Motor fault detection method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a motor fault detection method and device, electronic equipment and a storage medium. The method comprises the following steps: detecting a spindle position offset range of a motor; detecting the operation noise frequency of the motor in response to the fact that the position deviation range of the main shaft is larger than a preset range; determining operation stability data according to the operation noise frequency; and determining a fault type according to the operation stability data. According to the embodiment of the invention, the fault type of the motor can be accurately detected, so that the fault motor can be maintained in a targeted manner; the maintenance efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of motor maintenance, and in particular to a motor fault detection method, a motor fault detection device, an electronic device and a storage medium. Background Art

[0002] Common motor fault detection methods and devices often use experienced engineers to judge whether the motor is good or bad based on their experience by listening to the noise generated by the motor. However, this method has the problem that the accuracy of manual judgment is not high. In addition, due to human subjectivity, there are errors in judgment, resulting in low accuracy of motor fault detection methods. Summary of the invention

[0003] In view of the above problems, embodiments of the present invention are proposed to provide a motor fault detection method, a motor fault detection device, an electronic device and a storage medium that overcome the above problems or at least partially solve the above problems.

[0004] In order to solve the above problems, in a first aspect of the present invention, an embodiment of the present invention discloses a motor fault detection method, comprising:

[0005] Detect the spindle position offset range of the motor;

[0006] In response to the spindle position offset range being greater than a preset range, detecting an operating noise frequency of the motor;

[0007] determining operation stability data according to the operation noise frequency;

[0008] A fault type is determined based on the operational stability data.

[0009] Optionally, the step of determining the operation stability data according to the operation noise frequency includes:

[0010] Calculating the fluctuation value of the operating noise frequency;

[0011] The operation stability data is determined according to the fluctuation value of the operation noise frequency.

[0012] Optionally, the step of calculating the fluctuation value of the operating noise frequency includes:

[0013] Calculating the variance of the operating noise frequency;

[0014] The variance is determined as a fluctuation value of the operating noise frequency.

[0015] Optionally, the step of determining the fault type according to the operation stability data includes:

[0016] The variance is compared with a preset fault registration value to determine the fault type.

[0017] Optionally, the preset fault registration value includes 1, 3, 5, 7, and 9; and the step of comparing the variance with the preset fault registration value to determine the fault type includes:

[0018] In response to the variance being no greater than 1, or being greater than 3 and not greater than 5, determining that the fault type is a bearing lubrication fault;

[0019] In response to the variance being greater than 1 and less than 3, determining the fault type to be a bearing ball deformation fault;

[0020] In response to the variance being greater than 5 and less than 7, determining the fault type to be a fitting clearance abnormality fault;

[0021] In response to the variance being greater than 7 and not greater than 9, it is determined that the fault type is a motor sweeping fault.

[0022] Optionally, the method further comprises:

[0023] Collect fault noise frequency;

[0024] The preset fault registration information is determined according to the fluctuation value of the fault noise frequency.

[0025] Optionally, the step of detecting the noise frequency of the motor includes:

[0026] Detect the noise frequency of the motor within a preset time period.

[0027] Optionally, the method further comprises:

[0028] Perform troubleshooting based on the fault type described.

[0029] Optionally, the method further comprises:

[0030] In response to the spindle position offset range being not greater than a preset range, it is determined that the motor operates normally.

[0031] In a second aspect of the present invention, an embodiment of the present invention discloses a motor fault detection device, comprising:

[0032] The first detection module is used to detect the main shaft position offset range of the motor;

[0033] A second detection module, configured to detect the operating noise frequency of the motor in response to the spindle position offset range being greater than a preset range;

[0034] a stability determination module, configured to determine operation stability data according to the operation noise frequency;

[0035] A fault judgment module is used to determine the fault type according to the operation stability data.

[0036] Optionally, the stability determination module includes:

[0037] A calculation submodule, used for calculating the fluctuation value of the operating noise frequency;

[0038] The stability determination submodule is used to determine the operation stability data according to the fluctuation value of the operation noise frequency.

[0039] Optionally, the stability determination submodule includes:

[0040] A calculation unit, used for calculating the variance of the operating noise frequency;

[0041] The stability determination unit is used to determine the variance as a fluctuation value of the operating noise frequency.

[0042] Optionally, the fault judgment module includes:

[0043] The comparison submodule is used to compare the variance with a preset fault registration value to determine the fault type.

[0044] Optionally, the preset fault registration value includes 1, 3, 5, 7, and 9; and the comparison submodule includes:

[0045] A first fault determination unit, configured to determine that the fault type is a bearing lubrication fault in response to the variance being not greater than 1, or greater than 3 and not greater than 5;

[0046] a second fault determination unit, configured to determine, in response to the variance being greater than 1 and not greater than 3, that the fault type is a bearing ball deformation fault;

[0047] a third fault determination unit, configured to determine, in response to the variance being greater than 5 and less than 7, that the fault type is a fitting clearance abnormality fault;

[0048] The fourth fault determination unit is used to determine that the fault type is a motor sweeping fault in response to the variance being greater than 7 and not greater than 9.

[0049] Optionally, the device further comprises:

[0050] A collection module, used for collecting fault noise frequency;

[0051] A registration module is used to determine the preset fault registration information according to the fluctuation value of the fault noise frequency.

[0052] Optionally, the second detection module includes:

[0053] The noise frequency detection submodule is used to detect the noise frequency of the motor within a preset time period.

[0054] Optionally, the device further comprises:

[0055] The normal operation module is used to determine that the motor is operating normally in response to the spindle position offset range being not greater than a preset range.

