Elevator permanent magnet synchronous motor operation state monitoring method, computer device and system

Abstract

The application discloses an elevator permanent magnet synchronous motor operation state monitoring method, computer equipment and system, and relates to the technical field of elevators.The method comprises the following steps: acquiring PSM temperature information, pulse count and elevator running frequency of a target elevator in real time; constructing a pixel coordinate system based on gray levels according to the PSM temperature information, pulse count and elevator running frequency, wherein the pixel points of the pixel coordinate system represent the PSM temperature information in the form of gray levels, the abscissa of the pixel coordinate system is used for representing the elevator running frequency, and the ordinate of the pixel coordinate system is used for representing the pulse count; extracting target feature points from the pixel coordinate system, and constructing a temperature failure model according to the target feature points; and predicting the failure time of the PSM permanent magnet of the target elevator according to the temperature failure model. The application can realize effective prediction of the demagnetization state of the PSM permanent magnet, and has high accuracy.

Description

Technical Field

[0001] This invention relates to the field of elevator technology, and in particular to a method, computer equipment and system for monitoring the operating status of an elevator permanent magnet synchronous motor. Background Technology

[0002] Currently, elevators generally use permanent magnet synchronous motors (PSMs) as their drive units. These PSMs are typically located in machine rooms at the top of buildings, and often lack adequate heat dissipation. Under high temperatures, the permanent magnets in the PSM inevitably demagnetize due to the rapid changes in elevator operating conditions and environmental influences. Demagnetization leads to a decrease in the PSM's no-load potential and performance degradation, resulting in frequent unexpected elevator stops and negatively impacting elevator use and management.

[0003] According to relevant research, the demagnetization of neodymium iron boron permanent magnet motors used in modern elevators is mainly affected by temperature. For example, in high-temperature environments, there are electrical and mechanical shocks generated during elevator starting, braking, acceleration, and deceleration. During elevator operation, the load (car) alternates between unloaded upward movement and fully loaded downward movement (power generation mode) and unloaded downward movement and fully loaded upward movement (electric mode), which will generate superimposed current impacts on the PSM permanent magnet. Especially in some densely populated places, the elevator load changes at a high frequency (such as fully loaded upward movement and unloaded downward movement at concentrated time points), and the continuous energization rate is high, which leads to the PMSM temperature rising and the current fluctuating frequently, generating a strong armature reaction. This reaction will form a demagnetizing magnetic field, which manifests as the alternating demagnetization phenomenon of the permanent magnet. That is, when the demagnetization intensity reaches a certain level, the elevator will suddenly stop or even trap people. During idle periods (low operating frequency and few passengers), the magnetic properties may recover, and the elevator will run normally again.

[0004] In my country, elevators have been equipped with PSM (Permanent Magnet Synchronous Motor) for more than 20 years. Elevators that used PSM in the early days are now experiencing frequent failures. The failures of PSM are mainly caused by the uniform demagnetization of the permanent magnets. Therefore, it is urgent and necessary to monitor the demagnetization of PSM permanent magnets and make timely suggestions for prevention and improvement through safety assessments to prevent elevator failures.

[0005] Under current technology, research on permanent magnet demagnetization is mainly based on the current signal method to track and predict changes in magnetic flux amplitude, which has certain limitations.

[0006] Engineering practice shows that the demagnetization phenomenon of PSM permanent magnets mainly takes three forms: (1) Local demagnetization: may cause mechanical failures such as magnet falling off or rubbing, resulting in elevator vibration, abnormal noise and elevator stoppage due to related mechanical failure; (2) Uniform demagnetization: Generally, it is manifested as the elevator's driving torque gradually decreasing and energy consumption increasing significantly over time. It is an irreversible deterioration fault caused by aging. (3) Alternating demagnetization: The demagnetization intensity of the permanent magnet alternates within the range not exceeding its coercivity, which is a reversible change that varies with the elevator's operating conditions (currently the most common elevator stop failure and the biggest problem affecting the normal use of elevators).

