Motor health degree scoring method, device, equipment and storage medium

Abstract

The application provides a motor health degree scoring method, device and equipment and a storage medium, and belongs to the technical field of motor state detection. The method comprises the following steps: acquiring electrical parameters of a target motor at each sampling time within a preset time period; for each sampling time, determining the corresponding sub-grid of the current effective value and the frequency effective value of the sampling time in a preset grid; for each sub-grid in the preset grid, determining the corresponding operation duration of the target motor in the sub-grid; determining the motor degradation amount corresponding to the sub-grid of the target motor based on the operation duration corresponding to the sub-grid, the current representative value of the sub-grid and the frequency representative value; determining the cumulative degradation amount based on the motor degradation amounts of the sub- grids; determining the half-life coefficient in the scoring function; and scoring the motor health degree based on the scoring function with the determined half-life coefficient and the cumulative degradation amount to obtain the health degree score. The application provides a motor health degree scoring method for mapping the motor degradation degree to a unified sub-grid.

Description

Technical Field

[0001] This application belongs to the field of motor condition detection technology, and more specifically, relates to a method, device, equipment and storage medium for motor health scoring. Background Technology

[0002] Electric motors are the most widely used power equipment in industrial settings. Pumps, fans, compressors, and various conveyor lines all rely on electric motors as their drive system. Over long-term operation, problems such as bearing wear and winding insulation aging gradually accumulate, resulting in performance degradation.

[0003] In the daily operation of motors, maintenance personnel need to arrange inspection and maintenance plans based on the motor's degradation status. Currently, the quantification of motor degradation status is mostly approximated by indirect indicators such as cumulative running time or number of start-stop cycles, but there is a lack of a unified comparison scale, making it difficult for maintenance personnel to intuitively judge the current degree of degradation or health status of the motor.

[0004] Therefore, this application aims to provide a method for mapping the degree of motor degradation to a unified scoring system for motor health. Summary of the Invention

[0005] The purpose of this application is to provide a method, apparatus, device, and storage medium for scoring motor health, so as to provide a method for scoring motor health by mapping the degree of motor degradation to a unified scoring system.

[0006] A first aspect of this application provides a method for scoring motor health, including: Acquire the electrical parameters of the target motor at each sampling time within a preset time period; the electrical parameters include the effective value of the current and the effective value of the frequency; For each sampling time, determine the corresponding grid cells in the preset grid for the effective current value and effective frequency value at that sampling time; the preset grid is a two-dimensional planar grid with current as the first dimension and frequency as the second dimension. For each segment in the preset grid, the running time of the target motor in that segment is determined; based on the running time of that segment, the representative current value and the representative frequency value of that segment, the motor degradation amount of the target motor in that segment is determined; the representative current value and the representative frequency value are determined based on the electrical parameters at the sampling time to which that segment belongs; The cumulative degradation of the target motor within a preset time period is determined based on the degradation of the motor in each segment. Determine the half-life coefficient in the scoring function; the half-life coefficient is used to ensure that the motor health calculated based on the scoring function is half of the full score when the cumulative degradation of the target motor is equal to the half-life coefficient. The health score of the target motor is obtained by scoring the motor health based on the scoring function with a determined half-life coefficient and the cumulative degradation amount.

[0007] A second aspect of this application provides a motor health rating device, comprising: The data acquisition module is used to acquire the electrical parameters of the target motor at each sampling time within a preset time period; the electrical parameters include the effective value of the current and the effective value of the frequency; The grid module is used to determine the grid corresponding to the effective current value and effective frequency value at each sampling time in the preset grid; the preset grid is a two-dimensional planar grid with current as the first dimension and frequency as the second dimension. The motor degradation determination module is used to determine the running time of the target motor in each cell of the preset grid; based on the running time of the cell, the representative current value and the representative frequency value of the cell, the motor degradation amount of the target motor in the cell is determined; the representative current value and the representative frequency value are determined based on the electrical parameters at the sampling time of the cell. The cumulative degradation determination module is used to determine the cumulative degradation of the target motor within a preset time period based on the motor degradation of each segment; The half-life coefficient determination module is used to determine the half-life coefficient in the scoring function. The half-life coefficient is used to ensure that the motor health calculated based on the scoring function is half of the full score when the cumulative degradation of the target motor is equal to the half-life coefficient. The health rating module is used to score the motor health based on a scoring function with a determined half-life coefficient and cumulative degradation, thereby obtaining the health rating of the target motor.

[0008] A third aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of the above-described motor health rating method.

[0009] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above-described motor health rating method.

