Magnetic suspension motor state analysis method, device, equipment and medium

Abstract

The invention discloses a magnetic suspension motor state analysis method, device and equipment and a medium, and is applied to the field of motor analysis. Wherein the operation parameters of the magnetic suspension motor are obtained, and the operation parameters comprise the magnetic suspension height, the magnetic force, the inlet flow, the outlet pressure, the rotating speed and the temperature; acquiring environment parameters of the magnetic suspension motor; constructing a state space model corresponding to the magnetic suspension motor according to a Kalman filtering algorithm and a preset operation environment threshold value; and determining operation states corresponding to the operation parameters and the environment parameters according to the space model. Therefore, according to the application, the operation parameters and the environment parameters are automatically analyzed, and manual intervention is integrally reduced; meanwhile, specific parameters such as magnetic suspension height and magnetic force of the magnetic suspension motor are added into a Kalman filtering algorithm, all parameters are intelligently fused through the Kalman filtering algorithm and are mutually corrected, and more accurate and more stable motor state estimation is obtained.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of motor analysis, in particular to a magnetic levitation motor state analysis method, device, equipment and medium. BACKGROUND

[0002] Magnetic levitation motors are moving from the laboratory to industrialization, and their high efficiency, low noise and long life characteristics are driving technological innovation in multiple fields. However, magnetic levitation motor quality testing is a key link to ensure that products meet design standards, safety requirements and user needs.

[0003] The existing magnetic levitation motor testing or state analysis generally needs to build a magnetic levitation motor single machine test bench, then modify the speed and frequency of the magnetic levitation motor through the PC end and test, and the data acquisition method is generally manual recording, but this method cannot guarantee the safety and accuracy of the record, and such methods ignore the influence of motor temperature and levitation height on back EMF, inductance and magnetic force, thereby affecting the test results (operation state analysis results) of the magnetic levitation motor. At the same time, since this method is manual, the test efficiency of the magnetic levitation motor is reduced.

[0004] In view of the above-mentioned technology, it is an urgent problem for those skilled in the art to seek a method that can reduce the test efficiency of the magnetic levitation motor and improve the test accuracy. SUMMARY

[0005] The purpose of the present application is to provide a magnetic levitation motor state analysis method, device, equipment and medium. It can solve the problems of low test efficiency and low test accuracy in the prior art.

[0006] To solve the above technical problems, the present application provides a magnetic levitation motor state analysis method, comprising:

[0007] Obtaining the operating parameters of the magnetic levitation motor, wherein the operating parameters include: magnetic levitation height, magnetic force, inlet flow, outlet pressure, speed and temperature;

[0008] Obtaining the environmental parameters of the magnetic levitation motor;

[0009] According to the Kalman filter algorithm and the preset operating environment threshold, a state space model corresponding to the magnetic levitation motor is constructed;

[0010] According to the space model, the operating state corresponding to the operating parameters and the environmental parameters is determined.

[0011] Preferably, according to the Kalman filter algorithm and the preset operating threshold, a state space model corresponding to the magnetic levitation motor is constructed, comprising:

[0012] Obtaining the preset operating threshold and the preset environmental threshold corresponding to each type of parameter in the operating parameters and the environmental parameters;

[0013] determine the weight corresponding to each type of parameter based on the correlation intensity between the environmental parameter and the operating parameter and the operating state;

[0014] construct a state space model based on each type of parameter, the corresponding weight, and a preset operating threshold or a preset environmental threshold through a Kalman filtering algorithm.

[0015] Preferably, the preset operating threshold and the preset environmental threshold corresponding to each type of parameter in the operating parameter and the environmental parameter are obtained, including:

[0016] obtain a baseline operating threshold corresponding to normal operation of the magnetic levitation motor under a baseline test and a current baseline environmental parameter;

[0017] obtain a limit operating threshold corresponding to normal operation of the magnetic levitation motor under a limit test and a current limit environmental parameter;

[0018] determine the preset operating threshold corresponding to each type of parameter based on the baseline operating threshold and the limit operating threshold;

[0019] determine the preset environmental threshold corresponding to each type of parameter based on the baseline environmental parameter and the limit environmental parameter.