[0007] Under current technology, the following technical measures are generally used to predict the demagnetization of PSM permanent magnets: (1) Current signal method: Currently, online monitoring technology for permanent magnet demagnetization faults mainly relies on frequency analysis of current signals. This includes extracting the stator current of the PMSM and processing it to extract the characteristic harmonic frequencies of the current that are newly generated or significantly increased when a PMSM demagnetization fault occurs, in order to predict the demagnetization status; or extracting the characteristic harmonic components of the PMSM current related to permanent magnet demagnetization faults through computer algorithms and comparing them with the permanent magnet characteristics of the normal model. When they exceed the quality tolerance threshold, corrective and preventive measures are taken in time. However, the main problem with this type of method is the resolution of time and frequency. If the time resolution is too low, it is difficult to accurately capture the frequency changes during transient processes, while if the frequency resolution is too high, it is impossible to obtain the valuable frequencies at a specific time. In particular, when a permanent magnet is demagnetized uniformly, it does not break the symmetry of the air gap magnetic field inside the PMSM, and the fault characteristic harmonics will not be generated in the motor phase current. The current signal method is generally ineffective for online monitoring of permanent magnet demagnetization. (2) Manual observation method: By monitoring the machine temperature and feeling abnormal sounds or vibrations, it is determined whether there is a problem with the main unit. These problems are often related to the control system and mechanical system. The analysis and elimination delay the fault correction time. Repeated inspection and judgment not only cause confusion for users when the elevator stops, but once it is determined that the PMSM permanent magnet has failed and the main unit needs to be replaced, the elevator will be shut down for repairs for several days or even dozens of days, causing great inconvenience to the work and life of elevator users, and even causing public incidents.

[0008] The above-mentioned technical measures have the following main problems: (1) The elevator operating conditions are complex and changeable, and there are many related influencing factors, which offset the monitoring effect mentioned above; (2) The monitoring and calculation data volume is large, the software and hardware facilities involved are complex, and the economic efficiency is poor; (3) It lacks intuitiveness and is not suitable for monitoring by ordinary elevator maintenance and management personnel; (4) It is difficult to monitor the elevator operating condition - alternating demagnetization.

[0009] Therefore, existing predictive measures are no longer sufficient to meet actual needs. Summary of the Invention

[0010] The technical problem to be solved by the present invention is to provide a method, computer equipment and system for monitoring the operating status of elevator permanent magnet synchronous motors, which can effectively predict the demagnetization state of PSM permanent magnets with high accuracy.

[0011] To address the aforementioned technical problems, this invention provides a method for monitoring the operating status of a permanent magnet synchronous motor (PMSM) in an elevator, comprising: acquiring in real-time PSM temperature information, pulse count, and elevator operation count of a target elevator; constructing a pixel coordinate system based on grayscale levels according to the PSM temperature information, pulse count, and elevator operation count, wherein the pixels in the pixel coordinate system represent the PSM temperature information using grayscale levels, the horizontal axis of the pixel coordinate system represents the elevator operation count, and the vertical axis of the pixel coordinate system represents the pulse count; extracting target feature points from the pixel coordinate system and constructing a temperature failure model based on the target feature points; and predicting the failure time of the PSM permanent magnet of the target elevator based on the temperature failure model.

[0012] As an improvement to the above scheme, the step of representing the PSM temperature information with gray levels includes: converting the PSM temperature information into gray levels through an image mapping algorithm, wherein the PSM temperature information is positively correlated with the gray levels.

[0013] As an improvement to the above scheme, the step of extracting target feature points from the pixel coordinate system and constructing a temperature failure model based on the target feature points includes: extracting the pixel with the largest gray level during each elevator operation as the target feature point from the pixel coordinate system, wherein the gray level is negatively correlated with the gray value; connecting the target feature points to construct a trend curve of PSM permanent magnet failure; and constructing the relationship between the gray level and the coercivity of the PSM permanent magnet.

[0014] As an improvement to the above scheme, each elevator operation includes a sequential execution of the door closing process, the operation process, the stop process, and the door opening process.