[0010] The beneficial effects of the motor health scoring method, apparatus, device, and storage medium provided in this application embodiment are as follows: This application's embodiment maps motor operating conditions to a two-dimensional planar grid of current and frequency. Operating time is statistically analyzed by grid, and representative operating points are determined using measured parameters within each grid. Motor degradation is determined grid by grid and accumulated to obtain a physically meaningful cumulative degradation amount. This cumulative degradation amount is then mapped to a unified health score using a scoring function calibrated with a half-life coefficient. The half-life coefficient is defined as the cumulative degradation amount corresponding to when the motor health score drops to half of the full score. This links the tightness of the scoring curve to the actual lifespan characteristics of the motor. The degradation states of motors with different power ratings and bearing configurations can be directly compared under the same scoring scale, facilitating maintenance personnel to quickly assess the motor's health status and urgency, and to rationally arrange inspection and maintenance plans. Attached Figure Description

[0011] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0012] Figure 1 A flowchart illustrating a motor health scoring method provided in an embodiment of this application; Figure 2 This is a structural block diagram of a motor health scoring device provided in an embodiment of this application; Figure 3 This is a schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0013] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0014] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0015] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a motor health rating method provided in an embodiment of this application. The method can be executed by an electronic device and may include steps S101-S106.

[0016] S101: Obtain the electrical parameters of the target motor at each sampling time within a preset time period.

[0017] In this embodiment, the target motor is the motor to be evaluated for degradation. The preset time period can be set by the user; for example, the preset time period can be set to a continuous 7-day history. The electrical parameters include the RMS value of the current and the RMS value of the frequency. For example, in this embodiment, the sampling interval is 0.3 seconds.

[0018] S102: For each sampling time, determine the grid segment corresponding to the effective current value and effective frequency value at that sampling time in the preset grid.

[0019] For example, in this embodiment, the preset grid is a two-dimensional planar grid with current as the first dimension and frequency as the second dimension. For instance, the current dimension is divided into 10 equal grids within the interval [0, 60A], and the frequency dimension is divided into 10 equal grids within the interval [0, 60Hz], forming a total of 100 grids. The number of grids is determined based on the expected number of samples in each grid and the operating resolution.

[0020] For example, if the effective value of the current at a certain sampling moment is 49.5A, it falls into the current dimension covering the range of 48A to 54A; and the effective value of the frequency is 50Hz, it falls into the frequency dimension covering the range of 48Hz to 54Hz. Then, the sampling moment is assigned to the segment determined by the intersection of the two dimensions.

[0021] S103: For each segment in the preset grid, determine the running time of the target motor in that segment; based on the running time of that segment, the representative current value and the representative frequency value of that segment, determine the motor degradation amount of the target motor in that segment.

[0022] In this embodiment, after all sampling times are mapped, the number of sampling times in each grid is counted, and the number is multiplied by the sampling interval to obtain the running time of the target motor in that grid. Alternatively, it can be converted to other time units such as hours or minutes.

[0023] In this embodiment, the representative current value and the representative frequency value are representative values ​​that characterize the actual operating conditions of the grid. These values ​​are determined based on the electrical parameters at the sampling time of that grid. Specifically, the arithmetic mean of the effective current values ​​at all sampling times belonging to a certain grid can be used as the representative current value for that grid. The representative frequency value is determined similarly, that is, the mean of the measured data within the grid represents the actual operating point of that grid. In this embodiment, the representative current value can also be the mode of the current values ​​in the grid. If there are multiple modes, one can be randomly selected. The representative frequency value is determined similarly.

[0024] In this embodiment, the motor degradation amount is used to quantify the cumulative amount of degradation contribution of the motor under the corresponding segmented operating conditions.

[0025] S104: Determine the cumulative degradation amount of the target motor within a preset time period based on the motor degradation amount of each segment.

[0026] In this embodiment, the sum of the motor degradation amounts of each segment is determined as the cumulative degradation amount of the target motor within a preset time period.

[0027] S105: Determine the half-life coefficient in the scoring function.

[0028] In this embodiment, the scoring function maps the cumulative degradation amount to a uniform scoring system for motor health, such as a percentage system with a maximum score of 100. The half-life coefficient is a calibration parameter in the scoring function, and its physical meaning is: when the cumulative degradation amount of the target motor equals the half-life coefficient, the motor health calculated based on the scoring function is exactly half the maximum score, i.e., 50 points. A larger half-life coefficient means the motor needs to accumulate more degradation to reduce the score to 50 points, resulting in a more lenient scoring curve; a smaller half-life coefficient results in a more stringent scoring curve. The specific method for determining the half-life coefficient is detailed in subsequent embodiments.