[0056] In the third aspect of the present invention, an embodiment of the present invention discloses an electronic device, including a processor, a memory, and a computer program stored in the memory and capable of running on the processor, wherein the computer program implements the steps of the motor fault detection method as described above when executed by the processor.

[0057] In a fourth aspect of the present invention, an embodiment of the present invention discloses a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the motor fault detection method as described above are implemented.

[0058] The embodiments of the present invention include the following advantages:

[0059] The embodiment of the present invention detects the spindle position offset range of the motor; in response to the spindle position offset range being greater than a preset range, detects the operating noise frequency of the motor; determines the operating stability data based on the operating noise frequency; and determines the fault type based on the operating stability data. By detecting the spindle position offset range, it is possible to detect whether the motor has a fault, and then analyze the type of fault based on the operating noise frequency of the motor. Only the spindle position offset range and the operating noise frequency of the motor need to be detected, and no additional detection equipment is required, which can reduce the detection cost. Moreover, the entire detection process can be judged using quantitative indicators, without relying on manual experience, and the consistency and accuracy of fault detection can be maintained, so that the fault condition and fault type of the motor can be detected efficiently and accurately. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 is a flowchart of a motor fault detection method embodiment of the present invention;

[0061] Figure 2 is a flowchart of another motor fault detection method embodiment of the present invention;

[0062] Figure 3 is a noise frequency schematic diagram of an example of a motor fault detection method of the present invention;

[0063] Figure 4 is a flowchart of steps of another motor fault detection method embodiment of the present invention;

[0064] Figure 5 It is a control flow chart of noise collection and analysis of an example of a motor fault detection method of the present invention;

[0065] Figure 6 is a flowchart of an example of a motor fault detection method of the present invention;

[0066] Figure 7 is a structural block diagram of an embodiment of a motor fault detection device of the present invention;

[0067] Figure 8 is a structural block diagram of an electronic device provided by an embodiment of the present invention;

[0068] Fig. 9 It is a structural block diagram of a storage medium provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0069] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0070] Reference Figure 1 , shows a flow chart of steps of an embodiment of a motor fault detection method of the present invention, and the motor fault detection method may specifically include the following steps:

[0071] Step 101, detecting the main shaft position offset range of the motor;

[0072] In the embodiment of the present invention, infrared sensors, travel switches, Hall sensors, visual sensors and other sensors may be used to detect the position offset range of the main shaft of the motor.

[0073] Among them, the infrared sensor usually includes two parts: a transmitter and a receiver. The transmitter and the receiver can be installed on the motor housing, and their detection direction is the main shaft of the motor. The infrared ray is emitted by the transmitter, and the receiver receives the reflected infrared ray. According to the needs, optical elements such as Fresnel lenses can be installed to enhance the emission and reception of infrared rays. The infrared sensor uses the infrared energy emitted or reflected by the surface of the object to detect the position and distance of the object. When the object is in front of the sensor, it will reflect or block the infrared ray emitted by the transmitter. After the receiver receives the signal, it processes it to determine the position and distance of the object, thereby detecting the spindle position offset range. The detection process is that the transmitter continuously emits infrared rays. The receiver receives the reflected infrared ray and converts it into an electrical signal. The position and distance of the object are determined by processing and analyzing the electrical signal through the circuit.

[0074] The travel switch can usually be installed on the main shaft of the motor at the position that needs to be detected. It has a movable contact and a fixed contact. When the contact moves to a certain position, it will contact the contact and send a signal. The travel switch uses the contact between the contact and the contact to detect the position of the object. When the mechanical moving part moves to the extreme position or the position that needs to be detected, the contact will contact the contact, thereby triggering the switch signal in the circuit. The mechanical moving part moves and drives the contact to move. When the contact contacts the contact, the circuit is connected or disconnected, and a switch signal is sent. The control system receives the signal and performs corresponding processing.

[0075] The Hall sensor is installed at the position where the magnetic field change needs to be detected. The position of the magnetic field change can be the position corresponding to the main shaft of the motor that needs to be detected. It has a Hall element and a magnetic field source (such as a magnet). When the magnetic field source moves near the sensor, it changes the magnetic field strength around the Hall element. The Hall sensor uses the Hall effect to detect changes in the magnetic field. When the magnetic field source moves near the sensor, it changes the magnetic field strength around the Hall element, thereby generating a potential difference (Hall voltage) in the Hall element. By measuring the magnitude and direction of the Hall voltage, the position and direction of movement of the magnetic field source can be determined. The magnetic field source moves and changes the magnetic field strength around the Hall element. The Hall element generates a potential difference (Hall voltage). The position and direction of movement of the magnetic field source are determined by circuit processing and analysis of the Hall voltage.

[0076] Visual sensors usually include a camera (or image sensor) and an image processing system. The camera is installed at the location where detection is required to capture the image of the object. The image processing system processes and analyzes the captured image. Visual sensors use image processing technology to detect the position and shape of objects. The camera captures the image of the object and converts it into a digital signal. The image processing system processes and analyzes the digital signal to extract the characteristics and location information of the object. The camera captures the image of the object. The image processing system pre-processes the image (such as denoising, enhancement, etc.). The characteristics and location information of the object are extracted through the image recognition algorithm. The extracted information is compared with the preset threshold or template to determine the position and state of the object.

