information to a data accumulation unit (not shown) on the cloud.

[0040] [Findings Obtained by the Inventors] Next, the findings obtained by the present inventor will be described. As a result of research, the present inventor has found that various noise frequency components can affect the "specific frequency component (C1) used in the estimation process." For example, noise frequency components of frequencies corresponding to the absolute value of the sum or difference of at least two of the frequencies that are integer multiples of the electrical angular frequency of the motor (50), the frequency that is integer multiples of the power supply frequency, the frequency that is integer multiples of the carrier frequency of the inverter (23), and the frequency that is integer multiples of the sampling frequency that samples a physical quantity in the calculation process can affect the specific frequency component (C1).

[0041] Furthermore, as a result of extensive research, the inventors of the present application have found that, among various noise frequency components that can affect the specific frequency component (C1), the effects of the following noise frequency components tend to be particularly significant.

[0042] (1) When the physical quantity is a DC signal, the noise frequency component at a frequency expressed by any one of the following formulas 1, 2, and 3 (2) When the physical quantity is an AC signal, the noise frequency component at a frequency expressed by any one of the following Equations 4, 5, and 6

[0043]

number

[0044] The formulas 2 and 5 show |Mfs -6Nf0|" corresponds to the frequency associated with aliasing that occurs when sampling a frequency component that is six times the electrical angular frequency of the motor (50). s "-|fc±6Nf0||" corresponds to the frequency associated with aliasing that occurs when sampling the frequency component of the frequency equivalent to the difference between the "carrier frequency of the inverter (23)" and the "frequency 6N times the electrical angular frequency of the motor (50)." Note that 6Nf0 is the spatial harmonic of the motor, and has the characteristic that the larger the value of N, the smaller the amplitude of the noise frequency components. Also, the larger f0 is, the more sparsely the frequency spacing of the noise frequency components becomes.

[0045] In this specification, a noise frequency component having a frequency expressed by any one of the above formulas 1 to 6 is referred to as a "noise frequency component (Cn)."

[0046] Furthermore, the influence of the noise frequency component (Cn) appears in the magnitude (amplitude) of the specific frequency component (C1). In other words, the noise frequency component (Cn) can fluctuate the magnitude of the specific frequency component (C1). For example, as shown in Fig. 3, when the noise frequency component (Cn) occurs near the specific frequency component (C1), as shown in Fig. 4, the calculated magnitude of the noise frequency component (Cn) fluctuates with a period (1 / X) represented by the reciprocal of the frequency difference (X) between the noise frequency component (Cn) and the specific frequency component (C1).

[0047] In addition, the smaller the difference between the noise frequency component (Cn) and the specific frequency component (C1), the greater the amplitude fluctuation of the specific frequency component (C1) due to the influence of the noise frequency component (Cn). For example, Fig. 5 illustrates the waveform of the specific frequency component (C1) when the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) is relatively large, and Fig. 6 illustrates the waveform of the specific frequency component (C1) when the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) is relatively small. In the example of Fig. 5, the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) is 3 Hz, and in the example of Fig. 6, the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) is 0.2 Hz.

[0048] Furthermore, the inventors of the present application have found, as a result of intensive research, that when the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) is 3 Hz, the "fluctuation width of the specific frequency component (C1) when the noise frequency component (Cn) is influencing" is 10% or less of the "amplitude of the specific frequency component (C1) when the noise frequency component (Cn) is not influencing". FIG. 7 illustrates the relationship between the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) and the fluctuation width of the specific frequency component (C1). In the example of FIG. 7, the fluctuation width of the specific frequency component (C1) is shown as a value obtained by dividing the difference between the maximum and minimum values ​​of the amplitude of the specific frequency component (C1) by 2. Also, the dashed line L10 shown in FIG. 7 indicates 10% of the amplitude of the specific frequency component (C1) when the noise frequency component (Cn) is not influencing.

[0049] [Processing flow by the control unit] Next, with reference to FIG. 8, a flow of processes (specifically, a calculation process, an estimation process, and a limiting process) performed by the control unit (31) will be described.

[0050] The control unit (31) performs a calculation process at each predetermined calculation time. The calculation process is repeated to calculate the specific frequency component (C1) at each calculation time. For example, the calculation time is set to a time equal to or longer than the time required to calculate the specific frequency component (C1) from the physical quantity obtained from the device (70).

[0051] Then, the control unit (31) performs an estimation process based on the specific frequency component (C1) calculated by the calculation process for each predetermined estimation time. The estimation process is repeated to obtain an estimation result for each estimation time. The estimation time is set to a time equal to or longer than the calculation time. For example, the estimation time is set to a time equal to or longer than the time required to estimate the state of the device (70) based on the specific frequency component (C1) calculated by the calculation process.

[0052] Furthermore, the control unit (31) performs a limiting process in parallel with the calculation process and the estimation process. Specifically, the control unit (31) repeatedly performs the processes of steps (S101 to S104) shown in FIG.

[0053] <Step (S101)> The control unit (31) derives a noise frequency component (Cn). For example, the control unit (31) calculates the noise frequency component (Cn) based on a predetermined calculation formula (specifically, any one of formulas 1 to 6). The control unit (31) also acquires a specific frequency component (C1) calculated by the calculation process. Then, the control unit (31) determines whether the noise frequency component (Cn) and the specific frequency component (C1) satisfy a predetermined relationship.

[0054] In this example, the predetermined relationship is that the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) is equal to or less than the frequency difference threshold. For example, the frequency difference threshold is set to 3 Hz. The control unit (31) determines whether the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) is equal to or less than the frequency difference threshold.

[0055] When the noise frequency component (Cn) and the specific frequency component (C1) satisfy the predetermined relationship, the process of step (S102) is performed. For example, the process of step (S101) is performed at every predetermined judgment time. In other words, the process of step (S101) is repeatedly performed until the noise frequency component (Cn) and the specific frequency component (C1) satisfy the predetermined relationship.

[0056] <Step (S102)> When the noise frequency component (Cn) and the specific frequency component (C1) satisfy a predetermined relationship, the control unit (31) limits the estimation process or the operation of the motor (50).

[0057] <Step (S103)> Next, the control unit (31) determines whether or not a restriction release condition is satisfied. Examples of the restriction release condition include a condition that the noise frequency component (Cn) and the specific frequency component (C1) do not satisfy a predetermined relationship, a condition that the control unit (31) receives a release command, etc. The release command is transmitted from an operation unit (not shown) to the control unit (31) when an operator inputs an operation to release the restriction to the operation unit.

[0058] When the restriction release condition is satisfied, the process of step (S104) is performed. For example, the process of step (S103) is performed at every predetermined determination time. In other words, the process of step (S103) is repeatedly performed until the restriction release condition is satisfied.

[0059] <Step (S104)> When the restriction removal condition is met, the control unit (31) removes the restriction (restriction on the estimation process or restriction on the operation of the motor (50)).

[0060] [Specific examples of specific frequency components and noise frequency components] Next, specific examples of the specific frequency components and the noise frequency components will be described with reference to Fig. 9. In the example of Fig. 9, there are two types of specific frequency components (C1) and a mechanical angular frequency (f m ) is 83.1Hz, the motor's electrical angular frequency (f0) is 332.4Hz, and the carrier frequency (f c ) is 5900Hz.

[0061] In the example of Fig. 9, two specific frequency components (C1) appear symmetrically with respect to the motor's electrical angular frequency (f0), and a noise frequency component (Cn) appears near each of the two specific frequency components (C1). One specific frequency component (C1) is 249.3 Hz, and one noise frequency component (Cn) located near the first specific frequency component (C1) has a frequency of 249.2 Hz. The other specific frequency component (C1) is 415.5 Hz, and the other noise frequency component (Cn) located near the other specific frequency component (C1) has a frequency of 415.6 Hz. In this example, the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) is 0.1 Hz, so that the estimation process or the operation of the motor (50) is restricted in the restriction process.

[0062] In this way, in the first embodiment, it is possible to take into consideration the influence of noise frequency components (C1) of frequencies other than the "greatest common divisor (greatest common divisor of 2 or more) disclosed in Patent Document 1 and frequencies that are integer multiples thereof." On the other hand, the abnormality diagnosis device of Patent Document 1 cannot take into consideration the influence of the above-mentioned noise frequency components (C1).

[0063] [Advantages of the First Embodiment] As described above, in the first embodiment, the control unit (31) restricts the estimation process or the operation of the motor (50) in the restriction process when the noise frequency component (Cn) and the specific frequency component (C1) included in the physical quantity satisfy a predetermined relationship. When the physical quantity is a DC signal, the noise frequency component (Cn) is a frequency expressed by any one of the following formulas 1, 2, and 3, and when the physical quantity is an AC signal, the noise frequency component (Cn) is a frequency expressed by any one of the following formulas 4, 5, and 6 under a condition where there is no greatest common divisor of two or more frequencies including the electrical angle frequency among the electrical angle frequency, the carrier frequency, and the frequency for sampling the modulated wave used to control the inverter (23).

[0064]

number

[0065] In the above configuration, the noise frequency component (Cn) having a frequency expressed by any one of the above formulas 1 to 6 is a frequency component that can affect the specific frequency component (C1). Therefore, in the restriction process, the estimation process or the operation of the motor (50) is restricted based on the relationship between the noise frequency component (Cn) and the specific frequency component (C1), thereby making it possible to suppress erroneous estimation of the state of the equipment (70). In this example, it is possible to prevent the equipment (70) from being erroneously estimated as having an abnormality, thereby making it possible to prevent the equipment (70) from being erroneously estimated as having an abnormality.

[0066] In the first embodiment, the influence of noise frequency components of frequencies other than the "greatest common divisor (greatest common divisor of 2 or more) disclosed in Patent Document 1 and its integer multiples" can be taken into consideration. This makes it possible to appropriately suppress erroneous estimation of the state of the device (70).

[0067] In the first embodiment, the predetermined relationship is that the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) is equal to or smaller than a predetermined frequency difference threshold. This makes it possible to suppress erroneous estimation of the state of the equipment (70) by restricting the estimation process or the operation of the motor (50) based on the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1).

[0068] In the first embodiment, the frequency difference threshold is 3 Hz. This makes it possible to restrict the estimation process or the operation of the motor (50) when the "fluctuation range of the specific frequency component (C1) when it is affected by the noise frequency component (Cn)" is greater than 10% of the "amplitude of the specific frequency component (C1) when it is not affected by the noise frequency component (Cn)." As a result, it is possible to appropriately suppress erroneous estimation of the state of the equipment (70).