[0020] Preferably, the weight corresponding to each type of parameter is determined based on the correlation intensity between the environmental parameter and the operating parameter and the operating state, including:

[0021] obtain an environmental temperature in the environmental parameter;

[0022] determine a target operating parameter with the strongest correlation intensity based on the correlation intensity between the temperature and the operating parameter;

[0023] determine a target correlation intensity corresponding to the environmental temperature and the target operating parameter, so as to determine the weight corresponding to each type of parameter in the environmental parameter and the operating parameter based on the target correlation intensity.

[0024] Preferably, the operating state corresponding to the operating parameter and the environmental parameter is determined based on the space model, including:

[0025] determine the score corresponding to each type of parameter in the operating parameter and the environmental parameter based on the space model;

[0026] determine an effective score parameter of the magnetic levitation motor based on each score;

[0027] determine the operating state corresponding to the effective score parameter based on the corresponding relationship between the score and the state.

[0028] Preferably, it is characterized in that, after the operating state corresponding to the operating parameter and the environmental parameter is determined based on the space model, it further includes:

[0029] The change trend of each parameter in the predicted operation parameter at different time is predicted.

[0030] The operation state at different time is predicted according to the preset operation environment threshold corresponding to each parameter and the change trend corresponding to each parameter.

[0031] Preferably, after the operation state at different time is predicted according to the preset operation environment threshold corresponding to each parameter and the change trend corresponding to each parameter, the method further comprises:

[0032] An operation state report is generated according to the operation state at different time and the corresponding each parameter.

[0033] In another aspect, the application provides a magnetic suspension motor state analysis device, comprising:

[0034] A first acquisition module is configured to acquire operation parameters of the magnetic suspension motor, wherein the operation parameters include magnetic suspension height, magnetic force, inlet flow, outlet pressure, rotating speed and temperature.

[0035] A second acquisition module is configured to acquire environment parameters of the magnetic suspension motor.

[0036] A model construction module is configured to construct a state space model corresponding to the magnetic suspension motor according to a Kalman filtering algorithm and a preset operation environment threshold.

[0037] An operation state determination module is configured to determine an operation state corresponding to the operation parameters and the environment parameters according to the space model.

[0038] In another aspect, the application further provides an electronic device, comprising a memory configured to store a computer program.

[0039] A processor is configured to execute the computer program to implement the steps of the magnetic suspension motor state analysis method.

[0040] In another aspect, the application further provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps of the magnetic suspension motor state analysis method.

[0041] The magnetic suspension motor state analysis method provided in the application comprises: obtaining operation parameters of a magnetic suspension motor, wherein the operation parameters comprise: magnetic suspension height, magnetic force, inlet flow, outlet pressure, rotating speed and temperature; obtaining environmental parameters of the magnetic suspension motor; constructing a state space model corresponding to the magnetic suspension motor according to a Kalman filtering algorithm and a preset operation environment threshold; and determining an operation state corresponding to the operation parameters and the environmental parameters according to the space model. As can be seen, the application automatically analyzes the operation parameters and the environmental parameters, and reduces the intervention of manual work as a whole; meanwhile, the application adds the parameters specific to the magnetic suspension motor, such as the magnetic suspension height and the magnetic force, to the Kalman filtering algorithm, intelligently integrates all the parameters through the Kalman filtering algorithm, and mutually corrects them to obtain a more accurate and stable motor state estimation. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the application, the drawings needed in the embodiments will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor.

[0043] Figure 1 The flowchart of the magnetic suspension motor state analysis method provided in the application is shown in

[0044] Figure 2 The module diagram of the magnetic suspension motor state analysis device provided in the embodiments of the application is shown in

[0045] Figure 3 The structural diagram of the electronic device provided in another embodiment of the application is shown in DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the application will be described clearly and completely in combination with the drawings in the embodiments of the application. Obviously, the described embodiments are only some of the embodiments of the application, but not all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor are within the protection scope of the application.

[0047] The core of the application is to provide a magnetic suspension motor state analysis method, device, equipment and medium.

[0048] In order to enable those skilled in the art to better understand the application scheme, the application will be further described in detail in combination with the drawings and specific embodiments.

