Intelligent environmental protection transfer method based on data learning

Abstract

The application discloses an intelligent environmental protection transfer method based on data learning, which comprises detecting material flow passing data, comparing the obtained data with a set model by a background central controller to obtain a conveying capacity and a material accumulation degree; calculating abnormal data and making a nonlinear relationship curve of action strength-action time PLC program instruction; executing a vibration material accumulation removal operation according to the obtained PLC program instruction, and updating the material flow passing data in real time, and the background central controller further optimizes the execution solution; when the material flow passing data returns to normal, the central controller sends a vibration motor shutdown signal and keeps standby. Compared with the prior art, the application matches a vibration motor optimal working instruction program through pre-conveying calculation result data, controls the vibration motor according to the accumulated weight information data, and then can intelligently control the vibration motor to adjust and control, adjusts and controls the working strength and start-stop in real time, and realizes intelligent analysis and solution decision of the material accumulation solution.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of transfer equipment, and particularly relates to an intelligent environmental protection transfer method based on data learning, which is mainly applied to monitoring the actual operation state of a transfer hopper. BACKGROUND

[0002] At present, in the material yard, power plant and corridor conveying engineering, the conventional transfer station equipped with a transfer hopper often causes hopper blockage due to the adhesion and accumulation of bulk materials, thereby leading to insufficient bulk material conveying capacity, causing shutdown maintenance and production stagnation. The use of a vibration motor can effectively eliminate the problems of accumulated materials and blockage, but the stage and degree of bulk material blockage and accumulation are different, the excitation intensity and effective action time are different, and the service life of the long-term working vibration motor cannot be guaranteed and additional failure loss is caused. SUMMARY

[0003] The present application aims to provide an intelligent environmental protection transfer method based on data learning, which has reliable detection accuracy, stable hopper operation, powerful function and long service life.

[0004] The present application discloses an intelligent environmental protection transfer method based on data learning, and the steps are as follows:

[0005] Step a) detecting the material flow passing data, and comparing the obtained data with the set model by the background central control to obtain the conveying capacity and the degree of accumulated materials;

[0006] Step b) combining the data obtained in step a), calculating the abnormal data and making a PLC program instruction of the nonlinear relationship curve of the action intensity-action time;

[0007] Step c) executing the vibration de-accumulation operation according to the PLC program instruction obtained in step b), and updating the material flow passing data in real time, and the background central control further optimizes the execution solution;

[0008] Step d) when the material flow passing data returns to normal, the central control sends a vibration motor shutdown signal and remains standby.

[0009] Preferably, step a) is specifically: detecting the material flow passing data by means of a flow rate sensor and a pressure sensor, transmitting the material flow pattern, passing flow rate and accumulated weight distribution data to the background central control, comparing with the set hopper operation state calculation model operation result, and judging the conveying capacity and the degree of accumulated materials.

[0010] Preferably, step b) is specifically: if the conveying capacity and the degree of accumulated materials are abnormal, combining the detected material flow pattern, passing flow rate and accumulated weight distribution data, and based on the calculation model, the accumulated material solution is obtained by algorithm and the vibration operation instruction program of the vibration motor to achieve the expected effect is simulated and converted.

[0011] Preferably, step c) is specifically: after receiving the PLC control instruction, the vibration motor performs the vibration material accumulation removal operation, the flow rate sensor and the pressure sensor detect the real-time changes in the data due to the material accumulation relief and update the transmission to the central controller database for record analysis, the central controller compares the theoretical excitation instruction parameters, the expected execution effect and the real-time transmission detection data based on the calculation model, further modifies the calculation model and the algorithm parameters, and continuously iterates the calculation, learns and optimizes the execution solution.

[0012] Preferably, step d) is specifically: after the flow rate and pressure measurement data return to the normal parameter range value interval, the central controller releases the vibration motor stop signal according to the detection data, the flow rate and pressure sensor elements continue the state inspection, and the central controller remains in the standby execution state.

[0013] The application also discloses an environmental protection transfer hopper adopting the intelligent environmental protection transfer method based on data learning.

[0014] In particular, a field value-keeping system is further included, the field value-keeping system and the PLC system are connected to a server platform, and the server platform is connected to a background operation system.

[0015] Advantages of the application:

[0016] 1. The field value-keeping system is used to keep the field work of the transfer hopper, the data of the pressure sensor and the flow rate detector are transmitted to the background operation system through the server platform, the analysis module of the background operation system analyzes the field work data, the calculation result data of the pre-structure conveying model are matched with the optimal work instruction program of the vibration motor, the vibration motor is controlled according to the bulk material flow rate and the accumulated weight information data of the bulk material in the hopper, and the vibration motor can be intelligently controlled, the work intensity is real-timely adjusted, and the start-stop is realized.

[0017] 2. The vibration intensity, the start-stop intervention time are automatically modified and corrected according to the flow rate, the excitation intensity, the pressure signal and other execution history data after the vibration execution, the PLC control system has intelligent learning ability, and the solution is adapted and optimized based on the historical data. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is the environmental protection transfer scene simulation diagram provided by the embodiment of the application;

[0019] Figure 2This is a schematic diagram of the environmentally friendly transfer hopper structure provided in an embodiment of the present invention;

[0020] Figure 3 This is a schematic diagram illustrating the working principle of the environmentally friendly transportation method provided in this embodiment of the invention.

