A dynamic evaluation method for industrial screening effect based on digital twin

Abstract

The present invention relates to a dynamic evaluation method for industrial screening effect based on digital twin, which belongs to the field of mineral screening technology and solves the problem that the existing technology cannot dynamically observe and evaluate the industrial screening effect online. The evaluation method includes: step 1, collecting the structural parameters, material parameters, particle group classification parameters, screening process load parameters and equipment operation surrounding environment information of the screening machine; step 2, establishing a three-dimensional structural model of the screening machine; step 3, establishing a digital twin simulation model of the screening machine; step 4, correcting the digital twin simulation model of the screening machine; step 5, building a cloud database based on the corrected digital twin simulation model of the screening machine, and obtaining the real-time operating status of the equipment through the terminal device; step 6, based on the obtained real-time operating status of the equipment, the screening effect is evaluated in real time. The present invention can collect the working parameters of the screening machine during the screening process in real time, and realize the real-time detection of the screening machine structure, operating status, fault warning and screening results.

Description

Technical Field

[0001] The present invention relates to the field of screening technology, and in particular to a dynamic evaluation method for industrial screening effects based on digital twins. Background Art

[0002] Screening is a separation technology that allows bulk mixed materials of different particle sizes to pass through the sieve holes and be divided into materials of different particle size ranges according to their particle size. Industrial screening refers to the large-scale screening of continuously produced materials as a key link in the industrial production process during the mining and processing of factories or mines.

[0003] Traditional screening effect evaluation mainly focuses on static sampling and evaluation of screening effects for materials undergoing a single screening operation. For industrial screening, in the continuous production process, the traditional screening effect evaluation system can only perform random sampling and evaluation, and cannot achieve real-time online accurate measurement; at the same time, the operating conditions of the screening machine are extremely complex, and the traditional screening effect evaluation system has poor timeliness and cannot reflect the operating conditions of the screening machine in real time. Summary of the invention

[0004] In view of the above analysis, the present invention aims to provide a dynamic evaluation method for industrial screening effects based on digital twins, so as to solve the technical problem that the existing technology cannot perform real-time evaluation of industrial screening effects.

[0005] The purpose of the present invention is mainly achieved through the following technical solutions:

[0006] The present invention provides a dynamic evaluation method for industrial screening effect based on digital twin, and the evaluation method comprises the following steps: step 1, collecting screening machine structure parameters, material parameters, particle group classification parameters, screening process load parameters and equipment operation surrounding environment information;

[0007] Step 2: establishing a three-dimensional structural model of the sieve machine according to the sieve machine structural parameters, material parameters and particle group classification parameters collected in step 1;

[0008] Step 3: obtaining a digital twin simulation model of the screen machine based on the established three-dimensional structural model of the screen machine;

[0009] Step 4: Correcting the digital twin simulation model of the screen machine according to the virtual test data and actual production data of the digital twin simulation model of the screen machine;

[0010] Step 5: Build a cloud database based on the revised digital twin simulation model of the screening machine, and obtain the real-time operating status of the equipment through the terminal device;

[0011] Step 6: Based on the acquired real-time operating status of the equipment, the screening effect is evaluated in real time.

[0012] Furthermore, the above step 3 includes: meshing the established three-dimensional structural model of the screen machine, calculating the multiple small units divided into meshes, selecting the corresponding interpolation algorithm for synthesis, and using the terminal device to control the motion state of the screen machine according to the collected acceleration information to achieve consistency with the actual operation, thereby obtaining the overall structural characteristics of the screen machine, monitoring the key components of the screen machine and overload warning, and finally obtaining a digital twin simulation model;

[0013] Furthermore, in step 4, the virtual test data includes stress and strain information of the screen structure, speed and temperature change information of the motor, acceleration information of key parts of the screen, and process parameter information of the material;

[0014] Collect virtual test data of the digital twin simulation model of the screening machine under working conditions in real time, compare the collected virtual test data with the test data collected in actual production at the same time, and correct the digital twin simulation model to accurately reflect the actual industrial screening process.