[0015] As an improvement to the above scheme, the relationship between the gray level and the coercivity of the PSM permanent magnet is as follows: when the gray level is 0, the coercivity of the PSM permanent magnet is 0.

[0016] As an improvement to the above scheme, the step of predicting the failure time of the PSM permanent magnet of the target elevator according to the temperature failure model includes: predicting the temperature failure model by means of an extended Kalman filter algorithm to generate prediction feature points; and taking the time corresponding to the prediction feature points as the failure time of the PSM permanent magnet.

[0017] As an improvement to the above scheme, the recursive equation for the prediction stage of the extended Kalman filter algorithm is as follows:

[0018]

[0019] in, For the current moment The predicted ideal state For the previous moment The predicted ideal state For system parameters, For the previous moment Control variables of the system Number of sampling periods for variance for variance For the previous moment Model error, for The first derivative, It is a time-invariant diagonal matrix.

[0020] As an improvement to the above scheme, the correction value in the correction stage of the extended Kalman filter algorithm is expressed as:

[0021]

[0022] in, For the ultimate ideal state, For the current moment The predicted ideal state These are the actual observed values. For the predicted observations, For the predicted ideal state variance for variance Let be the system's gain matrix. The system's observation matrix, for The first derivative, To observe the noise covariance matrix.

[0023] Accordingly, the present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor executes the computer program to implement the steps of the above-described elevator permanent magnet synchronous motor operating status monitoring method.

[0024] Accordingly, the present invention also provides an elevator permanent magnet synchronous motor operation status monitoring system, characterized in that it includes: a temperature sensor for real-time acquisition of PSM temperature information of the target elevator; a pulse generator for real-time acquisition of pulse count of the target elevator; an operation counter for real-time acquisition of elevator operation count of the target elevator; and the aforementioned computer equipment.

[0025] Implementing this invention has the following beneficial effects: This invention combines PSM temperature information, pulse count, and elevator operation count to construct a pixel coordinate system of elevator operation time points (real-time operating conditions) with respect to PSM temperature information. This allows elevator maintenance personnel to clearly monitor the elevator's operating temperature status through the pixel coordinate system, achieving visualized monitoring of the elevator's operating condition. Meanwhile, this invention constructs a temperature failure model and tracks the target feature points in the model in real time. Based on the changing trend of the target feature points, it predicts the future trajectory of the target feature points and determines the time point (i.e., the coordinate position point) when the demagnetization intensity of the PSM permanent magnet reaches the design coercivity threshold of the PSM permanent magnet based on the future trajectory. This allows the failure time of the PSM permanent magnet to be obtained, so that managers can make reasonable elevator safety operation and maintenance technical plans accordingly, so as to maximize the service life of the elevator PSM and prevent the risk of irreversible demagnetization of the PSM permanent magnet. Attached Figure Description

[0026] Figure 1 This is a flowchart of an embodiment of the elevator permanent magnet synchronous motor operation status monitoring method of the present invention; Figure 2 This is a schematic diagram of the pixel coordinate system in the elevator permanent magnet synchronous motor operation status monitoring method of the present invention; Figure 3 This is a schematic diagram of an embodiment of the elevator permanent magnet synchronous motor operation status monitoring system of the present invention. Detailed Implementation

[0027] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings. It is hereby declared that the directional terms such as up, down, left, right, front, back, inside, and outside used in this text are based solely on the accompanying drawings and are not intended to specifically limit the invention.

[0028] See Figure 1 , Figure 1 The flowchart of an embodiment of the elevator permanent magnet synchronous motor operation status monitoring method of the present invention is shown, which includes: S101, real-time acquisition of the target elevator's PSM temperature information, pulse count, and elevator operation count; It should be noted that the target elevator's PSM is equipped with a temperature sensor and a pulse encoder; the temperature sensor collects the PSM temperature information in real time during PSM operation, and the pulse encoder feeds back pulse signals to the pulse generator set on the elevator control system in real time to represent signals such as landing, position and direction of travel.