[0069] (Modification of the specified relationship) In addition, the predetermined relationship between the noise frequency component (Cn) and the specific frequency component (C1) that is determined in step (S101) to be satisfied or not is not limited to the relationship that the frequency difference between the noise frequency component (Cn) and the specific frequency component (C1) is equal to or less than the frequency difference threshold value.

[0070] For example, as shown in Fig. 10, the above-mentioned predetermined relationship may be a relationship in which a noise frequency component (Cn) is included in a specific frequency band (FR) based on the frequency of a specific frequency component (C1). In step (S101), the control unit (31) may determine whether or not a noise frequency component (Cn) is included in the specific frequency band (FR) based on the frequency of the specific frequency component (C1).

[0071] The specific frequency band (FR) may be set to a frequency band centered on the frequency of the specific frequency component (C1) and having a bandwidth of 6 Hz. By setting it in this way, it is possible to restrict the estimation process or the operation of the motor (50) when the "fluctuation width of the specific frequency component (C1) when it is affected by the noise frequency component (Cn)" is greater than 10% of the "amplitude of the specific frequency component (C1) when it is not affected by the noise frequency component (Cn)."

[0072] (Examples of signals) Next, a specific example of a "signal based on the current or voltage of the motor (50)" will be described, which is an example of a physical quantity obtained from the device (70). This signal is roughly classified into a DC signal and an AC signal.

[0073] [Examples of DC signals] Examples of DC signals include a "signal correlating to the phase currents (iu, iv, iw) of the motor (50)," a "signal correlating to the phase voltages (Vu, Vv, Vw) of the motor (50)," and a "signal correlating to the power of the motor (50)."

[0074] Other examples of DC signals include "currents (iγ, iδ) obtained by coordinate transformation of the phase currents (iu, iv, iw) of the motor (50) with the phase (ωi·t) of the phase currents (iu, iv, iw) of the motor (50)" and "voltages (Vγ, Vδ) obtained by coordinate transformation of the phase voltages (Vu, Vv, Vw) of the motor (50) with the phase (ωv·t) of the phase voltages (Vu, Vv, Vw) of the motor (50)." )”, “currents (iζ, iη) obtained by coordinate transforming the phase currents (iu, iv, iw) of the motor (50) with the phase (ωv·t) of the phase voltages (Vu, Vv, Vw) of the motor (50)”, and “voltages (Vζ, Vη) obtained by coordinate transforming the phase voltages (Vu, Vv, Vw) of the motor (50) with the phase (ωi·t) of the phase currents (iu, iv, iw) of the motor (50)”.

[0075] Further examples of DC signals include "dq-axis magnetic flux (λd, λq) coordinate-transformed to match the armature flux linkage caused by a permanent magnet" and "the magnitude λ0 of the armature flux linkage vector resulting from the combination of the armature flux linkage of the permanent magnet and the armature reaction."

[0076] In the following description, the term "phase currents (iu, iv, iw) of the motor (50)" refers to the phase currents (iu, iv, iw) of the motor (50) detected by the phase current detection unit (41). The term "phase voltages (Vu, Vv, Vw) of the motor (50)" refers to the phase voltages (Vu, Vv, Vw) of the motor (50) indicated in a voltage command value used inside the control unit (31) or the phase voltages (Vu, Vv, Vw) of the motor (50) detected by a phase voltage detection unit (not shown) provided in the motor drive device (20). The term "electrical angular frequency (ω) of the motor (50)" refers to the electrical angular frequency (ω) of the motor (50) detected by the electrical angular frequency detection unit (42).

[0077] [1. Specific examples of signals correlated with motor phase currents] Specific examples of signals correlated with the phase currents (iu, iv, iw) of the motor (50) include the current vector amplitude (Ia), the square of the current vector amplitude (Ia 2 ), phase current amplitude (I), and phase current effective value (Irms).

[0078] In addition, the current vector amplitude (Ia) and the square value of the current vector amplitude (Ia 2 ) is an example of a value proportional to the sum of the squares of the three phase currents (iu, iv, iw) of the motor (50). The value proportional to the sum of the squares of the three phase currents (iu, iv, iw) of the motor (50) is an example of a value proportional to an integer power of the magnitude of the phase currents (iu, iv, iw) of the motor (50).

[0079] (1) Current vector amplitude The current vector amplitude (Ia) is derived based on the phase currents (iu, iv, iw) of the motor (50). The current vector amplitude (Ia) may also be derived based on an α-phase current (iα) and a β-phase current (iβ) obtained by transforming the phase currents (iu, iv, iw) of the motor (50) into a fixed coordinate system. The current vector amplitude (Ia) may also be derived based on an M-axis current (iM) and a T-axis current (iT) obtained by coordinate transforming the phase currents (iu, iv, iw) of the motor (50) by an angle based on the direction of the primary magnetic flux. The current vector amplitude (Ia) may also be derived based on a d-axis current (id) and a q-axis current (iq) obtained by coordinate transforming the phase currents (iu, iv, iw) of the motor (50) by an angle based on the direction of the magnetic pole position. Specifically, the current vector amplitude (Ia) can be expressed as follows:

[0080]

number

[0081] (2) Square value of the current vector amplitude The squared value of the current vector magnitude (Ia 2 ) is derived based on the phase currents (iu, iv, iw) of the motor (50). 2 ) may be derived based on an α-phase current (iα) and a β-phase current (iβ) obtained by transforming the phase currents (iu, iv, iw) of the motor (50) into a fixed coordinate system. 2) may be derived based on the M-axis current (iM) and the T-axis current (iT) obtained by coordinate transformation of the phase currents (iu, iv, iw) of the motor (50) by an angle based on the direction of the primary magnetic flux. 2 ) may be derived based on the d-axis current (id) and the q-axis current (iq) obtained by coordinate transformation of the phase currents (iu, iv, iw) of the motor (50) by an angle based on the orientation of the magnetic pole position. Specifically, the square value of the current vector amplitude (Ia 2 ) can be expressed as the following formula:

[0082]

number

[0083] (3) Phase current amplitude The phase current amplitude (I) is derived based on one of the phase currents (iu, iv, iw) of the motor (50), for example, the U-phase current (iu), and the phase current phase (ωi). The phase current phase (ωi) is derived based on the phase currents (iu, iv, iw) of the motor (50), for example. Specifically, the phase current amplitude (I) can be expressed by the following equation.

[0084]

number

[0085] (4) Phase current effective value The phase current effective value (Irms) is derived based on the phase current amplitude (I). Specifically, the phase current effective value (Irms) can be expressed as follows:

[0086]

number

[0087] (5)Other In the above description, an example has been given in which the current vector amplitude (Ia) is derived based on the three-phase currents (iu, iv, iw) of the motor (50). However, the current vector amplitude (Ia) may be derived based on two of the three-phase currents (iu, iv, iw) of the motor (50). The current vector amplitude (Ia) may also be derived based on a DC current of the inverter (23) detected by a DC current detection unit (e.g., a shunt resistor, not shown) provided in the motor drive device (20). The square value of the current vector amplitude (Ia 2 ) is also similar.

[0088] [2. Specific examples of signals correlated with motor phase voltages] Specific examples of signals correlated with the phase voltages (Vu, Vv, Vw) of the motor (50) include the voltage vector amplitude (Va), the squared value of the voltage vector amplitude (Va 2 ), phase voltage amplitude (V), and phase voltage effective value (Vrms).

[0089] In addition, the voltage vector amplitude (Va) and the squared value of the voltage vector amplitude (Va 2 ) is an example of a value proportional to the sum of the squares of the three phase voltages (Vu, Vv, Vw) of the motor (50). The value proportional to the sum of the squares of the three phase voltages (Vu, Vv, Vw) of the motor (50) is an example of a value proportional to an integer power of the magnitude of the phase voltages (Vu, Vv, Vw) of the motor (50).

[0090] (1) Voltage Vector Amplitude The voltage vector amplitude (Va) is derived based on the phase voltages (Vu, Vv, Vw) of the motor (50). The voltage vector amplitude (Va) may be derived based on an α-phase voltage (Vα) and a β-phase voltage (Vβ) obtained by transforming the phase voltages (Vu, Vv, Vw) of the motor (50) into a fixed coordinate system. The voltage vector amplitude (Va) may be derived based on an M-axis voltage (VM) and a T-axis voltage (VT) obtained by coordinate transforming the phase voltages (Vu, Vv, Vw) of the motor (50) by an angle based on the direction of the primary magnetic flux. The voltage vector amplitude (Va) may be derived based on a d-axis voltage (Vd) and a q-axis voltage (Vq) obtained by coordinate transforming the phase voltages (Vu, Vv, Vw) of the motor (50) by an angle based on the direction of the magnetic pole position. Specifically, the voltage vector amplitude (Va) can be expressed as follows:

[0091]

number

[0092] (2) Squared value of voltage vector amplitude Voltage vector magnitude squared value (Va 2 ) is derived based on the phase voltages (Vu, Vv, Vw) of the motor (50). 2 ) may be derived based on an α-phase voltage (Vα) and a β-phase voltage (Vβ) obtained by transforming the phase voltages (Vu, Vv, Vw) of the motor (50) into a fixed coordinate system. 2 ) may be derived based on the M-axis voltage (VM) and the T-axis voltage (VT) obtained by coordinate transformation of the phase voltages (Vu, Vv, Vw) of the motor (50) by an angle based on the direction of the primary magnetic flux. 2 ) may be derived based on the d-axis voltage (Vd) and the q-axis voltage (Vq) obtained by coordinate transformation of the phase voltages (Vu, Vv, Vw) of the motor (50) by an angle based on the orientation of the magnetic pole position. 2 ) can be expressed as the following formula:

[0093]

number

[0094] (3) Phase voltage amplitude The phase voltage amplitude (V) is derived based on one of the phase voltages (Vu, Vv, Vw) of the motor (50), for example, the U-phase voltage (Vu), and the phase voltage phase (ωv). The phase voltage phase (ωv) is derived based on the phase voltages (Vu, Vv, Vw) of the motor (50), for example. Specifically, the phase voltage amplitude (V) can be expressed by the following equation.

[0095]

number

[0096] (4) Phase voltage effective value The phase voltage effective value (Vrms) is derived based on the phase voltage amplitude (V). Specifically, the phase voltage effective value (Vrms) can be expressed as follows:

[0097]

number

[0098] (5)Other In the above description, an example has been given in which the voltage vector amplitude (Va) is derived based on the three-phase voltages (Vu, Vv, Vw) of the motor (50), but the voltage vector amplitude (Va) may be derived based on two of the three-phase voltages (Vu, Vv, Vw) of the motor (50). 2 ) is also similar.

