Motor stability testing method, device and system and storage medium

Abstract

The invention provides a motor stability testing method, device and system and a storage medium, and the method comprises the steps: obtaining an attitude angle of a to-be-tested motor at at least one sampling moment in an operation process through a sensor, generating an attitude angle difference value sequence based on the difference of attitude angles at any two adjacent sampling moments, and determining an attitude angle difference value curve of the attitude angle difference value sequence; measurement data are quantized into digital signals to be output, the jitter amplitude of the to-be-detected motor in the operation process can be determined in real time according to the waveform change condition of the attitude angle difference curve, calculation time consumption is short, and the jitter amplitude of the motor can represent the stability of the motor, so that the stability of the motor can be detected in real time, and the stability of the to-be-detected motor is improved. The requirement for real-time detection of motor jitter can be met, and the problem that jitter detection based on a visual detection system is low in response speed is solved.

Description

Technical Field

[0001] This disclosure relates to automated testing technology, and in particular to a method, apparatus, system, and storage medium for testing motor stability. Background Technology

[0002] In modern industry and electronic products, electric motors are widely used in various types of equipment. During operation, motors may experience vibration, which not only affects equipment performance but can also lead to mechanical wear and increased energy consumption.

[0003] In related technologies, visual inspection systems are typically used to detect motor jitter. However, visual inspection systems based on high-speed cameras require complex image processing algorithms to process high-speed video frames, resulting in long computation times. Due to the high latency of image analysis, they cannot meet the requirements for real-time detection. Summary of the Invention

[0004] This disclosure provides a method, apparatus, system, and storage medium for testing motor stability, which can improve the real-time performance and accuracy of motor stability testing.

[0005] One aspect of this disclosure provides a method for testing motor stability, applied to a chip, the method comprising: Acquire sensor data collected by the sensor for the motor under test, the sensor data including the attitude angle of the motor under test during operation; Based on the sensor data, an attitude angle difference sequence is determined, where any attitude angle difference in the attitude angle difference sequence is the difference between the attitude angle at the corresponding sampling time and the attitude angle at the previous sampling time. Determine the attitude angle difference curve corresponding to the attitude angle difference sequence; Waveform analysis is performed on the attitude angle difference curve to obtain the waveform changes of the attitude angle difference curve; The vibration amplitude of the motor under test is determined based on the waveform change of the attitude angle difference curve.

[0006] Optionally, determining the attitude angle difference curve corresponding to the attitude angle difference sequence includes: The attitude angle difference sequence is smoothed using a first sliding window. The attitude angle difference curve is generated based on the attitude angle difference sequence after the first smoothing process.

[0007] Optionally, the first smoothing process performed on the attitude angle difference sequence using a first sliding window includes: For any sampling time within the first sliding window, the attitude angle difference value of the x sampling times before the intermediate sampling time and the attitude angle difference value of the y sampling times after the intermediate sampling time are weighted averaged to determine the attitude angle difference value of the intermediate sampling time, where x and y are both positive integers, and the intermediate sampling time is the sampling time located in the middle position of the first sliding window.

[0008] Optionally, determining the attitude angle difference curve corresponding to the attitude angle difference sequence includes: Determine the first attitude angle difference curve corresponding to the attitude angle difference sequence; The waveform analysis of the attitude angle difference curve to obtain the waveform changes of the attitude angle difference curve includes: Based on the waveform of the first attitude angle difference curve, the attitude angle difference sequence is subjected to a second smoothing process using a second sliding window; Based on the attitude angle difference sequence after the second smoothing process, a second attitude angle difference curve is generated; Waveform analysis was performed on the second attitude angle difference curve to obtain the waveform changes of the second attitude angle difference curve.

[0009] Optionally, the second smoothing process of the attitude angle difference sequence based on the waveform of the first attitude angle difference curve using a second sliding window includes: Determine the waveform width of each jitter wave in the first attitude angle difference curve, wherein the waveform width is the lateral distance between adjacent peaks and troughs; The length of the second sliding window is determined based on the minimum waveform width among the waveform widths, wherein the length of the second sliding window is less than or equal to the minimum waveform width; For any sampling time within the second sliding window, the attitude angle difference value of the m sampling times before the intermediate sampling time and the attitude angle difference value of the n sampling times after the intermediate sampling time are weighted averaged to determine the attitude angle difference value of the intermediate sampling time, where m and n are both positive integers, and the intermediate sampling time is the sampling time located in the middle position of the second sliding window.

[0010] Optionally, the step of performing waveform analysis on the attitude angle difference curve to obtain the waveform changes of the attitude angle difference curve includes: Waveform analysis is performed on the attitude angle difference curve to determine the intervals corresponding to each operating stage of the motor under test, and the peak-to-peak value of each wave in each interval of the attitude angle difference curve is obtained. The operating stage includes at least one of the acceleration stage, constant speed stage and deceleration stage, and the peak-to-peak value is the difference between the amplitudes of adjacent peaks and troughs. The determination of the jitter amplitude of the motor under test based on the waveform change of the attitude angle difference curve includes: The jitter amplitude for the corresponding operating stage is determined based on the peak-to-peak value of each wave in each interval of the attitude angle difference curve, wherein the jitter amplitude is one of the maximum peak-to-peak value, minimum peak-to-peak value, and average peak-to-peak value of the attitude angle difference curve in the interval.

[0011] Optionally, the sensor data further includes the attitude angles of the motor under test in at least one dimension during its operation in three-dimensional space; Determining the attitude angle difference curve corresponding to the attitude angle difference sequence includes: Determine the attitude angle difference curve corresponding to the attitude angle difference sequence in at least one dimension; The waveform analysis of the attitude angle difference curve to obtain the waveform changes of the attitude angle difference curve includes: Waveform analysis is performed on the attitude angle difference curve in at least one dimension to obtain the waveform changes of the attitude angle difference curve in at least one dimension.

