CN116490760A

CN116490760A - Diagnostic device for motor

Info

Publication number: CN116490760A
Application number: CN202080107078.7A
Authority: CN
Inventors: 安原裕登; 宫内俊彦
Original assignee: Mitsubishi Electric Corp
Current assignee: Mitsubishi Electric Corp
Priority date: 2020-11-16
Filing date: 2020-11-16
Publication date: 2023-07-25
Also published as: KR20230075513A; JP7422896B2; WO2022102113A1; DE112020007771T5; JPWO2022102113A1

Abstract

In the motor diagnosis device, a threshold value calculation unit (123) calculates a threshold value for determining abnormality of a motor (5) based on the calculation result of a rotation frequency sigma value calculation unit (122), a normal state storage unit (124) stores the calculation result of an averaging calculation unit (121) as the normal state of the motor (5), a load factor calculation unit (110) calculates the operation load factor of the motor (5), an FFT analysis result correction unit (125) corrects the FFT analysis result of an FFT analysis unit (112) when diagnosis is performed, an FFT result correction matrix selection unit (118) selects a correction value of the FFT analysis result based on the operation frequency and the value of the operation load factor of the motor (5), an abnormal state comparison unit (117) determines the operation state of the motor (5) based on the correction value of the FFT result correction matrix selection unit (118) and the threshold value for determining abnormality of the motor (5), and if abnormality exists, the operation state is displayed on a display unit (11).

Description

Diagnostic device for motor

Technical Field

The present invention relates to a diagnostic device for diagnosing whether or not an abnormality is present in a motor driven by an inverter.

Background

In recent years, in the context of environmental problems, there is a trend toward an increase in the use of a system for driving a motor by an inverter (hereinafter referred to as an inverter driving system) in order to achieve high-efficiency operation of the motor. The range in which the inverter-driven motor is used is the power of a machine or a production line in the process industry. For example, pumps, compressors, blowers, industrial robots, and the like have been widely used, and there is a growing demand.

Therefore, such motors are required to run continuously with robustness at all times. However, not all motors operate in a suitable environment of use, nor are they rarely operated in high-stress environments such as high temperature, high humidity, heavy loads, corrosion, wear, and the like.

Conventionally, such equipment is often diagnosed by a maintenance department through a five-element diagnosis by time schedule maintenance (TBM: time Based Maintenance: maintenance based on time). Particularly important motors require periodic diagnosis of the presence or absence of a faulty portion, which is a very serious problem in terms of cost.

Thus, there is an increasing concern about the state monitoring and maintenance technology of motors (CBM: condition Based Maintenance: condition-based maintenance).

In the current case, the diagnosis of the inverter-driven motor is performed by attaching various measuring devices such as sensors to each motor. Examples of the measuring device include a torque meter, a speed and acceleration vibration sensor, and the like.

Patent document 1 discloses a device for determining the presence or absence of an abnormality based on a distance between a pattern of power spectrum density obtained by performing fourier analysis on various signals representing the state of a rotary device such as a pump or a motor and a reference pattern of various signals in a normal state.

Prior art literature

Patent literature

Patent document 1: japanese patent laid-open No. 58-100734

Disclosure of Invention

Technical problem to be solved by the invention

However, for example, it is not realistic to apply the motor control center to centrally manage many motors of hundreds or thousands. Therefore, there is a need for a device for diagnosing the motor state of the inverter drive system based on information such as current and voltage that can be measured in the past by the motor control center, without using a special sensor that must be additionally provided, and for ensuring reliability, productivity, and safety.

The rotational speed or the running load of the inverter-driven motor varies from time to time according to the operation of the driver. As the rotational speed or the running load fluctuates, the current value, the voltage value, or other parameters required for diagnosis also fluctuates, and it is therefore difficult to determine whether the state of the motor is a phenomenon due to the running condition or a phenomenon due to degradation or failure. Regarding the inverter-driven motor, a method for diagnosing the motor independently of the fluctuation of the operation state is required.