[0099] [3. Specific examples of signals correlated with motor power] Examples of signals correlated to the power of the motor (50) include instantaneous power (p), instantaneous imaginary power (q), apparent power (S), active power (P), and reactive power (Q).

[0100] (1) Instantaneous power The instantaneous power (p) is derived based on the phase currents (iu, iv, iw) of the motor (50) and the phase voltages (Vu, Vv, Vw) of the motor (50). Alternatively, the instantaneous power (p) may be derived based on an α-phase current (iα) and a β-phase current (iβ) obtained by transforming the phase currents (iu, iv, iw) of the motor (50) into a fixed coordinate system, and an α-phase voltage (Vα) and a β-phase voltage (Vβ) obtained by transforming the phase voltages (Vu, Vv, Vw) of the motor (50) into the fixed coordinate system. The instantaneous power (p) may be derived based on an M-axis current (iM) and a T-axis current (iT) obtained by coordinate transforming the phase currents (iu, iv, iw) of the motor (50) by an angle based on the direction of the primary magnetic flux, and an M-axis voltage (VM) and a T-axis voltage (VT) obtained by coordinate transforming the phase voltages (Vu, Vv, Vw) of the motor (50) by an angle based on the direction of the primary magnetic flux. The instantaneous power (p) may be derived based on a d-axis current (id) and a q-axis current (iq) obtained by coordinate transforming the phase currents (iu, iv, iw) of the motor (50) by an angle based on the direction of the magnetic pole position, and a d-axis voltage (Vd) and a q-axis voltage (Vq) obtained by coordinate transforming the phase voltages (Vu, Vv, Vw) of the motor (50) by an angle based on the direction of the magnetic pole position. Specifically, the instantaneous power (p) can be expressed as follows:

[0101]

number

[0102] (2) Instantaneous reactive power The instantaneous imaginary power (q) is derived based on an α-phase current (iα) and a β-phase current (iβ) obtained by transforming the phase currents (iu, iv, iw) of the motor (50) into a fixed coordinate system, and an α-phase voltage (Vα) and a β-phase voltage (Vβ) obtained by transforming the phase voltages (Vu, Vv, Vw) of the motor (50) into a fixed coordinate system. The instantaneous imaginary power (q) may also be derived based on an M-axis current (iM) and a T-axis current (iT) obtained by coordinate transforming the phase currents (iu, iv, iw) of the motor (50) by an angle based on the direction of the primary magnetic flux, and an M-axis voltage (VM) and a T-axis voltage (VT) obtained by coordinate transforming the phase voltages (Vu, Vv, Vw) of the motor (50) by an angle based on the direction of the primary magnetic flux. In addition, the instantaneous imaginary power (q) may be derived based on a d-axis current (id) and a q-axis current (iq) obtained by coordinate transforming the phase currents (iu, iv, iw) of the motor (50) by an angle based on the orientation of the magnetic pole position, and a d-axis voltage (Vd) and a q-axis voltage (Vq) obtained by coordinate transforming the phase voltages (Vu, Vv, Vw) of the motor (50) by an angle based on the orientation of the magnetic pole position. Specifically, the instantaneous imaginary power (q) can be expressed by the following equation.

[0103]

number

[0104] (3) Apparent power The apparent power (S) is derived based on the phase voltage effective value (Vrms) and the phase current effective value (Irms). Specifically, the apparent power (S) can be expressed by the following equation.

[0105]

number

[0106] (4) Active power The active power (P) is derived based on the phase voltage effective value (Vrms), the phase current effective value (Irms), and the phase difference (φ1) between the phase voltage and the phase current. The phase difference (φ1) between the phase voltage and the phase current is the phase difference between one phase voltage (e.g., U-phase voltage (Vu)) and one phase current (e.g., U-phase current (iu)), and is derived based on the phase (ωi) of the phase current and the phase (ωv) of the phase voltage. Specifically, the active power (P) can be expressed as follows:

[0107]

number

[0108] (5) Reactive power The reactive power (Q) is derived based on the phase voltage effective value (Vrms), the phase current effective value (Irms), and the phase difference (φ1) between the phase voltage and the phase current. The phase difference (φ1) between the phase voltage and the phase current is, for example, the phase difference between the U-phase voltage (Vu) and the U-phase current (iu), and is derived based on the phase (ωi) of the phase current and the phase (ωv) of the phase voltage. Specifically, the reactive power (Q) can be expressed as the following equation.

[0109]

number

[0110] [4. Current obtained by coordinate transformation of phase current with the phase current phase] Currents (iγ, iδ) obtained by coordinate transformation of the phase currents (iu, iv, iw) of the motor (50) using the phase (ωi·t) of the phase currents (iu, iv, iw) of the motor (50) can be expressed by the following equation.

[0111]

number

[0112] [5. Voltage obtained by coordinate transformation of phase voltage with the phase voltage phase] Voltages (Vγ, Vδ) obtained by coordinate transformation of the phase voltages (Vu, Vv, Vw) of the motor (50) using the phase (ωv·t) of the phase voltages (Vu, Vv, Vw) of the motor (50) can be expressed by the following equation.

[0113]

number

[0114] [6. Current obtained by coordinate transformation of phase current with phase voltage] Currents (iζ, iη) obtained by coordinate transformation of the phase currents (iu, iv, iw) of the motor (50) using the phase (ωv·t) of the phase voltages (Vu, Vv, Vw) of the motor (50) can be expressed by the following equations.

[0115]

number

[0116] [7. Voltage obtained by converting the phase voltage into the phase current] Voltages (Vζ, Vη) obtained by coordinate transformation of the phase voltages (Vu, Vv, Vw) of the motor (50) using the phase (ωi·t) of the phase currents (iu, iv, iw) of the motor (50) can be expressed by the following equations.

[0117]

number

[0118] [6. Magnitude of dq-axis magnetic flux and armature interlinkage magnetic flux vector] The dq-axis magnetic flux (λd, λq) transformed into coordinates according to the armature flux linkage caused by the permanent magnet, and the magnitude λ0 of the armature flux linkage vector which is the composite of the armature flux linkage of the permanent magnet and the armature reaction, can be expressed as follows. In the following equation, "Ld" is the d-axis inductance, and "Lq" is the q-axis inductance.

[0119]

number

[0120] [7. Other examples of DC signals] The DC signal may be a DC signal obtained by performing three-phase to two-phase conversion on the phase current, phase voltage, line current, or line voltage of the motor (50) and further performing rotational coordinate conversion. For example, the DC signal may be a d-axis current and a q-axis current obtained by performing rotational coordinate conversion on an angle based on the orientation of the magnetic poles of the rotor of the motor (50) using an α-axis current and a β-axis current obtained by performing three-phase to two-phase conversion on the phase current of the motor (50). The DC signal may be an M-axis current and a T-axis current obtained by performing rotational coordinate conversion on the α-axis current and the β-axis current using an angle based on the orientation of the primary magnetic flux of the rotor of the motor (50).

[0121] In addition, the DC signal may be power input to the converter (21) of the motor drive device (20), power output from the converter (21), power output from the DC section (22), a current flowing between the converter (21) and the DC section (22), a current flowing between the DC section (22) and the inverter (23), etc.

[0122] [Examples of AC signals] Examples of the AC signals include “phase currents (iu, iv, iw) of the motor (50)”, “phase voltages (Vu, Vv, Vw) of the motor (50)”, and “flux linkage of each phase (Ψfu, Ψfv, Ψfw)”.

[0123] The interlinkage magnetic flux of each phase (Ψfu, Ψfv, Ψfw) can be expressed as follows:

[0124]

number

[0125] Another example of the AC signal is a current or voltage flux linkage of fixed coordinates obtained by three-phase to two-phase conversion of the AC signal.

[0126] The AC signal may be a line current, a line voltage, or the like of the motor (50). The AC signal may be a two-phase AC current (e.g., an α-axis current and a β-axis current) or a two-phase AC voltage obtained by three-phase to two-phase conversion of a phase current, a phase voltage, a line current, or a line voltage. The AC current may be a current flowing between a commercial power supply system (specifically, the AC power supply (60)) and the converter (21) of the motor drive device (20).

[0127] (Examples of specific frequency components) Next, a specific example of the specific frequency component will be described.

[0128] For example, when the physical quantity is a DC signal, the frequency of the specific frequency component (C1) is at least one of 1, 1 / 3, and 2 / 3 times the mechanical angular frequency of the motor (50). When the physical quantity is an AC signal, the frequency of the specific frequency component (C1) is at least one of a frequency obtained by adding a predetermined frequency to the electrical angular frequency of the motor (50), a frequency obtained by subtracting a predetermined frequency from the electrical angular frequency of the motor (50), and three times the electrical angular frequency of the motor (50). The predetermined frequency is one of 1, 1 / 3, and 2 / 3 times the mechanical angular frequency of the motor (50).

[0129] By setting the frequency of the specific frequency component (C1) as described above, various states (particularly abnormalities) of the device (70) can be estimated.

[0130] (Various equipment conditions) Here, various states of the device (70) will be described. Examples of the states of the device (70) include breakdown of an oil seal in a compression chamber, insulation deterioration of the motor (50), bearing wear, dilution, liquid compression, imbalance, blockage of a flow path, etc. These states of the device (70) are examples of abnormalities of the device (70).

[0131] [1. Compression chamber oil seal failure] The breakdown of the oil seal in the compression chamber is a condition that can occur when the motor (50) is a “motor (50) mounted on a compressor”, and is a condition in which there is a shortage of lubricating oil to seal the compression chamber (not shown) in the compressor.

[0132] When the physical quantity is a DC signal, when an oil seal in a compression chamber breaks down, the frequency component corresponding to one time the mechanical angular frequency of the motor (50) tends to decrease. Therefore, when the physical quantity is a DC signal, by setting the frequency of the specific frequency component (C1) to "one time the mechanical angular frequency of the motor (50)," it is possible to estimate "breakdown of the oil seal in the compression chamber."

[0133] Furthermore, when the physical quantity is an AC signal, when an oil seal in a compression chamber breaks down, there is a tendency for a frequency component corresponding to a frequency obtained by adding "one times the mechanical angular frequency of the motor (50)" to the electrical angular frequency of the motor (50) and a frequency component corresponding to a frequency obtained by subtracting "one times the mechanical angular frequency of the motor (50)" from the electrical angular frequency of the motor (50) to decrease. Therefore, when the physical quantity is an AC signal, by setting the frequency of the specific frequency component (C1) to a frequency obtained by adding "one times the mechanical angular frequency of the motor (50)" to the electrical angular frequency of the motor (50) or a frequency obtained by subtracting "one times the mechanical angular frequency of the motor (50)" from the electrical angular frequency of the motor (50), it is possible to estimate "an oil seal breakage in a compression chamber".