[0029] S106: The health score of the target motor is obtained by scoring the motor health based on the scoring function with a determined half-life coefficient and the cumulative degradation amount.

[0030] For example, in this embodiment, the scoring function may be: ; in, Rate the health of the target motor. For cumulative degradation, This is the half-life factor.

[0031] As can be seen from the above, the embodiments of this application map the motor operating conditions onto a two-dimensional planar grid of current and frequency, count the operating time by grid and determine the representative operating point by the measured parameters within the grid, determine the motor degradation amount grid by grid and accumulate it to obtain the cumulative degradation amount with physical meaning, and then map it to a unified score for health status using a scoring function calibrated by the half-life coefficient; the half-life coefficient is defined as the cumulative degradation amount corresponding to the motor health status dropping to half of the full score, so that the tightness of the scoring curve is linked to the actual life characteristics of the motor. The degradation status of motors with different power levels and different bearing configurations can be directly compared under the same scoring scale, which makes it convenient for maintenance personnel to quickly judge the motor health status and urgency level, and reasonably arrange inspection and maintenance plans.

[0032] In one embodiment of this application, the half-life coefficient is determined based on one of the following methods: Obtain the critical cumulative degradation level for the target motor when it is recommended to repair or replace it, and the target health score corresponding to the critical cumulative degradation level; determine the half-life coefficient based on the critical cumulative degradation level and the target health score; Obtain the warning health level and the expected cumulative degradation corresponding to the warning health level; determine the half-life coefficient based on the warning health level and the expected cumulative degradation. Obtain the cumulative degradation amount when a motor of the same model as the target motor fails; determine the half-life coefficient based on the cumulative degradation amount when a motor of the same model fails.

[0033] For example, in this embodiment, the first method is the end-of-life anchoring method: the maintenance party determines the critical cumulative degradation amount corresponding to the recommended maintenance or replacement time based on the motor's maintenance procedures or manufacturer's recommendations. And set the target health score that you want the health score to display at that critical point. For example, a score of 20 to 30 indicates that the motor is nearing the end of its lifespan but has not yet completely failed; substituting these two values ​​into the scoring function yields the following result. For example, if the critical cumulative degradation of a standard continuously operating motor is 400 and the target health score is 30, then k = 400 × 30 / (100 - 30) ≈ 171.4.

[0034] In this embodiment, the second method is the early warning point reverse calculation method: taking the early warning health level set in the operation and maintenance. For example, a score of 70, and obtain the expected cumulative degradation of the corresponding health status for the warning. For example, the cumulative degradation at the end of the motor's break-in period is approximately 60. Substituting this into the inverse solution yields... This method makes the scoring curve more relaxed in the early stages of motor operation, avoiding a sharp drop in score caused by slight degradation during the break-in period.

[0035] In this embodiment, the third method is a data-driven batch calibration method: collecting complete historical records of multiple motors of the same model as the target motor from commissioning to repair or replacement, and calculating the cumulative degradation amount at the time of failure of each motor. The median or P25 / P75 quantile of the cumulative failure degradation is taken as the typical cumulative failure degradation for this model. Then set the corresponding health score when it fails. For example, 25 points, substituting into the inverse solution yields... For example, statistics for a certain type of motor were obtained. For 350, Taking 25 points, then k = 350 × 25 / 75 ≈ 116.7. This calibration is based on failure data under real operating conditions, and has the best consistency with the field load spectrum and maintenance conditions; motors of different models and bearing configurations should be calibrated separately in groups, and should not share the same half-life coefficient.

[0036] As can be seen from the above, this embodiment provides three paths for determining the half-life coefficient: the life end anchor point method, which back-calculates the scoring curve based on the life end determined by the maintenance procedure; the early warning point back-calculation method, which back-calculates the curve by using early known nodes to make the early part of the curve more relaxed; and the data-driven batch calibration method, which determines the calibration parameters by statistically analyzing real failure data of the same model. All three methods can map the cumulative degradation amount with physical meaning to a unified scoring scale, and the calibration process is linked to the actual life characteristics of the motor, making the health score intuitive and in line with the actual situation on site.

[0037] In one embodiment of this application, the motor degradation amount of the target motor corresponding to the segment is determined based on the running time corresponding to the segment, the representative current value of the segment, and the representative frequency value of the segment, including: Substitute the rated current of the target motor, the rated frequency of the target motor, the representative current value and the representative frequency value of the segment into the preset formula to determine the motor degradation rate of the target motor in the segment. The amount of motor degradation of the target motor in that segment is determined based on the running time corresponding to that segment and the motor degradation rate of the target motor in that segment. The preset formula includes: a current term used to evaluate the rate at which current affects the degree of motor degradation, and a frequency term used to evaluate the rate at which frequency affects the degree of motor degradation; the current term is constructed based on the exponential effect of current on the degree of motor degradation; and the frequency term is constructed based on the linear effect of frequency on the degree of motor degradation.