[0012] In another aspect of this disclosure, a motor stability testing device is provided, applied to a chip, the device comprising: The acquisition module is used to acquire sensor data collected by the sensor for the motor under test, the sensor data including the attitude angle of the motor under test during operation; The first determining module is used to determine an attitude angle difference sequence based on the sensor data, wherein any attitude angle difference in the attitude angle difference sequence is the difference between the attitude angle at the corresponding sampling time and the attitude angle at the previous sampling time. The second determining module is used to determine the attitude angle difference curve corresponding to the attitude angle difference sequence; The analysis module is used to perform waveform analysis on the attitude angle difference curve to obtain the waveform changes of the attitude angle difference curve; The third determining module is used to determine the jitter amplitude of the motor under test based on the waveform change of the attitude angle difference curve.

[0013] Another aspect of this disclosure provides a motor stability testing system, including electronic equipment and sensors; The sensor is mounted on a load device connected to the motor under test, and the straight line of the central axis of the sensor coincides with the straight line of the central axis of the output shaft of the motor under test. The electronic device is configured to: acquire sensor data collected by the sensor for the motor under test, the sensor data including the attitude angles of the motor under test during operation; determine an attitude angle difference sequence based on the sensor data, wherein any attitude angle difference in the attitude angle difference sequence is the difference between the attitude angle at the corresponding sampling time and the attitude angle at the previous sampling time; determine an attitude angle difference curve corresponding to the attitude angle difference sequence; perform waveform analysis on the attitude angle difference curve to obtain the waveform change of the attitude angle difference curve; and determine the jitter amplitude of the motor under test based on the waveform change of the attitude angle difference curve.

[0014] In another aspect of this disclosure, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the methods described above.

[0015] In another aspect of this disclosure, a computer program product is provided, including computer program instructions that, when executed by a processor, implement the method described above.

[0016] Based on the embodiments of this disclosure, the attitude angle of the motor under test at at least one sampling moment during operation is acquired by a sensor. Then, an attitude angle difference sequence is generated based on the difference between the attitude angles of any two adjacent sampling moments, and its attitude angle difference curve is determined. This realizes the quantization of measurement data into digital signal output. The vibration amplitude of the motor under test during operation can be determined in real time by observing the waveform changes of the attitude angle difference curve. The calculation time is short. Since the vibration amplitude of the motor can characterize the stability of the motor, the stability of the motor can be detected in real time, which can meet the needs of real-time detection of motor vibration and solve the problem of slow response speed in vibration detection based on vision detection system.

[0017] The technical solutions of this disclosure will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] The accompanying drawings, which form part of this specification, illustrate embodiments of this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0019] This disclosure will become clearer with reference to the accompanying drawings and the following detailed description, wherein: Figure 1 This is a flowchart of one embodiment of the motor stability testing method disclosed herein; Figure 2 A schematic diagram of an attitude angle difference curve provided for an exemplary embodiment of this disclosure; Figure 3 This is a flowchart of another embodiment of the motor stability test method disclosed herein; Figure 4 This is a schematic diagram of the structure of one embodiment of the motor stability testing device disclosed herein; Figure 5 This is a schematic diagram of the structure of one embodiment of the motor stability testing system disclosed herein; Figure 6 This is a schematic diagram of the structure of an application embodiment of the electronic device disclosed herein. Detailed Implementation

[0020] Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of the present disclosure.

[0021] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of this disclosure are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0022] It should also be understood that in the embodiments disclosed herein, "a plurality of" may refer to two or more, and "at least one" may refer to one, two or more.

[0023] It should also be understood that any component, data or structure mentioned in the embodiments of this disclosure can generally be understood as one or more unless expressly defined or given to the contrary in the context.

[0024] Furthermore, the term "and / or" in this disclosure is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this disclosure generally indicates that the preceding and following related objects have an "or" relationship.

[0025] It should also be understood that the description of the various embodiments in this disclosure emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0026] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0027] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit this disclosure or its application or use.

[0028] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0029] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0030] Traditional methods for testing motor stability typically rely on complex piezoelectric sensor systems or high-speed camera-based vision inspection systems. Piezoelectric sensors can only detect single-axis vibrations of the motor under test, failing to capture complex vibrations in three-dimensional space and making it difficult to distinguish between anomalies caused by mechanical resonance and sudden load changes. High-speed camera-based vision inspection systems require significant time for image processing, and are limited by image analysis latency, failing to meet the demands of real-time testing; they are also costly.

[0031] To address the aforementioned technical issues, this disclosure provides a method for testing motor stability, applicable to the stability testing of motor structures such as industrial motors, UAV propulsion systems, and robot joints. It analyzes the vibration amplitude of the motor under test based on the change curve of the attitude angle difference, and requires short data processing time, thus meeting the needs of real-time testing.

[0032] Figure 1 This is a flowchart illustrating an exemplary embodiment of the present disclosure regarding a motor stability testing method. The motor stability testing method of this embodiment can be implemented using a chip communicatively connected to a sensor. The sensor is mounted on a load device connected to the motor under test, and the straight line containing the sensor's central axis coincides with the straight line containing the central axis of the motor's output shaft, in order to acquire data such as the attitude angle and angular velocity of the motor under test during rotation. The chip can be a system-on-a-chip (SoC), and the sensor can be an inertial measurement unit (IMU). The sensor can be integrated into the chip, and the chip can be mounted on the load device connected to the motor under test; alternatively, the chip can be mounted within an electronic device. This embodiment does not limit the relationship between the sensor and the chip.