In the abnormality detection device for a rotating machine disclosed in patent document 1, when considering the operation in the actual environment, there is a possibility that a change in the operation state specific to the inverter drive method is erroneously detected as deterioration of the motor. In patent document 1, a threshold value for diagnosis is compared with a predetermined value, and there is a possibility that erroneous detection is caused by a deviation in a frequency spectrum value of a rotation frequency of the motor depending on a mounting condition of the motor.

The present invention has been made to solve the above-described problems, and an object of the present invention is to provide a motor diagnostic device capable of detecting a change in an operation state peculiar to an inverter drive system and a deterioration symptom of a motor separately, thereby improving detection accuracy, and capable of preventing erroneous detection of motor diagnosis by detecting a mounting state of the motor as a deviation of a frequency spectrum value of a rotation frequency of the motor.

Technical proposal for solving the technical problems

The diagnostic device of the motor disclosed in the application comprises: a measurement circuit for inputting a current and a voltage of a motor driven by the inverter; a sampling frequency calculation unit for determining a sampling frequency when the current is in a steady state; an FFT analysis unit for performing frequency analysis on the current of the motor when the current is in a steady state; a peak detection operation unit for detecting a peak portion of the power spectrum deposited by the FFT analysis unit; a rotation band detection unit that obtains a peak portion generated by the rotation frequency of the motor from a peak portion of the power spectrum; a rotational frequency spectrum value detection unit for calculating a spectrum value of a peak portion generated by a rotational frequency of the motor; a rotational frequency spectrum value moving average buffer for performing a plurality of moving average processes on the spectrum value of the rotational frequency spectrum value detecting section; an averaging unit that averages the power spectrum a plurality of times; a rotation frequency sigma value calculation unit for calculating a deviation of a rotation frequency spectrum value in the rotation frequency spectrum value moving average buffer; a threshold value calculation unit that calculates a threshold value for determining an abnormality of the motor based on a result of the calculation by the rotation frequency σ value calculation unit; a normal state storage unit that stores the calculation result of the averaging calculation unit as a normal state of the motor; a load factor calculation unit that calculates an operation load factor of the motor; an FFT analysis result correction unit that corrects an FFT analysis result of the FFT analysis unit when diagnosis is performed; a correction value data storage unit that stores a correction value corresponding to the operation load factor; an FFT result correction matrix selection unit that selects a correction value of an FFT analysis result based on values of an operation frequency and an operation load factor of the motor; and an abnormal state comparing unit that determines an operation state of the motor based on the correction value of the FFT result correction matrix selecting unit and a threshold value for performing abnormality determination of the motor.

Effects of the invention

According to the motor diagnostic device of the present application, the change in the characteristic operation state of the motor of the inverter drive system can be detected separately from the sign of deterioration of the motor, and the detection accuracy can be improved.

Further, by detecting the mounting condition of the motor as a deviation of the frequency spectrum value of the rotational frequency of the motor, erroneous detection of motor diagnosis can be prevented.

Drawings

Fig. 1 is a schematic configuration diagram showing an installation state of a diagnostic device for a motor according to embodiment 1.

Fig. 2 is a block diagram showing the configuration of an arithmetic processing unit in the motor diagnosis apparatus according to embodiment 1.

Fig. 3 is a flowchart for explaining the operation of the motor diagnosis device according to embodiment 1.

Fig. 4 is a flowchart for explaining a correction method of the motor diagnostic device according to embodiment 1.

Fig. 5 is a diagram showing an example of an FFT result correction matrix used in the motor diagnosis apparatus according to embodiment 1.

Detailed Description

Hereinafter, a diagnostic device for an electric motor according to an embodiment will be described with reference to the drawings. In the drawings, the same reference numerals denote the same or corresponding parts.

Embodiment 1.