[0029] Meanwhile, the elevator control system of the target elevator (i.e., the control device for elevator starting, braking, running, stopping, and opening / closing doors) is equipped with a pulse generator and a running counter; the pulse generator receives the pulse signal from the pulse encoder to collect the pulse count of the target elevator; the running counter records the number of elevator runs of the target elevator according to the number of cycles of "closing door-running-stopping-opening door" (i.e., each cycle of "closing door-running-stopping-opening door" is recorded as "one elevator run").

[0030] Correspondingly, by analyzing pulse counts and elevator operation times, the elevator control system can also obtain the elevator's real-time operating conditions (going up, going down, empty, full load), time (season), and location (floor information).

[0031] S102, construct a pixel coordinate system based on grayscale levels based on PSM temperature information, pulse count, and elevator operation count; like Figure 2 As shown, the pixels in the pixel coordinate system represent PSM temperature information in terms of grayscale levels, the horizontal axis of the pixel coordinate system is used to represent the number of elevator runs, and the vertical axis of the pixel coordinate system is used to represent the pulse count.

[0032] Furthermore, this invention can convert PSM temperature information into grayscale levels using an image mapping algorithm, representing the PSM temperature information as a visual, digital planar pixel graphic. The PSM temperature information and grayscale level are positively correlated; that is, the lower the PSM temperature, the smaller the grayscale value; conversely, the smaller the grayscale value, the larger the grayscale level. In this embodiment, the grayscale value ranges from 0 to 255, with the grayscale level being the largest when the value is 0.

[0033] It should be noted that after each pulse count, the PSM temperature information forms a vertical grayscale pixel frame in the pixel coordinate system. As the monitoring continues, the vertical grayscale pixels within the preset monitoring period (such as the elevator inspection cycle required by regulations) expand along the X-axis, forming a visual image of the periodic temperature change over the preset monitoring period.

[0034] Therefore, this invention combines PSM temperature information, pulse count, and elevator operation count to construct a pixel coordinate system of elevator operation time points (real-time operating conditions) with respect to PSM temperature information. This allows elevator maintenance personnel to clearly monitor the elevator operating temperature status through the pixel coordinate system, enabling visualized monitoring of elevator operation status. It can also track relevant risk factors (abnormal temperature changes) and, when necessary, take measures to schedule the elevator's operating rhythm.

[0035] S103, extract target feature points from the pixel coordinate system, and construct a temperature failure model based on the target feature points; Accordingly, the steps of extracting target feature points from the pixel coordinate system and constructing a temperature failure model based on the target feature points include: (1) Extract the pixel with the highest gray level during each elevator operation from the pixel coordinate system as the target feature point; Gray level is negatively correlated with gray value; for example, the gray level is at its maximum when the gray level value (i.e., gray value) is "0"; that is, the pixel with gray value = 0 is selected as the target feature point.

[0036] Each elevator operation includes the following steps executed sequentially: door closing, operation, stopping, and door opening.

[0037] (2) Connect the target feature points to construct the trend curve of PSM permanent magnet failure; (3) Construct the relationship between gray level and coercivity of PSM permanent magnet.

[0038] The relationship between gray level and coercivity of PSM permanent magnet is as follows: when gray level is 0, coercivity of PSM permanent magnet is 0, that is, when coercivity of PSM permanent magnet reaches the threshold, PSM permanent magnet fails.

[0039] Furthermore, the ideal range of pixels in the pixel coordinate system can be determined based on the failure trend curve of the PSM permanent magnet, and the elevator can be managed within the ideal range.

[0040] S104, predict the failure time of the PSM permanent magnet of the target elevator based on the temperature failure model.

[0041] In other words, by tracking the target feature points in the temperature failure model in real time, the trajectory of the target feature points can be recursively calculated in real time, thereby predicting the change trend of the PSM permanent magnet.

[0042] Accordingly, the steps for predicting the failure time of the PSM permanent magnet of the target elevator based on the temperature failure model include: (1) The temperature failure model is predicted by the Extended Kalman Filter (EKF) algorithm to generate predicted feature points; (2) The time corresponding to the predicted feature point is taken as the failure time of the PSM permanent magnet.