[0049] Figure 1 The flowchart of the magnetic suspension motor state analysis method provided in the application is shown in Figure 1As shown, comprising the following steps:

[0050] S10: Obtain the operating parameters of the magnetic suspension motor, wherein the operating parameters include: magnetic suspension height, magnetic force, inlet flow, outlet pressure, rotating speed and temperature.

[0051] S11: Obtain the environmental parameters of the magnetic suspension motor.

[0052] S12: Construct the state space model corresponding to the magnetic suspension motor according to the Kalman filtering algorithm and the preset operating environment threshold.

[0053] S13: Determine the operating state corresponding to the operating parameters and the environmental parameters according to the space model.

[0054] In a specific embodiment, a test table is first built, which is composed of a motor placement table, an electrical cabinet and an upper computer operating table. Among them, the motor placement table: used for placing the magnetic suspension motor to be tested (analyzed) and the corresponding sensor device; the electrical cabinet: provides adjustable frequency three-phase power supply for the magnetic suspension motor, and provides soft start and protection function; the upper computer operating table: uses self-made operation software to realize a series of operations such as suspension of the magnetic suspension motor, start of the frequency converter, data acquisition and alarm display.

[0055] Needless to say, before the magnetic suspension motor is placed on the motor placement table for operation, the corresponding sensor device needs to be specifically installed in the corresponding position of the magnetic suspension motor for detecting the corresponding operating parameters. The flow meter sensor is installed at the inlet of the cooling pipeline of the magnetic suspension motor for obtaining the inlet flow; the pressure sensor is installed at the air gap outlet of the magnetic suspension motor for obtaining the outlet pressure; the stator temperature sensor is annularly distributed on the stator shell for obtaining the temperature; the rotor temperature sensor observes the rotor surface through a high-speed infrared transparent window; the encoder is directly connected with the shaft end of the magnetic suspension motor for obtaining the rotating speed; the height sensor is installed on the surface of the magnetic suspension motor for obtaining the magnetic suspension height; the magnetic force sensor is installed on the surface of the magnetic suspension motor for obtaining the magnetic force. In addition, eddy current displacement sensors, Hall sensor arrays and MEMS (MICro EleCTRo Mechanical Systems) accelerometers can also be placed in the magnetic suspension motor, respectively used for obtaining the parameters of the suspension performance, electromagnetic performance and mechanical performance of the magnetic suspension motor.

[0056] At the same time, the parameters corresponding to the environment where the state is analyzed or tested at that time are taken as the environmental parameters, such as environmental temperature, environmental humidity, etc.

[0057] Since the data measured by the sensor all have errors or interference, the Kalman filtering is adopted in the application to intelligently fuse all the parameters collected by the sensors, mutually "correct", and obtain a more accurate and stable motor state. Since the Kalman filtering algorithm and the preset running environment threshold are firstly constructed into the state space model corresponding to the magnetic suspension motor in the application, and then the running state corresponding to the running parameters and the environmental parameters is determined according to the space model, that is, on the basis of the running parameters including the magnetic suspension height, magnetic force and the like, the parameters used in the process of constructing the state space model according to the Kalman filtering algorithm and the preset running environment threshold also involve the magnetic suspension height and the magnetic force and the like. It can also be understood that the magnetic suspension height and the corresponding suspension height change, the magnetic force and the change of the magnetic force with temperature and the like are explicitly added to the "calculation model" of the Kalman filtering. Similarly, the state space model constructed by the Kalman filtering algorithm can be determined according to the working principle of the magnetic suspension motor (electromagnetic force, heat, mechanical vibration how to interact) to represent the complex relationship between the temperature change, vibration, suspension height instability and other difficult problems of the magnetic suspension motor when rotating at high speed.

[0058] Further, since the Kalman filtering is an algorithm for optimal estimation of system state by using linear system state equation and observing data of system input and output, the change trend of various parameters in the running parameters at different times can be predicted; and then the running state at different times is predicted according to the preset running environment threshold corresponding to various parameters and the change trend. Of course, the running state at different times and the corresponding various parameters can be generated into a running state report for the convenience of the running personnel to check.

[0059] It should be further pointed out that the magnetic suspension motor itself has multiple protection functions such as overload, overvoltage, overheating and short circuit.