[0033] like Figure 1 As shown, the method includes the following steps: Step 101: Obtain sensor data collected by the sensor for the motor under test. The sensor data includes the attitude angle of the motor under test during operation.

[0034] In one possible implementation, at least one sensor is installed on the motor under test (DUT), or at least one sensor is installed on a load device that moves under the drive of the DUT. During the operation of the DUT, the chip acquires sensor data collected by the sensor in real time. This sensor data includes the attitude angle of the DUT during operation, and may also include data such as the acceleration and angular velocity of the DUT. When the sensor is installed on the load device, directly acquiring the attitude angle of the load device is equivalent to acquiring the attitude angle of the DUT.

[0035] When an IMU (Induction Unit) is used as the sensor, the motion state of the motor under test or load device in three-dimensional space can be measured in real time. For example, the acceleration, angular velocity, and attitude angle of the motor under test or load device can be measured. Illustratively, the IMU may specifically include an accelerometer, a gyroscope, and a magnetometer. The accelerometer can be used to measure the linear acceleration of an object along the x, y, and z axes in three-dimensional space, and the pitch and roll angles can be calculated through static measurements. The gyroscope can measure angular velocity based on the Coriolis principle, and the rotation angle of the object can be obtained after integration processing. The magnetometer can be used to detect the direction of the magnetic field for assistance. The sensor data obtained in this embodiment mainly includes attitude angles, which refer to the angles between the motor under test and the coordinate axes of the world coordinate system in three-dimensional space. For example, the attitude angles may include at least one of the rotation angles of the motor under test about the horizontal axis (y-axis), the vertical axis (x-axis), and the vertical axis (z-axis).

[0036] Optionally, the sensor collects the attitude angle of the motor under test at a preset collection frequency. For example, if the sensor collects sensor data at a frequency of 20 times / second, the time interval between two adjacent sensor data is 0.05 seconds.

[0037] Step 102: Determine the attitude angle difference sequence based on sensor data. Any attitude angle difference in the attitude angle difference sequence is the difference between the attitude angle at the corresponding sampling time and the attitude angle at the previous sampling time.

[0038] After acquiring sensor data, the difference in attitude angles between any two adjacent sampling times is determined to obtain an attitude angle difference sequence. For example, if the attitude angles in a set of acquired sensor data are 10°, 16°, 20°, and 25° respectively, then starting from the second sampling time, the attitude angle difference sequence is obtained as 6°, 4°, and 5°.

[0039] Step 103: Determine the attitude angle difference curve corresponding to the attitude angle difference sequence.

[0040] In one possible implementation, an attitude angle difference curve is generated, using the sampling time as the independent variable and the attitude angle difference as the dependent variable, corresponding to the attitude angle difference sequence. This curve reflects the change of the attitude angle difference over time. For example, during the uniform rotation of the motor under test, if the motor runs smoothly without vibration, the attitude angle changes uniformly, the attitude angle difference remains constant, and the attitude angle difference curve should be a straight line with a fixed value. During the accelerated rotation of the motor under test, if the motor runs smoothly without vibration, the attitude angle changes rapidly, the attitude angle difference gradually increases, and the attitude angle difference curve should be a smooth curve with a gradually increasing value. Conversely, if vibration occurs during the rotation of the motor under test, it will lead to irregular changes in the attitude angle difference, and the corresponding attitude angle difference curve will fluctuate irregularly.

[0041] Indicative Figure 2 The attitude angle difference curves corresponding to two sets of attitude angle difference value sequences are shown. For example... Figure 2 As shown, when the vibration amplitude of the motor under test is small or there is no vibration, the corresponding attitude angle difference curve is relatively smooth. When the vibration amplitude of the motor under test is large, the corresponding attitude angle difference curve has vibration waves of different sizes and shapes.

[0042] Step 104: Perform waveform analysis on the attitude angle difference curve to obtain the waveform changes of the attitude angle difference curve.

[0043] Optionally, the waveform changes can include parameters such as amplitude, peak value, peak-to-peak value, and waveform width of each wave. It can also analyze and determine the changing trend of the attitude angle difference curve and divide it into intervals. For example, it can divide the intervals corresponding to the downward trend of the attitude angle difference curve, the intervals corresponding to the upward trend, and the intervals where the attitude angle difference is stable and unchanged, so as to analyze the vibration amplitude of the motor under test in different operating stages.

[0044] Step 105: Determine the jitter amplitude of the motor under test based on the waveform change of the attitude angle difference curve.

[0045] In one possible implementation, the jitter amplitude of the motor under test can be determined directly based on the parameters obtained from the above waveform analysis. For example, the jitter amplitude of the motor under test can be determined based on the peak-to-peak value of the attitude angle difference curve. Alternatively, the jitter amplitude of the motor under test can be determined by fitting the attitude angle difference curve to obtain the target difference curve (i.e., simulating the attitude angle difference curve under jitter-free conditions) and then by the deviation value of the attitude angle difference curve (the magnitude of deviation from the target difference curve).

[0046] In another possible implementation, the jitter amplitude of the motor under test can be determined by analyzing the waveform of the attitude angle difference curve. For example, the attitude angle difference curve can be input into a neural network model (such as a recurrent neural network, convolutional neural network, graph neural network, etc.) to obtain the jitter amplitude of the motor under test output by the neural network model. The method of determining the jitter amplitude of the motor under test can be set based on actual needs, and this disclosure does not limit this.