[0015] Furthermore, in step 2, the process of establishing the three-dimensional structural model of the screening machine includes:

[0016] Upload the collected screening machine structural parameters to the same industrial computer for processing and analysis;

[0017] Add the material parameters and particle group classification parameters processed and analyzed by the above industrial computer, as well as the screening process load parameters and equipment operation surrounding environment information;

[0018] By running the visualization platform, a three-dimensional structural model of the screening machine is obtained.

[0019] Further, in step 6, the real-time evaluation includes evaluation of screening efficiency, processing capacity, mismatch content, upper limit rate, and lower limit rate;

[0020] While conducting real-time evaluation, the operating conditions of the screen machine are tested and collected in real time, and the vibration parameters of the screen machine are regulated through the digital terminal.

[0021] Furthermore, the method also includes: monitoring the screening machine and issuing overload warnings when evaluating the screening effect in real time; issuing warnings and reports when abnormalities occur, and shutting down the actual production screening machine for maintenance in a timely manner.

[0022] Furthermore, in the above step 1, the structural parameters of the screen machine include the structural dimensions, stress strain, acceleration, motor speed and temperature change parameters of the screen machine itself;

[0023] Material parameters include density, elastic modulus, Poisson’s ratio, hardness, tensile strength, and yield strength;

[0024] Particle group component parameters: particle size composition, particle shape, ash content and moisture content.

[0025] Furthermore, in step 1, the load parameter of the screening process refers to the impact of material particles on the screen surface; the equipment operation surrounding environment information includes temperature and humidity information around the equipment.

[0026] Furthermore, in step 1, the process of collecting the structural parameters of the screening machine includes:

[0027] A stress strain sensor and a first acceleration sensor are respectively arranged on the screen frame and the exciting beam of the screen machine to collect the stress strain and acceleration of the screen machine;

[0028] A temperature sensor and a speed sensor are set on the vibration motor to monitor the speed and temperature changes of the vibration motor;

[0029] Along the moving direction of the screened material, multiple groups of second acceleration sensors are arranged on the screen surface in sequence to collect the acceleration information of the screen surface during the screening process.

[0030] Furthermore, in step 1, the process of collecting the particle group component parameters includes: respectively setting a visual sensor and an X-ray at the periphery of the feed end and the discharge end of the screen machine; at the feed end of the screen machine, the corresponding visual sensor is used to collect the particle size composition and particle size of the feed material, and the corresponding X-ray is used to collect the ash content and moisture content of the feed material;

[0031] At the discharging end of the screening machine, the corresponding visual sensor is used to collect the particle size composition and particle shape of the discharging material, and the corresponding X-ray is used to collect the ash content and moisture content of the discharging material.

[0032] Compared with the prior art, the present invention can achieve at least one of the following beneficial effects:

[0033] (1) The method for dynamic evaluation of industrial screening effects based on digital twins provided by the present invention can perform real-time dynamic evaluation of the screening effects of large-scale industrial screening processes of materials, and at the same time perform real-time detection of the operating conditions of the screening machine. It is suitable for screening effect evaluation in industrial production processes such as mining and processing processes, sand and gravel aggregate preparation processes, and industrial solid waste disposal.

[0034] (2) The method for dynamic evaluation of industrial screening effects based on digital twins provided by the present invention has the following advantages over the existing evaluation systems: by establishing a digital twin simulation model to simulate the industrial screening process, real-time dynamic evaluation of the industrial screening effect can be achieved; at the same time, based on the real-time collected screening machine operating parameters during the screening process, real-time detection of the reliability of the screening machine structure can be achieved; the present invention can effectively solve the problem that the existing technology cannot perform real-time dynamic evaluation of industrial screening effects.

[0035] (3) The dynamic evaluation method of industrial screening effect based on digital twin provided by the present invention has the characteristics of real-time, accuracy and high matching degree; Regarding real-time: the system of the present invention can realize real-time evaluation; while the traditional screening evaluation takes representative samples of the equipment running at a certain moment in industrial production, and evaluates the screening effect based on the samples taken, which has a certain delay and cannot achieve real-time sampling. Regarding accuracy: the present invention can fully analyze and evaluate the screening effect of a certain cross-section or a certain section of the material above the screen surface, which is more accurate than traditional random sampling. Regarding matching degree: the screening effect result obtained by the present invention is consistent with the current working condition of the screening machine, and has a good matching degree, which is convenient for feedback adjustment of the running equipment according to the screening effect evaluation result. Based on the above two points, the traditional screening evaluation cannot have the good matching degree between the evaluation result of the present invention and the working condition.