[0043] This invention uses the EKF algorithm to track target feature points in a temperature failure model in real time, predicts the future trajectory of the target feature points based on their changing trends, and determines the time point (i.e., coordinate position point) when the demagnetization intensity of the PSM permanent magnet reaches the design coercivity threshold of the PSM permanent magnet based on the future trajectory. This allows managers to make reasonable elevator safety operation and maintenance technical plans to maximize the service life of the elevator PSM and prevent the risk of irreversible demagnetization of the PSM permanent magnet.

[0044] It should be noted that the extended Kalman filter algorithm includes a prediction phase and a correction phase, which will be explained in detail below: I. Forecasting Phase Adopt from The input vector acting on the system during the time interval, the latest state estimate, the predicted state vector, and the state error covariance.

[0045] Accordingly, the recursive equation for the prediction stage of the extended Kalman filter algorithm is:

[0046]

[0047] in: For the current moment The predicted ideal state; For the previous moment The predicted ideal state; For system parameters; For the previous moment Control variables of the system; Number of sampling periods; for The variance; for The variance; For the previous moment The model error, i.e., the matrix formula; for The first derivative; It is a time-invariant diagonal matrix.

[0048] II. Revision Phase The actual PSM temperature information obtained by monitoring the pixel coordinate system is used to correct the state estimate and state error covariance matrix obtained in the prediction stage.

[0049] Accordingly, the correction value in the correction stage of the extended Kalman filter algorithm is expressed as:

[0050]

[0051] in: For the ultimate ideal state; For the current moment Predicted ideal state These are the actual observed values; These are the predicted observations; For the predicted ideal state The variance; for The variance; The gain matrix of the system can be obtained recursively using the estimated values ​​obtained during the prediction phase. The system's observation matrix; for The first derivative; To observe the noise covariance matrix.

[0052] Therefore, the elevator permanent magnet synchronous motor operation status monitoring method of the present invention can obtain the change trend of PSM temperature information in real time, generate a pixel coordinate system based on gray level through image mapping algorithm, establish a temperature failure model, and use EKF algorithm to dynamically track the change trend of pixel points in pixel coordinate system, predict the impact of elevator running time on PSM permanent magnet demagnetization, and provide a scientific basis for elevator safety assessment.

[0053] Accordingly, the present invention also discloses a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described elevator permanent magnet synchronous motor operating status monitoring method.

[0054] See Figure 3 , Figure 3The specific structure of the elevator permanent magnet synchronous motor operation status monitoring system of the present invention is shown. It includes a temperature sensor 1, a pulse generator 2, an operation counter 3, and a computer device 4. The temperature sensor 1, pulse generator 2, and operation counter 3 are respectively connected to the computer device 4. Specifically: Temperature sensor 1 is used to collect PSM temperature information of the target elevator in real time; Pulse generator 2 is used to collect the pulse count of the target elevator in real time; Run counter 3 is used to collect the number of elevator runs of the target elevator in real time; Computer device 4 includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described elevator permanent magnet synchronous motor operation status monitoring method.

[0055] It should be noted that the target elevator's PSM is equipped with a temperature sensor and a pulse encoder; the temperature sensor collects the PSM temperature information in real time during PSM operation, and the pulse encoder feeds back pulse signals to the pulse generator set on the elevator control system in real time to represent signals such as landing, position and direction of travel.

[0056] Meanwhile, the elevator control system of the target elevator (i.e., the control device for elevator starting, braking, running, stopping, and opening / closing doors) is equipped with a pulse generator and a running counter; the pulse generator receives the pulse signal from the pulse encoder to collect the pulse count of the target elevator; the running counter records the number of elevator runs of the target elevator according to the number of cycles of "closing door-running-stopping-opening door" (i.e., each cycle of "closing door-running-stopping-opening door" is recorded as "one elevator run").