[0038] In this embodiment, considering that the influence characteristics of current and frequency on the rate of motor degradation are different, the current term in the preset formula is constructed based on the exponential influence of current on the degree of motor degradation, and the frequency term is constructed based on the linear influence of frequency on the degree of motor degradation.

[0039] In one embodiment of this application, the current term further includes a lifetime index for characterizing the exponential effect of current on the degree of motor degradation. The method for scoring motor health also includes: determining the life index based on the bearing type of the target motor; Accordingly, the rated current of the target motor, the rated frequency of the target motor, the representative current value and the representative frequency value of the segment are substituted into the preset formula, including: substituting the life index, rated current, rated frequency, and the representative current value and the representative frequency value of the segment into the preset formula.

[0040] For example, in this embodiment, the preset formula can be: ; in, The current represents the value Frequency represents the value The rate of motor degradation at that time; For current; For frequency terms; Rated current; The rated frequency; This is a lifespan index.

[0041] In this embodiment, the degree of motor degradation is characterized by the degree of bearing degradation. When the bearing type is a ball bearing, When the bearing type is a roller bearing, .

[0042] In this embodiment, the product of the motor degradation rate corresponding to the segment and the motor's operating time in that segment is determined as the motor degradation amount of that segment, that is... Cumulative degradation For all the grids sum.

[0043] As can be seen from the above, the embodiments of this application use the exponential influence of the current term to characterize the accelerating effect of heavy-load conditions on degradation, and use the linear influence of the frequency term to characterize the proportional relationship between frequency and wear accumulation. This gives the calculation of degradation rate a clear physical basis rather than pure data fitting. Secondly, this embodiment also takes into account the bearing type of the motor and determines the life index in the above formula based on this, avoiding overestimation of degradation for roller bearing motors and underestimation of degradation for ball bearing motors, further improving the consistency between the degradation calculation results and the actual degradation mechanism of the motor.

[0044] In one embodiment of this application, the time corresponding to each sampling time belongs to the operating segment of the target motor; The process of determining each sampling time includes: Obtain the electrical parameters of the target motor at all sampling times within a preset time period; The preset time period is segmented based on the electrical parameters at all sampling times to obtain the operating and non-operating segments of the target motor within the preset time period; Extract the sampling times that belong to the running segment from all sampling times to obtain each sampling time.

[0045] In this embodiment, the running segment refers to the continuous time interval during which the motor operates stably under load. During the running segment, the motor's current and frequency remain above the operating threshold and fluctuate gently; the bearings are under continuous load, and this is the interval where degradation truly occurs. The non-running segment refers to the time interval during which the motor is not operating stably under load, including the stopping segment, starting segment, and braking segment.

[0046] In this embodiment, considering that motor operation typically includes start-stop processes, and motor degradation can be considered to occur during the operating phase, indiscriminately including data from starting inrush current and braking deceleration phases in the degradation accumulation would result in an inflated degradation calculation, leading to inaccurate health scores. Therefore, this embodiment obtains the electrical parameters of the target motor at all sampling moments within a preset time period. Based on the electrical parameters at all sampling moments, the preset time period is segmented to obtain the operating and non-operating phases of the target motor within the preset time period. Then, the sampling moments belonging to the operating phase are extracted from all sampling moments and used as the sampling moments participating in the operating condition mapping and degradation calculation.

[0047] For example, if a water pump motor starts and stops 12 times a day, the total operating time in the preset period of 7 days is about 96 hours. The starting, braking and stopping periods occupy the remaining time. Only about 1.15 million sampling moments corresponding to the 96-hour operating period are included in the segmented statistics and degradation calculation, and the remaining sampling moments are excluded.

[0048] Therefore, the degradation assessment results only reflect the cumulative degradation of the motor under actual load operation, and the assessment criteria are consistent with the physical process of degradation.

[0049] In one embodiment, the non-operational segment includes: a shutdown segment, a startup segment, and a braking segment; Based on the electrical parameters at all sampling times, the preset time period is segmented to obtain the operating and non-operating segments of the target motor within the preset time period, including: SG filtering is applied to the electrical parameters at all sampling times to obtain the filtered electrical parameters corresponding to all sampling times; Based on the filtered electrical parameters corresponding to all sampling times, the preset time period is divided into multiple initial time periods, and the attributes of each initial time period are stop, start, run or braking. For each initial time period with the attribute of starting segment or braking segment, the rationality of the initial time period is determined based on the attribute of the initial time period, the attribute of the initial time period adjacent to the initial time period, and the preset state transition path. If the determination passes, the attribute of the initial time period is fixed; if the determination fails, the attribute of the initial time period is fixed as stopping segment. The initial time period with the attribute fixed as the running segment is defined as the running segment of the target motor within the preset time period; the initial time period with the attribute fixed as the stopping segment, starting segment, or braking segment is defined as the non-running segment of the target motor within the preset time period.

