A screening machine health monitoring method and system based on digital twinning

Abstract

The present application relates to a kind of screening machine health monitoring method and system based on digital twinning, the screening machine health monitoring method based on digital twinning includes the following steps: 3D digital twin workshop corresponding to real workshop is built, 3D screening machine model in the 3D digital twin workshop corresponds with screening machine batch;The relevant parameters of the motor of all the screening machine are collected in real time, the relevant parameters are processed to obtain processed data, the health status of all the screening machine is judged as normal or abnormal based on the processed data;The health status of the screening machine is displayed on the corresponding 3D screening machine model by different colors, to realize the health monitoring of screening machine.The present application makes equipment operation and maintenance change from after-maintenance to before-prevention, reduces maintenance cost, improves equipment reliability, reduces human resource cost, equipment health problem can be solved in real time, real-time is high.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of equipment state detection, and particularly relates to a screening machine health monitoring method and system based on digital twinning. BACKGROUND

[0002] A screening machine is a device for screening materials. Traditional screening machine health monitoring is performed by assigning multiple technicians to check whether each part of the screening machine is healthy at fixed intervals, determine whether the screening machine needs to be repaired or can continue to be used, and then perform repair. Figure 4 As shown in the flowchart, when the screening machine has problems, it cannot be discovered and solved in time, causing certain economic losses.

[0003] Therefore, it is necessary to provide a new screening machine health monitoring method based on digital twinning to solve the above technical problems. SUMMARY

[0004] The purpose of the present application is to provide a screening machine health monitoring method based on digital twinning to solve the above problems.

[0005] The present application achieves the above-mentioned purposes through the following technical solutions:

[0006] A screening machine health monitoring method based on digital twinning, comprising the following steps:

[0007] A 3D digital twin workshop corresponding to the real workshop is constructed, and a 3D screening machine model in the 3D digital twin workshop corresponds to a batch of screening machines;

[0008] Real-time collection of relevant parameters of the motors of all the screening machines is performed, the relevant parameters are processed to obtain processed data, and the health status of all the screening machines is determined to be normal or abnormal based on the processed data;

[0009] The health status of the screening machines is displayed on the corresponding 3D screening machine model through different colors to realize health monitoring of the screening machines.

[0010] As a further optimization scheme of the present application, the specific process of constructing a 3D digital twin workshop corresponding to the real workshop, in which a 3D screening machine model corresponds to a batch of screening machines, is as follows:

[0011] Material-free modeling of the screening machine is performed according to the design original drawing of the screening machine to obtain a material-free screening machine model;

[0012] Real material data of the screening machine is collected, and each part of the material-free screening machine model is given material based on the real material data to obtain a 3D screening machine model.

[0013] Collect the light parameters of the real workshop to make the light and bulb, and get the 3D digital twin workshop corresponding to the real workshop.

[0014] As a further optimization scheme of the present application, the screening machine is modeled without material according to the design original drawing paper of the screening machine, and a no-material screening machine model is obtained, and the specific process is as follows:

[0015] According to the design original drawing paper of the screening machine, the shell of the screening machine and the optical fiber rotating wheel rotating in the screening machine are modeled without material by using UE4 software, and the optical fiber rotating wheel is set as a rotating body, and a no-material screening machine model is obtained.

[0016] As a further optimization scheme of the present application, the screening machine is installed with a sensor and a PLC controller, the sensor is used to collect the related parameters of the motor of the screening machine in real time, and the PLC controller is used to control the rotating speed of the motor and transmit the related parameters to the AIoT platform for storage.

[0017] As a further optimization scheme of the present application, the related parameters of the motor of all the screening machines are collected in real time, the related parameters are processed to obtain processed data, and the health status of all the screening machines is determined to be normal or abnormal based on the processed data, and the specific process is as follows:

[0018] The related parameters of the motor of all the screening machines are collected in real time, and the related parameters include the rotating speed data and the acceleration data of the motor.