Fig. 1 is a schematic configuration diagram showing an installation state of a diagnostic device for a motor in embodiment 1.

In the figure, a main circuit 1 introduced from a power system is provided with a circuit breaker 2 for wiring, an electromagnetic contactor 3, and a voltage current detector 4 for detecting a load current of the main circuit 1. The main circuit 1 is connected to a motor 5 as a load, for example, a three-phase induction motor, and the motor 5 drives the machine 6. The motor 5 is an inverter-driven motor driven by an inverter.

The motor diagnostic apparatus 100 includes a measurement circuit 7 to which a current and a voltage detected by the voltage-current detector 4 are input; and an arithmetic processing unit 8 for detecting whether or not the load of the motor 5, the machine 6, and the like is abnormal using the current input from the measurement circuit 7.

The motor diagnostic device 100 is provided with: a rated information setting circuit 9 to which a power frequency of the motor 5, a rated output of the motor 5, a rated current, a number of poles, a rated rotational speed, and the like are input in advance; and a setting information storage circuit 10 that stores the rating information input from the rating information setting circuit 9. The rating information is information that can be easily obtained by looking at a catalog of a manufacturing company of the motor 5 or a nameplate mounted on the motor 5. When there are a plurality of motors 5 to be diagnosed, it is necessary to input rated information of the motors 5 to be diagnosed in advance, however, in the following description, description will be given with respect to 1 motor 5.

The display unit 11 is connected to the operation processing unit 8, and displays, for example, a physical quantity of the detected load current and an abnormal state and an alarm when the operation processing unit 8 detects an abnormality of the motor 5.

The driving circuit 12 is connected to the operation processing section 8, and outputs a control signal for opening and closing the electromagnetic contactor 3 based on a result of the operation processing section 8 being operated from the current signal detected by the voltage-current detector 4.

The output circuit unit 13 outputs signals such as abnormal states and warnings from the arithmetic processing unit 8 to the outside.

The external monitoring device 200 is constituted by, for example, a PC (personal computer), and is connected to the diagnostic device 100 of 1 or more motors, and appropriately receives information of the arithmetic processing unit 8 via the communication circuit 14 to monitor the operation state of the diagnostic device 100 of the motor. The connection between the external monitoring device 200 and the communication circuit 14 of the diagnostic device 100 may be a cable or may be a wireless connection. A network may be established between the diagnostic devices 100 of the plurality of motors and connected via the internet.

The configuration of the arithmetic processing unit 8 will be described with reference to fig. 2. The arithmetic processing unit 8 includes: a load factor calculation unit 110 that calculates a load factor from the current and voltage of the main circuit 1 input from the measurement circuit 7; a sampling frequency calculation unit 111 that measures a power supply frequency from a current or a voltage and calculates a sampling frequency; an FFT (Fast Fourier Transform: fast Fourier transform) analysis unit 112 that performs power spectrum analysis using the current of the measurement circuit 7; a peak detection operation unit 113 that selects a peak portion of the power spectrum analyzed by the FFT analysis unit 112; and a rotation band detection unit 114 that obtains a peak portion generated by the rotation frequency of the motor 5 from the peak portion detected by the peak detection operation unit 113.

Further, it includes: a rotation frequency spectrum value detection unit 115 for extracting a spectrum value of the rotation frequency band detection unit 114; a frequency axis conversion operation unit 119 for matching the frequencies of the rotation bands of the power spectrum for a plurality of times; a rotation frequency spectrum value moving average buffer 120 that saves the spectrum value of the rotation frequency as a stored value to perform an averaging and arithmetic processing; an averaging operation unit 121 for averaging the power spectrum obtained by the rotation band detection unit 114 having the frequency axis converted a plurality of times, which is stored in the rotation frequency spectrum value moving average buffer 120; a rotation frequency σ value calculation unit 122 that calculates a deviation σ of the rotation frequency spectrum value using the stored value of the rotation frequency spectrum value moving average buffer 120; and a threshold value calculation unit 123 for selecting a threshold value for abnormality diagnosis based on the result of the operation in the rotation frequency σ value operation unit 122.