[0050] In this embodiment, SG filtering is a smoothing method based on local polynomial least squares fitting, which can suppress random noise while preserving the slope change trend of the signal. For example, this embodiment uses an 11-point window and a third-order polynomial. The 11-point window corresponds to a time span of approximately 3.3 seconds. This window can cover a complete acceleration process, capturing the slope change trend without losing the transient characteristics of the braking moment due to an excessively large window. The stopping segment, starting segment, and braking segment are three attributes of the non-operational segment. The stopping segment is the interval where the motor is stationary; the starting segment is the interval where the motor accelerates from a standstill; and the braking segment is the interval where the motor decelerates until it stops.

[0051] In this embodiment, the initial time period is a time interval with attribute tags obtained by initially dividing a preset time period based on filtered electrical parameters. The attribute of each initial time period is a stop segment, a start segment, a running segment, or a braking segment. The state transition path is a constraint describing the legal jump order of the motor operating condition attributes. In this embodiment, the state transition path is a cyclic path of stop, start, running, braking, and stop.

[0052] In this embodiment, considering that the criteria for judging the shutdown segment and the running segment are relatively clear, only the startup segment and the braking segment are judged for reasonableness. Reasonableness judgment refers to the legality verification of the initial time period with the attribute of startup segment or braking segment based on the state transition path: if the judgment passes, the attribute of the initial time period is fixed; if the judgment fails, the attribute of the initial time period is fixed as a shutdown segment. The purpose of this step is to clean up isolated startup segments and isolated braking segments, that is, startup segments without subsequent running segments are reverted to shutdown to eliminate false triggering, and braking segments without preceding running segments are reverted to shutdown.

[0053] For example, if a starting segment is preceded by a stopping segment and followed by a running segment, conforming to the path of stopping, starting, and running, it is deemed successful, and its starting segment attribute is fixed. If a starting segment returns directly to the stopping segment without a running segment following it, it is an isolated starting segment without subsequent running, often caused by accidental triggering by current spikes, and is deemed unsuccessful, so the attribute of this initial time period is fixed as a stopping segment. Similarly, if a braking segment is not preceded by a running segment, it is an isolated braking segment without a leading running segment, and is also deemed unsuccessful, reverting to a stopping segment. After all judgments are completed, the initial time period with the attribute fixed as a running segment is determined as the running segment of the target motor within the preset time period, and the initial time period with the attribute fixed as a stopping segment, starting segment, or braking segment is determined as a non-running segment.

[0054] As can be seen from the above, this embodiment performs legality verification on the starting segment and braking segment one by one through the state transition path, and reverts the isolated false triggering segment caused by noise to the stopping segment, so that the boundary of the running segment is closer to the actual physical operation process of the motor; the subsequent degradation accumulation only includes the actual load running time, and the degradation degree assessment result is not affected by transient impact and misjudged working conditions, so as to improve the accuracy of motor degradation degree assessment.

[0055] In one embodiment of this application, the process of obtaining electrical parameters at each sampling time includes: Obtain the initial electrical parameters for each sampling moment belonging to the running segment; For each sampling time, the initial electrical parameters at that sampling time are subjected to a moving average filter to obtain the electrical parameters at that sampling time.

[0056] In this embodiment, the initial electrical parameters refer to the raw RMS current and RMS frequency values ​​directly acquired by the current sampling circuit without smoothing. Moving average filtering refers to taking the arithmetic mean of the initial electrical parameters over N consecutive sampling times, including that sampling time, as the electrical parameters for that sampling time. For example, in this case, N is 5, meaning the average of the current sampling time and the two sampling times before and after it (a total of 5 sampling points) is used as the RMS current and RMS frequency values ​​for that sampling time, corresponding to a time span of approximately 1.5 seconds. The window length N is determined based on the noise level and rate of change of the current sampling conditions: too small a value results in insufficient smoothing, while too large a value blurs the true fluctuations in the operating conditions.