[0060] The magnetic suspension motor state method provided by the application comprises: acquiring running parameters of a magnetic suspension motor, wherein the running parameters comprise: magnetic suspension height, magnetic force, inlet flow, outlet pressure, rotating speed and temperature; acquiring environmental parameters of the magnetic suspension motor; constructing a state space model corresponding to the magnetic suspension motor according to a Kalman filtering algorithm and a preset running environment threshold; and determining a running state corresponding to the running parameters and the environmental parameters according to the space model. As can be seen, the application automatically analyzes the running parameters and the environmental parameters, and reduces the overall manual intervention; meanwhile, the application adds the parameters specific to the magnetic suspension motor such as the magnetic suspension height and the magnetic force into the Kalman filtering algorithm, intelligently fuses all the parameters through the Kalman filtering algorithm, mutually "corrects", and obtains a more accurate and stable motor state estimation.

[0061] On the basis of the above-mentioned embodiments, as a preferred embodiment, the step S12: the specific implementation manner of constructing the state space model corresponding to the magnetic suspension motor according to the Kalman filtering algorithm and the preset operation threshold is: obtaining the preset operation threshold and the preset environment threshold corresponding to each type of parameter in the operation parameter and the environment parameter respectively; determining the weight corresponding to each type of parameter based on the association strength of the environment parameter and the operation parameter with the operation state; and constructing the state space model based on each type of parameter, the corresponding weight and the preset operation threshold or the preset environment threshold through the Kalman filtering algorithm.

[0062] And the specific implementation manner of obtaining the preset operation threshold and the preset environment threshold corresponding to each type of parameter in the operation parameter and the environment parameter respectively is: obtaining the baseline operation threshold corresponding to the normal operation of the magnetic suspension motor under the baseline test and the current baseline environment parameter; obtaining the limit operation threshold corresponding to the normal operation of the magnetic suspension motor under the limit test and the current limit environment parameter; determining the preset operation threshold corresponding to each type of parameter according to the baseline operation threshold and the limit operation threshold; and determining the preset environment threshold corresponding to each type of parameter according to the baseline environment parameter and the limit environment parameter.

[0063] And the specific implementation manner of determining the weight corresponding to each type of parameter based on the association strength of the environment parameter and the operation parameter with the operation state is: obtaining the environment temperature in the environment parameter; determining the target operation parameter with the maximum association strength with the environment temperature based on the association strength between the temperature and the operation parameter; determining the target association strength corresponding to the environment temperature and the target operation parameter, so as to determine the weight corresponding to each type of parameter in the environment parameter and the operation parameter according to the target association strength.

[0064] In specific embodiments, the parameters involved in the present application are specifically divided into two categories, one is the operation parameter, and the other is the environment parameter. Therefore, the preset operation environment threshold is essentially the preset operation threshold and the preset environment threshold. The specific acquisition method is to perform baseline test and limit test on the magnetic suspension motor, so as to obtain the threshold corresponding to each type of parameter. The purpose of the baseline test is to check the running-in of each device in the current type of magnetic suspension motor, to judge whether the current performance, vibration, noise and the like meet the national standards and the standards of the design drawings, and the like, so as to ensure that the current type of magnetic suspension motor is qualified. The purpose of the limit test is to judge the change and limit of the state index of the current type of magnetic suspension motor in the limit state, and whether the protection measures can be safely executed. The baseline test and the limit test in the present application are adopted in stages, which can more comprehensively, more safely and more intelligently analyze the parameters and state of the current magnetic suspension motor. Since the baseline test and the limit test can detect the change of each type of parameter and the corresponding state in real time, the threshold corresponding to each type of parameter is determined according to the needs of the user.

[0065] The flow (automatic flow) of the benchmark test phase is: 1, set the standard voltage; 2, let the magnetic suspension motor start from static, slowly speed up (such as 500 revolutions each time), and keep normal speed; 3, every time a speed point, the computer (host computer) automatically records all sensor data (flow, pressure, temperature, vibration, suspension height…), draw a curve; 4, if any parameter suddenly exceeds the standard (compared with the national standard), immediately alarm and record.