[0047] Optionally, to improve the accuracy of the test results, the motor under test can be subjected to multiple data acquisitions. For example, sensor data in three different operating periods can be obtained, and the jitter amplitude corresponding to the three operating periods can be obtained through steps 102 to 105 above. The weighted average of the three measured jitter amplitudes can be used as the jitter amplitude of the motor under test.

[0048] Optionally, after determining the vibration amplitude of the motor under test, a motor stability test report can be generated based on this vibration amplitude. For example, the motor stability test report includes, but is not limited to, the following information: the vibration amplitude of the motor under test, the vibration duration of the motor under test, and the stability parameters of the motor under test. The larger the vibration amplitude of the motor under test, the lower its stability. The corresponding stability parameters can be determined based on the pre-set relationship between the stability parameters and the vibration amplitude. To quantify the stability of the motor under test, in one optional example, the stability parameter can be a specific numerical value. For example, the stability parameter can be the reciprocal of the vibration amplitude; the larger the vibration amplitude, the smaller the stability parameter, indicating worse stability of the motor under test. In another optional example, the stability parameter can be a stability level. For example, multiple stability levels (e.g., 10) can be pre-set, and a vibration amplitude range corresponding to each stability level can be set. Based on the vibration amplitude range to which the vibration amplitude of the motor under test belongs, and the correspondence between the vibration amplitude range and the stability level, the stability level of the motor under test can be determined.

[0049] Based on the embodiments of this disclosure, the attitude angle of the motor under test at at least one sampling moment during operation is acquired by a sensor. Then, an attitude angle difference sequence is generated based on the difference between the attitude angles of any two adjacent sampling moments, and its attitude angle difference curve is determined. This realizes the quantization of measurement data into digital signal output. The vibration amplitude of the motor under test during operation can be determined in real time by observing the waveform changes of the attitude angle difference curve. The calculation time is short. Since the vibration amplitude of the motor can characterize the stability of the motor, the stability of the motor can be detected in real time, which can meet the needs of real-time detection of motor vibration and solve the problem of slow response speed in vibration detection based on vision detection system.

[0050] In one possible implementation, before generating the attitude angle difference curve, the attitude angle difference sequence can be filtered to eliminate data with significant interference due to factors such as measurement errors. Figure 3 As shown, step 103 above may specifically include the following steps: Step 301: Perform a first smoothing process on the attitude angle difference sequence using a first sliding window.

[0051] Step 302: Generate an attitude angle difference curve based on the attitude angle difference sequence after the first smoothing process.

[0052] Optionally, a first sliding window of preset length can be used to smooth the attitude angle difference values ​​within each first sliding window by calculating a weighted average. Step 301 may specifically include the following steps: For any sampling time within the first sliding window, the attitude angle difference value of the x sampling times before the intermediate sampling time and the attitude angle difference value of the y sampling times after the intermediate sampling time are weighted averaged to determine the attitude angle difference value of the intermediate sampling time. x and y are both positive integers, and the intermediate sampling time is the sampling time located in the middle position of the first sliding window.

[0053] Optionally, the attitude angle difference at intermediate sampling times can be smoothed using a weighted average formula, where the weighted average formula is as follows: Weighted average of attitude angle differences = ∑(Attitude angle difference i × Weight i) / ∑Weight i, where i is a positive integer, ranging from [1, K], and K is the number of sampling times within the sliding window excluding the intermediate sampling time, K = x + y. Optionally, the weight i for each sampling time can be a real number greater than 0, and the specific value can be set according to actual needs and modified as required. For example, when performing the weighted average calculation, different sampling times correspond to different weights, with higher weights for sampling times closer to the intermediate sampling time; or, the weights for different sampling times can be the same, i.e., the average of the attitude angle differences of the x sampling times before the intermediate sampling time and the attitude angle differences of the y sampling times after the intermediate sampling time can be determined as the attitude angle difference at the intermediate sampling time.

[0054] To illustrate, the length of the first sliding window corresponds to an odd number of sampling times, meaning that the values ​​of x and y are the same. For example, the length of the first sliding window is 5 sampling times, and the sliding step of the first sliding window is 1 sampling time. For each sliding window, the weighted average of the attitude angle difference values ​​of the first two sampling times and the attitude angle difference values ​​of the last two sampling times is determined as the attitude angle difference value of the third sampling time.

[0055] Optionally, when the motor under test has vibration, if the length of the first sliding window is too large, it will affect the waveform of the attitude angle difference curve and lead to inaccurate measurement results. Therefore, the preset length of the first sliding window should be as small as possible, for example, the preset length of the first sliding window is 3 sampling times.

[0056] In one possible implementation, after the initial generation of the attitude angle difference curve, the attitude angle difference sequence can be further smoothed based on the waveform of the attitude angle difference curve to obtain a smoother attitude angle difference curve. Step 103 above may specifically include the following steps: Determine the first attitude angle difference curve corresponding to the attitude angle difference sequence.

[0057] First, the attitude angle difference sequence is initially fitted to obtain the attitude angle difference curve (hereinafter referred to as the first attitude angle difference curve).

[0058] Optionally, the first attitude angle difference curve can be generated after performing the first sliding process on the attitude angle difference sequence in steps 301 to 302 above. Alternatively, the first attitude angle difference curve can be generated directly based on the attitude angle difference sequence determined in step 102.

[0059] Accordingly, step 104 above may specifically include the following steps: Step 104a: Based on the waveform of the first attitude angle difference curve, the attitude angle difference sequence is smoothed using a second sliding window.

[0060] Optionally, the waveform width of each jitter wave can be determined by analyzing the waveform of the first attitude angle difference curve, and the length of the second sliding window can be determined based on the waveform width. By selecting a second sliding window of a reasonable length to smooth the attitude angle difference sequence (hereinafter referred to as the second smoothing process), the attitude angle difference curve is made as smooth as possible without affecting its waveform, facilitating subsequent analysis to determine the jitter amplitude. Step 104a may specifically include the following steps: Step 1: Determine the waveform width of each jitter wave in the first attitude angle difference curve. The waveform width is the lateral distance between adjacent peaks and troughs.