Further comprises: a sideband wave extracting unit 116 that extracts whether or not there are peak portions (hereinafter, peak portions are referred to as sideband waves) on both sides of the power supply frequency other than the rotation band of the motor 5, using the power spectrum averaged by the averaging unit 121; an FFT result correction matrix selection unit 118 that determines a correction value of the FFT analysis result based on the rotation band detection unit 114 and the load factor calculation unit 110; an FFT analysis result correction unit 125 that corrects the current FFT analysis result of the motor at the time of diagnosis using the correction value selected by the FFT result correction matrix selection unit 118; and a correction value data storage section 126 that stores correction value information of the FFT analysis result from both the load factor and the frequency.

Further comprises: a normal state storage unit 124 that stores and stores a measured value of the normal state to compare the abnormal state with the normal state; and an abnormal state comparing unit 117 that compares the value stored in the normal state storing unit 124 with the current value to perform a good judgment diagnosis of whether or not the motor is good.

In the present embodiment, when the current of the motor 5 is in a steady state, the sampling frequency is determined by the sampling frequency calculation unit 111, and the FFT analysis unit 112 performs frequency analysis on the current of the motor 5.

The peak detection operation unit 113 detects a peak portion of the power spectrum analyzed by the FFT analysis unit 112, and the rotation band detection unit 114 obtains a peak portion due to the rotation frequency of the motor 5 from the peak portion of the power spectrum.

Next, the rotational frequency spectrum value detection unit 115 calculates a spectrum value of a peak portion generated by the rotational frequency of the motor 5, and the rotational frequency spectrum value detection unit 115 performs a plurality of times of moving averaging processing on the spectrum value in the rotational frequency spectrum value moving average buffer 120.

The averaging unit 121 averages the power spectrum a plurality of times, and the rotational frequency σ value calculating unit 122 calculates the deviation of the rotational frequency spectrum value in the rotational frequency spectrum value moving average buffer 120.

Further, the frequency spectrum value is corrected for each of the operation load rate and the operation frequency of the motor 5, and the threshold value of the abnormality determination is determined from the deviation of the frequency spectrum value of the motor 5 at the threshold value calculating section 123.

The threshold value calculating unit 123 calculates a threshold value for determining abnormality of the motor 5 based on the calculation result of the rotation frequency σ value calculating unit 122, and the normal state storing unit 124 stores the calculation result of the averaging calculating unit 121 as a normal state of the motor 5.

The load factor calculation unit 110 calculates the operating load factor of the motor 5, and the FFT analysis result correction unit 125 corrects the FFT analysis result of the FFT analysis unit 112 when performing diagnosis.

The correction value data storage section 126 stores a correction value corresponding to the operation load factor, and the FFT result correction matrix selection section 118 is configured to select a correction value of the FFT analysis result in accordance with the operation frequency of the motor 5 and the value of the operation load factor.

The abnormal state comparing unit 117 determines the operation state of the motor 5 based on the correction value in the FFT result correction matrix selecting unit 118 and the threshold value for performing the abnormality determination of the motor 5, and if the abnormal state comparing unit 117 determines that there is an abnormality, the display unit 11 displays the abnormal state.

Next, the operation of the motor diagnostic device in embodiment 1 will be described with reference to fig. 3. The diagnosis of the motor is considered to be divided into a phase of learning an initial state (normal state) of the motor and a phase of performing the diagnosis. Fig. 3 (a) shows a flow of processing operations in a stage of learning an initial state, and fig. 3 (b) shows a flow of processing operations in a stage of performing diagnosis. The present diagnosis is characterized in that the initial state of the motor is learned as a normal state, and the motor is evaluated based on a difference from the current value in the diagnosis.