[0019] A curve table is generated based on the rotating speed data and the acceleration data;

[0020] According to the rotating speed data, the acceleration data and the corresponding curve table, an expression formula corresponding to the curve table is calculated:

[0021] y=Asin(Bx+C)+D;

[0022] Wherein, y is the acceleration, x is the time, A, B, C are constants;

[0023] Based on the above formula, the amplitude of the curve table is calculated as A, and the period is T=2π / B, wherein the rotating speed N of the motor satisfies the relationship with the amplitude A as follows:

[0024] N1=f*A 1 / 2 ;

[0025] Wherein, N1 is the first rotating speed of the motor, f is a fixed constant, and A is the amplitude;

[0026] The period T satisfies the following relationship:

[0027] N2 = g * T -2 ;

[0028] Wherein, N2 is the second rotating speed of the motor, g is a fixed constant, and T is a period;

[0029] determine whether the difference between the first rotating speed N1 and the second rotating speed N2 is within 5%, if yes, set the average value of N1 and N2 as the rotating speed N obtained after calculation; if no, determine that the health state of the screening machine is abnormal;

[0030] determine whether the difference between the rotating speed N and the rotating speed data is within 5%, if no, determine that the health state of the screening machine is abnormal; if yes, determine whether the rotating speed N exceeds the maximum value of the motor rotating speed, if yes, determine that the health state of the screening machine is abnormal; if no, determine that the health state of the screening machine is normal.

[0031] As a further optimization scheme of the present application, the reasons for the abnormal health state of the screening machine include non-standard operation, motor failure and abnormal PLC control of motor rotating speed;

[0032] When the difference between the first rotating speed N1 and the second rotating speed N2 is not within 5%, the reason for the abnormal health state of the screening machine is motor failure;

[0033] When the difference between the rotating speed N and the rotating speed data is not within 5%, the reason for the abnormal health state of the screening machine is abnormal PLC control of motor rotating speed;

[0034] When the rotating speed N exceeds the maximum value of the motor rotating speed, the reason for the abnormal health state of the screening machine is motor failure or non-standard operation.

[0035] As a further optimization scheme of the present application, the health state of the screening machine is displayed on the corresponding 3D screening machine model through different colors, and the specific process is as follows:

[0036] According to the four types of health states of the screening machine, different colors are given, wherein the normal health state is the original color, non-standard operation is yellow, motor failure is red, and abnormal PLC control of motor rotating speed is blue; the health state of the screening machine with different colors is given to the corresponding 3D screening machine model in the 3D digital twin workshop through the API interface, and the health state of the screening machine is displayed synchronously.

[0037] A screening machine health monitoring system based on digital twinning includes:

[0038] A modeling module is used to construct a 3D digital twin workshop corresponding to a real workshop, and a 3D screening machine model in the 3D digital twin workshop corresponds to a screening machine batch.

[0039] a data acquisition module, configured to acquire, in real time, relevant parameters of motors of all the screening machines;

[0040] a data processing module, configured to process the relevant parameters to obtain processed data;

[0041] a health state judgment module, configured to judge, based on the processed data, health states of all the screening machines as normal or abnormal;

[0042] a display module, configured to display the health states of the screening machines on corresponding 3D screening machine models through different colors.

[0043] An electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus;

[0044] a memory, configured to store a computer program;

[0045] a processor, configured to execute the program stored on the memory, and realize the screening machine health monitoring method based on digital twinning in any one of claims 1-7.

[0046] A computer readable storage medium, having a computer program stored thereon, wherein the computer program is executed by a processor to realize the screening machine health monitoring method based on digital twinning in any one of claims 1-7.

[0047] The present application has the following advantages:

[0048] The present application changes the equipment operation and maintenance from after-maintenance to pre-prevention, reduces the maintenance cost (from multi-person on-site inspection to single-person or few-person monitoring of a virtual factory), improves the equipment reliability (predicts the future state of the equipment to give early warning), reduces the human resource cost (from multi-person troubleshooting to single-person monitoring), and the equipment health problem can be solved in real time, and the real-time performance is high. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 is a general flow block diagram of the method of the present application;

[0050] Figure 2 is a relevant parameter processing flow block diagram of the motor of the present application;

[0051] Figure 3 is a specific flow block diagram of the present application;

[0052] Figure 4 is a traditional equipment health state detection method flow chart. DETAILED DESCRIPTION

[0053] The application will be further described in detail below with reference to the drawings. It is necessary to point out here that the following specific embodiments are only used to further illustrate the application and cannot be understood as limiting the scope of protection of the application. Those skilled in the art can make some non-essential improvements and adjustments to the application according to the above application content.