[0036] In the present invention, the above-mentioned technical solutions can also be combined with each other to achieve more preferred combination solutions. Other features and advantages of the present invention will be described in the subsequent description, and some advantages can become obvious from the description, or can be understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained through the contents particularly pointed out in the embodiments of the description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The drawings are only for the purpose of illustrating particular embodiments and are not to be considered limiting of the present invention. Like reference symbols denote like components throughout the drawings.

[0038] Figure 1 It is a process flow chart of the material screening effect dynamic evaluation method based on digital twin of the present invention;

[0039] Figure 2 This is a flow chart of the material screening effect dynamic evaluation system based on digital twin of the present invention. DETAILED DESCRIPTION

[0040] The preferred embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings, wherein the accompanying drawings constitute a part of the present invention and are used together with the embodiments of the present invention to illustrate the principles of the present invention, but are not used to limit the scope of the present invention.

[0041] Digital twin refers to making full use of data such as physical models, sensor updates, and operation history to build a simulation process and complete mapping in virtual space, thereby reflecting the entire life cycle of the corresponding physical equipment. Traditional screening effect evaluation mainly conducts static sampling to evaluate the screening effect of materials undergoing a single screening operation. For industrial screening, in the continuous production process, the traditional screening effect evaluation system can only perform random sampling evaluation and cannot achieve real-time online precise measurement; at the same time, the operating conditions of the screening machine are extremely complex, and the traditional screening effect evaluation system has poor timeliness and cannot reflect the operating conditions of the screening machine in real time. Therefore, it is of great significance to develop a dynamic evaluation method for industrial screening effects based on digital twins.

[0042] The present invention provides a method for dynamic evaluation of industrial screening effect based on digital twins. Figure 1 , the method comprises the following steps:

[0043] Step 1: Collect the screen machine structure parameters, material parameters, particle group classification parameters, screening process load parameters and equipment operation surrounding environment information;

[0044] Step 2: Establish a digital twin simulation model using the sieve machine structure parameters, material parameters and particle group classification parameters;

[0045] Step 3: obtaining a digital twin simulation model of the screen machine based on the established three-dimensional structural model of the screen machine;

[0046] Step 4: correcting the digital twin simulation model of the screening machine according to the virtual test data and actual production data of the digital twin simulation model of the screening machine;

[0047] Step 5: Build a cloud database based on the revised digital twin simulation model of the screening machine, and obtain the real-time operating status of the equipment through the terminal device;

[0048] Step 6: Based on the acquired real-time operating status of the equipment, the screening effect is evaluated in real time.

[0049] Compared with the prior art, the dynamic evaluation method of industrial screening effects based on digital twins provided by the present invention can perform real-time dynamic evaluation of the screening effects of large-scale industrial screening processes of materials, and perform real-time detection of the operating conditions of the screening machine. It is suitable for screening effect evaluation in industrial production processes such as mining and processing processes, sand and gravel aggregate preparation processes, and industrial solid waste disposal.

[0050] Specifically, in the above step 1, the screen machine structural parameters include the screen machine's own structural dimensions, stress and strain, acceleration, motor speed and temperature change. Material parameters are the inherent properties of various structures, including density, elastic modulus, Poisson's ratio, hardness, tensile strength, and yield strength. Particle group component parameters: particle size composition, particle shape, ash content and moisture content.

[0051] It should be noted that in the above step 1, the material parameters do not need to be obtained by testing, but can be obtained through standard query.

[0052] In the above step 1, the process of collecting the structural parameters of the screen machine includes: respectively setting a stress strain sensor and a first acceleration sensor on the screen frame and the exciting beam of the screen machine to collect the stress strain and acceleration of the screen machine; setting a temperature sensor and a speed sensor on the exciting motor to monitor the speed and temperature changes of the exciting motor; arranging multiple groups of second acceleration sensors on the screen surface in sequence along the movement direction of the screened material to collect the acceleration information of the screen surface during the screening process.