[0061] Here, the peak refers to the maximum value in the first attitude angle difference curve, and the trough refers to the minimum value in the first attitude angle difference curve. The waveform width can be represented by the lateral distance (i.e., time difference) between adjacent peaks and troughs.

[0062] Step 2: Determine the length of the second sliding window based on the minimum waveform width. The length of the second sliding window is less than or equal to the minimum waveform width.

[0063] Optionally, the minimum waveform width can be directly set to the length of the second sliding window. By setting the length of the second sliding window to be less than or equal to the minimum waveform width, the waveform of the attitude angle difference curve can be avoided when smoothing using the second sliding window (e.g., reducing the peak value of the attitude angle difference curve). At the same time, setting the length of the second sliding window as close as possible to or equal to the minimum waveform width can make the attitude angle difference curve smoother and reduce the impact of noise data without affecting the waveform of the attitude angle difference curve.

[0064] Optionally, the length of the second sliding window can be determined based on the minimum waveform width and the window length threshold. For example, by setting a reasonable window length threshold, if the minimum waveform width is greater than or equal to the window length threshold, the length of the second sliding window is less than or equal to the minimum waveform width; if the minimum waveform width is less than the window length threshold, the length of the second sliding window is equal to the window length threshold, so as to prevent the sliding process from being invalid due to the length of the second sliding window being too small.

[0065] Step 3: For any sampling time within the second sliding window, the weighted average of the attitude angle differences of the m sampling times before the intermediate sampling time and the attitude angle differences of the n sampling times after the intermediate sampling time is determined as the attitude angle difference value at the intermediate sampling time.

[0066] Where m and n are both positive integers, and the intermediate sampling time is the sampling time located in the middle position of the second sliding window.

[0067] Optionally, after determining the length of the second sliding window, the attitude angle difference value within each second sliding window is smoothed by calculating a weighted average value using the second sliding window. The specific implementation of the smoothing process can be referred to the first smoothing process in step 301 above, and will not be repeated here.

[0068] Step 104b: Generate a second attitude angle difference curve based on the attitude angle difference sequence after the second smoothing process.

[0069] Step 104c: Perform waveform analysis on the second attitude angle difference curve to obtain the waveform changes of the second attitude angle difference curve.

[0070] In one possible implementation, the waveform changes of the second attitude angle difference curve can be obtained by analyzing the waveform, thereby determining the jitter amplitude of the motor under test. In an optional example, the waveform changes may include parameters such as the amplitude, peak value, peak-to-peak value, and waveform width of each wave. Furthermore, the changing trend of the attitude angle difference curve can be analyzed and intervals can be divided. For example, intervals corresponding to a downward trend, an upward trend, and a stable attitude angle difference can be defined, thereby analyzing the jitter amplitude of the motor under test at different operating stages.

[0071] In another optional example, the second attitude angle difference curve can be input into a neural network model (such as a recurrent neural network, convolutional neural network, graph neural network, etc.) to obtain the jitter amplitude of the motor under test output by the neural network model. Alternatively, the second attitude angle difference curve can be fitted to obtain a target difference curve (i.e., simulate the attitude angle difference curve under jitter-free conditions), and then the amplitude of each jitter wave in the second attitude angle difference curve (i.e., the deviation from the target difference curve) can be calculated. The maximum amplitude is determined as the jitter amplitude of the motor under test. Alternatively, the peak-to-peak value of each jitter wave in the second attitude angle difference curve can be calculated, i.e., the difference between the amplitudes of adjacent peaks and troughs, and the maximum peak-to-peak value is taken as the jitter amplitude of the motor under test. The method of determining the jitter amplitude of the motor under test can be set based on actual needs, and this embodiment of the disclosure does not limit this.

[0072] Based on the embodiments of this disclosure, a preliminary filtering is performed through a first sliding process before generating the attitude angle difference curve to eliminate data with large interference caused by factors such as measurement errors. After generating the attitude angle difference curve, the length of the second sliding window is determined based on the waveform width of each jitter wave in the attitude angle difference curve, and a second sliding process is performed. Without affecting the waveform of the attitude angle difference curve, the attitude angle difference curve is made as smooth as possible, thereby improving the accuracy of the motor stability test results.

[0073] In one possible implementation, since the motor under test does not rotate at a constant speed throughout its operation, but typically undergoes acceleration and deceleration phases, the stability of the motor under test may differ in different operating phases. Therefore, segmented testing can be performed to improve the accuracy of the stability test results. Step 104 may further include the following steps: Waveform analysis is performed on the attitude angle difference curve to determine the intervals corresponding to each operating stage of the motor under test. The peak-to-peak value of each wave in each interval of the attitude angle difference curve is obtained. The operating stage includes at least one of the acceleration stage, constant speed stage, and deceleration stage. The peak-to-peak value is the difference between the amplitudes of adjacent peaks and troughs, that is, the difference between adjacent maxima and minima.

[0074] Accordingly, step 105 above may include the following steps: Based on the peak-to-peak values ​​of each wave in each interval of the attitude angle difference curve, the jitter amplitude of the corresponding operating stage is determined. The jitter amplitude is one of the maximum peak-to-peak value, minimum peak-to-peak value, and average peak-to-peak value of the attitude angle difference curve in the interval.