[0057] Therefore, the elevator permanent magnet synchronous motor operation status monitoring system of the present invention combines temperature sensor 1, pulse generator 2, operation counter 3 and computer equipment 4. By collecting the PSM temperature information, pulse count and elevator operation number of the target elevator in real time, a targeted pixel coordinate system is constructed. Thus, a temperature failure model is established based on the target feature points, and the demagnetization state of the PSM permanent magnet is effectively predicted with high accuracy.

[0058] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for monitoring the operating status of an elevator permanent magnet synchronous motor, characterized in that, include: Real-time acquisition of PSM temperature information, pulse count, and elevator operation count of the target elevator; A pixel coordinate system based on grayscale levels is constructed based on the PSM temperature information, pulse count, and elevator operation count. The pixels in the pixel coordinate system represent the PSM temperature information using grayscale levels, the horizontal axis of the pixel coordinate system represents the elevator operation count, and the vertical axis of the pixel coordinate system represents the pulse count. Extract target feature points from the pixel coordinate system, and construct a temperature failure model based on the target feature points; The failure time of the PSM permanent magnet of the target elevator is predicted based on the temperature failure model.

2. The elevator permanent magnet synchronous motor operation status monitoring method as described in claim 1, characterized in that, The step of representing the PSM temperature information with gray levels includes: converting the PSM temperature information into gray levels using an image mapping algorithm, wherein the PSM temperature information is positively correlated with the gray levels.

3. The elevator permanent magnet synchronous motor operation status monitoring method as described in claim 1, characterized in that, The step of extracting target feature points from the pixel coordinate system and constructing a temperature failure model based on the target feature points includes: The pixel with the highest gray level during each elevator operation is extracted from the pixel coordinate system as the target feature point, wherein the gray level is negatively correlated with the gray value. Connect the target feature points to construct a trend curve of PSM permanent magnet failure; The relationship between the grayscale levels and the coercivity of the PSM permanent magnet was established.

4. The elevator permanent magnet synchronous motor operation status monitoring method as described in claim 3, characterized in that, Each elevator operation includes the following steps executed sequentially: door closing, operation, stopping, and door opening.

5. The elevator permanent magnet synchronous motor operation status monitoring method as described in claim 3, characterized in that, The relationship between the gray level and the coercivity of the PSM permanent magnet is as follows: when the gray level is 0, the coercivity of the PSM permanent magnet is 0.

6. The method for monitoring the operating status of an elevator permanent magnet synchronous motor as described in claim 1, characterized in that, The step of predicting the failure time of the PSM permanent magnet of the target elevator based on the temperature failure model includes: The temperature failure model is predicted using an extended Kalman filter algorithm to generate predicted feature points; The time corresponding to the predicted feature point is taken as the failure time of the PSM permanent magnet.

7. The method for monitoring the operating status of an elevator permanent magnet synchronous motor as described in claim 1, characterized in that, The recursive equation for the prediction stage of the extended Kalman filter algorithm is as follows: in, For the current moment The predicted ideal state For the previous moment The predicted ideal state For system parameters, For the previous moment Control variables of the system Number of sampling periods for variance for variance For the previous moment Model error, for The first derivative, It is a time-invariant diagonal matrix.

8. The method for monitoring the operating status of an elevator permanent magnet synchronous motor as described in claim 7, characterized in that, The correction value in the correction stage of the extended Kalman filter algorithm is expressed as follows: in, For the ultimate ideal state, For the current moment The predicted ideal state These are the actual observed values. For the predicted observations, For the predicted ideal state variance for variance Let be the system's gain matrix. The system's observation matrix, for The first derivative, To observe the noise covariance matrix.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the elevator permanent magnet synchronous motor operation status monitoring method according to any one of claims 1 to 8.

10. A monitoring system for the operating status of an elevator permanent magnet synchronous motor, characterized in that, include: Temperature sensor, used to collect PSM temperature information of the target elevator in real time; A pulse generator is used to collect pulse counts of the target elevator in real time. A running counter is used to collect the number of times the target elevator runs in real time. The computer device as claimed in claim 7.

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