[0054] As shown in the figure, a screening machine health monitoring method based on digital twinning includes the following steps: Figure 1

[0055] S1: A 3D digital twinning workshop corresponding to a real workshop is constructed, and a 3D screening machine model in the 3D digital twinning workshop corresponds to a screening machine batch;

[0056] S2: Real-time collection of relevant parameters of motors of all screening machines is performed, the relevant parameters are processed to obtain processed data, and the health status of all screening machines is determined to be normal or abnormal based on the processed data;

[0057] S3: The health status of the screening machine is displayed on the corresponding 3D screening machine model through different colors to realize health monitoring of the screening machine.

[0058] In this embodiment, a gateway, a sensor, and a PLC controller are arranged inside the screening machine.

[0059] A 4G Internet of Things card is installed inside the gateway, and a 24V power adapter is configured to connect the 220V power supply inside the screening machine;

[0060] The sensor is connected to the 485 interface of the gateway through a 485 line, and a 12V power adapter is configured to connect the 220V power supply inside the screening machine;

[0061] The PLC controller is a motor controller inside the screening machine, which is directly connected to the network port of the gateway through a network cable. The gateway is configured to determine the connection port and the protocol pair of the collected equipment. After the computer is connected to the gateway through a network cable or the WIFI of the gateway, the gateway IP address is input into the gateway configuration page using a browser, and the configuration page of the connection port of the collected equipment is entered under the intelligent gateway application configuration page. The data protocol, baud rate, data bits, stop bits, check bits, and collection address, function code, start address, collection number, data type, and data ID of the equipment are filled in the protocol document consistent with the equipment, and then the data is collected to the gateway. The reporting application transmission protocol of the gateway is configured to use MQTT, the server address and port are set to be consistent with the AIoT platform server IP port, the subscription Topic topic is set, the reporting period and the reporting number are set, and then the AIoT platform on the cloud server can receive the data and save the data to the database on the cloud server. ​

[0062] The gateway can collect the upload time, the gateway has the Internet of Things card time verification, real-time accuracy, and will not produce time error, the data collection time interval is 1s, the inquiry data is collected immediately, the response is fast, and the gateway can also support other network interfaces and 485 data collection to facilitate subsequent installation of other data collection, installation directly on the upper part of the magnetic motor, the motor rotation sensor synchronously moves, the collection is more accurate, the sensor is small, and will not affect the work of the equipment itself, the gateway and the sensor power are less than 24V, which is relatively safe; the AIoT background management software has functions of device management, data collection, protocol conversion, data storage, etc., can provide data service API for device state identification algorithm and optical fiber intelligent factory digital twin system, support collection of various device data, and can perform edge calculation on data; the algorithm can directly convert the collected data into device health monitoring related information.

[0063] In the embodiment, as shown in Figure 2 After the collected data is stored in the database through the AIoT platform on the cloud server, the data collected by the sensor is processed: first, the three types of data are generated into corresponding curve tables, the curve substantially obeys a sinusoidal curve, and the expression formula of the curve is calculated according to the corresponding data and the curve table: y=Asin(Bx+C)+D (where y is acceleration, x is time, A, B, and C are constants), after the expression is calculated, the amplitude of the curve is calculated according to the calculated curve formula, and the period T=2π / B, wherein the motor speed N obeys the amplitude A: N1=f*A 1 / 2 (where N1 is the motor speed, f is a fixed constant, and A is the amplitude), and the period T: N2=g*T -2 (where N2 is the motor speed, g is a fixed constant, and T is the period), different motors have different types, and the data collected by the sensor is different, so the constants f and g are different, if the difference between the motor speeds N1 and N2 calculated by the amplitude and the period is within 5%,

[0064] at this time, the average value of N1 and N2 is considered to be the true speed N after calculation, the calculated speed is analyzed, if the difference between the calculated speed and the collected PLC speed exceeds 5%, it is judged that the PLC control motor speed of the screening machine may be abnormal, if the calculated speed is too high and exceeds the maximum value of the original motor, it is judged that the motor has a fault, and various judgments of the state of the motor are made. The health state of the running screening machine and the predicted health state of the future screening machine are judged and stored in the database, the screening machine health state and the predicted data in the database are written into the MySQL statement of the AIoT platform code end to query the corresponding data, and then written into the display data port to open the corresponding API interface.