First, as a flow of initial calculation, as shown in a flow chart of fig. 3 (a), the start of motor operation is detected (step S101), and the current and voltage of the main circuit 1 of the motor 5 are measured by current and voltage measurement (step S102). Next, the load factor is calculated from the measured values of the current and the voltage (step S103). The main circuit current is subjected to frequency analysis by FFT analysis (step S104). By the rotational signal intensity extraction, rotational vibration intensity is calculated from the analysis result of the FFT (step S105), and the averaging process is performed for each frequency and load factor (step S106). The averaged value is stored a plurality of times for a certain period of time, and initial learning is performed as a determination value of a normal state (step S107). After the initial learning is completed, a stabilized correction value for trend diagnosis and a determination threshold value for abnormal vibration are calculated for each load factor by the correction value and determination value calculation (step S108). Finally, storage of the correction matrix for storing the correction values and the determination threshold is performed (step S109).

Next, a diagnostic start flow performed after learning will be described. As shown in fig. 3 b, if the operation of the motor is confirmed (step S110), the processing up to the current-voltage measurement step S111, the load factor calculation step S112, the FFT analysis step S113, the rotational vibration intensity extraction step S114, and the averaging processing step S115 for each frequency and load factor is performed in the same manner as the initial learning flow shown in fig. 3 a. In the diagnosis, the correction matrix position of the correction value at the current load factor is read from the correction matrix learned in the initial learning process (step S116), and the correction value and the determination threshold value are read. Then, a process of comparing the initial learning value with the corrected measurement value to perform initial and current value comparison (step S118) and performing abnormality determination based on the comparison (step S119) is performed.

In the initial calculation start flow of fig. 3 (a), by the averaging process of each frequency and load factor of step S106 and the correction value and determination threshold calculation of step S108, erroneous detection of diagnosis due to the operation or running condition of the motor can be avoided. In the diagnosis start flow of fig. 3 (b), the correction value and the determination threshold value acquired in the initial calculation are corrected by referring to the determination threshold value and the initial value in step S117, whereby accurate determination can be achieved.

For the initial calculation start flow of fig. 3 (a), the correction value and determination threshold value calculation step S108 and the correction matrix storage step S109 average the rotation signal spectrum value used in diagnosis based on the load factor calculated in the load factor calculation step S103 and the rotation frequency of the motor obtained in the rotation signal intensity extraction step S105. Even if the running state of the motor fluctuates, diagnosis can be performed without false detection. Further, by the correction value and determination threshold value calculation step S108 on the initial calculation start flow, the likelihood of the diagnostic threshold value can be ensured among factors such as the setting conditions of the motor, so that false detection can be prevented.

Step S106 for calculating the average of each frequency and load factor of fig. 3 (a) is performed, and stored in the rotational frequency spectrum value moving average buffer 120, initial learning step S107 is performed, the average value is calculated from the rotational frequency spectrum value moving average buffer 120, as shown in fig. 4, after the unbiased variance is calculated in the flow FL1, the determination threshold value for the unbiased variance motor is selected from the determination threshold value selection table in the flow FL2, correction value and determination threshold value calculation step S108 is performed, and storage of the correction matrix to the correction value data storage unit 126 is performed (step S109). As shown in fig. 5, the correction matrix is a matrix composed of frequencies and load factors, and has a unit that stores, in addition to the correction values, the determination threshold selected in the flow of fig. 4 for each frequency.

The diagnosis may be performed without depending on the operation condition (load fluctuation and frequency fluctuation) of the motor of the inverter drive system. Further, since the vibration phenomenon of the motor to be diagnosed changes due to the operation of the motor running speed, which is a characteristic of the inverter driving method, the diagnosis threshold can be automatically tuned for each frequency of the motor, and thus erroneous detection of diagnosis can be prevented, and detection can be performed with high accuracy.