[0057] In this embodiment, considering that the current and frequency within the operating segment may still be superimposed with measurement noise and instantaneous fluctuations, if the initial electrical parameters are directly used for segment mapping, individual noise points may cause the sampling time to be assigned to a segment that deviates from the actual operating condition, resulting in an incorrect allocation of degradation among different segments. Therefore, this embodiment first performs a moving average filter on the initial electrical parameters of each sampling time belonging to the operating segment, and then performs segment mapping in S102 with the filtered electrical parameters, so that the segment assignment reflects the actual operating condition level at the sampling time.

[0058] Corresponding to the motor health scoring method in the above embodiment, Figure 2 This is a structural block diagram of a motor health scoring device provided in one embodiment of this application. For ease of explanation, only the parts relevant to the embodiment of this application are shown. References Figure 2 The motor health rating device 20 includes: a data acquisition module 21, a grid module 22, a motor degradation determination module 23, a cumulative degradation determination module 24, a half-life coefficient determination module 25, and a health rating module 26.

[0059] The data acquisition module 21 is used to acquire the electrical parameters of the target motor at each sampling time within a preset time period; the electrical parameters include the effective value of the current and the effective value of the frequency. The grid module 22 is used to determine the grid corresponding to the effective value of current and the effective value of frequency at each sampling time in the preset grid; the preset grid is a two-dimensional planar grid with current as the first dimension and frequency as the second dimension. The motor degradation determination module 23 is used to determine the running time of the target motor in each cell of the preset grid; and to determine the motor degradation of the target motor in each cell based on the running time, the representative current value and the representative frequency value of the cell; the representative current value and the representative frequency value are determined based on the electrical parameters at the sampling time of the cell. The cumulative degradation amount determination module 24 is used to determine the cumulative degradation amount of the target motor within a preset time period based on the motor degradation amount of each segment; The half-life coefficient determination module 25 is used to determine the half-life coefficient in the scoring function. The half-life coefficient is used to ensure that the motor health calculated based on the scoring function is half of the full score when the cumulative degradation of the target motor is equal to the half-life coefficient. The health rating module 26 is used to score the motor health based on a scoring function with a determined half-life coefficient and cumulative degradation, and obtain the health rating of the target motor.

[0060] In one embodiment of this application, the motor health scoring device 20 further includes: a half-life coefficient determination module, used to determine the half-life coefficient based on one of the following methods: Obtain the critical cumulative degradation level for the target motor when it is recommended to repair or replace it, and the target health score corresponding to the critical cumulative degradation level; determine the half-life coefficient based on the critical cumulative degradation level and the target health score; Obtain the warning health level and the expected cumulative degradation corresponding to the warning health level; determine the half-life coefficient based on the warning health level and the expected cumulative degradation. Obtain the cumulative degradation amount when a motor of the same model as the target motor fails; determine the half-life coefficient based on the cumulative degradation amount when a motor of the same model fails.

[0061] In one embodiment of this application, the motor degradation determination module 23 is specifically used to substitute the rated current of the target motor, the rated frequency of the target motor, the current representative value and the frequency representative value of the segment into a preset formula to determine the motor degradation rate of the target motor in the segment. The amount of motor degradation of the target motor in that segment is determined based on the running time corresponding to that segment and the motor degradation rate of the target motor in that segment. The preset formula includes: a current term used to evaluate the rate at which current affects the degree of motor degradation, and a frequency term used to evaluate the rate at which frequency affects the degree of motor degradation; the current term is constructed based on the exponential effect of current on the degree of motor degradation; and the frequency term is constructed based on the linear effect of frequency on the degree of motor degradation.

[0062] In one embodiment of this application, the current term further includes a lifetime index for characterizing the exponential effect of current on the degree of motor degradation. The motor health rating device 20 also includes a life index determination module, used to determine the life index based on the bearing type of the target motor; The segmentation module 22 is specifically used to substitute the life index, rated current, rated frequency, and the representative values ​​of current and frequency for that segment into a preset formula.

[0063] In one embodiment of this application, the time corresponding to each sampling time belongs to the operating segment of the target motor; The motor health rating device 20 also includes: a sampling time determination module, which is used to perform SG filtering on the electrical parameters at all sampling times to obtain the filtered electrical parameters corresponding to all sampling times; Based on the filtered electrical parameters corresponding to all sampling times, the preset time period is divided into multiple initial time periods, and the attributes of each initial time period are stop, start, run or braking. For each initial time period with the attribute of starting segment or braking segment, the rationality of the initial time period is determined based on the attribute of the initial time period, the attribute of the initial time period adjacent to the initial time period, and the preset state transition path. If the determination passes, the attribute of the initial time period is fixed; if the determination fails, the attribute of the initial time period is fixed as stopping segment. The initial time period with the attribute fixed as the running segment is defined as the running segment of the target motor within the preset time period; the initial time period with the attribute fixed as the stopping segment, starting segment, or braking segment is defined as the non-running segment of the target motor within the preset time period.