[0134] 2. Deterioration of motor insulation The insulation deterioration of the motor (50) is a state (abnormality) of insufficient insulation performance of the motor (50). As the deterioration of the insulation performance of the motor (50) progresses, the insulation level of the motor (50) falls below an allowable level.

[0135] When the physical quantity is an AC signal, the occurrence of insulation deterioration in the motor (50) tends to increase a frequency component that is three times the electrical angular frequency of the motor (50). Therefore, when the physical quantity is an AC signal, by setting the frequency of the specific frequency component (C1) to "three times the electrical angular frequency of the motor (50)," it is possible to estimate "insulation deterioration of the motor (50)."

[0136] 3. Bearing wear Bearing wear is a state (abnormality) in which the rotating shaft rotated by the motor (50) or the bearings of the rotating shaft wear out.

[0137] When the physical quantity is a DC signal, the occurrence of bearing wear tends to increase frequency components that correspond to 1 / 3 and 2 / 3 times the mechanical angular frequency of the motor (50). Therefore, when the physical quantity is a DC signal, "bearing wear" can be estimated by setting the frequency of the specific frequency component (C1) to "at least one of 1 / 3 and 2 / 3 times the mechanical angular frequency of the motor (50)."

[0138] Furthermore, in the case where the physical quantity is an AC signal, when bearing wear occurs, there tends to be an increase in a frequency component corresponding to a frequency obtained by adding "1 / 3 times the mechanical angular frequency of the motor (50)" to the electrical angular frequency of the motor (50), a frequency component corresponding to a frequency obtained by subtracting "1 / 3 times the mechanical angular frequency of the motor (50)" from the electrical angular frequency of the motor (50), a frequency component corresponding to a frequency obtained by adding "2 / 3 times the mechanical angular frequency of the motor (50)" to the electrical angular frequency of the motor (50), and a frequency component corresponding to a frequency obtained by subtracting "2 / 3 times the mechanical angular frequency of the motor (50)" from the electrical angular frequency of the motor (50). Therefore, when the physical quantity is an AC signal, the “bearing wear” can be estimated by setting the frequency of the specific frequency component (C1) to a frequency obtained by adding “1 / 3 times the mechanical angular frequency of the motor (50)” to the electrical angular frequency of the motor (50), a frequency obtained by subtracting “1 / 3 times the mechanical angular frequency of the motor (50)” from the electrical angular frequency of the motor (50), a frequency obtained by adding “2 / 3 times the mechanical angular frequency of the motor (50)” to the electrical angular frequency of the motor (50), or a frequency obtained by subtracting “2 / 3 times the mechanical angular frequency of the motor (50)” from the electrical angular frequency of the motor (50).

[0139] [4. Dilution] Dilution is a state (abnormality) that can occur when the motor (50) is a "motor (50) mounted on a compressor," and is a state in which the oil concentration in the compressor is insufficient. When dilution occurs, friction at the bearings (not shown) in the compressor increases, leading to wear of the bearings. Furthermore, when dilution occurs, the sliding parts (not shown) in the compressor run out of lubricating oil, causing friction and leading to surface roughness of the sliding parts.

[0140] When the physical quantity is a DC signal, the occurrence of dilution tends to decrease the frequency component corresponding to one time the mechanical angular frequency of the motor (50). Therefore, when the physical quantity is a DC signal, "dilution" can be estimated by setting the frequency of the specific frequency component (C1) to "one time the mechanical angular frequency of the motor (50)."

[0141] Furthermore, when the physical quantity is an AC signal, when dilution occurs, there is a tendency for a frequency component corresponding to a frequency obtained by adding "1x the mechanical angular frequency of the motor (50)" to the electrical angular frequency of the motor (50) and a frequency component corresponding to a frequency obtained by subtracting "1x the mechanical angular frequency of the motor (50)" from the electrical angular frequency of the motor (50) to decrease. Therefore, when the physical quantity is an AC signal, "dilution" can be estimated by setting the frequency of the specific frequency component (C1) to a frequency obtained by adding "1x the mechanical angular frequency of the motor (50)" to the electrical angular frequency of the motor (50) or a frequency obtained by subtracting "1x the mechanical angular frequency of the motor (50)" from the electrical angular frequency of the motor (50).

[0142] [5. Liquid Compression] Liquid compression is a state (abnormality) that can occur when the motor (50) is a "motor (50) mounted on a compressor," in which liquid fluid is sucked into a compression chamber (not shown) of the compressor. The occurrence of liquid compression can lead to metal fatigue or damage to the components that constitute the compression chamber.

[0143] When the physical quantity is a DC signal, the occurrence of liquid compression tends to increase the frequency component corresponding to one time the mechanical angular frequency of the motor (50). Therefore, when the physical quantity is a DC signal, the "liquid compression" can be estimated by setting the frequency of the specific frequency component (C1) to "one time the mechanical angular frequency of the motor (50)."

[0144] Furthermore, when the physical quantity is an AC signal, the occurrence of liquid compression tends to increase a frequency component corresponding to a frequency obtained by adding "1x the mechanical angular frequency of the motor (50)" to the electrical angular frequency of the motor (50) and a frequency component corresponding to a frequency obtained by subtracting "1x the mechanical angular frequency of the motor (50)" from the electrical angular frequency of the motor (50). Therefore, when the physical quantity is an AC signal, "liquid compression" can be estimated by setting the frequency of the specific frequency component (C1) to a frequency obtained by adding "1x the mechanical angular frequency of the motor (50)" to the electrical angular frequency of the motor (50) or a frequency obtained by subtracting "1x the mechanical angular frequency of the motor (50)" from the electrical angular frequency of the motor (50).

[0145] [6. Unbalance] The imbalance is a state (abnormality) that can occur when the motor (50) is a "motor (50) that drives the blades of a fan," and is a state in which an imbalance occurs among the multiple blades provided in the fan. For example, the imbalance occurs due to different degrees of deformation, damage, dirt, and frost on each of the multiple blades.

[0146] When the physical quantity is an AC signal, the occurrence of an imbalance tends to increase a frequency component corresponding to a frequency obtained by adding "1x the mechanical angular frequency of the motor (50)" to the electrical angular frequency of the motor (50) and a frequency component corresponding to a frequency obtained by subtracting "1x the mechanical angular frequency of the motor (50)" from the electrical angular frequency of the motor (50). Therefore, when the physical quantity is an AC signal, the "imbalance" can be estimated by setting the frequency of the specific frequency component (C1) to a frequency obtained by adding "1x the mechanical angular frequency of the motor (50)" to the electrical angular frequency of the motor (50) or to a frequency obtained by subtracting "1x the mechanical angular frequency of the motor (50)" from the electrical angular frequency of the motor (50).

[0147] [7. Flow path blockage] Blockage of the flow path is a state (abnormality) that can occur when the motor (50) is a "motor (50) that drives the blades of a fan," and is a state in which the flow path in which the fan is provided is blocked. Blockage of the flow path occurs, for example, when a filter (not shown) provided in the flow path together with the fan becomes clogged. When blockage of the flow path occurs, turbulence causes load fluctuations, which disturb the reaction force during air blowing, causing a change in speed.

[0148] When the physical quantity is a DC signal, blockage of the flow path tends to cause a frequency component having a peak near one time the mechanical angular frequency of the motor (50) to fluctuate. Therefore, when the physical quantity is a DC signal, by setting the frequency of the specific frequency component (C1) to "one time the mechanical angular frequency of the motor (50)," it is possible to estimate "blockage of the flow path."

[0149] Furthermore, when the physical quantity is an AC signal, blockage of the flow path tends to fluctuate the electrical angular frequency of the motor (50). Therefore, when the physical quantity is an AC signal, the "blockage of the flow path" can be estimated by setting the frequency of the specific frequency component (C1) to the electrical angular frequency of the motor (50).

[0150] (Specific example of estimation process) Next, specific examples of the estimation process will be described. Examples of the estimation process include the following four estimation processes (first to fourth estimation processes). Note that the following will be described taking as an example a case where the estimation process is performed based on the amplitude of a specific frequency component (C1). In the following description, the "specific frequency component (C1)" means the "amplitude of the specific frequency component (C1)".

[0151] [First estimation process] First, the first estimation process will be described with reference to Fig. 11. In the first estimation process, the control unit (31) estimates whether or not the state of the device (70) is abnormal, based on the instantaneous value of the specific frequency component (C1). Specifically, the control unit (31) performs the following processes (steps (S11) to (S13)) for each predetermined detection period.

[0152] <Step (S11)> The control unit (31) acquires an instantaneous value of the specific frequency component (C1).

[0153] <Step (S12)> Next, the control unit (31) determines whether or not the instantaneous value of the specific frequency component (C1) acquired in step (S11) is equal to or greater than a predetermined upper limit value. Note that this upper limit value is an example of a threshold value used in the estimation process. If the instantaneous value of the specific frequency component (C1) is equal to or greater than the upper limit value, the process of step (S13) is performed. On the other hand, if not, the process of step (S14) is performed.

[0154] <Step (S13)> When the instantaneous value of the specific frequency component C1 is equal to or greater than the upper limit in step S12, the control unit 31 estimates that the state of the device 70 is abnormal, and outputs an estimation result indicating that the state of the device 70 is abnormal.

[0155] <Step (S14)> On the other hand, if the instantaneous value of the specific frequency component (C1) is not equal to or greater than the upper limit in step (S12), the control unit (31) estimates that the state of the device (70) is normal, and outputs an estimation result indicating that the state of the device (70) is normal.

[0156] [Second estimation process] The second estimation process will be described with reference to Fig. 12 and Fig. 13. In the second estimation process, the control unit (31) estimates whether or not the state of the device (70) is abnormal, based on the rate of change of the specific frequency component (C1). Specifically, the control unit (31) repeatedly performs the following processes (steps (S21) to (S23)) for each predetermined detection period.

[0157] <Step (S21)> The control unit (31) acquires the rate of change of the specific frequency component (C1). For example, the control unit (31) derives the rate of change of the specific frequency component (C1) by differentiating the instantaneous value of the specific frequency component (C1) with respect to time. In the example of Fig. 13, the rate of change of the specific frequency component (C1) changes at each of times (t1, t2, t3).