[0053] In the above step 1, the process of collecting the particle group component parameters includes: setting visual sensors and X-rays at the periphery of the feed end and the discharge end of the screening machine respectively; at the feed end of the screening machine, the corresponding visual sensor is used to collect the particle size composition and particle shape of the feed material, and the corresponding X-ray is used to collect the ash content and moisture content of the feed material; at the discharge end of the screening machine, the corresponding visual sensor is used to collect the particle size composition and particle size of the discharge material, and the corresponding X-ray is used to collect the ash content and moisture content of the discharge material.

[0054] It should be noted that, in the above step 1, the load parameter of the screening process refers to the impact of material particles on the screen surface; the equipment operation surrounding environment information includes the temperature and humidity information around the equipment.

[0055] In the above step 2, the specific establishment process of the digital twin simulation model is: establish a three-dimensional structural model of the screen machine according to the screen machine structural parameters collected in step 1, and the establishment process includes: uploading the collected screen machine structural parameters to the same industrial computer for processing and analysis. The purpose of processing and analysis is: because the collected signal is a digital signal, it must be processed and analyzed to obtain the corresponding physical information, including a series of parameters such as acceleration vibration frequency, and these parameters are fed back to the user from the twin model. Add the material parameters and particle group classification parameters processed and analyzed by the above industrial computer, as well as the screening process load parameters and equipment operation surrounding environment information; run through the visualization platform.

[0056] At the same time, the established three-dimensional structural model of the screen machine is gridded, and the multiple small units are calculated. The corresponding interpolation algorithm is selected for synthesis, and the terminal equipment is used to control the motion state of the screen machine according to the collected acceleration information to achieve consistency with the actual operation, and then obtain the overall structural characteristics of the screen machine (referring to the real-time structural parameters of the screen machine, such as stress and strain, acceleration, speed and temperature changes, etc.), so as to facilitate the monitoring and overload warning of the key components of the screen machine (including the screen surface, side plates and excitation beams), and then obtain the digital twin simulation model.

[0057] It should be noted that the above step 3 includes: meshing the established three-dimensional structural model of the screen machine, calculating the multiple small units divided into it, selecting the corresponding interpolation algorithm for synthesis, and using the terminal device to control the motion state of the screen machine according to the collected acceleration information to achieve consistency with the actual operation, thereby obtaining the overall structural characteristics of the screen machine, monitoring the key components of the screen machine and overload warning, and finally obtaining a digital twin simulation model. Among them, the specific control process is: in order to make the digital twin simulation model consistent with the actual screen machine operating parameters, the physical information obtained by the collection and analysis needs to be displayed on the digital twin simulation model of the screen machine in a simulated manner.

[0058] In the above step 3, the specific process of correcting the digital twin simulation model is: under certain working conditions, the digital twin simulation model established in step 2 is used to collect t i The virtual test data at time t includes the stress and strain information of the screen structure, the speed and temperature change information of the motor, the acceleration information of the key parts of the screen (including the screen surface, side plates and exciting beams), and the particle group component parameter information (including particle size composition, particle shape, ash content and moisture content); i At time, the virtual test data collected by the digital twin simulation model and t i The test data collected in the actual production corresponding to the moment is compared for multiple repeatability to judge its credibility; when its credibility does not meet the requirements, the screen machine structure parameters entered in step 2 are modified to realize the correction of the digital twin simulation model of the screen machine, and the process is repeated to continuously correct the digital twin simulation model until it can accurately reflect the actual industrial screening process.

[0059] It should be noted that when modifying the digital twin simulation model of the screen machine, the modification is made directly in the source file of the input parameters. The basis for the modification is t i The data actually measured at a moment needs to be measured multiple times during the correction process, where i is the moment number. In addition, the structural parameters (screen machine's own structural dimensions, stress and strain, acceleration, motor speed and temperature change) are all obtained through testing with corresponding measuring equipment.

[0060] In the above step 4, the virtual test data includes stress and strain information of the screen machine structure, speed and temperature change information of the motor, acceleration information of key parts of the screen machine and process parameter information of the material; the virtual test data of the digital twin simulation model of the screen machine under working conditions is collected in real time, and the collected virtual test data is compared with the test data collected in actual production at the same time, and the digital twin simulation model is corrected to accurately reflect the actual industrial screening process.