[0066] The flow of the limit test phase is: 1, add a little load (such as from 110% normal load, add 5% each time, to 150%); 2, keep an eye on the change rate of key data; 3, intelligently predict the next state through the learning model; 4, if it is predicted that there is a high probability (> 90%) of serious problems (such as burning or collision), or the key change rate is too fast to exceed the safety line, immediately cut off the power and start the emergency brake (such as mechanical brake), protect the motor and test bench; 5, the computer automatically organizes all data and generates a detailed test report.

[0067] Since there are many types of parameters involved in the present application, the running state cannot be determined according to any one parameter, therefore, the present application adopts the weight method to determine. The association strength of any type of parameter with the running state is large, then the corresponding weight is large. For example: the weight corresponding to the efficiency parameter can be 35%; the weight corresponding to the temperature rise parameter is 25%, etc.

[0068] It needs to be pointed out here that, since the environmental temperature in the environmental parameter has a great influence on the running parameters of the magnetic suspension motor, the target running parameter (any type of parameter in the running parameter) with the largest association strength with the environmental temperature can be further determined, and then the weights corresponding to each type of parameter in the environmental parameter and the running parameter are determined according to the current target association strength. For example: when the environmental temperature is 25 degrees Celsius, the weight corresponding to the efficiency parameter can be 35%; when the environmental temperature is 35 degrees Celsius, the target running parameter with the largest association strength is magnetic force, then the weight corresponding to the efficiency parameter can be 25% according to the association strength.

[0069] It should be noted that the embodiments provided by the present application are only one possible implementation, but are not limited to only this implementation, and can be set by the user as needed.

[0070] The present application provides a specific implementation method of constructing a state space model corresponding to the magnetic suspension motor according to the Kalman filtering algorithm and the preset running threshold, which fully considers the association strength existing in different situations, thereby improving the accuracy of the running state of the magnetic suspension motor.

[0071] On the basis of the above-mentioned embodiments, as a preferred embodiment, the implementation manner of step S13: determining the running state corresponding to the running parameter and the environmental parameter according to the space model is: determining the score corresponding to each type of parameter in the running parameter and the environmental parameter according to the space model; determining the effective score parameter of the magnetic suspension motor according to each score; and determining the running state corresponding to the effective score parameter according to the corresponding relationship between the score and the state.

[0072] In specific embodiments, the application determines the running state in the form of scoring, that is, determines the score corresponding to each type of parameter, then adds these scores to obtain the final effective score, and finally determines the running state according to the effective score. For example: the smaller the temperature rise parameter, the higher the score; the smaller the vibration parameter, the higher the score; the smaller the suspension gap fluctuation parameter, the higher the score. When the effective score is 60-80, the running state is normal, and the running effect is qualified; when the effective score is 80-90, the running state is normal, and the running effect is excellent; when the effective score is 90-100, the running state is normal, and the running effect is perfect; when the effective score is less than 60, the running state is abnormal.

[0073] It should be noted that the embodiments provided by the application are only one possible implementation, but are not limited to only this implementation. Users can set it up according to their needs.

[0074] As can be seen, the magnetic suspension motor state analysis method provided by the application has the following advantages:

[0075] 1. Intelligent control: The host computer console obtains the running parameters and environmental parameters of the magnetic suspension motor and automatically analyzes them.

[0076] 2. Multiple protection mechanisms: Overload, overvoltage, overheating, short circuit, and other multiple protection functions.

[0077] 3. Automated process management: Automated scripts and intelligent analysis reduce human intervention.

[0078] 4. Improved safety: Can reduce safety accidents caused by electrical faults, such as fires and electric shocks.

[0079] 5. Improved efficiency: The automation of magnetic suspension motor state evaluation improves efficiency.

[0080] 6. Reduced costs: By reducing the probability of equipment damage and failure, maintenance and replacement costs can be reduced.

[0081] In the above embodiments, the magnetic levitation motor state analysis method is described in detail, and the present application also provides a corresponding embodiment of the magnetic levitation motor testing device. It should be noted that the embodiments of the device part are described from two angles, one is based on the functional module angle, and the other is based on the hardware angle.