[0077] Step 102, in response to the spindle position offset range being greater than a preset range, detecting the operating noise frequency of the motor;

[0078] After the spindle position offset range is detected, it can be determined whether the spindle position offset range is greater than the preset range to determine whether the motor is in an abnormal state. When the spindle position offset range is greater than the preset range, it indicates that the current spindle operation is in an abnormal state. In response to the spindle position offset range being greater than the preset range, the motor operation noise frequency can be detected to further determine the type of fault. Otherwise, the operation is normal.

[0079] Among them, the size of the preset range can be determined according to the motor structural conditions such as the motor manufacturing error and installation error, and the preset range is used to characterize the maximum spindle offset range when the motor is operating normally. Manufacturing errors are errors that may exist in the motor spindle and its related components during the manufacturing process, such as insufficient machining accuracy, improper assembly, etc., which may cause the spindle position to shift. These errors may be caused by quality problems of raw materials, insufficient control of production processes, or precision limitations of equipment. Installation errors are during the installation process of the motor spindle. If the fixation is improper, the installation direction is wrong, or the centering is not accurate, the spindle position may shift. In addition, environmental factors during installation, such as temperature and humidity, may also affect the installation accuracy.

[0080] Step 103, determining operation stability data according to the operation noise frequency;

[0081] According to the collected running noise frequency, the motor is identified and the running stability of the motor is determined by the change of the running noise frequency, and the running stability data is determined. The running stability data characterizes the dynamic changes of the motor during operation, that is, the running stability data corresponds to the running stability of the motor. The larger the data in the running stability data, the more drastic the dynamic changes of the motor during operation; conversely, the smaller the data in the running stability data, the more stable the dynamic changes of the motor during operation.

[0082] Step 104: determine the fault type according to the operation stability data.

[0083] Through different operating stability data, the different dynamic changes of the motor are determined, from which the specific fault type is determined.

[0084] The embodiment of the present invention detects the spindle position offset range of the motor; in response to the spindle position offset range being greater than a preset range, detects the operating noise frequency of the motor; determines the operating stability data based on the operating noise frequency; and determines the fault type based on the operating stability data. By detecting the spindle position offset range, it is possible to detect whether the motor has a fault, and then analyze the type of fault based on the operating noise frequency of the motor. Only the spindle position offset range and the operating noise frequency of the motor need to be detected, and no additional detection equipment is required, which can reduce the detection cost. Moreover, the entire detection process can be judged using quantitative indicators, without relying on manual experience, and the consistency and accuracy of fault detection can be maintained, so that the fault condition and fault type of the motor can be detected efficiently and accurately.

[0085] Reference Figure 2 , shows a flowchart of another motor fault detection method embodiment of the present invention, the motor fault detection method may specifically include the following steps:

[0086] Step 201, detecting the main shaft position offset range of the motor;

[0087] In the embodiment of the present invention, the types of motors to be detected include but are not limited to stepper motors and servo motors. Among them, stepper motor: an open-loop control motor that converts an electrical pulse signal into an angular displacement, is an induction motor. The stepper drive is used to convert direct current into a multi-phase timing control current that is supplied in batches. The optimal working range of the stepper motor is 150-500r / min, and stepper motors are often used in occasions such as synchronous belt transmission and flat belt conveyors where the positioning accuracy requirements are not very high. The closed-loop stepper motor adds an encoder to the tail to achieve closed-loop control, and the speed can reach 1500r / min. In occasions where low-cost and high-precision positioning is required, it can replace the general servo system application. Servo motor: The control speed and position accuracy are very accurate, and the voltage signal can be converted into torque and speed to drive the control object. The servo motor puts the control circuit outside the motor, and the motor part inside is a standard DC motor or AC induction motor. Among them, the most commonly used servo motor is a permanent magnet synchronous AC servo. General industrial servo motors adopt current loop, speed loop, and position loop control modes to feedback the angular acceleration, angular velocity, and rotational position of the motor respectively. The chip controls the driving current of each phase of the motor through the feedback of the three, so that the motor speed and position can be accurately operated. The servo has a short-term overload capacity, and the motor overload multiple during acceleration and deceleration should be considered when selecting. There are many different power supply forms for this motor, such as DC brush motor. DC brushless motor, also known as DC variable frequency motor (BLDC), uses Hall sensor electronic commutation, the coil (armature) is stationary and the magnetic pole is moving, and there are outer rotor brushless motor and inner rotor brushless motor. Its structure is the same as that of permanent magnet synchronous motor, using DC input, but using the frequency conversion technology of synchronous motor. The driving current of brushless motor has two types: square wave and sine wave, corresponding to DC brushless motor and AC servo motor (i.e. a type of AC servo motor). Asynchronous AC motor: a motor whose motor speed cannot reach the synchronous speed of the stator magnetic field. Synchronous AC motor, the motor speed is synchronized with the speed of the stator magnetic field.

[0088] The running position of the main shaft of the motor during operation may be detected first to obtain the main shaft position offset range of the motor.

[0089] Step 202, in response to the spindle position offset range being greater than a preset range, detecting the operating noise frequency of the motor;

[0090] By determining whether the spindle position offset range is greater than a preset range, it is determined whether the motor is faulty. When the spindle position offset range is greater than the preset range, it can be determined that the motor is faulty, and the running noise frequency of the motor can be detected in response to the spindle position offset range being greater than the preset range.

[0091] In an optional embodiment of the present invention, the step of detecting the noise frequency of the motor includes: detecting the noise frequency of the motor within a preset time period.

[0092] The noise of the motor is in a constantly changing state. The noise frequency required for fault judgment can be the noise frequency of the motor within a preset time period. The specific time of the preset time period can be determined based on the operating characteristics of the motor, and the embodiment of the present invention does not limit the specific cycle stage.