[0075] like Figure 2 As shown, when the motor accelerates, the attitude angle changes rapidly, and the attitude angle difference gradually increases, with the attitude angle difference curve showing an increasing trend. When the motor runs at a constant speed, the attitude angle changes at a constant speed, and the attitude angle difference remains constant, with the attitude angle difference curve approaching a straight line with a constant value. When the motor decelerates, the attitude angle changes decelerate, and the attitude angle difference gradually decreases, with the attitude angle difference curve showing a decreasing trend. By analyzing the trend of the attitude angle difference curve, we can roughly divide the intervals corresponding to different operating stages, thereby allowing us to analyze the jitter amplitude of each operating stage.

[0076] Optionally, waveform analysis can be performed on the second attitude angle difference curve to determine the intervals corresponding to each operating stage of the motor under test, and the jitter amplitude of the corresponding operating stage can be determined based on the waveform of the second attitude angle difference curve in each interval.

[0077] In one possible implementation, sensor data of the motor under test in at least one dimension can be measured using a sensor. The sensor data in step 101 further includes the attitude angles of the motor under test in at least one dimension during its operation in three-dimensional space. For example, it may include at least one of the rotation angles of the motor under test about the horizontal axis (y-axis), the vertical axis (x-axis), and the vertical axis (z-axis). The attitude angle difference sequence in step 102 further includes an attitude angle difference sequence corresponding to at least one dimension. Step 103 may specifically include the following steps: Determine the attitude angle difference curve corresponding to the attitude angle difference sequence in at least one dimension.

[0078] Before determining the attitude angle difference curve, a first smoothing process can be performed on the attitude angle difference sequence for each dimension. After generating the attitude angle difference curve, a second smoothing process can be performed based on the waveform width of the attitude angle difference curve for each dimension. The generation process of attitude angle difference curves for different dimensions can be referred to step 103 above, and will not be repeated here in this embodiment.

[0079] Accordingly, step 104 above may specifically include the following steps: Waveform analysis is performed on the attitude angle difference curve in at least one dimension to obtain the waveform changes of the attitude angle difference curve in at least one dimension.

[0080] Based on the embodiments of this disclosure, the attitude angles of the motor under test are measured in different dimensions using sensors. For each dimension, the attitude angle difference curve and waveform analysis are determined to determine the jitter amplitude of the motor under test in at least one dimension. This allows for the determination of the degree of composite jitter of the motor under test in three-dimensional space. Compared with the method of piezoelectric sensors that only measure single axial vibration, this method can distinguish between mechanical resonance and abnormalities caused by sudden load changes, thereby improving the accuracy of motor stability testing.

[0081] Please refer to Figure 4 This illustration shows a structural block diagram of a motor stability testing apparatus provided in an exemplary embodiment of the present disclosure. The motor stability testing apparatus is applied to a chip, and the motor stability testing apparatus provided in this embodiment includes: The acquisition module 401 is used to acquire sensor data collected by the sensor for the motor under test, including the attitude angle of the motor under test during operation. The first determining module 402 is used to determine an attitude angle difference sequence based on the sensor data acquired by the acquisition module 401. Any attitude angle difference in the attitude angle difference sequence is the difference between the attitude angle at the corresponding sampling time and the attitude angle at the previous sampling time. The second determining module 403 is used to determine the attitude angle difference curve corresponding to the attitude angle difference sequence determined by the first determining module 402; The analysis module 404 is used to perform waveform analysis on the attitude angle difference curve determined by the second determination module 403 to obtain the waveform change of the attitude angle difference curve; The third determining module 405 is used to determine the jitter amplitude of the motor under test based on the waveform change of the attitude angle difference curve.

[0082] Optionally, in one possible implementation, the second determining module 403 described above is further configured to: The attitude angle difference sequence is smoothed using a first sliding window. An attitude angle difference curve is generated based on the attitude angle difference sequence after the first smoothing process.

[0083] Optionally, in one possible implementation, the second determining module 403 described above is further configured to: For any sampling time within the first sliding window, the attitude angle difference value of the x sampling times before the intermediate sampling time and the attitude angle difference value of the y sampling times after the intermediate sampling time are weighted averaged to determine the attitude angle difference value of the intermediate sampling time. x and y are both positive integers. The intermediate sampling time is the sampling time located in the middle position of the first sliding window.

[0084] Optionally, in one possible implementation, the second determining module 403 described above is further configured to: Determine the first attitude angle difference curve corresponding to the attitude angle difference sequence; The aforementioned analysis module 404 is further used for: Based on the waveform of the first attitude angle difference curve, the attitude angle difference sequence is smoothed using a second sliding window. A second attitude angle difference curve is generated based on the attitude angle difference sequence after the second smoothing process. Waveform analysis was performed on the second attitude angle difference curve to obtain the waveform changes of the second attitude angle difference curve.

[0085] Optionally, in one possible implementation, the analysis module 404 described above is further used for: Determine the waveform width of each jitter wave in the first attitude angle difference curve. The waveform width is the lateral distance between adjacent peaks and troughs. The length of the second sliding window is determined based on the minimum waveform width, and the length of the second sliding window is less than or equal to the minimum waveform width. For any sampling time within the second sliding window, the attitude angle difference value of the m sampling times before the middle sampling time and the attitude angle difference value of the n sampling times after the middle sampling time are weighted averaged to determine the attitude angle difference value of the middle sampling time. m and n are both positive integers, and the middle sampling time is the sampling time located in the middle position of the second sliding window.