[0064] In one embodiment of this application, the data acquisition module 21 is specifically used to acquire the initial electrical parameters of each sampling time belonging to the running segment; For each sampling time, the initial electrical parameters at that sampling time are subjected to a moving average filter to obtain the electrical parameters at that sampling time.

[0065] See Figure 3 , Figure 3 This is a schematic block diagram of an electronic device provided according to an embodiment of this application. Figure 3 The electronic device 300 in this embodiment may include one or more processors 301, one or more input devices 302, one or more output devices 303, and one or more memories 304. The processors 301, input devices 302, output devices 303, and memories 304 communicate with each other via a communication bus 305. The memories 304 store computer programs, including program instructions. The processors 301 execute the program instructions stored in the memories 304. Specifically, the processors 301 are configured to invoke the program instructions to perform the functions of each module / unit in the above-described device embodiments, for example... Figure 2The functions of the data acquisition module 21, the grid module 22, the motor degradation determination module 23, the cumulative degradation determination module 24, the half-life coefficient determination module 25, and the health rating module 26 are shown.

[0066] It should be understood that, in the embodiments of this application, the processor 301 may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0067] Input device 302 may include a touchpad, a fingerprint sensor (for collecting the user's fingerprint information and fingerprint orientation information), a microphone, etc., and output device 303 may include a display (LCD, etc.), a speaker, etc.

[0068] The memory 304 may include read-only memory and random access memory, and provides instructions and data to the processor 301. A portion of the memory 304 may also include non-volatile random access memory. For example, the memory 304 may also store device type information.

[0069] In specific implementations, the processor 301, input device 302, and output device 303 described in the embodiments of this application can execute the implementation method described in the motor health scoring method provided in the embodiments of this application, or they can execute the implementation method of the electronic device described in the embodiments of this application, which will not be repeated here.

[0070] In another embodiment of this application, a computer-readable storage medium is provided. This computer-readable storage medium stores a computer program, which includes program instructions. When executed by a processor, the program instructions implement all or part of the processes in the methods described above. Alternatively, the computer program can instruct related hardware to complete the process. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include any entity or device capable of carrying computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0071] The computer-readable storage medium can be an internal storage unit of the electronic device in any of the foregoing embodiments, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the electronic device, such as a plug-in hard disk, smart media card (SMC), secure digital card (SD), flash card, etc., equipped on the electronic device. Furthermore, the computer-readable storage medium can include both internal and external storage units of the electronic device. The computer-readable storage medium is used to store computer programs and other programs and data required by the electronic device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0072] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.

[0073] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the electronic devices and units described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0074] In the several embodiments provided in this application, it should be understood that the disclosed electronic devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces or units, or it may be an electrical, mechanical, or other form of connection.

[0075] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of the embodiments of this application, depending on actual needs.

[0076] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0077] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0078] The above are merely specific embodiments of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for scoring the health of a motor, characterized in that, include: Obtain the electrical parameters of the target motor at each sampling time within a preset time period; The electrical parameters include the effective value of the current and the effective value of the frequency; For each sampling time, the effective current value and effective frequency value at that sampling time are determined in the corresponding grid cells of a preset grid; the preset grid is a two-dimensional planar grid with current as the first dimension and frequency as the second dimension. For each segment in the preset grid, the running time of the target motor in that segment is determined; based on the running time of that segment, the representative current value and the representative frequency value of that segment, the motor degradation amount of the target motor in that segment is determined; the representative current value and the representative frequency value are determined based on the electrical parameters at the sampling time to which that segment belongs; The cumulative degradation amount of the target motor within the preset time period is determined based on the motor degradation amount of each segment; Determine the half-life coefficient in the scoring function; The half-life coefficient is used to ensure that the motor health calculated based on the scoring function is half of the full score when the cumulative degradation of the target motor is equal to the half-life coefficient. The health score of the target motor is obtained by scoring the motor health based on the scoring function with a determined half-life coefficient and the cumulative degradation amount.

2. The motor health scoring method as described in claim 1, characterized in that, The half-life coefficient is determined based on one of the following methods: Obtain the critical cumulative degradation amount for the recommended maintenance or replacement of the target motor, and the target health score corresponding to the critical cumulative degradation amount; The half-life coefficient is determined based on the critical cumulative degradation amount and the target health score; Obtain the early warning health status and the expected cumulative degradation amount corresponding to the early warning health status; The half-life coefficient is determined based on the warning health status and the expected cumulative degradation. Obtain the cumulative degradation amount when a motor of the same model as the target motor fails; determine the half-life coefficient based on the cumulative degradation amount when the motor of the same model fails.