[0093] like Figure 3 As shown, the noise frequency change of the motor running in an abnormal state is in an unstable change, and the frequency of the noise will show a periodic change pattern. Within a certain time period (for example, collecting the frequency peak and trough value changes within 30 seconds), the noise frequency will repeat the peak and trough values. The periodic noise frequency changes caused by different motor mechanical failures are different. The noise can be collected within a preset time period to detect the noise frequency.

[0094] Step 203, determining operation stability data according to the operation noise frequency;

[0095] The collected operating noise frequency can be analyzed, and the stability of the motor operation can be determined by the change of the operating noise frequency to determine the operating stability data.

[0096] In an optional embodiment of the present invention, the step of determining the operation stability data according to the operation noise frequency includes: calculating the fluctuation value of the operation noise frequency; and determining the operation stability data according to the fluctuation value of the operation noise frequency.

[0097] For operational stability, it can be calculated by the fluctuation value of the operating noise frequency. The stability is reflected by the fluctuation. The fluctuation value of the operating noise frequency can be calculated. The fluctuation value of the operating noise frequency can be determined by a variety of methods, including but not limited to: spectrum analysis method, fast Fourier transform (FFT) and power spectral density (PSD); statistical method, variance and standard deviation; autocorrelation function. Among them, fast Fourier transform (FFT) is a mathematical method for converting time domain signals into frequency domain signals. Through FFT, the intensity distribution of the noise signal on each frequency component can be obtained. By observing the FFT results, it is possible to analyze in which frequency ranges the noise signal has significant fluctuations to determine the fluctuation value. Power spectral density describes the energy distribution of the noise signal in the frequency domain. By calculating PSD, the energy intensity of the noise signal at different frequencies can be understood. The fluctuation of PSD can reflect the change of the noise frequency characteristics. Variance is used to evaluate the contribution of variability from different sources to the overall variability. In noise frequency analysis, the variance between noises of different frequencies can be calculated to evaluate their fluctuations in the overall noise and obtain the fluctuation value. The fluctuation of variance can reflect the instability of the noise frequency characteristics. The standard deviation is a statistic that measures the degree of data dispersion of the noise frequency. In noise frequency analysis, the standard deviation of each frequency component can be calculated to evaluate their degree of fluctuation in the frequency domain. An increase in the standard deviation indicates an increase in the fluctuation of the noise frequency characteristics. The autocorrelation function is used to describe the similarity between a signal and itself at different time delays. In noise frequency analysis, the autocorrelation function can be used to evaluate the periodicity or correlation of the noise signal in the frequency domain. The fluctuation of the autocorrelation function can reflect the periodic changes in the noise frequency characteristics.

[0098] After the fluctuation value of the operating noise frequency is obtained, it is determined whether the noise change during the operation of the motor is in a stable state based on the fluctuation value of the operating noise frequency, so that the operating stability data is calculated through these fluctuation values ​​of the operating noise frequency.

[0099] In an optional embodiment of the present invention, the step of calculating the fluctuation value of the operating noise frequency includes: calculating the variance of the operating noise frequency; and determining the variance as the fluctuation value of the operating noise frequency.

[0100] The fluctuation value of the operating noise frequency can be characterized by the variance between the operating noise frequencies. That is, the variance of the operating noise frequency is calculated; the variance is determined to be the fluctuation value of the operating noise frequency. For example, the operating noise frequencies are collected, and the variances Σ of the operating noise frequencies A0, A1, A2, A3, A4, and A5 are calculated respectively. Σ=1 / N*((A1-A0)+(A2-A0)+(A3-A0)+(A4-A0)+(A5-A0)). The value of the variance Σ is determined to be the fluctuation value of the operating noise frequency.

[0101] Step 204, determining the fault type according to the operation stability data;

[0102] Different fault types can be determined based on different operating stability data, and the fault type can be used to determine the fault location, making it easier to repair the motor.

[0103] In an optional embodiment of the present invention, the step of determining the fault type based on the operation stability data includes: comparing the variance with a preset fault registration value to determine the fault type.

[0104] The obtained variance is compared with the preset fault registration value, and the interval range of the variance is determined by comparison, thereby determining the corresponding fault type.

[0105] Among them, the preset fault registration value can be obtained in advance through laboratory experiments or simulations, etc., and the corresponding data can be obtained for statistics. The fault noise frequency can be collected; the preset fault registration information is determined according to the fluctuation value of the fault noise frequency. That is, the fault noise frequency corresponding to different faults of the motor is collected in advance, the fluctuation value of the fault noise frequency is calculated, and the fault characteristics are registered according to these fluctuation values ​​and stored in the relevant memory to generate the preset fault registration information. When comparing later, the preset fault registration information can be extracted from these relevant memories.

[0106] Further, the preset fault registration values ​​include 1, 3, 5, 7, and 9; the step of comparing the variance with the preset fault registration value to determine the fault type includes: in response to the variance being not greater than 1, or greater than 3 and not greater than 5, determining that the fault type is a bearing lubrication fault; in response to the variance being greater than 1 and not greater than 3, determining that the fault type is a bearing ball deformation fault; in response to the variance being greater than 5 and not greater than 7, determining that the fault type is an abnormal fit clearance fault; in response to the variance being greater than 7 and not greater than 9, determining that the fault type is a motor bore cleaning fault.