[0086] Optionally, in one possible implementation, the analysis module 404 described above is further used for: Waveform analysis is performed on the attitude angle difference curve to determine the intervals corresponding to each operating stage of the motor under test. The peak-to-peak value of each wave in each interval of the attitude angle difference curve is obtained. The operating stage includes at least one of the acceleration stage, constant speed stage and deceleration stage. The peak-to-peak value is the difference between the amplitudes of adjacent peaks and troughs. The aforementioned third determining module 405 is further used for: Based on the peak-to-peak values ​​of each wave in each interval of the attitude angle difference curve, the jitter amplitude of the corresponding operating stage is determined. The jitter amplitude is one of the maximum peak-to-peak value, minimum peak-to-peak value, and average peak-to-peak value of the attitude angle difference curve in the interval.

[0087] Optionally, in one possible implementation, the sensor data further includes the attitude angles of the motor under test in at least one dimension during its operation in three-dimensional space; The second determining module 403 mentioned above is further used for: Determine the attitude angle difference curve corresponding to the attitude angle difference sequence in at least one dimension; The aforementioned analysis module 404 is further used for: Waveform analysis is performed on the attitude angle difference curve in at least one dimension to obtain the waveform changes of the attitude angle difference curve in at least one dimension.

[0088] like Figure 5 As shown in the figure, this disclosure also provides a motor stability testing system. The motor stability testing system includes at least one sensor 501 and a chip 502.

[0089] Sensor 501 is mounted on load device 504 connected to motor 503 under test, and the straight line of the central axis of sensor 501 coincides with the straight line of the central axis of the output shaft of motor 503 under test. Optionally, sensor 501 may be mounted on top of load device 504, inside load device 504, or between load device 504 and motor 503 under test.

[0090] Chip 502 is used for: acquiring sensor data collected by the sensor on the motor under test 503, the sensor data including the attitude angles of the motor under test 503 during operation; determining an attitude angle difference sequence based on the sensor data, where any attitude angle difference in the sequence is the difference between the attitude angle at the corresponding sampling time and the attitude angle at the previous sampling time; determining the attitude angle difference curve corresponding to the attitude angle difference sequence; performing waveform analysis on the attitude angle difference curve to obtain the waveform change of the attitude angle difference curve; and determining the jitter amplitude of the motor under test 503 based on the waveform change of the attitude angle difference curve.

[0091] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar, identical, or corresponding parts between embodiments can be referred to mutually. Since the method, apparatus, circuit, and device embodiments are basically corresponding, relevant parts can be referred to the corresponding descriptions. The methods, apparatus, circuits, and devices in the embodiments of this disclosure also correspond to each other in specific implementation and beneficial technical effects; related content can be referred to mutually and will not be repeated here.

[0092] In addition, this disclosure also provides an electronic device, including: Memory, used to store computer programs; A processor is configured to execute a computer program stored in the memory, wherein when the computer program is executed, it implements the motor stability testing method described in any of the above embodiments of the present disclosure.

[0093] Figure 6 This is a schematic diagram illustrating the structure of an application embodiment of the electronic device disclosed herein. Below, reference is made to… Figure 6This describes an electronic device according to embodiments of the present disclosure. The electronic device may be either or both of a first device and a second device, or a standalone device independent of them, which may communicate with the first device and the second device to receive acquired input signals from them.

[0094] like Figure 6 As shown, the electronic device includes one or more processors and memory.

[0095] A processor can be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.

[0096] The memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and a processor may execute the program instructions to implement the motor stability testing methods of the various embodiments of this disclosure described above, and / or other desired functions.

[0097] In one example, the electronic device may also include input devices and output devices, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0098] In addition, the input device may include, for example, a keyboard, a mouse, etc.

[0099] This output device can output various information to the outside, including determined distance information, direction information, etc. The output device may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0100] Of course, for the sake of simplicity, Figure 6 Only some of the components of the electronic device relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0101] In addition to the methods and apparatus described above, embodiments of this disclosure may also be computer program products, including computer program instructions that, when executed by a processor, cause the processor to perform the steps in the motor stability testing methods according to various embodiments of this disclosure as described in the foregoing portion of this specification.

[0102] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this disclosure. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on a user's computing device, partially on a user's computing device, as a standalone software package, partially on a user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0103] Furthermore, embodiments of this disclosure may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps in the motor stability testing methods according to various embodiments of this disclosure as described in the foregoing portion of this specification.

[0104] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0105] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media that can store program code, such as ROM, RAM, magnetic disk, or optical disk.

[0106] The basic principles of this disclosure have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this disclosure are merely examples and not limitations, and should not be considered as essential features of each embodiment of this disclosure. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the scope of this disclosure to the necessity of employing the aforementioned specific details for implementation.

[0107] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0108] The block diagrams of devices, apparatuses, devices, and systems disclosed herein are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0109] The methods and apparatus of this disclosure may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of this disclosure are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, this disclosure may also be implemented as a program recorded on a recording medium, the program including machine-readable instructions for implementing the methods according to this disclosure. Thus, this disclosure also covers recording media storing programs for performing the methods according to this disclosure.

[0110] It should also be noted that in the apparatus, devices, and methods of this disclosure, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions to this disclosure.

[0111] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of this disclosure. Therefore, this disclosure is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0112] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this disclosure to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations therein.

Claims

1. A method of testing the stability of an electrical machine, characterized in that, The method applied to a chip comprises: Obtaining sensor data collected by a sensor for a motor to be tested, the sensor data comprising an attitude angle of the motor to be tested during operation; Determining an attitude angle difference value sequence based on the sensor data, any attitude angle difference value in the attitude angle difference value sequence being a difference between an attitude angle at a corresponding sampling time and an attitude angle at a previous sampling time; Determining an attitude angle difference value curve corresponding to the attitude angle difference value sequence; Performing waveform analysis on the attitude angle difference value curve to obtain waveform variation of the attitude angle difference value curve; Determining a jitter amplitude of the motor to be tested based on the waveform variation of the attitude angle difference value curve.