[0158] <Step (S22)> The control unit (31) determines whether the rate of change of the specific frequency component (C1) acquired in step (S21) is equal to or greater than a predetermined upper limit. Note that this upper limit is an example of a threshold used in the estimation process. If the rate of change of the specific frequency component (C1) is equal to or greater than the upper limit, the process of step (S23) is performed. On the other hand, if not, the process of step (S24) is performed. In the example of FIG. 13, the rate of change of the specific frequency component (C1) is equal to or greater than the upper limit at time (t2).

[0159] <Step (S23)> If the rate of change of the specific frequency component C1 is equal to or greater than the upper limit in step S22, the control unit 31 estimates that the state of the device 70 is abnormal, and outputs an estimation result indicating that the state of the device 70 is abnormal.

[0160] <Step (S24)> On the other hand, if the rate of change of the specific frequency component C1 is not equal to or greater than the upper limit in step S22, the control unit 31 estimates that the state of the device 70 is normal, and outputs an estimation result indicating that the state of the device 70 is normal.

[0161] [Third estimation process] The third estimation process will be described with reference to Fig. 14 and Fig. 15. In the third estimation process, the control unit (31) estimates whether or not the state of the device (70) is abnormal, based on an accumulated time obtained by accumulating the time during which the specific frequency component (C1) is equal to or greater than the upper limit. Specifically, the control unit (31) repeatedly performs the following processes (steps (S31) to (S33)) for each predetermined detection period.

[0162] <Step (S31)> The control unit 31 obtains a cumulative value (cumulative time) of the time during which the specific frequency component C1 is equal to or greater than the upper limit value. Note that this upper limit value is an example of a threshold value used in the estimation process.

[0163] For example, the control unit (31) acquires an instantaneous value of the specific frequency component (C1) that is a representative value in a detection cycle, and determines whether or not the instantaneous value of the specific frequency component (C1) is equal to or greater than an upper limit value. If the instantaneous value of the specific frequency component (C1) is equal to or greater than the upper limit value, the control unit (31) increments the count value, and if the instantaneous value of the specific frequency component (C1) is not equal to or greater than the upper limit value, the control unit (31) does not increment the count value. This count value corresponds to the accumulated value (accumulated time) of the time during which the specific frequency component (C1) is equal to or greater than the upper limit value. For example, the accumulated time is a value obtained by multiplying the count value by a time equivalent to the detection cycle.

[0164] In the example of FIG. 15, the third estimation process is performed at each of the times (t1 to t12), and the count value is incremented at the times (t2 to t5, t9 to t12) among the times (t1 to t12).

[0165] <Step (S32)> Next, the control unit (31) determines whether the accumulated time (count value in this example) acquired in step (S31) exceeds a predetermined threshold value. This threshold value is an example of a threshold value used in the estimation process. If the accumulated time exceeds the threshold value, the process of step (S33) is performed, whereas if not, the process of step (S34) is performed. In the example of FIG. 15, the control unit (31) determines that the count value exceeds the threshold value at time (t11).

[0166] <Step (S33)> If the accumulated time exceeds the threshold in step S32, the control unit 31 estimates that the state of the device 70 is abnormal, and outputs an estimation result indicating that the state of the device 70 is abnormal.

[0167] <Step (S34)> On the other hand, if the accumulated time does not exceed the threshold in step S32, the control unit 31 estimates that the state of the device 70 is normal, and outputs an estimation result indicating that the state of the device 70 is normal.

[0168] [Fourth estimation process] The fourth estimation process will be described with reference to Fig. 16 and Fig. 17. In the fourth estimation process, the control unit (31) estimates whether or not the state of the device (70) is abnormal, based on the proportion (time ratio) of the time during which the specific frequency component (C1) is equal to or greater than a predetermined upper limit value within a predetermined determination time. Specifically, the control unit (31) repeatedly performs the following processes (steps (S41) to (S43)) for each predetermined detection period.

[0169] <Step (S41)> The control unit 31 acquires the ratio (time ratio) of the time during which the specific frequency component C1 is equal to or greater than the upper limit value within the determination time. Note that this upper limit value is an example of a threshold value used in the estimation process.

[0170] For example, the control unit (31) stores the specific frequency component (C1) in a judgment period (at least a period equivalent to the judgment time) ending at the current time. Then, based on the stored specific frequency component (C1), the control unit (31) derives a time during which the specific frequency component (C1) is equal to or greater than the upper limit value (upper limit exceeding time) in the judgment period ending at the current time and having a duration equivalent to the judgment time, and derives a time ratio by dividing the upper limit exceeding time by the judgment time. In the example of Fig. 17, the time (t2) is the current time, the period from time (t1) to time (t2) is the judgment period, the time (T1) and the time (T2) are the upper limit exceeding time, and the value obtained by dividing the sum of the time (T1) and the time (T2) by the judgment time (T0) is the time ratio.

[0171] <Step (S42)> Next, the control unit (31) determines whether or not the time ratio acquired in step (S41) (the ratio of the time during which the specific frequency component (C1) is equal to or greater than the upper limit value within the determination time) exceeds a predetermined threshold value. Note that this threshold value is an example of a threshold value used in the estimation process. If the time ratio exceeds the threshold value, the process of step (S43) is performed. On the other hand, if not, the process of step (S44) is performed.

[0172] <Step (S43)> If the time ratio exceeds the threshold in step S42, the control unit 31 estimates that the state of the device 70 is abnormal, and outputs an estimation result indicating that the state of the device 70 is abnormal.

[0173] <Step (S44)> On the other hand, if the time ratio does not exceed the threshold in step S42, the control unit 31 estimates that the state of the device 70 is normal, and outputs an estimation result indicating that the state of the device 70 is normal.

[0174] In the above description of the estimation process, the specific frequency component (C1) is compared with an upper limit value, but the present invention is not limited to this. For example, the specific frequency component (C1) may be compared with a predetermined lower limit value. In other words, the above "upper limit value or more" may be read as "lower limit value or less". The specific frequency component (C1) may be compared with a predetermined allowable range. In other words, the above "upper limit value or more" may be read as "outside allowable range".

[0175] (Specific example of the first restriction process) Next, a specific example of the first restriction process will be described. The following five estimation restriction processes (first to fifth estimation restriction processes) are examples of the "process for restricting the estimation process" performed in the first restriction process.

[0176] [First presumption restriction process] First, the first estimation restriction process will be described. The first estimation restriction process is a process for prohibiting (stopping) the execution of the estimation process. In the first estimation restriction process, the control unit (31) stops the estimation process and outputs a predetermined estimation result. This directly restricts the estimation process so that the predetermined estimation result is output. In this way, it is possible to prevent an erroneous estimation result from being obtained, thereby suppressing erroneous estimation of the state of the device (70).

[0177] [Second presumption restriction process] Next, the second estimation restriction process will be described. The second estimation restriction process is a process for correcting an estimation result obtained by the estimation process. In the second estimation restriction process, the control unit (31) continues the estimation process while correcting the estimation result obtained by the estimation process to a "predetermined estimation result". This directly restricts the estimation process so that the predetermined estimation result is output. In this way, it is possible to prevent an erroneous estimation result from being obtained, thereby suppressing erroneous estimation of the state of the device (70).

[0178] [Third Presumption Restriction Processing] Next, the third estimation restriction process will be described. The third estimation restriction process is a process for prohibiting (stopping) the execution of the calculation process. In the third estimation restriction process, the control unit (31) stops the calculation process and sets the specific frequency component (C1) used in the estimation process to a "predetermined specific frequency component (C1)" so that a predetermined estimation result is obtained in the estimation process. This indirectly restricts the estimation process so that a predetermined estimation result is output. In this way, it is possible to prevent an erroneous estimation result from being obtained, thereby suppressing erroneous estimation of the state of the device (70).

[0179] [Fourth Presumption Restriction Processing] Next, the fourth estimation restriction process will be described. The fourth estimation restriction process is a process for correcting the specific frequency component (C1) calculated by the calculation process. In the fourth estimation restriction process, the control unit (31) continues the calculation process, while correcting the specific frequency component (C1) calculated by the calculation process to a "predetermined specific frequency component (C1)" so that a predetermined estimation result is obtained in the estimation process. This indirectly restricts the estimation process so that a predetermined estimation result is output. In this way, it is possible to prevent an erroneous estimation result from being obtained, and therefore it is possible to suppress erroneous estimation of the state of the device (70).

[0180] [5th ​​Presumption Restriction Processing] Next, the fifth estimation restriction process will be described. The fifth estimation restriction process is a process that is performed when the control unit (31) estimates the state of the device (70) based on a result of comparing the amplitude of the specific frequency component (C1) with a predetermined threshold in the estimation process, and is a process of correcting at least one of the threshold and the amplitude of the specific frequency component (C1). In the fifth estimation restriction process, the control unit (31) corrects the threshold used in the estimation process to a "predetermined threshold" so that a predetermined estimation result is obtained in the estimation process. Alternatively, in the fifth estimation restriction process, the control unit (31) corrects the specific frequency component (C1) used in the estimation process to a "predetermined specific frequency component (C1)" so that a predetermined estimation result is obtained in the estimation process. This directly restricts the estimation process so that a predetermined estimation result is output. In this way, it is possible to prevent an erroneous estimation result from being obtained, and therefore it is possible to suppress erroneous estimation of the state of the device (70).

[0181] (Specific example of the second restriction process) Next, a specific example of the second limiting process will be described. Examples of the “process for limiting the operation of the motor (50)” performed in the second limiting process include the following two operation limiting processes (first and second operation limiting processes).

[0182] [First operation restriction process] First, the first operation restriction process will be described. The first operation restriction process is a process for changing the operating conditions of the motor (50) so as to prevent erroneous estimation in the estimation process. The process for changing the operating conditions of the motor (50) is a process for changing at least one of the carrier frequency, the sampling frequency for sampling a physical quantity in the calculation process, and the mechanical angular frequency of the motor (50). In the first operation restriction process, the control unit (31) changes the operating conditions of the motor (50) including at least one of the carrier frequency, the sampling frequency, and the mechanical angular frequency of the motor (50) so as to prevent erroneous estimation in the estimation process.

[0183] In this manner, by changing the operating conditions of the motor (50), the noise frequency component (Cn) and the specific frequency component (C1) can be prevented from satisfying a predetermined relationship, thereby suppressing fluctuations in the magnitude of the specific frequency component (C1) due to the influence of the noise frequency component (Cn), thereby suppressing erroneous estimation of the state of the equipment (70).