[0107] The obtained variance can be compared with 1, 3, 5, 7, and 9 respectively to determine the range interval of the variance. In response to the variance being not greater than 1, or greater than 3 and not greater than 5, that is, the motor's main shaft bearing lacks lubricating oil and causes a fault, and the fault type is determined to be a bearing lubrication fault. The fault location is located in the main shaft bearing. In response to the variance being greater than 1 and not greater than 3, that is, the ball in the motor's main shaft bearing is deformed and causes a fault, and the fault type can be determined to be a bearing ball deformation fault. The fault location is located in the main shaft bearing. In response to the variance being greater than 5 and not greater than 7, that is, the source is from the motor suddenly starting, stopping, reverse braking and other speed change conditions, the rotor core and the shaft loosen and cause a fault, and the fault type can be determined to be an abnormal fit clearance fault; the fault location is located in the main shaft. In response to the variance being greater than 7 and not greater than 9, it is judged that the noise caused by the motor sweeping the bore, and it is necessary to focus on investigating the cause of the sweeping bore and determine that the fault type is a motor sweeping bore fault.

[0108] Step 205: troubleshooting based on the fault type.

[0109] Perform corresponding troubleshooting according to different fault types to repair the motor.

[0110] Specifically, if the fault type is a bearing lubrication fault, it is caused by dry grinding of the bearing due to lack of oil. The bearing needs to be disassembled and grease needs to be added to eliminate the fault. If the fault type is a bearing ball deformation fault, that is, the sound made by the irregular movement of the ball in the bearing, the bearing clearance and ball shape need to be tested to eliminate the fault. If the fault type is an abnormal matching clearance fault, it is necessary to detect the matching of the rotor core and the shaft to eliminate the fault. If the fault type is a motor bore scraping fault, the motor needs to be disassembled, the cause of the bore scraping needs to be checked, and measures need to be taken to deal with it.

[0111] The embodiment of the present invention detects the spindle position offset range of the motor; in response to the spindle position offset range being greater than a preset range, detects the operating noise frequency of the motor; determines the operating stability data based on the operating noise frequency; determines the fault type based on the operating stability data; and performs troubleshooting based on the fault type. By detecting the spindle position offset range, it is possible to detect whether the motor has a fault, and then analyze the type of fault based on the running noise frequency of the motor. Only the spindle position offset range and the running noise frequency of the motor need to be detected, and no additional detection equipment is required to reduce the detection cost. Moreover, the entire detection process can be judged using quantitative indicators without relying on manual experience. The consistency and accuracy of fault detection can be maintained, so that the fault condition and fault type of the motor can be detected efficiently and accurately. Troubleshooting can also be performed based on the fault type, and the fault can be eliminated in a timely manner to ensure the running stability and reliability of the motor.

[0112] Reference Figure 4, shows a flowchart of another motor fault detection method embodiment of the present invention, the motor fault detection method may specifically include the following steps:

[0113] Step 401, detecting the main shaft position offset range of the motor;

[0114] In the embodiment of the present invention, the main shaft position offset range of the motor can be detected by infrared sensors, travel switches, Hall sensors, visual sensors, etc. The main shaft position offset range of the motor is used to determine whether there is a fault.

[0115] Step 402, in response to the spindle position offset range being greater than a preset range, detecting the operating noise frequency of the motor;

[0116] When the spindle position offset range is greater than the preset range, it indicates that the current spindle operation is abnormal, and the motor operation noise frequency can be further detected to further determine the type of fault. The spindle position offset range and the preset range can be determined by the number axis method, difference method, quotient method, absolute value comparison, etc., which is not specifically limited in the embodiment of the present invention.

[0117] Among them, the number axis method is that the size relationship of the values ​​can be determined by their position on the number axis. The value represented by the point on the right is greater than the point on the left. The difference method is to calculate the difference between two values ​​and judge the size according to the sign of the difference. If the difference is positive, the first value is greater than the second; if the difference is negative, the first value is less than the second; if the difference is zero, the two values ​​are equal. The quotient method is to calculate the quotient of two values ​​(when the two have the same sign) and judge the size according to the value of the quotient. If the quotient is greater than 1, the numerator is greater than the denominator; if the quotient is less than 1, the numerator is less than the denominator; if the quotient is equal to 1, the two are equal. When the two have different signs, the positive number is always greater than the negative number. The absolute value comparison method is that for negative numbers, their sizes can be indirectly compared by comparing their absolute values. Negative numbers with large absolute values ​​are actually smaller.

[0118] Step 403, determining operation stability data according to the operation noise frequency;

[0119] Based on the collected operating noise frequency, whether the motor operation is stable is determined by the change of the operating noise frequency, and the operating stability data is generated.

[0120] Step 404, determining the fault type according to the operation stability data;

[0121] Through different operating stability data, the different dynamic changes of the motor are determined, from which the specific fault type is determined.

[0122] Step 405: In response to the spindle position offset range being not greater than a preset range, determining that the motor is operating normally.

[0123] When the spindle position offset range is not greater than the preset range, it indicates that the current spindle operation is in a normal state, and then waits for the next cycle to perform fault detection, so that the motor fault can be discovered in time and the reliability of the motor can be improved.

[0124] The embodiment of the present invention detects the spindle position offset range of the motor; in response to the spindle position offset range being greater than a preset range, detects the operating noise frequency of the motor; determines operating stability data based on the operating noise frequency; determines the fault type based on the operating stability data; and in response to the spindle position offset range being not greater than a preset range, determines that the motor is operating normally. By detecting whether the motor has a fault after the spindle position offset range is detected, and then analyzing the type of fault based on the operating noise frequency of the motor, it is only necessary to detect the spindle position offset range and the operating noise frequency of the motor, and no additional detection equipment is required, which can reduce the detection cost, and the entire detection process can be judged using quantitative indicators, without relying on manual experience to make judgments, which can maintain the consistency and accuracy of fault detection, so that the fault condition and fault type of the motor can be detected efficiently and accurately.