3. The motor health scoring method as described in claim 1, characterized in that, The determination of the motor degradation amount of the target motor corresponding to the segment based on the running time, the representative current value, and the representative frequency value of the segment includes: Substitute the rated current of the target motor, the rated frequency of the target motor, the representative current value and the representative frequency value of the segment into a preset formula to determine the motor degradation rate of the target motor in the segment. The amount of motor degradation of the target motor in that segment is determined based on the running time corresponding to that segment and the motor degradation rate of the target motor in that segment. The preset formula includes: a current term for evaluating the rate at which current affects the degree of motor degradation, and a frequency term for evaluating the rate at which frequency affects the degree of motor degradation; the current term is constructed based on the exponential effect of current on the degree of motor degradation; and the frequency term is constructed based on the linear effect of frequency on the degree of motor degradation.

4. The motor health scoring method as described in claim 3, characterized in that, The current term also includes a life index, which characterizes the exponential effect of current on the degree of motor degradation. The motor health rating method further includes: determining a life index based on the bearing type of the target motor; Accordingly, substituting the rated current of the target motor, the rated frequency of the target motor, the current representative value and frequency representative value of the segment into the preset formula includes: substituting the life index, the rated current, the rated frequency, the current representative value and frequency representative value of the segment into the preset formula.

5. The motor health scoring method as described in claim 1, characterized in that, The time corresponding to each sampling time belongs to the operating segment of the target motor; The process of determining each sampling time includes: Obtain the electrical parameters of the target motor at all sampling times within the preset time period; The preset time period is segmented based on the electrical parameters at all sampling times to obtain the operating and non-operating segments of the target motor within the preset time period; Extract the sampling times that belong to the running segment from all the sampling times to obtain each sampling time.

6. The motor health scoring method as described in claim 5, characterized in that, The non-operational sections include: the shutdown section, the startup section, and the braking section; Based on the electrical parameters at all sampling times, the preset time period is segmented to obtain the operating and non-operating segments of the target motor within the preset time period, including: SG filtering is performed on the electrical parameters at all sampling times to obtain the filtered electrical parameters corresponding to all sampling times; Based on the filtered electrical parameters corresponding to all sampling times, the preset time period is divided into multiple initial time periods, and the attributes of each initial time period are a stop segment, a start segment, a running segment, or a braking segment; For each initial time period with the attribute of starting segment or braking segment, the rationality of the initial time period is determined based on the attribute of the initial time period, the attribute of the initial time period adjacent to the initial time period, and the preset state transition path. If the determination passes, the attribute of the initial time period is fixed; if the determination fails, the attribute of the initial time period is fixed as stopping segment. The initial time period with the attribute fixed as the running segment is determined as the running segment of the target motor within the preset time period; the initial time period with the attribute fixed as the stopping segment, starting segment, or braking segment is determined as the non-running segment of the target motor within the preset time period.

7. The motor health scoring method as described in claim 5, characterized in that, The process of obtaining the electrical parameters at each sampling time includes: Obtain the initial electrical parameters for each sampling moment belonging to the running segment; For each sampling time, the initial electrical parameters at that sampling time are subjected to a moving average filter to obtain the electrical parameters at that sampling time.

8. A motor health rating device, characterized in that, include: The data acquisition module is used to acquire the electrical parameters of the target motor at each sampling time within a preset time period; The electrical parameters include the effective value of the current and the effective value of the frequency; The grid segmentation module is used to determine the grid segment corresponding to the effective current value and effective frequency value at each sampling time in a preset grid; the preset grid is a two-dimensional planar grid with current as the first dimension and frequency as the second dimension. The motor degradation determination module is used to determine the running time of the target motor in each segment of the preset grid. Based on the running time corresponding to the segment, the representative current value and the representative frequency value of the segment, the motor degradation amount of the target motor corresponding to the segment is determined; the representative current value and the representative frequency value are determined based on the electrical parameters at the sampling time to which the segment belongs; The cumulative degradation amount determination module is used to determine the cumulative degradation amount of the target motor within the preset time period based on the motor degradation amount of each segment; The half-life coefficient determination module is used to determine the half-life coefficient in the scoring function; The half-life coefficient is used to ensure that the motor health calculated based on the scoring function is half of the full score when the cumulative degradation of the target motor is equal to the half-life coefficient. The health rating module is used to score the health of the motor based on a rating function with a determined half-life coefficient and the cumulative degradation amount, so as to obtain the health rating of the target motor.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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