[0061] In the above step 5, a cloud database is constructed based on the revised digital twin simulation model of the screen machine, and a cloud platform is built. Users can obtain the real-time operation status of the equipment through terminal devices such as computers and mobile phones; at the same time, the digital twin simulation model of the screen machine is used to evaluate the screening effect in real time, including the evaluation of screening efficiency, processing capacity, mismatch content, upper limit rate, and lower limit rate. At the same time, the operating conditions of the screen machine are tested and collected in real time, and the vibration parameters of the screen machine can be adjusted through the digital terminal.

[0062] In the above step 6, the screening effect includes screening efficiency, processing capacity, mismatch content, upper limit rate, and lower limit rate indicators. When the screening effect is evaluated in real time, the screening machine is monitored and overload warning is given; when an abnormality occurs, a warning and report are given, and the actual production screening machine is shut down for maintenance in a timely manner.

[0063] When evaluating screening efficiency, the evaluation calculation formula for specific indicators is as follows:

[0064] Upper limit rate U c , lower limit rate U f Calculation:

[0065] U c =1-O f (1)

[0066] U f =1-O c (2)

[0067] Among them, U c Indicates the upper limit rate (%), U f Indicates the lower limit rate (%), O f Indicates the ratio of fine particles in the undersize product (%), O c It indicates the ratio (%) of coarse particles in the oversize product.

[0068] Calculation of screening efficiency η:

[0069]

[0070]

[0071] η=E c +E f -100 (5)

[0072] Where, η represents the screening efficiency (%), E c Indicates the proportion of coarse particles (%), E f represents the normal distribution ratio of fine particles (%), γ o represents the yield of the product on the sieve (%), γ u represents the yield of the undersize product (%), M cIndicates the ratio of coarse particles in the undersize product to the input material (%), M f It indicates the ratio of fine particles in the oversize product to the input material (%); The proportion of fine particles in the screen feed (%); The proportion of coarse particles in the screen feed (%).

[0073] Total mismatch content M t Calculation:

[0074] M c =100γ u U c (6)

[0075] M f =100γ o O f (7)

[0076] M t =M c +M f (8)

[0077] M t Indicates the content of total mismatch (%), M c Indicates the ratio of coarse particles in the undersize product to the input material (%), M f Indicates the ratio of fine particles in the oversize product to the input material (%), γ u It represents the yield of the product under the sieve (%), U c Indicates the upper limit rate (%), O f Indicates the ratio of fine particles in the undersize product (%), γ o It indicates the yield (%) of the product on the sieve.

[0078] Calculation of processing capacity Q:

[0079] Q=q×S (9)

[0080] Q represents the processing capacity (t / h), q represents the processing capacity per unit area (t / (h·m 2 )), S represents the screening area (m 2 ).

[0081] It should be emphasized that the screening performance of the equipment is evaluated by obtaining data on screening efficiency, processing capacity, mismatch content, upper limit rate and lower limit rate through the above-mentioned indicator calculation formula, mainly based on whether the particle size and output (processing capacity) of the screening products meet the needs of industrial production; if there is a large deviation from the production demand (depending on the situation, there is no unified standard), the equipment parameters and material parameters can be adjusted to meet the needs of industrial production, and the digital twin simulation model can be modified according to the adjusted parameters.

[0082] It should be noted that the industrial screening effect dynamic evaluation method of the present invention also includes:

[0083] It should be noted that when monitoring and overload warning of the screen machine, the operating parameters of the vibrating screen need to be monitored and warned. The specific process is as follows:

[0084] (i) Under a certain working condition, the time is defined as t0, and the stress and strain, acceleration, rotation speed and temperature of the screen machine at time t0 and the acceleration information of the screen surface are first collected.

[0085] (ii) The stress-strain, acceleration, rotation speed, temperature and acceleration information of the screen surface corresponding to time t0 are compared with the data range of the cloud database established earlier to determine whether they exceed the range of ±5%.

[0086] (iii) If the value exceeds the range of ±5%, it indicates that the vibrating screen may have a fault, which is promptly fed back to the actual screen operation process, and then the actual production screen is shut down for maintenance.