The arithmetic processing unit 8 is configured by a processor and a storage device as a hardware configuration. The storage device includes, for example, a volatile storage device such as a random access memory and a nonvolatile auxiliary storage device such as a flash memory. In addition, an auxiliary storage device such as a hard disk may be provided instead of the flash memory. The processor executes a program input from the storage device. In this case, the program is input from the auxiliary storage device to the processor via the volatile storage device. The processor may output the data of the operation result to a volatile memory device of the storage device, or may store the data to an auxiliary storage device via the volatile memory device, for example.

The present application describes exemplary embodiments, but the various features, aspects, and functions described in the embodiments are not limited to application to particular embodiments, and can be applied to embodiments alone or in various combinations.

Accordingly, numerous modifications not illustrated are considered to be included in the technical scope disclosed in the present specification. For example, the case of deforming at least one component, the case of adding, or the case of omitting is included.

Description of the reference numerals

The device comprises a 4-voltage current detector, a 5-motor, a 7-measurement circuit, an 8-operation processing unit, a 100-diagnosis device, a 110-load factor calculating unit, a 111-sampling frequency calculating unit, a 112FFT analyzing unit, a 113-peak detection calculating unit, a 114-rotation frequency band detecting unit, a 115-rotation frequency spectrum value detecting unit, a 117 abnormal state comparing unit, a 118FFT result correction matrix selecting unit, a 120-rotation frequency spectrum value moving average buffer, a 121-averaging calculating unit, a 122-rotation frequency sigma value calculating unit, a 123-threshold calculating unit, a 124-normal state storing unit, a 125FFT analyzing result correcting unit and a 126-correction value data storing unit.

Claims

1. A diagnostic device for an electric motor includes an arithmetic processing unit that diagnoses an abnormality of the electric motor based on a current and a voltage of the electric motor driven by an inverter; the diagnostic device of the motor is characterized in that,

the arithmetic processing unit includes: a measurement circuit for inputting a current and a voltage of the motor;

a sampling frequency calculation unit configured to determine a sampling frequency when the current is in a steady state;

an FFT analysis unit for performing frequency analysis on the current of the motor when the current is in a steady state;

a peak detection operation unit for detecting a peak portion of the power spectrum deposited by the FFT analysis unit;

a rotation band detection unit that obtains a peak portion generated by a rotation frequency of the motor from a peak portion of the power spectrum;

a rotational frequency spectrum value detection unit for calculating a spectrum value of a peak portion generated by a rotational frequency of the motor;

a rotational frequency spectrum value moving average buffer for performing a plurality of moving average processes on the spectrum value of the rotational frequency spectrum value detecting unit;

an averaging unit that averages the power spectrum a plurality of times;

a rotation frequency σ value calculation unit configured to calculate a deviation of a rotation frequency spectrum value in the rotation frequency spectrum value moving average buffer;

a threshold value calculation unit that calculates a threshold value for determining abnormality of the motor based on a result of the calculation by the rotation frequency σ value calculation unit;

a normal state storage unit that stores a calculation result of the averaging calculation unit as a normal state of the motor;

a load factor calculation unit that calculates an operation load factor of the motor;

an FFT analysis result correction unit that corrects an FFT analysis result of the FFT analysis unit when diagnosis is performed;

a correction value data storage unit that stores a correction value corresponding to the operation load factor;

an FFT result correction matrix selection unit that selects a correction value of an FFT analysis result based on values of an operation frequency and an operation load factor of the motor; and

an abnormal state comparing unit that determines an operation state of the motor based on a correction value of the FFT result correction matrix selecting unit and a threshold value for performing abnormality determination of the motor.

2. The motor diagnosis device according to claim 1, wherein,

the spectral values are corrected for each operating load factor and operating frequency of the motor.

3. The motor diagnosis device according to claim 1, wherein,

a threshold value for abnormality determination is determined in the threshold value calculation unit based on the deviation of the frequency spectrum value of the motor.