[0065] In the embodiment, as shown in Figure 3The 3D model digital twin workshop building process is shown as follows: the screening machine model in the UE4 modeling workshop is filtered, the screening machine is modeled according to the design drawing of the screening machine, the material-free shell of the screening machine is modeled, the material-free rotating optical fiber rotating wheel in the screening machine is modeled, the materials of each part of the screening machine are surveyed on site, the materials of different parts of the screening machine are designed in UE4, finally, the materials of the material-free shell and the motor rotating wheel of each part of the screening machine are given, and the 3D model is corresponded to the screening machine. The screening machine in the workshop is corresponded in batches, the light and bulb are made, and the digital twin workshop scene is built;

[0066] The data collected by the IoT is accessed to the digital twin workshop and displayed: the API interface of the open rotating speed of the optical fiber rotating wheel is accessed to complete the post of the optical fiber rotating wheel model rotating at different rotating speeds in the blueprint of the motor optical fiber rotating wheel of the screening machine and the screening, so that the rotating speed API of the different screening machines is corresponded to the screening machine blueprint, the optical fiber rotating wheel is set as a rotating body according to the blueprint, the screened value is given to the rotating body, and the screening machine has a corresponding direction of rotation in space; similarly, the motor rotating speed API and the screening machine motor health status API of each different screening machine are given to the UI blueprint, the corresponding required data is screened according to the designed UI diagram, the state of the data is judged in the blueprint according to the demand, the blueprint event loop is designed to keep the data in the latest state, the data is refreshed in real time, the single data API index of the historical data is designed, the completed 3D model modeling is combined with the UI page, the 3D view is set in the blueprint, and the UI page is displayed at the same time, and the whole digital twin workshop is built;

[0067] The result calculated by the AI algorithm is displayed in the digital twin workshop: different colors and materials are displayed under different health states of the screening machine according to the preset health states of the screening machine, the API of the screening machine health state is given to the screening machine blueprint, the health state of the device is judged in a loop, and it is ensured that the screening machine motor rotating wheel can reflect the health state of the screening machine in real time according to the color and material (such as normal real scene material for normal screening machine, yellow for non-standard operator, red for abnormal screening machine motor, etc.), and the related API is also given to the UI page to display the health state of the screening machine synchronously, and the two are combined to display intuitively.

[0068] A screening machine health monitoring system based on digital twinning includes:

[0069] A modeling module is configured to build a 3D digital twin workshop corresponding to a real workshop, and a 3D screening machine model in the 3D digital twin workshop corresponds to a screening machine in batch;

[0070] A data acquisition module is configured to acquire real-time parameters of a motor of each screening machine;

[0071] A data processing module is configured to process the correlation parameters to obtain processed data.

[0072] A health state judging module is configured to judge, based on the processed data, health states of all the screening machines as normal or abnormal.

[0073] A display module is configured to display the health states of the screening machines on corresponding 3D screening machine models by different colors.

[0074] An electronic device includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete communication with each other through the communication bus.

[0075] The memory is configured to store a computer program.

[0076] The processor is configured to execute the program stored in the memory to implement the screening machine health monitoring method based on digital twinning.

[0077] The communication bus can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0078] The communication interface is configured to complete communication between the electronic device and other devices.

[0079] The memory can include a random access memory (RAM) and can also include a non-volatile memory, such as at least one disk memory. Optionally, the memory can also be at least one storage device located away from the processor.

[0080] The processor described above can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0081] A computer readable storage medium, having stored thereon a computer program, the computer program being executed by a processor to implement a screening machine health monitoring method based on digital twinning.