[0184] [Second operation restriction process] Next, the second operation restriction process will be described. The second operation restriction process is a process for prohibiting operation of the motor (50) under an operating condition in which the noise frequency component (Cn) and the specific frequency component (C1) satisfy a predetermined relationship. In the second operation restriction process, the control unit (31) prohibits operation of the motor (50) when the operating condition of the motor (50) is "an operating condition in which the noise frequency component (Cn) and the specific frequency component (C1) satisfy a predetermined relationship," and permits operation of the motor (50) otherwise.

[0185] In this manner, by prohibiting the operation of the motor (50) under operating conditions where the noise frequency component (Cn) and the specific frequency component (C1) satisfy a predetermined relationship, it is possible to prevent erroneous estimation results, thereby suppressing erroneous estimation of the state of the equipment (70).

[0186] (Modification of the first embodiment) The drive system (10) of the modified example of the first embodiment differs from the drive system (10) of the first embodiment in the restriction process by the control unit (31). Other configurations and processes of the drive system (10) of the modified example of the first embodiment are similar to those of the drive system (10) of the first embodiment.

[0187] In the restriction process of the modification of the first embodiment, the control unit (31) restricts the estimation process or the operation of the motor (50) when the noise frequency component (Cn) and the specific frequency component (C1) satisfy a predetermined relationship. Then, when a predetermined restriction release condition is satisfied after starting the restriction on the estimation process or the operation of the motor (50), the control unit (31) lifts the restriction on the estimation process or the operation of the motor (50) after a predetermined standby release condition is satisfied. The standby release condition will be described in detail later.

[0188] As shown in FIG. 18, in the restriction process of the modification of the first embodiment, step (S110) is performed between step (S103) and step (S104).

[0189] <Step (S110)> When a predetermined restriction release condition is satisfied in step (S103), the control unit (31) determines whether or not a standby release condition is satisfied. When the standby release condition is satisfied, the process of step (S104) is performed. For example, the process of step (S110) is performed at predetermined determination time intervals. In other words, the process of step (S110) is repeatedly performed until the standby release condition is satisfied.

[0190] [Effects of the Modification of the First Embodiment] In the modification of the first embodiment, the same effects as those of the first embodiment can be obtained.

[0191] In the modification of the first embodiment, the restriction can be released after the specific frequency component (C1) used in the estimation process is stabilized, rather than releasing the restriction (restriction on the estimation process or on the motor (50)) after the restriction release condition is satisfied without waiting for the standby release condition to be satisfied, which makes it possible to suppress erroneous estimation of the state of the device (70) after the restriction is released.

[0192] (Specific examples of standby release conditions) Next, specific examples of the standby release conditions will be described. Examples of the standby release conditions include the following three standby release conditions (first to third standby release conditions).

[0193] [First standby release condition] First, the first standby release condition will be described. The first standby release condition is a condition that a predetermined time has elapsed since the restriction release condition was satisfied. When the restriction release condition is satisfied, the control unit (31) releases the restriction on the estimation process or the operation of the motor (50) after the predetermined time has elapsed. Specifically, when the restriction release condition is satisfied, the control unit (31) starts measuring the elapsed time. Then, when the elapsed time reaches a predetermined time, the control unit (31) releases the restriction on the estimation process or the operation of the motor (50). Note that the predetermined time is set, for example, to a time longer than the time required for a feature amount used to estimate the state of the device to change from a non-steady state to a steady state. The feature amount may be calculated from a physical amount obtained from the device (70) within a predetermined period, and may be, for example, a specific frequency component (C1).

[0194] [Second standby release condition] Next, the second standby release condition will be described. The second standby release condition is a condition in which the number of times the restriction release condition is continuously satisfied reaches a predetermined number. The control unit (31) repeatedly determines whether the restriction release condition is satisfied, and when the restriction release condition is satisfied, the control unit (31) releases the restriction on the estimation process or the operation of the motor (50) after the number of times the restriction release condition is continuously satisfied reaches a predetermined number. Specifically, when the restriction release condition is satisfied, the control unit (31) starts measuring the number of times the restriction release condition is continuously satisfied. Then, when the number of times the restriction release condition is continuously satisfied reaches a predetermined number, the control unit (31) releases the restriction on the estimation process or the operation of the motor (50). Note that the predetermined number is set, for example, to a number greater than the number of times the restriction release condition is continuously satisfied measured until the feature quantity changes from an unsteady state to a steady state.

[0195] [Third standby release condition] Next, the third standby release condition will be described. The third standby release condition is a condition that the specific frequency component (C1) calculated by the calculation process is in a steady state. The control unit (31) monitors the specific frequency component (C1) calculated by the calculation process, and when the restriction release condition is satisfied, the control unit (31) releases the restriction on the estimation process or the operation of the motor (50) after the specific frequency component (C1) calculated by the calculation process is in a steady state. Specifically, when the restriction release condition is satisfied, the control unit (31) determines whether the specific frequency component (C1) calculated by the calculation process is in a steady state. Then, when the control unit (31) determines that the specific frequency component (C1) calculated by the calculation process is in a steady state, it releases the restriction on the estimation process or the operation of the motor (50).

[0196] The steady state of the specific frequency component (C1) is, for example, a state in which the ratio between the current value and the previous value of the moving average value of the specific frequency component (C1) within a predetermined time is within a predetermined ratio. For example, the moving average value within a predetermined time is a moving average value for one second, the previous value is a moving average value acquired one second before (the previous value), and the predetermined ratio is 1%. The non-steady state of the specific frequency component (C1) is a state in which the ratio between the current value and the previous value of the moving average value of the specific frequency component (C1) within a predetermined time is higher than the predetermined ratio.

[0197] (Embodiment 2) The drive system (10) of the second embodiment differs from the drive system (10) of the first embodiment in the processing by the control unit (31) of the control device (30). Other configurations and processing of the drive system (10) of the second embodiment are similar to the configurations and processing of the drive system (10) of the first embodiment.

[0198] [Processing by the control unit] In the second embodiment, the control unit (31) performs a control process, a calculation process, an estimation process, a determination process, a restriction process, and a response process. The control process, the calculation process, the estimation process, and the response process are the same as those in the first embodiment.

[0199] [Determination process] In the determination process, the presence or absence of noise interference is determined based on the magnitude of a periodic component included in a variable calculated based on the magnitude of the specific frequency component (C1). An example of a "variable calculated based on the magnitude of the specific frequency component (C1)" is a value obtained by dividing the short-term moving average value of the specific frequency component (C1) by the long-term moving average value. The short-term moving average value is the moving average value of the specific frequency component (C1) within a first time period. The long-term moving average value is the moving average value of the specific frequency component (C1) within a second time period. The second time period is longer than the first time period.

[0200] Other examples of the "variable calculated based on the magnitude of the specific frequency component (C1)" include the instantaneous value of the specific frequency component (C1), the square root of the sum of the squares of the specific frequency component (C1), the rate of change of the specific frequency component (C1), the ratio of the short-term moving average to the long-term moving average of the specific frequency component (C1), addition, subtraction, multiplication, and division of multiple specific frequency components (C1), the power of the specific frequency component (C1), and a combination of at least two of these.

[0201] In addition, when there is noise interference (specifically, when the noise component affects the specific frequency component (C1)), the magnitude (amplitude) of the specific frequency component (C1) fluctuates. In addition, when there is noise interference, the periodic component included in the variable calculated based on the magnitude of the specific frequency component (C1) becomes large.

[0202] For example, when the specific frequency component (C1) contains a periodic component, the control unit (31) determines that there is noise interference, and when the specific frequency component (C1) does not contain a periodic component, the control unit (31) determines that there is no noise interference. Note that a specific example of the determination process will be described in detail later.

[0203] [Restriction processing] In the limiting process, when it is determined in the determination process that there is noise interference, the control unit (31) limits the estimation process or the operation of the motor (50). The limiting process is a first limiting process that limits the estimation process so that a predetermined estimation result is output, or a second limiting process that limits the operation of the motor (50) so that erroneous estimation is not performed in the estimation process.

[0204] [Processing flow by the control unit] Next, with reference to FIG. 19, a flow of processes (specifically, a calculation process, an estimation process, a determination process, and a limiting process) performed by the control unit (31) will be described.

[0205] The control unit (31) performs a calculation process at each predetermined calculation time. The calculation process is repeated to calculate a specific frequency component (C1) at each calculation time.

[0206] Then, the control unit (31) performs an estimation process based on the specific frequency component (C1) calculated by the calculation process for each predetermined estimation time. By repeatedly performing the estimation process, an estimation result is obtained for each estimation time.

[0207] Furthermore, the control unit (31) performs a determination process in parallel with the calculation process and the estimation process. Specifically, the control unit (31) performs the determination process based on the specific frequency component (C1) calculated by the calculation process at each predetermined determination time. The determination process is repeated to obtain a determination result at each determination time. The determination time is set to a time equal to or longer than the time required to determine the presence or absence of noise interference based on the specific frequency component (C1) calculated by the calculation process.

[0208] Furthermore, the control unit (31) performs a limiting process in parallel with the above processes (the calculation process, the estimation process, and the determination process). Specifically, the control unit (31) repeatedly performs the processes of steps (S201 to S204) shown in FIG.

[0209] <Step (S201)> The control unit (31) acquires a determination result from the determination process. Then, the control unit (31) determines whether or not there is noise interference based on the determination result from the determination process. If there is noise interference, the process of step (S202) is performed. For example, the process of step (S201) is performed at predetermined determination time intervals. In other words, the process of step (S201) is repeatedly performed until a determination result indicating the presence of noise interference is obtained.

[0210] <Step (S202)> If there is noise interference, the control unit (31) limits the estimation process or the operation of the motor (50).

[0211] <Step (S203)> Next, the control unit (31) determines whether or not a restriction release condition is satisfied. Examples of the restriction release condition include a condition that there is no noise interference, a condition that the control unit (31) receives a release command, etc. The release command is automatically transmitted to the control unit (31) after a predetermined time has elapsed since the restriction release condition was satisfied.

[0212] When the restriction removal condition is satisfied, the process of step (S204) is performed. For example, the process of step (S213) is performed at every predetermined determination time. In other words, the process of step (S203) is repeatedly performed until the restriction removal condition is satisfied.

[0213] <Step (S204)> When the restriction removal condition is met, the control unit (31) removes the restriction (restriction on the estimation process or restriction on the operation of the motor (50)).

[0214] [Effects of the second embodiment] As described above, in the second embodiment, the control unit (31) determines the presence or absence of noise interference in the determination process based on the magnitude of the periodic component included in the variable calculated based on the magnitude of the specific frequency component (C1). Then, in the restriction process, when it is determined in the determination process that there is noise interference, the control unit (31) restricts the estimation process or the operation of the motor (50).