[0021] Figure 4 This is a process flow diagram of the environmentally friendly transportation method provided in the embodiments of the present invention. Detailed Implementation

[0022] The technical solution of the present invention will be further described in detail below with reference to specific embodiments. It should be understood that the following embodiments are merely illustrative and explanatory of the present invention, and should not be construed as limiting the scope of protection of the present invention. All technologies implemented based on the above content of the present invention are covered within the scope of protection intended by the present invention.

[0023] Unless otherwise stated, the raw materials and reagents used in the following examples are commercially available products or can be prepared by known methods.

[0024] like Figure 1 The data-driven, learning-based intelligent and environmentally friendly transportation method shown below comprises the following steps:

[0025] Step a) Use flow rate and pressure sensors to detect material flow data, transmit the material flow pattern, flow rate, and accumulated weight distribution data to the central controller in the background, compare the results with the calculation model of the set hopper operating status, and determine the conveying volume and the degree of material accumulation.

[0026] Step b) If the conveying volume and the degree of material accumulation are determined to be abnormal, the material flow pattern, flow velocity and accumulation weight distribution data are combined with the detected material flow pattern, flow velocity and accumulation weight distribution data. Based on the calculation model, the accumulation solution is obtained by algorithm solution and the vibration motor vibration operation instruction program (PLC program instruction to realize the nonlinear relationship curve of action intensity-action time) is simulated and calculated to achieve the expected effect.

[0027] Step c) After receiving the PLC control command, the vibratory motor performs the vibration de-accumulation operation. The data detected by the flow rate sensor and pressure sensor change in real time as the material accumulation is relieved and are updated and transmitted to the central controller database for recording and analysis. The central controller compares the theoretical excitation command parameters and expected execution effect with the real-time transmitted detection data based on the calculation model, further corrects the calculation model and algorithm parameters, and continuously iterates the calculation, learns and optimizes the execution solution.

[0028] Step d) After the flow rate and pressure measurement data return to the normal parameter range, the central controller releases the vibration motor stop signal based on the detection data, the flow rate and pressure sensor components continue to be inspected, and the central controller remains in standby mode.

[0029] An environmental protection transfer hopper using the above-mentioned intelligent environmental protection transfer method based on data learning, comprising a hopper steel structure, a vibration motor and a PLC system connected to the transfer hopper body, the environmental protection transfer hopper is located at a transfer station, the PLC system is used for controlling the working state of the vibration motor attached to the discharge hopper body. In particular, it also includes a field on-duty system, the field on-duty system and the PLC system are connected to a server platform, and the server platform is connected to a background operating system. The unattended is realized.

[0030] The above describes the embodiments of the present application. However, the present application is not limited to the above-mentioned embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. An intelligent environmental protection transfer method based on data learning, characterized in that, It comprises the following steps: Step a) detecting the flow data, the background central controller compares the obtained data with the set model, and the conveying capacity and the accumulation degree are obtained; Step b) combining the data obtained in step a), calculating the abnormal data and making the PLC program instruction of the nonlinear relationship curve of the action strength-action time; Step c) according to the PLC program instruction obtained in step b), executing the vibration and accumulation removal operation, and updating the flow data in real time, and the background central controller further optimizes the execution solution; Step d) when the flow data returns to normal, the central controller sends a vibration motor shutdown signal and keeps standby. 2.The intelligent environment-friendly transfer method based on data learning according to claim 1, wherein, Step a) is: with the help of flow rate sensor and pressure sensor to detect the flow data, the flow pattern, flow rate, and accumulation weight distribution data are transmitted to the background central controller and the set hopper running state calculation model running result comparison, to judge the conveying capacity and the accumulation degree. 3.The intelligent environment-friendly transfer method based on data learning of claim 1, wherein, Step b) is: if the conveying capacity and the accumulation degree are abnormal, combining the detected flow pattern, flow rate, and accumulation weight distribution data, based on the calculation model, the accumulation solution is obtained by algorithm, and the vibration motor vibration operation instruction program to achieve the expected effect is simulated and converted. 4.The intelligent environment-friendly transfer method based on data learning of claim 1, wherein, Step c) is: the vibration motor receives the PLC control instruction and executes the vibration and accumulation removal operation, the flow rate sensor and the pressure sensor detect the real-time change of the data due to the accumulation relief and update the transmission to the central controller database for record analysis, the central controller compares the theoretical excitation instruction parameters and the expected execution effect with the real-time transmission detection data based on the calculation model, further modifies the calculation model and the algorithm parameters, and continuously iterates the calculation, learns and optimizes the execution solution. 5.The intelligent environment-friendly transfer method based on data learning of claim 1, wherein, Step d) is: after the flow rate and pressure measurement data return to the normal parameter range value interval, the central controller releases the vibration motor shutdown signal according to the detection data, the flow rate and pressure sensor continue to be in the state of inspection, and the central controller keeps standby.

6. An environmentally friendly transfer hopper using the data learning-based intelligent environmental protection transfer method of claim 1, comprising a hopper steel structure, a vibration motor, and a PLC system connected to the transfer hopper body, the environmentally friendly transfer hopper is located at a transfer station, and the PLC system is used to control the working state of the vibration motor attached to the discharge hopper body.

7. An environmentally friendly transfer hopper according to claim 6, wherein It also includes a field value system, the field value system and the PLC system are connected to a server platform, the server platform is connected to a background operating system, and the unattended operation of the blockage inspection and solution is realized.

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