[0125] In order to make the embodiments of the present invention clear to those skilled in the art, an example is used to illustrate the embodiments of the present invention as follows:

[0126] You can refer to Figure 5 The noise collection module collects the frequency fluctuations of several common abnormal noises when the motor has a mechanical failure, and registers the abnormal noise. The peak and trough values ​​of the noise frequency fluctuations when the motor runs stably for 30 seconds under the fault state are collected, and 5 groups are collected continuously according to the motor working cycle. Under normal working conditions, the motor position sensor can detect the change of the motor position within a threshold range. When the motor has an abnormal failure, the frequency of the motor rotation will change. The infrared sensor installed at the position of the motor motion spindle will sense the change of the motor position and send out an alarm signal. At the same time, multiple detections are performed to see whether the abnormal change of the motor position is in a stable state. When the abnormal position change is stable, the noise collection module starts to collect noise for 30 consecutive seconds. Then the noise analysis module compares the collected noise with the sound noise frequency fluctuation change of the abnormal noise registration of the acquisition template. The motor fault detection module matches it to determine the cause of the motor noise failure.

[0127] The specific process can be found in Figure 6First, the motor noise under abnormal operation status is recorded and classified. For example, common motor noise is divided into three categories: electromagnetic noise, wind duct noise, and mechanical noise. Among them, the noise that has a serious impact on the motor's operating performance is divided into five categories, corresponding to five types of abnormal motor fault noises, namely "hissing", "creaking", "chirping", "dongdong", and "scratching". They correspond to different abnormal fault conditions of the motor. The fluctuation of the noise frequency at this time is completely different. The motor fault is judged and classified according to the change of frequency fluctuation;

[0128] The motor noise acquisition module first records the five abnormal mechanical noises generated by the motor under abnormal conditions. The position sensor that detects the position change of the motor shaft is responsible for detecting the position offset of the motor during operation. When the motor is working normally, the noise frequency fluctuation of the motor, whether it is forward or reverse, is within a stable range. At this time, the motor rotates at a frequency that is approximately uniform, the noise frequency is stable, and the position offset of the motor shaft is within the allowable threshold range of 5mm (millimeter). When the motor fails, because the motor speed is abnormal due to lack of oil or braking, blocking and other problems, the motor will have a position offset exceeding the threshold range of 5mm. At this time, it can be judged that the motor is in an abnormal working state, and the motor noise acquisition module needs to be started to collect and analyze the noise of the motor in the abnormal working state at this time, so as to determine the type of abnormal motor failure;

[0129] The noise frequency change of the motor running in an abnormal state is in an unstable change. The frequency of the noise will show a periodic change law. Within a certain time period (for example, collecting the frequency peak and trough value changes within 30s), the noise frequency will repeat the peak and trough values. The periodic noise frequency changes caused by different motor mechanical failures are different. The motor acquisition module collects the noise, classifies the recorded noise according to the frequency fluctuation value, and obtains the noise frequency A0, A1, A2, A3, A4, A5. The variance is calculated to judge the stability Σ=1 / N*((A1-A 0)+(A2-A0)+(A3-A0)+(A4-A0)+(A5-A0)), if Σ≤1 or Σ≤5, it is usually caused by dry grinding of the bearing due to lack of oil, and the bearing needs to be disassembled to add grease; if Σ≤3, it is usually the sound made by the irregular movement of the balls in the bearing, and the bearing clearance needs to be checked; if Σ≤7, it may be caused by the loose fit between the rotor core and the shaft under speed change conditions such as sudden start, stop, and reverse braking of the motor; if Σ≤9, it is judged that the noise is caused by motor bore sweeping, and the cause of the bore sweeping needs to be investigated and measures taken to deal with it.

[0130] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0131] Reference Figure 7 , shows a structural block diagram of an embodiment of a motor fault detection device of the present invention, and the motor fault detection device may specifically include the following modules:

[0132] The first detection module 701 is used to detect the spindle position offset range of the motor;

[0133] A second detection module 702, configured to detect the operating noise frequency of the motor in response to the spindle position offset range being greater than a preset range;

[0134] A stability determination module 703, configured to determine operation stability data according to the operation noise frequency;

[0135] The fault judgment module 704 is used to determine the fault type according to the operation stability data.

[0136] In an optional embodiment of the present invention, the stability determination module 703 includes:

[0137] A calculation submodule, used for calculating the fluctuation value of the operating noise frequency;

[0138] The stability determination submodule is used to determine the operation stability data according to the fluctuation value of the operation noise frequency.

[0139] In an optional embodiment of the present invention, the calculation submodule includes:

[0140] A calculation unit, used for calculating the variance of the operating noise frequency;

[0141] The stability determination unit is used to determine the variance as a fluctuation value of the operating noise frequency.

[0142] In an optional embodiment of the present invention, the fault judgment module 704 includes:

[0143] The comparison submodule is used to compare the variance with a preset fault registration value to determine the fault type.

[0144] In an optional embodiment of the present invention, the preset fault registration values ​​include 1, 3, 5, 7, and 9; and the comparison submodule includes:

[0145] A first fault determination unit, configured to determine that the fault type is a bearing lubrication fault in response to the variance being not greater than 1, or greater than 3 and not greater than 5;

[0146] a second fault determination unit, configured to determine, in response to the variance being greater than 1 and not greater than 3, that the fault type is a bearing ball deformation fault;

[0147] a third fault determination unit, configured to determine, in response to the variance being greater than 5 and less than 7, that the fault type is a fitting clearance abnormality fault;

[0148] The fourth fault determination unit is used to determine that the fault type is a motor sweeping fault in response to the variance being greater than 7 and not greater than 9.