[0215] In the above configuration, when a noise component affects the specific frequency component (C1), a fluctuation appears in the magnitude (amplitude) of the specific frequency component (C1). Therefore, in the determination process, the presence or absence of noise interference can be appropriately determined based on "the magnitude of the periodic component included in the variable calculated based on the magnitude of the specific frequency component (C1)." Then, in the restriction process, the estimation process or the operation of the motor (50) is restricted based on the determination result of the determination process, thereby suppressing erroneous estimation of the state of the equipment (70).

[0216] In the second embodiment, the influence of noise frequency components of frequencies other than the "greatest common divisor (greatest common divisor of 2 or more) disclosed in Patent Document 1 and its integer multiples" can be taken into consideration. This makes it possible to appropriately suppress erroneous estimation of the state of the device (70).

[0217] (Specific example of judgment process) Next, specific examples of the determination process will be described. As examples of the determination process, the following seven determination processes (first to seventh determination processes) can be given.

[0218] [First determination process] First, the first determination process will be described with reference to Fig. 20. In the first determination process, the control unit (31) determines the presence or absence of noise interference based on the average value of the absolute value of the amount of fluctuation (amount of fluctuation per unit time) of the specific frequency component (C1) within a predetermined time.

[0219] Specifically, the control unit (31) acquires an instantaneous value of the specific frequency component (C1) at each predetermined time (t). Then, the control unit (31) calculates the instantaneous value (U k )) and the instantaneous value (U k+1The amount of fluctuation of the specific frequency component (C1) per unit time within a given time is derived by dividing the difference between "(C1)" and "(C2)" by "time (t)". ​​In this way, the amount of fluctuation of the specific frequency component (C1) per unit time within a given time is derived for each given time (t).

[0220] The control unit (31) averages the absolute values ​​of the "fluctuation amount per unit time of the specific frequency component (C1) within a predetermined time" derived for each predetermined time (t) to derive an average value of the fluctuation amount (fluctuation amount per unit time) of the specific frequency component (C1) within the predetermined time. It is desirable to set the averaging period (the period during which the average value is derived) to a time equal to or longer than the period of the fluctuation of the specific frequency component (C1) assumed to be caused by noise interference. For example, the averaging period is set to 3 minutes. Then, the control unit (31) determines that there is noise interference when the derived average value of the fluctuation amount of the specific frequency component (C1) within the predetermined time exceeds a threshold value, and determines that there is no noise interference when this is not the case. For example, by setting the threshold value to "0.24% of the average value in the averaging period of the amplitude of the specific frequency component (C1)", it can be determined that "there is noise interference" when the specific frequency component (C1) fluctuates by 10% or more in a 3-minute period.

[0221] In addition, the average value of the fluctuation amount (fluctuation amount per unit time) of the specific frequency component (C1) within a specified time may be derived using various filters such as a low-pass filter, or may be derived using various processes such as a moving average.

[0222] [Second Determination Process] Next, the second determination process will be described with reference to Fig. 21. In the second determination process, the control unit (31) determines the presence or absence of noise interference based on the magnitude of the periodic component included in the specific frequency component (C1).

[0223] Specifically, the control unit (31) performs frequency conversion on the specific frequency component (C1) and extracts the "periodic component with the largest amplitude" from among the periodic components of the specific frequency component (C1). The control unit (31) then determines whether or not there is noise interference based on the magnitude (amplitude) of the periodic component of the specific frequency component (C1). Specifically, the control unit (31) determines that there is noise interference when the amplitude of the "periodic component with the largest amplitude" of the specific frequency component (C1) exceeds a threshold, and determines that there is no noise interference when this is not the case. For example, by setting the threshold to "10% of the average value over a predetermined time period," it can be determined that "there is noise interference" when there is a periodic component in the specific frequency component (C1) that varies by 10% or more.

[0224] [Third Determination Process] Next, the third determination process will be described with reference to Fig. 22. In the third determination process, the control unit (31) determines the presence or absence of noise interference based on the magnitude of the standard deviation of the specific frequency component (C1) within a predetermined time. Note that the predetermined time is desirably set to a time equal to or greater than the period of fluctuation of the specific frequency component (C1) expected due to noise interference. For example, the predetermined time is three minutes.

[0225] As shown in FIG. 22, the distribution of a specific frequency component (C1) within a specified time period tends to be such that when there is no noise interference (when the impact of noise interference is relatively small), the data values, which are the amplitude values ​​of the specific frequency component (C1), are concentrated near the average value, whereas when there is noise interference (when the impact of noise interference is relatively large), the data values ​​are dispersed rather than concentrated near the average value.

[0226] Specifically, in the third determination process, the control unit (31) derives the standard deviation of the specific frequency component (C1) within a predetermined time based on multiple data values ​​(amplitude values ​​of the specific frequency component (C1)) obtained within the predetermined time. Then, the control unit (31) determines that there is noise interference if the standard deviation of the specific frequency component (C1) within the predetermined time exceeds a threshold value, and determines that there is no noise interference if this is not the case. For example, the threshold value is 7% of the average value of the amplitude of the specific frequency component (C1) within the predetermined time. In this case, it can be determined that "there is noise interference" if there is a periodic component with a fluctuation of 10% or more in the specific frequency component.

[0227] In the third determination process, the control unit (31) may determine the presence or absence of noise interference based on a moving average of the standard deviation of the specific frequency component (C1) within a predetermined time. Specifically, the control unit (31) may determine that there is noise interference when the moving average of the standard deviation of the specific frequency component (C1) within a predetermined time exceeds a threshold value, and may determine that there is no noise interference when this is not the case.

[0228] [Fourth determination process] Next, the fourth determination process will be described with reference to Fig. 23. In the fourth determination process, the control unit (31) determines the presence or absence of noise interference based on the kurtosis of the distribution of the specific frequency component (C1) within a predetermined time. Note that the predetermined time is desirably set to a time equal to or longer than the period of fluctuation of the specific frequency component (C1) expected due to noise interference.

[0229] As shown in FIG. 23, the distribution of a specific frequency component (C1) within a specified time period tends to have a relatively high kurtosis when there is no noise interference (when the impact of noise interference is relatively small), and a relatively low kurtosis when there is noise interference (when the impact of noise interference is relatively large).

[0230] Specifically, in the fourth determination process, the control unit (31) derives the kurtosis of the distribution of the specific frequency component (C1) within a predetermined time based on a plurality of data values ​​(amplitude values ​​of the specific frequency component (C1)) obtained within the predetermined time. Then, the control unit (31) determines that there is noise interference if the kurtosis of the distribution of the specific frequency component (C1) within the predetermined time is below a predetermined value, and determines that there is no noise interference if not. For example, the predetermined value (the threshold value of kurtosis) is "-1.5".

[0231] [Fifth judgment process] Next, the fifth determination process will be described with reference to FIG. 24. In the fifth determination process, the control unit (31) determines the presence or absence of noise interference based on the accumulated value of the absolute value of the difference between the specific frequency component (C1) and the average value within a predetermined time. The average value is the average value of the specific frequency component (C1) within the predetermined time. In the example of FIG. 24, the accumulated value of the absolute value of the difference between the specific frequency component (C1) and the average value within the predetermined time corresponds to the area of ​​the hatched region. Note that the predetermined time is desirably set to a time equal to or longer than the period of the fluctuation of the specific frequency component (C1) expected due to noise interference. For example, the predetermined time is three minutes.

[0232] Specifically, in the fifth determination process, the control unit (31) derives an average value of the specific frequency component (C1) within a predetermined time based on a plurality of data values ​​(amplitude values ​​of the specific frequency component (C1)) obtained within the predetermined time. Next, the control unit (31) derives an absolute value of the difference between each of the plurality of data values ​​(amplitude values ​​of the specific frequency component (C1)) obtained within the predetermined time and the average value, and derives a cumulative value of the absolute value of the difference between the specific frequency component (C1) and the average value within the predetermined time by adding up the absolute values. Then, the control unit (31) determines that there is noise interference when the cumulative value of the absolute value of the difference between the specific frequency component (C1) and the average value within the predetermined time exceeds a threshold value, and determines that there is no noise interference when this is not the case. For example, the threshold value is set to "11% of the average value of the amplitude of the specific frequency component (C1) within a predetermined time" when the absolute value of the difference between each of the plurality of data values ​​(amplitude values ​​of the specific frequency component (C1)) obtained within the predetermined time and the average value is calculated every second and added up. In this case, if a periodic component with a fluctuation of 10% or more exists in the specific frequency component (C1), it can be determined that "there is noise interference."

[0233] [Sixth judgment process] Next, the sixth determination process will be described with reference to Fig. 25. In the sixth determination process, the control unit (31) determines the presence or absence of noise interference based on the accumulated value of the amplitude of frequency components in a predetermined bandwidth excluding 0 Hz of the spectrum of the periodic component included in the specific frequency component (C1). In the example of Fig. 25, the accumulated value of the amplitude of frequency components in a predetermined bandwidth of the spectrum of the periodic component included in the specific frequency component (C1) corresponds to the area of ​​the hatched region.

[0234] Specifically, in the sixth determination process, the control unit (31) extracts a periodic component of the specific frequency component (C1) by frequency conversion of the specific frequency component (C1). Next, the control unit (31) derives an accumulated value of the amplitude values ​​of the periodic component for each frequency by summing up the amplitude values ​​of the periodic component for each frequency in a predetermined bandwidth of the specific frequency component (C1). Then, the control unit (31) determines that there is noise interference when the accumulated value of the amplitude values ​​of the periodic component for each frequency of the specific frequency component (C1) exceeds a threshold value, and determines that there is no noise interference when this is not the case. For example, the threshold value is 10% of the average value of the amplitude of the specific frequency component (C1) over a predetermined time. In this case, it can be determined that there is "noise interference" when there is a periodic component in the specific frequency component (C1) with a fluctuation of 10% or more.

[0235] [Seventh judgment process] Next, the seventh determination process will be described with reference to Fig. 26. In the seventh determination process, the control unit (31) determines the presence or absence of noise interference based on the magnitude of the difference between the maximum value and the minimum value of the specific frequency component (C1) within a predetermined period (TP). Note that the predetermined period (TP) is desirably set to a time equal to or longer than the period of fluctuation of the specific frequency component (C1) expected due to noise interference. For example, the predetermined period (TP) is three minutes.