[0087] In the above step 5, when monitoring and warning of overload of materials, it is necessary to monitor and warn of material parameters, and the specific process is as follows:

[0088] (i) Collect the particle size composition, particle shape, ash content and moisture content of the input coal, and the particle size composition of the oversize product and undersize product at the discharge end.

[0089] (ii) Based on the particle size composition of the three materials at the feed end, the oversize discharge end and the undersize discharge end, and the processing capacity of the equipment itself, the yield of the oversize product and the undersize product, as well as the yield of materials of different particle sizes, is obtained.

[0090] (iii) Calculate the screening efficiency (comprehensive separation index), mismatch content, upper limit rate, and lower limit rate of the equipment.

[0091] Compared with the prior art, the method for dynamic evaluation of industrial screening effects based on digital twins provided by the present invention also has the following advantages: the industrial screening process is simulated by a digital twin simulation model to realize real-time dynamic evaluation of the industrial screening effect; at the same time, according to the working parameters of the screening machine collected in real time during the screening process, real-time detection of the reliability of the screening machine structure is realized; the present invention can effectively solve the problem that the prior art cannot perform real-time dynamic evaluation of the industrial screening effect.

[0092] On the other hand, Figure 2 As shown, the present invention also provides a dynamic evaluation system for industrial screening effect based on digital twins, such as Figure 1As shown, the evaluation system includes a connected digital twin simulation unit and a screening effect real-time evaluation unit; the digital twin simulation unit is used to simulate the actual industrial screening process, and compare the virtual test data obtained with the actual industrial screening data, so as to reflect the actual industrial screening process; the screening effect real-time evaluation unit is used to evaluate the screening efficiency, processing capacity, mismatch content, upper limit rate, and lower limit rate; the screening effect real-time evaluation unit conducts real-time test and collection of the screening machine operating conditions while conducting real-time evaluation, and adjusts the vibration parameters of the screening machine through the digital twin simulation unit.

[0093] The evaluation system of the present invention also includes a data acquisition unit, which is connected to the digital twin simulation unit; the parameter acquisition unit is used to collect screening machine structural parameters, material parameters, particle group classification parameters, screening process load parameters and equipment operation surrounding environment information.

[0094] It needs to be explained that the structural parameters of the screen machine include the screen machine's own structural dimensions, stress and strain, acceleration, motor speed and temperature change parameters; the material parameters include density, elastic modulus, Poisson's ratio, hardness, tensile strength and yield strength; the particle group component parameters include particle size composition, particle shape, ash content and moisture content.

[0095] It should be noted that the load parameter of the screening process refers to the impact of material particles on the screen surface; the ambient environment information of the equipment operation includes the temperature and humidity information around the equipment.

[0096] It should be noted that the digital twin simulation unit includes a digital twin simulation model of a screening machine. The digital twin simulation module is established through the three-dimensional structural model of the screening machine. The establishment process is as follows: the three-dimensional structural model of the screening machine is gridded, and the multiple small units divided are calculated. The corresponding interpolation algorithm is selected for synthesis, and the motion state of the screening machine is controlled according to the collected acceleration information to achieve consistency with the actual operation, thereby obtaining the overall structural characteristics of the screening machine, monitoring the key components of the screening machine and issuing overload warnings, and finally obtaining the digital twin simulation model of the screening machine.

[0097] The process of establishing the three-dimensional structural model of the screening machine is as follows:

[0098] The collected structural parameters of the screening machine are uploaded to the same industrial computer for processing and analysis; the material parameters and particle group classification parameters processed and analyzed by the above industrial computer, as well as the screening process load parameters and the equipment operation surrounding environment information are added; and the three-dimensional structural model of the screening machine is obtained by running it through the visualization platform.

[0099] In order to accurately reflect the actual industrial screening process, the present invention obtains virtual test data from the digital twin simulation model of the screening machine, including stress and strain information of the screening machine structure, speed and temperature change information of the motor, acceleration information of key parts of the screening machine, and process parameter information of the material; collects the virtual test data of the digital twin simulation model of the screening machine under working conditions in real time, and compares the collected virtual test data with the test data collected in actual production at the same time, so as to obtain a revised digital twin simulation model of the screening machine, thereby ensuring that the actual industrial screening process is accurately reflected.