[0149] In an optional embodiment of the present invention, the device further comprises:

[0150] A collection module, used for collecting fault noise frequency;

[0151] A registration module is used to determine the preset fault registration information according to the fluctuation value of the fault noise frequency.

[0152] In an optional embodiment of the present invention, the second detection module 702 includes:

[0153] The noise frequency detection submodule is used to detect the noise frequency of the motor within a preset time period.

[0154] In an optional embodiment of the present invention, the device further comprises:

[0155] The normal operation module is used to determine that the motor is operating normally in response to the spindle position offset range being not greater than a preset range.

[0156] The embodiment of the present invention detects the spindle position offset range of the motor; in response to the spindle position offset range being greater than a preset range, detects the operating noise frequency of the motor; determines the operating stability data based on the operating noise frequency; and determines the fault type based on the operating stability data. By detecting the spindle position offset range, it is possible to detect whether the motor has a fault, and then analyze the type of fault based on the operating noise frequency of the motor. Only the spindle position offset range and the operating noise frequency of the motor need to be detected, and no additional detection equipment is required, which can reduce the detection cost. Moreover, the entire detection process can be judged using quantitative indicators, without relying on manual experience, and the consistency and accuracy of fault detection can be maintained, so that the fault condition and fault type of the motor can be detected efficiently and accurately.

[0157] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0158] Reference Figure 8 , an embodiment of the present invention further provides an electronic device, including:

[0159] A processor 801 and a storage medium 802, wherein the storage medium 802 stores a computer program executable by the processor 801, and when the electronic device is controlled to run, the processor 801 executes the computer program to implement the motor fault detection method as described in any one of the embodiments of the present invention.

[0160] The motor fault detection method comprises:

[0161] Detect the spindle position offset range of the motor;

[0162] In response to the spindle position offset range being greater than a preset range, detecting an operating noise frequency of the motor;

[0163] determining operation stability data according to the operation noise frequency;

[0164] A fault type is determined based on the operational stability data.

[0165] Optionally, the step of determining the operation stability data according to the operation noise frequency includes:

[0166] Calculating the fluctuation value of the operating noise frequency;

[0167] The operation stability data is determined according to the fluctuation value of the operation noise frequency.

[0168] Optionally, the step of calculating the fluctuation value of the operating noise frequency includes:

[0169] Calculating the variance of the operating noise frequency;

[0170] The variance is determined as a fluctuation value of the operating noise frequency.

[0171] Optionally, the step of determining the fault type according to the operation stability data includes:

[0172] The variance is compared with a preset fault registration value to determine the fault type.

[0173] Optionally, the preset fault registration value includes 1, 3, 5, 7, and 9; and the step of comparing the variance with the preset fault registration value to determine the fault type includes:

[0174] In response to the variance being no greater than 1, or being greater than 3 and not greater than 5, determining that the fault type is a bearing lubrication fault;

[0175] In response to the variance being greater than 1 and less than 3, determining the fault type to be a bearing ball deformation fault;

[0176] In response to the variance being greater than 5 and less than 7, determining the fault type to be a fitting clearance abnormality fault;

[0177] In response to the variance being greater than 7 and not greater than 9, it is determined that the fault type is a motor sweeping fault.

[0178] Optionally, the method further comprises:

[0179] Collect fault noise frequency;

[0180] The preset fault registration information is determined according to the fluctuation value of the fault noise frequency.

[0181] Optionally, the step of detecting the noise frequency of the motor includes:

[0182] Detect the noise frequency of the motor within a preset time period.

[0183] Optionally, the method further comprises:

[0184] Perform troubleshooting based on the fault type described.

[0185] Optionally, the method further comprises:

[0186] In response to the spindle position offset range being not greater than a preset range, it is determined that the motor operates normally.

[0187] The embodiment of the present invention detects the spindle position offset range of the motor; in response to the spindle position offset range being greater than a preset range, detects the operating noise frequency of the motor; determines the operating stability data based on the operating noise frequency; and determines the fault type based on the operating stability data. By detecting the spindle position offset range, it is possible to detect whether the motor has a fault, and then analyze the type of fault based on the operating noise frequency of the motor. Only the spindle position offset range and the operating noise frequency of the motor need to be detected, and no additional detection equipment is required, which can reduce the detection cost. Moreover, the entire detection process can be judged using quantitative indicators, without relying on manual experience, and the consistency and accuracy of fault detection can be maintained, so that the fault condition and fault type of the motor can be detected efficiently and accurately.

[0188] The memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the processor.

[0189] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0190] Reference Fig. 9 The embodiment of the present invention further provides a computer-readable storage medium 901, on which a computer program is stored. When the computer program is executed by a processor, the motor fault detection method as described in any one of the embodiments of the present invention is executed.

[0191] The motor fault detection method comprises:

[0192] Detect the spindle position offset range of the motor;

[0193] In response to the spindle position offset range being greater than a preset range, detecting an operating noise frequency of the motor;

[0194] determining operation stability data according to the operation noise frequency;

[0195] A fault type is determined based on the operational stability data.

[0196] Optionally, the step of determining the operation stability data according to the operation noise frequency includes:

[0197] Calculating the fluctuation value of the operating noise frequency;

[0198] The operation stability data is determined according to the fluctuation value of the operation noise frequency.