[0236] Specifically, the control unit (31) acquires an instantaneous value of the specific frequency component (C1) within a predetermined period (TP) and derives the difference between the maximum value and the minimum value of the specific frequency component (C1) within the predetermined period (TP). As a result, the difference between the maximum value and the minimum value of the specific frequency component (C1) within the predetermined period (TP) is derived for each predetermined period (TP). Then, the control unit (31) determines that there is noise interference if the difference between the maximum value and the minimum value of the specific frequency component (C1) within the predetermined period (TP) exceeds a threshold value, and determines that there is no noise interference if this is not the case. For example, by setting the threshold value to "20% of the average value of the specific frequency component (C1) within the predetermined period (TP)", it can be determined that "there is noise interference" when a periodic component with a fluctuation of 10% or more exists in the specific frequency component (C1).

[0237] (Modification of the second embodiment) The drive system (10) of the modified example of the second embodiment differs from the drive system (10) of the second embodiment in the restriction process by the control unit (31). The other configurations and processes of the drive system (10) of the modified example of the second embodiment are similar to those of the drive system (10) of the second embodiment.

[0238] In the restriction process of the modified example of the second embodiment, when it is determined in the determination process that there is noise interference, the control unit (31) restricts the estimation process or the operation of the motor (50). Then, when a predetermined restriction release condition is satisfied after starting the restriction on the estimation process or the operation of the motor (50), the control unit (31) lifts the restriction on the estimation process or the operation of the motor (50) after a predetermined standby release condition is satisfied. The standby release condition in the modified example of the second embodiment is similar to the standby release condition in the modified example of the first embodiment.

[0239] [Effects of the Modification of the Second Embodiment] In the modification of the second embodiment, the same effects as those of the second embodiment can be obtained.

[0240] In the modified example of the second embodiment, the restriction can be released after the specific frequency component (C1) used in the estimation process is stabilized, rather than releasing the restriction (restriction on the estimation process or on the motor (50)) after the restriction release condition is satisfied without waiting for the standby release condition to be satisfied, which makes it possible to suppress erroneous estimation of the state of the device (70) after the restriction is released.

[0241] (Refrigeration System) Fig. 27 illustrates the configuration of a refrigeration system (RR). The refrigeration system (RR) includes a refrigerant circuit (RR1) filled with refrigerant, a motor drive device (20), and a control device (30). The motor drive device (20) and the control device (30) illustrated in Fig. 27 are the motor drive device (20) and the control device (30) in the first or second embodiment.

[0242] The refrigerant circuit (RR1) includes a compressor (CC), a radiator (RR5), a pressure reduction mechanism (RR6), and an evaporator (RR7). In this example, the pressure reduction mechanism (RR6) is an expansion valve. The refrigerant circuit (RR1) performs a vapor compression refrigeration cycle.

[0243] The compressor (CC) has a compression mechanism (CCa) and a motor (50). The compression mechanism (CCa) is connected to the motor (50) by a rotating shaft. The motor (50) rotationally drives the rotating shaft to rotate the compression mechanism (CCa). The motor drive device (20) drives the motor (50). The control device (30) determines the state of the refrigeration system (RR) equipped with the compressor (CC) having the motor (50).

[0244] In the refrigeration cycle, the refrigerant discharged from the compressor (CC) dissipates heat in the radiator (RR5). The refrigerant flowing out from the radiator (RR5) is depressurized in the pressure reducing mechanism (RR6) and evaporates in the evaporator (RR7). The refrigerant flowing out from the evaporator (RR7) is sucked into the compressor (CC).

[0245] In this example, the refrigeration system (RR) is an air conditioner. The air conditioner may be a dedicated cooling machine or a dedicated heating machine. The air conditioner may also be an air conditioner that switches between cooling and heating. In this case, the air conditioner has a switching mechanism (e.g., a four-way switching valve) that switches the refrigerant circulation direction. The refrigeration system (RR) may also be a water heater, a chiller unit, a cooling device that cools the air inside a storage unit, or the like. The cooling device cools the air inside a refrigerator, a freezer, a container, or the like.

[0246] (Fan system) 28 illustrates the configuration of a fan system (FF). The fan system (FF) includes a fan (FF1), a motor drive device (20), and a control device (30). The motor drive device (20) and the control device (30) illustrated in FIG. 28 are the motor drive device (20) and the control device (30) in the first or second embodiment.

[0247] The fan (FF1) is provided in a flow path (not shown). The fan (FF1) has a rotor (FFa) having blades and a motor (50). The rotor (FFa) is connected to the motor (50) by a rotating shaft. The motor (50) rotates the rotor (FF2a) by driving the rotating shaft. The motor drive device (20) drives the motor (50). The control device (30) estimates the state of the fan system (FF) in which the motor (50) is mounted. The state of the fan system (FF) estimated by the control device (30) includes blockage of the flow path in which the fan (FF1) is provided (a state in which the flow path is blocked).

[0248] (Other embodiments) In the above description, the state of the device (70) may refer to the state of the device (70) as a whole, or may refer to the state of some of the elements included in the device (70). For example, when the device (70) is an "outdoor unit equipped with a compressor (CC) having a motor (50)," the state of the device (70) may refer to the state of the outdoor unit, the state of the compressor (CC), the state of the motor (50), or the state of other elements of the outdoor unit.

[0249] In the above description, a signal based on the current or voltage of the motor (50) has been given as an example of a physical quantity obtained from the device (70), but the physical quantity is not limited to this. For example, the physical quantity may be a signal indicating vibration of the device (70) or a signal indicating sound of the device (70). The signal indicating vibration of the device (70) may be acquired by a vibration sensor (not shown) provided in the device (70). The signal indicating sound of the device (70) may be acquired by a sound sensor (not shown) provided in the device (70).

[0250] Further, in the above description, an example has been given in which the estimation process estimates the presence or absence of an abnormality in the device (70); however, the present invention is not limited to this.

[0251] For example, in the estimation process, the control unit (31) may estimate the degree of wear of a rotating shaft (not shown) rotated by the motor (50) or a bearing (not shown) of the rotating shaft. In this case, the control unit (31) may estimate the degree of wear according to the specific frequency component (C1) obtained by the calculation process such that the degree of wear of the rotating shaft or the bearing increases as the specific frequency component (C1) obtained by the calculation process increases. Examples of the "predetermined estimation result" output when the estimation process for estimating the degree of wear is restricted include an estimation result indicating that the degree of wear of the equipment (70) is unknown, an estimation result indicating that the estimation process is prohibited (stopped), etc.

[0252] Furthermore, the control unit (31) may estimate the remaining life of the motor (50) in the estimation process. In this case, the control unit (31) may estimate the remaining life according to the feature amount obtained by the calculation process such that the remaining life of the motor (50) is shorter as the feature amount obtained by the calculation process increases. Examples of the "predetermined estimation result" output when the estimation process for estimating the remaining life is restricted include an estimation result indicating that the remaining life of the device (70) is unknown, an estimation result indicating that the estimation process is prohibited (stopped), etc.

[0253] In the above description, a bandpass filter may be used in the calculation process to extract a signal in a frequency band including the frequency of the specific frequency component (C1). In addition, a bandpass filter process may be performed in the calculation process to extract a signal in a frequency band including the frequency of the specific frequency component (C1).

[0254] In the above description, various filters such as a Kalman filter may be used to extract the periodic components contained in the specific frequency component (C1). Various frequency analysis processes such as a wavelet analysis may be used to extract the periodic components contained in the specific frequency component (C1). The same applies to the calculation (extraction) of the specific frequency component (C1).

[0255] In the above description, the instantaneous value of the specific frequency component (C1), the square root of the sum of the squares of the specific frequency component (C1), the rate of change of the specific frequency component (C1), the ratio of the short-term moving average to the long-term moving average of the specific frequency component (C1), addition, subtraction, multiplication, and division of a plurality of specific frequency components (C1), the power of the specific frequency component (C1), or a combination of at least two of these may be used as index values, and the estimation process may be performed based on such index values. The estimation process may also be performed based on the duration during which such index values ​​exceed a threshold value, the number of times such index values ​​exceed a threshold value, or the like. The estimation process may also be performed based on a combination of the specific frequency component (C1) and another characteristic frequency component (for example, a frequency component corresponding to an integer multiple of the mechanical angular frequency of the motor (50)).

[0256] In the above description, the specific frequency component (C1) may be a frequency component corresponding to a single frequency, or may be a frequency component corresponding to a frequency range based on a single frequency.

[0257] In addition, in the above description, when the physical quantity is an AC signal, the estimation process may be performed based on one of two specific frequency components (C1) that are symmetrical with respect to the electrical angular frequency of the motor (50), or the estimation process may be performed based on both of the two specific frequency components (C1).

[0258] In the above description, the physical quantities may be measured values, command values, or estimated values.

[0259] In addition, in the above description, the control unit (31) may be configured to perform the determination process using an algorithm (an algorithm for determining a state based on a change in a signal) constructed by a neural network or machine learning.

[0260] In the above description, the control unit 31 may be realized by one processor or by multiple processors. The control unit 31 may also be realized by multiple arithmetic processing devices (computers) that communicate with each other via a communication network.

[0261] In addition, although the embodiment and the modified examples have been described, it will be understood that various modifications of the form and details are possible without departing from the spirit and scope of the claims. In addition, the elements of the above embodiment, modified examples, and other embodiments may be appropriately combined or substituted. [Industrial Applicability]

[0262] INDUSTRIAL APPLICABILITY As described above, the present disclosure is useful as a state estimation technique. [Explanation of symbols]

[0263] 10 Drive System 20 Motor drive device 21 Converter 22 DC section 23 Inverter 30 Control device (state estimation device) 31 Control Unit 41 Phase current detection section 42 Electrical angle frequency detector 50 Motor 60 power supply 70 equipment CC Compressor RR Refrigeration System RR1 Refrigerant circuit FF Fan System FF1 Fan

Claims

1. A state estimation method for estimating a state of a device (70) equipped with a motor (50), comprising: an estimation step of estimating a state of the equipment (70) based on a magnitude of a specific frequency component (C1) of a signal indicating a physical quantity obtained from the equipment (70); a limiting step of limiting the estimation step or limiting the operation of the motor (50) based on a magnitude of a periodic component included in a variable calculated based on the magnitude of the specific frequency component (C1), The limiting step is a first limiting step for limiting the estimation step so that a predetermined estimation result is output, or a second limiting step for limiting the operation of the motor (50) so that erroneous estimation is not performed in the estimation step. State estimation methods.

2. A state estimation program that causes a computer to execute the state estimation method of claim 1.

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