[0082] The computer readable storage medium can be included in the device / apparatus described in the above embodiments; or can exist separately and not be assembled into the device / apparatus. The computer readable storage medium carries one or more programs, which, when executed, implement the molecular level reaction kinetics model construction method according to the embodiments of the present disclosure.

[0083] According to embodiments of the present disclosure, the computer readable storage medium can be a non-volatile computer readable storage medium, which can include, but is not limited to, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any appropriate combination thereof. In the present disclosure, the computer readable storage medium can be any tangible medium that contains or stores a program, which can be used by or in connection with an instruction execution system, apparatus or device.

[0084] The above described embodiments only express several implementation manners of the present application, which are described in a more specific and detailed manner, but should not be understood as a limitation on the scope of the present application. It should be noted that, for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the protection scope of the present application.

Claims

1. A health monitoring method for screening machines based on digital twins, characterized in that, Includes the following steps: Construct a 3D digital twin workshop that corresponds to the real workshop, and the 3D screening machine model in the 3D digital twin workshop corresponds to the batch of screening machines; Real-time collection of relevant parameters of all screening machine motors, processing of relevant parameters to obtain processed data, and determination of the health status of all screening machines as normal or abnormal based on the processed data; The health status of the screening machine is displayed on the corresponding 3D screening machine model using different colors to achieve health monitoring of the screening machine; The specific process of constructing a 3D digital twin workshop corresponding to the real workshop, and the correspondence between the 3D screening machine model and the screening machine batch within the 3D digital twin workshop, is as follows: Based on the original design drawings of the screening machine, a material-free model of the screening machine was created to obtain the material-free screening machine model. Collect real material data of the screening machine, and assign materials to each part of the unmaterialized screening machine model based on the real material data to obtain a 3D screening machine model; The lighting parameters of the real workshop were collected to produce lighting and light bulbs, resulting in a 3D digital twin workshop corresponding to the real workshop. The relevant parameters of the motors of all screening machines are collected in real time, and the parameters are processed to obtain processed data. Based on the processed data, the health status of all screening machines is determined to be normal or abnormal. The specific process is as follows: Real-time collection of relevant parameters of all motors in the screening machines, including motor speed data and acceleration data; A curve table is generated based on the rotational speed data and acceleration data; Based on the rotational speed data, acceleration data, and corresponding curves, calculate the formula corresponding to the curves: y = Asin(Bx + C) + D; Where y is acceleration, x is time, and A, B, and C are all constants; Based on the above formula, the amplitude of the curve is calculated to be A, and the period is T = 2π / B. The motor speed N follows the following relationship with respect to the amplitude A: N1=f*A 1 / 2 ; Where N1 is the first speed of the motor, f is a fixed constant, and A is the amplitude; The period T follows the following relationship: N2=g*T -2 ; Where N2 is the second speed of the motor, g is a fixed constant, and T is the period; Determine whether the difference between the first rotational speed N1 and the second rotational speed N2 is within 5%. If so, set the average value of N1 and N2 as the calculated rotational speed N. If not, determine that the health status of the screening machine is abnormal. Determine if the difference between the rotational speed N and the rotational speed data is within 5%. If not, the screening machine is considered to be in an abnormal health condition. If yes, determine if the rotational speed N exceeds the maximum motor speed. If yes, the screening machine is considered to be in an abnormal health condition. If no, the screening machine is considered to be in a normal health condition.

2. The health monitoring method for screening machines based on digital twins according to claim 1, characterized in that, Based on the original design drawings of the screening machine, a material-free model of the screening machine was created, resulting in a material-free screening machine model. The specific process is as follows: Based on the original design drawings of the screening machine, the shell of the screening machine and the rotating fiber optic wheel inside the screening machine were modeled without materials using UE4 software, and the fiber optic wheel was set as a rotating body to obtain the model of the screening machine without materials.

3. The health monitoring method for screening machines based on digital twins according to claim 1, characterized in that, The screening machine is equipped with sensors and a PLC controller. The sensors are used to collect relevant parameters of the motor of the screening machine in real time; the PLC controller is used to control the speed of the motor and transmit the relevant parameters to the AIoT platform for storage.