[0199] Optionally, the step of calculating the fluctuation value of the operating noise frequency includes:

[0200] Calculating the variance of the operating noise frequency;

[0201] The variance is determined as a fluctuation value of the operating noise frequency.

[0202] Optionally, the step of determining the fault type according to the operation stability data includes:

[0203] The variance is compared with a preset fault registration value to determine the fault type.

[0204] Optionally, the preset fault registration value includes 1, 3, 5, 7, and 9; and the step of comparing the variance with the preset fault registration value to determine the fault type includes:

[0205] In response to the variance being no greater than 1, or being greater than 3 and not greater than 5, determining that the fault type is a bearing lubrication fault;

[0206] In response to the variance being greater than 1 and less than 3, determining the fault type to be a bearing ball deformation fault;

[0207] In response to the variance being greater than 5 and less than 7, determining the fault type to be a fitting clearance abnormality fault;

[0208] In response to the variance being greater than 7 and not greater than 9, it is determined that the fault type is a motor sweeping fault.

[0209] Optionally, the method further comprises:

[0210] Collect fault noise frequency;

[0211] The preset fault registration information is determined according to the fluctuation value of the fault noise frequency.

[0212] Optionally, the step of detecting the noise frequency of the motor includes:

[0213] Detect the noise frequency of the motor within a preset time period.

[0214] Optionally, the method further comprises:

[0215] Perform troubleshooting based on the fault type described.

[0216] Optionally, the method further comprises:

[0217] In response to the spindle position offset range being not greater than a preset range, it is determined that the motor operates normally.

[0218] The embodiment of the present invention detects the spindle position offset range of the motor; in response to the spindle position offset range being greater than a preset range, detects the operating noise frequency of the motor; determines the operating stability data based on the operating noise frequency; and determines the fault type based on the operating stability data. By detecting the spindle position offset range, it is possible to detect whether the motor has a fault, and then analyze the type of fault based on the operating noise frequency of the motor. Only the spindle position offset range and the operating noise frequency of the motor need to be detected, and no additional detection equipment is required, which can reduce the detection cost. Moreover, the entire detection process can be judged using quantitative indicators, without relying on manual experience, and the consistency and accuracy of fault detection can be maintained, so that the fault condition and fault type of the motor can be detected efficiently and accurately.

[0219] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0220] It will be appreciated by those skilled in the art that the embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0221] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of the methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0222] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured product including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0223] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device so that a series of operating steps are executed on the computer or other programmable terminal device to produce a computer-implemented process, thereby providing instructions for executing on the computer or other programmable terminal device to implement the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0224] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present invention.

[0225] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or terminal device including the elements.

[0226] The above is a detailed introduction to a motor fault detection method, a motor fault detection, a device, an electronic device and a storage medium provided by the present invention. Specific examples are used in this article to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present invention, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A motor fault detection method, characterized in that: include: Detect the spindle position offset range of the motor; In response to the spindle position offset range being greater than a preset range, detecting an operating noise frequency of the motor; determining operation stability data according to the operation noise frequency; A fault type is determined based on the operational stability data.

2. The method according to claim 1, characterized in that The step of determining the operation stability data according to the operation noise frequency comprises: Calculating the fluctuation value of the operating noise frequency; The operation stability data is determined according to the fluctuation value of the operation noise frequency.

3. The method according to claim 2, characterized in that The step of calculating the fluctuation value of the operating noise frequency comprises: Calculating the variance of the operating noise frequency; The variance is determined as a fluctuation value of the operating noise frequency.

4. The method according to claim 3, characterized in that: The step of determining the fault type according to the operation stability data comprises: The variance is compared with a preset fault registration value to determine the fault type.

5. The method according to claim 3, characterized in that: The preset fault registration values ​​include 1, 3, 5, 7, and 9; and the step of comparing the variance with the preset fault registration value to determine the fault type includes: In response to the variance being no greater than 1, or being greater than 3 and not greater than 5, determining that the fault type is a bearing lubrication fault; In response to the variance being greater than 1 and less than 3, determining the fault type to be a bearing ball deformation fault; In response to the variance being greater than 5 and less than 7, determining the fault type to be a fitting clearance abnormality fault; In response to the variance being greater than 7 and not greater than 9, it is determined that the fault type is a motor sweeping fault.

6. The method according to claim 4, characterized in that The method further comprises: Collect fault noise frequency; The preset fault registration information is determined according to the fluctuation value of the fault noise frequency.

7. The method according to claim 1, characterized in that The step of detecting the noise frequency of the motor comprises: Detect the noise frequency of the motor within a preset time period.

8. The method according to claim 1, characterized in that The method further comprises: Perform troubleshooting based on the fault type described.

9. The method according to claim 1, characterized in that: The method further comprises: In response to the spindle position offset range being not greater than a preset range, it is determined that the motor operates normally.

10. A motor fault detection device, characterized in that: include: The first detection module is used to detect the main shaft position offset range of the motor; A second detection module, configured to detect the operating noise frequency of the motor in response to the spindle position offset range being greater than a preset range; a stability determination module, configured to determine operation stability data according to the operation noise frequency; A fault judgment module is used to determine the fault type according to the operation stability data.

11. An electronic device, characterized in that: The method comprises a processor, a memory and a computer program stored in the memory and capable of running on the processor, wherein when the computer program is executed by the processor, the steps of the motor fault detection method according to any one of claims 1 to 9 are implemented.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the motor fault detection method according to any one of claims 1 to 9 are implemented.

Images