2. The method of claim 1, wherein, The determination of the attitude angle difference value curve corresponding to the attitude angle difference value sequence comprises: Performing first smoothing processing on the attitude angle difference value sequence by using a first sliding window; Generating the attitude angle difference value curve based on the attitude angle difference value sequence after the first smoothing processing.

3. The method of claim 2, wherein, The first smoothing processing on the attitude angle difference value sequence by using the first sliding window comprises: For the sampling time in any first sliding window, determining a weighted average value of the attitude angle difference values of x sampling times before an intermediate sampling time and the attitude angle difference values of y sampling times after the intermediate sampling time as the attitude angle difference value of the intermediate sampling time, x and y being positive integers, and the intermediate sampling time being a sampling time at a middle position of the first sliding window.

4. The method of claim 1, wherein, The determination of the attitude angle difference value curve corresponding to the attitude angle difference value sequence comprises: Determining a first attitude angle difference value curve corresponding to the attitude angle difference value sequence; The waveform analysis on the attitude angle difference value curve to obtain the waveform variation of the attitude angle difference value curve comprises: Performing second smoothing processing on the attitude angle difference value sequence by using a second sliding window based on a waveform of the first attitude angle difference value curve; Generating a second attitude angle difference value curve based on the attitude angle difference value sequence after the second smoothing processing; Performing waveform analysis on the second attitude angle difference value curve to obtain waveform variation of the second attitude angle difference value curve.

5. The method of claim 4, wherein, The second smoothing processing on the attitude angle difference value sequence by using the second sliding window based on the waveform of the first attitude angle difference value curve comprises: Determining a waveform width of each jitter wave in the first attitude angle difference value curve, the waveform width being a horizontal distance between adjacent wave peaks and wave troughs; Determining a length of the second sliding window based on a minimum waveform width in the waveform width, the length of the second sliding window being less than or equal to the minimum waveform width; For the sampling time in any second sliding window, determining a weighted average value of the attitude angle difference values of m sampling times before an intermediate sampling time and the attitude angle difference values of n sampling times after the intermediate sampling time as the attitude angle difference value of the intermediate sampling time, m and n being positive integers, and the intermediate sampling time being a sampling time at a middle position of the second sliding window.

6. The method according to any one of claims 1 to 5, characterized in that, The waveform analysis on the attitude angle difference value curve to obtain the waveform variation of the attitude angle difference value curve comprises: The waveform of the attitude angle difference value curve is analyzed to determine intervals corresponding to each operation stage of the motor to be tested, and peak-to-peak values of each wave in each interval of the attitude angle difference value curve are obtained, the operation stage including at least one of an acceleration stage, a constant speed stage and a deceleration stage, and the peak-to-peak value being a difference between amplitudes of adjacent wave peaks and wave troughs. The determination of the jitter amplitude of the motor to be tested based on the waveform change of the attitude angle difference value curve comprises: The jitter amplitude of the corresponding operation stage is determined based on the peak-to-peak value of each wave in each interval of the attitude angle difference value curve, wherein the jitter amplitude is one of the maximum peak-to-peak value, the minimum peak-to-peak value and the average peak-to-peak value of the attitude angle difference value curve in the interval.

7. The method according to any one of claims 1 to 5, characterized in that, The sensor data further comprises an attitude angle of the motor to be tested in at least one dimension during operation in a three-dimensional space; The determination of the attitude angle difference value curve corresponding to the attitude angle difference value sequence comprises: The determination of the attitude angle difference value curve corresponding to the attitude angle difference value sequence of the at least one dimension; The waveform analysis of the attitude angle difference value curve to obtain the waveform change of the attitude angle difference value curve comprises: The waveform analysis of the attitude angle difference value curve of the at least one dimension to obtain the waveform change of the attitude angle difference value curve of the at least one dimension.

8. An electrical machine stability test apparatus, characterised in that, The apparatus is applied to a chip, and the apparatus comprises: An acquisition module is configured to acquire sensor data collected by a sensor for a motor to be tested, the sensor data comprising an attitude angle of the motor to be tested during operation; A first determination module is configured to determine an attitude angle difference value sequence based on the sensor data, any attitude angle difference value in the attitude angle difference value sequence being a difference between the attitude angle at a corresponding sampling time and the attitude angle at a previous sampling time; A second determination module is configured to determine an attitude angle difference value curve corresponding to the attitude angle difference value sequence; An analysis module is configured to perform waveform analysis on the attitude angle difference value curve to obtain a waveform change of the attitude angle difference value curve; A third determination module is configured to determine a jitter amplitude of the motor to be tested based on the waveform change of the attitude angle difference value curve.

9. An electrical machine stability test system characterized by, The apparatus comprises a chip and a sensor; The sensor is arranged on a load device connected to the motor to be tested, and a straight line on which a central axis of the sensor coincides with a straight line on which a central axis of an output shaft of the motor to be tested; The chip is configured to acquire sensor data collected by the sensor for the motor to be tested, the sensor data comprising an attitude angle of the motor to be tested during operation; The determination of the attitude angle difference value sequence based on the sensor data, any attitude angle difference value in the attitude angle difference value sequence being a difference between the attitude angle at a corresponding sampling time and the attitude angle at a previous sampling time; the determination of an attitude angle difference value curve corresponding to the attitude angle difference value sequence; the waveform analysis of the attitude angle difference value curve to obtain a waveform change of the attitude angle difference value curve; and the determination of a jitter amplitude of the motor to be tested based on the waveform change of the attitude angle difference value curve.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by a processor to implement the method of any one of claims 1-7.

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