[0082] Figure 2 A module diagram of a magnetic levitation motor state analysis device provided in an embodiment of the present application is shown in FIG. 1, which includes: Figure 2

[0083] The first acquisition module 11 is configured to acquire the operating parameters of the magnetic levitation motor, wherein the operating parameters include the magnetic levitation height, the magnetic force, the inlet flow, the outlet pressure, the rotating speed and the temperature.

[0084] The second acquisition module 12 is configured to acquire the environmental parameters of the magnetic levitation motor.

[0085] The model construction module 13 is configured to construct the state space model corresponding to the magnetic levitation motor according to the Kalman filtering algorithm and the preset operating environment threshold.

[0086] The operating state determination module 14 is configured to determine the operating state corresponding to the operating parameters and the environmental parameters according to the space model.

[0087] Since the embodiments of the device part correspond to the embodiments of the method part, the embodiments of the device part are described in the description of the embodiments of the method part, which will not be described here.

[0088] Figure 3 A structural diagram of an electronic device provided in another embodiment of the present application is shown in FIG. 2, which includes: Figure 3

[0089] The processor 21 is configured to implement the steps of the magnetic levitation motor state analysis method mentioned in the above embodiments when executing the computer program.

[0090] The electronic device provided in the embodiment can include but is not limited to a smart phone, a tablet computer, a notebook computer or a desktop computer, etc.

[0091] ​​The processor 21 can include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one of a hardware form of a digital signal processor (DSP), a field-programmable gate array (FPGA), a programmable logic array (PLA). The processor 21 can also include a main processor and a coprocessor. The main processor is a processor for processing data in a wake-up state, also known as a central processing unit (CPU). The coprocessor is a low-power processor for processing data in a standby state. In some embodiments, the processor 21 can be integrated with a graphics processor (GPU) for rendering and drawing content required to be displayed by the display screen. In some embodiments, the processor 21 can further include an artificial intelligence (AI) processor for processing machine learning related computing operations.

[0092] The memory 20 can include one or more computer-readable storage media that can be non-transitory. The memory 20 can also include a high-speed random access memory, and a nonvolatile memory such as one or more disk storage devices, flash storage devices. In this embodiment, the memory 20 is at least used to store the following computer program 201, wherein the computer program is loaded and executed by the processor 21, and can implement the related steps of the magnetic suspension motor state analysis method disclosed in any of the preceding embodiments. In addition, the resources stored by the memory 20 can also include an operating system 202 and data 203, etc., and the storage mode can be temporary storage or permanent storage. The operating system 202 can include Windows, Unix, Linux, etc.

[0093] In some embodiments, the electronic device can further include a display screen 22, an input / output interface 23, a communication interface 24, a power supply 25, and a communication bus 26.

[0094] Those skilled in the art can understand that the structure shown in the above embodiments is not a limitation on the electronic device, and the electronic device can include more or fewer components than those shown in the figure. Figure 3

[0095] The electronic device provided by the embodiments of the present application includes a memory and a processor. When the processor executes the program stored in the memory, the magnetic suspension motor state analysis method described above can be implemented. ​

[0096] Finally, the present application also provides an embodiment corresponding to a computer-readable storage medium. The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the steps described in the above method embodiments.

[0097] It can be understood that if the method in the above embodiments is implemented in the form of a software function unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and performs all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (Read-Only Memory, ROM), a random access memory (Random Access Memory, RAM), a magnetic disk or an optical disk, and various media that can store program codes.

[0098] The above provides a kind of magnetic suspension motor state analysis method, device, equipment and medium provided in the present application are introduced in detail.The progressive way is described in each embodiment of the specification, and each embodiment emphasizes the different place with other embodiments, and the same part of each embodiment is referred to each other.The device disclosed in the embodiment is described simply, and the related part is referred to the method part description since it is corresponding to the method disclosed in the embodiment.It should be pointed out that, for ordinary skilled in the art, without departing from the principles of the present application, some improvements and modifications can be made to the present application, and these improvements and modifications also fall within the scope of the claims of the present application.

[0099] It should also be noted that in the present specification, relational terms such as first and second are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply that there is any such actual relationship or order between these entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment. Without more limitations, the element defined by the statement "including a" does not exclude the presence of other identical elements in the process, method, article or equipment including the element.