[0100] In order to more conveniently control the operating status of the screening machine, the evaluation system of the present invention further includes a terminal device, and the operating status of the screening machine is displayed through the terminal device.

[0101] It should be noted that the evaluation system of the present invention also includes an early warning unit, which includes a monitor and an audible and visual alarm. When the screening effect is evaluated in real time, the monitor and the audible and visual alarm are used to monitor the screening machine and issue an overload early warning. When an abnormality occurs, an early warning and report are issued, prompting the actual production screening machine to be shut down for maintenance.

[0102] In summary, the industrial screening effect dynamic evaluation system provided by the present invention has the following advantages compared with the existing evaluation systems: the industrial screening process is simulated by the digital twin simulation model of the screening machine to realize real-time dynamic evaluation of the industrial screening effect; at the same time, according to the real-time collected screening machine operating parameters during the screening process, real-time detection of the reliability of the screening machine structure is realized; the present invention can effectively solve the problem that the existing technology cannot perform real-time dynamic evaluation of industrial screening effects.

[0103] Example 1

[0104] Taking a vibrating screen for 6mm coal screening as an example, when the vibrating screen in the model system is running stably, the operating parameters and material parameters of the vibrating screen are collected at any time. The details are as follows:

[0105] For the operating parameters of the vibrating screen, (i) firstly, the stress-strain, acceleration, rotation speed and temperature of the screen machine at time t0 and the acceleration information of the screen surface are collected.

[0106] (ii) The stress-strain, acceleration, rotation speed, temperature and acceleration information of the screen surface corresponding to time t0 are collected and compared with the data range of the cloud database established earlier to determine whether they exceed the range of ±5%.

[0107] (iii) If the value exceeds the range of ±5%, it indicates that the vibrating screen may have a fault, which is promptly fed back to the actual screen operation process, and then the actual production screen is shut down for maintenance.

[0108] For material parameters, (1) the particle size composition, particle shape, ash content, moisture content of the feed coal, and the particle size composition of the oversize product and undersize product at the discharge end are collected. (2) Based on the particle size composition of the three materials at the feed end, the oversize discharge end, and the undersize discharge end, as well as the processing capacity of the equipment itself, the yield of the oversize product and undersize product, and materials of different particle sizes are obtained.

[0109] (3) Calculate the screening efficiency (comprehensive separation index), mismatch content, upper limit rate, lower limit rate and other indicators of the equipment.

[0110] Based on the above results, while conducting real-time evaluation of the operating conditions and screening effects of the screen machine, it is also possible to build a digital twin screening simulation system and control the vibration parameters of the screen machine through digital feedback.

[0111] In summary, the dynamic evaluation method for industrial screening effects based on digital twins provided by the present invention has the characteristics of real-time, accuracy and high matching degree; in terms of real-time, the system of the present invention can realize real-time evaluation; while the traditional screening evaluation takes representative samples of the equipment running at a certain moment in industrial production, and evaluates the screening effect based on the samples taken, which has a certain delay and cannot achieve real-time sampling. In terms of accuracy, the present invention can fully analyze and evaluate the screening effect of a certain cross-section or a certain section of the material above the screen surface, which is more accurate than traditional random sampling. In terms of matching degree, the screening effect result obtained by the present invention is consistent with the current working condition of the screening machine, has a good matching degree, and is convenient for feedback adjustment of the running equipment according to the screening effect evaluation result. Based on the above two points, the traditional screening evaluation cannot have the good matching degree between the evaluation result of the present invention and the working conditions.

[0112] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention.