4. The health monitoring method for screening machines based on digital twins according to claim 1, characterized in that, The causes of abnormal health status of the screening machine include improper operation, motor failure, and abnormal motor speed control by the PLC. When the difference between the first rotational speed N1 and the second rotational speed N2 is not within 5%, the reason for the abnormal health status of the screening machine is that the motor has malfunctioned. When the difference between the rotational speed N and the rotational speed data is not within 5%, the reason for the abnormal health status of the screening machine is that the PLC control of the motor speed is abnormal. When the rotational speed N exceeds the maximum motor speed, the abnormal health status of the screening machine is due to motor failure or improper operation.

5. The health monitoring method for screening machines based on digital twins according to claim 4, characterized in that, The health status of the screening machine is displayed on the corresponding 3D screening machine model using different colors. The specific process is as follows: The screening machine is assigned different colors according to four preset health statuses: normal health status is the original color, improper operation is yellow, motor malfunction is red, and abnormal motor speed controlled by PLC is blue. The different colored health statuses of the screening machine are assigned to the corresponding 3D screening machine model in the 3D digital twin workshop through the API interface, and the health status of the screening machine is displayed synchronously.

6. A screening machine health monitoring system based on digital twins, characterized in that, include: The modeling module is used to construct a 3D digital twin workshop that corresponds to the real workshop, and the 3D screening machine model in the 3D digital twin workshop corresponds to the screening machine batch. The data acquisition module is used to collect relevant parameters of all motors of the screening machine in real time; The data processing module is used to process the relevant parameters to obtain processed data; The health status judgment module is used to determine whether the health status of all the screening machines is normal or abnormal based on the processed data. The display module is used to display the health status of the screening machine on the corresponding 3D screening machine model using different colors; The specific process of constructing a 3D digital twin workshop corresponding to the real workshop, and the correspondence between the 3D screening machine model and the screening machine batch in the 3D digital twin workshop, is as follows: Based on the original design drawings of the screening machine, a material-free model of the screening machine is created to obtain a material-free screening machine model. Collect the actual material data of the screening machine, and assign materials to each part of the materialless screening machine model based on the actual material data to obtain a 3D screening machine model; The lighting parameters of the real workshop were collected to produce lighting and light bulbs, resulting in a 3D digital twin workshop corresponding to the real workshop. The relevant parameters of all the motors of the screening machines are collected in real time, and the relevant parameters are processed to obtain processed data. Based on the processed data, the health status of all the screening machines is determined to be normal or abnormal. The specific process is as follows: Real-time acquisition of all relevant parameters of the motors of the screening machine, including motor speed data and acceleration data; A curve table is generated based on the rotational speed data and the acceleration data; Based on the rotational speed data, the acceleration data, and the corresponding curve table, the expression formula corresponding to the curve table is calculated: y = Asin(Bx + C) + D; Where y is acceleration, x is time, and A, B, and C are all constants; Based on the above formula, the amplitude of the curve is calculated to be A, and the period is T = 2π / B. The motor speed N follows the following relationship with respect to the amplitude A: N1=f*A 1 / 2 ; Where N1 is the first speed of the motor, f is a fixed constant, and A is the amplitude; The period T follows the following relationship: N2=g*T -2 ; Where N2 is the second speed of the motor, g is a fixed constant, and T is the period; Determine whether the difference between the first rotational speed N1 and the second rotational speed N2 is within 5%. If so, set the average value of N1 and N2 as the calculated rotational speed N. If not, determine that the health status of the screening machine is abnormal. Determine whether the difference between the rotational speed N and the rotational speed data is within 5%. If not, the health status of the screening machine is determined to be abnormal. If yes, determine whether the rotational speed N exceeds the maximum value of the motor speed. If yes, the health status of the screening machine is determined to be abnormal. If no, the health status of the screening machine is determined to be normal.

7. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in a memory, it implements the screening machine health monitoring method based on digital twins as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the screening machine health monitoring method based on digital twin as described in any one of claims 1-5.

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