Claims

1. A method for analyzing the state of a magnetic levitation motor, characterized in that: include: Acquiring operating parameters of the magnetic levitation motor, wherein the operating parameters include: magnetic levitation height, magnetic force, inlet flow, outlet pressure, speed, and temperature; Acquiring environmental parameters of the magnetic levitation motor; Constructing a state space model corresponding to the magnetic levitation motor according to a Kalman filter algorithm and a preset operating environment threshold; An operating state corresponding to the operating parameter and the environmental parameter is determined according to the space model.

2. The magnetic levitation motor state analysis method according to claim 1, characterized in that: The step of constructing a state space model corresponding to the magnetic levitation motor according to the Kalman filter algorithm and the preset operating threshold comprises: Obtaining preset operating thresholds and preset environmental thresholds corresponding to various types of parameters in the operating parameters and the environmental parameters; Determining weights corresponding to various parameters based on the strength of association between the environmental parameter and the operating parameter and the operating state; The state space model is constructed by the Kalman filter algorithm based on various parameters and corresponding weights and the preset operating threshold or the preset environmental threshold.

3. The magnetic levitation motor state analysis method according to claim 2, characterized in that: The obtaining of preset operating thresholds and preset environmental thresholds corresponding to various types of parameters in the operating parameters and the environmental parameters includes: Obtaining a benchmark operating threshold corresponding to normal operation of the magnetic levitation motor under a benchmark test and current benchmark environmental parameters; Obtaining the extreme operating threshold corresponding to the normal operation of the magnetic levitation motor under the extreme test and the current extreme environmental parameters; Determine the preset operating thresholds corresponding to the various parameters according to the benchmark operating thresholds and the limit operating thresholds; The preset environmental thresholds corresponding to the various parameters are determined according to the reference environmental parameters and the extreme environmental parameters.

4. The magnetic levitation motor state analysis method according to claim 2, characterized in that: The determining of the weights corresponding to the various parameters based on the strength of association between the environmental parameters and the operating parameters and the operating state, respectively, includes: Obtaining the ambient temperature in the environmental parameters; determining a target operating parameter having the greatest correlation strength with the ambient temperature based on the correlation strength between the temperature and the operating parameter; The target association strengths corresponding to the ambient temperature and the target operating parameters are determined, so as to determine the weights corresponding to the various types of parameters in the ambient parameters and the operating parameters according to the target association strengths.

5. The magnetic levitation motor state analysis method according to claim 1, characterized in that: The determining, according to the space model, the operating state corresponding to the operating parameter and the environmental parameter includes: Determining scores corresponding to various parameters in the operating parameters and the environmental parameters according to the spatial model; Determining effective scoring parameters of the magnetic levitation motor according to each score; The operating state corresponding to the valid scoring parameter is determined according to the corresponding relationship between the score and the state.

6. The magnetic levitation motor state analysis method according to any one of claims 1 to 5, characterized in that: After determining the operating states corresponding to the operating parameters and the environmental parameters according to the space model, the method further includes: Predicting the changing trends of various parameters in the operating parameters at different times; The operating status at different times is predicted based on the preset operating environment thresholds corresponding to various parameters and the corresponding change trends.

7. The magnetic levitation motor state analysis method according to claim 6, characterized in that: After predicting the operating status at different times according to the preset operating environment thresholds corresponding to the various parameters and the corresponding change trends, the method further includes: Generate an operating status report based on the operating status at different times and the corresponding various parameters.

8. A magnetic levitation motor state analysis device, characterized in that: include: A first acquisition module is used to acquire operating parameters of the magnetic levitation motor, wherein the operating parameters include: magnetic levitation height, magnetic force, inlet flow, outlet pressure, speed and temperature; A second acquisition module is used to obtain environmental parameters of the magnetic levitation motor; A model building module, configured to build a state space model corresponding to the magnetic levitation motor according to a Kalman filter algorithm and a preset operating environment threshold; An operating state determination module is used to determine the operating state corresponding to the operating parameters and the environmental parameters according to the space model.

9. An electronic device, characterized in that: including a memory for storing a computer program; A processor is configured to implement the steps of the magnetic levitation motor state analysis method according to any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the magnetic levitation motor state analysis method according to any one of claims 1 to 7 are implemented.

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