Claims

1. A dynamic evaluation method for industrial screening effect based on digital twin, characterized in that: The following steps are involved: Step 1: Collect the screen machine structure parameters, material parameters, particle group classification parameters, screening process load parameters and equipment operation surrounding environment information; Step 2: establishing a three-dimensional structural model of the sieve machine according to the sieve machine structural parameters, material parameters and particle group classification parameters collected in step 1; Step 3: obtaining a digital twin simulation model of the screen machine based on the established three-dimensional structural model of the screen machine; Step 4: correcting the digital twin simulation model of the screening machine according to the virtual test data and actual production data of the digital twin simulation model of the screening machine; Step 5: Build a cloud database based on the revised digital twin simulation model of the screening machine, and obtain the real-time operation status through the terminal device; Step 6: Based on the acquired real-time operating status, the screening effect is evaluated in real time; In step 2, the process of establishing the three-dimensional structural model of the screening machine includes: Upload the collected screening machine structural parameters to the same industrial computer for processing and analysis; Add the material parameters and particle group classification parameters processed and analyzed by the above industrial computer, as well as the screening process load parameters and equipment operation surrounding environment information; Through the operation of the visualization platform, the three-dimensional structural model of the screening machine is obtained; The step 3 includes: gridding the established three-dimensional structural model of the screen machine, calculating the multiple small units divided into grids, selecting the corresponding interpolation algorithm for synthesis, and using the terminal device to control the motion state of the screen machine according to the collected acceleration information to achieve consistency with the actual operation, thereby obtaining the overall structural characteristics of the screen machine, monitoring the key components of the screen machine and overload warning, and finally obtaining a digital twin simulation model.

2. The method for dynamic evaluation of industrial screening effect based on digital twin according to claim 1 is characterized in that: In step 4, the virtual test data includes stress and strain information of the screen structure, speed and temperature change information of the motor, acceleration information of key parts of the screen, and process parameter information of the material; The virtual test data of the digital twin simulation model of the screening machine under working conditions is collected in real time, and the collected virtual test data is compared with the test data collected in actual production at the same time, and then the digital twin simulation model is corrected to accurately reflect the actual industrial screening process.

3. The method for dynamic evaluation of industrial screening effect based on digital twin according to claim 1 is characterized in that: In step 6, the real-time evaluation includes evaluation of screening efficiency, processing capacity, mismatch content, upper limit rate, and lower limit rate; While conducting real-time evaluation, the operating conditions of the screen machine are tested and collected in real time, and the vibration parameters of the screen machine are regulated through the digital terminal.

4. The method for dynamic evaluation of industrial screening effect based on digital twin according to claim 1 is characterized in that: The method further comprises: monitoring the screening machine and issuing an overload warning when evaluating the screening effect in real time; issuing a warning and reporting when an abnormality occurs, and shutting down the actual production screening machine for maintenance in a timely manner.

5. The method for dynamic evaluation of industrial screening effect based on digital twin according to claim 1, characterized in that: In the above step 1, the structural parameters of the screen machine include the structural dimensions, stress strain, acceleration, motor speed and temperature change parameters of the screen machine itself; The material parameters include density, elastic modulus, Poisson's ratio, hardness, tensile strength, and yield strength; The particle group component parameters include: particle size composition, particle shape, ash content and moisture content.

6. The method for dynamic evaluation of industrial screening effect based on digital twin according to claim 1 is characterized in that: In step 1, the screening process load parameter refers to the impact of material particles on the screen surface; the equipment operation surrounding environment information includes temperature and humidity information around the equipment.

7. The method for dynamic evaluation of industrial screening effect based on digital twin according to claim 4 is characterized in that: In step 1, the process of collecting the structural parameters of the screening machine includes: A stress strain sensor and a first acceleration sensor are respectively arranged on the screen frame and the exciting beam of the screen machine to collect the stress strain and acceleration of the screen machine; A temperature sensor and a speed sensor are set on the vibration motor to monitor the speed and temperature changes of the vibration motor; Along the moving direction of the screened material, multiple groups of second acceleration sensors are arranged on the screen surface in sequence to collect the acceleration information of the screen surface during the screening process.

8. The method for dynamic evaluation of industrial screening effect based on digital twin according to any one of claims 1 to 7, characterized in that: In step 1, the process of collecting the particle group component parameters includes: Visual sensors and X-rays are respectively installed at the periphery of the feeding end and the discharging end of the screen machine; At the feeding end of the screen, the corresponding visual sensor is used to collect the particle size composition and particle size of the feeding material, and the corresponding X-ray is used to collect the ash content and moisture content of the feeding material; At the discharging end of the screening machine, the corresponding visual sensor is used to collect the particle size composition and particle shape of the discharging material, and the corresponding X-ray is used to collect the ash content and moisture content of the discharging material.

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