Perlite pneumatic conveying system for emulsion explosive production line

Abstract

The present invention relates to the field of perlite transportation and discloses a perlite pneumatic conveying system for an emulsion explosive production line. The system comprises a conveying data acquisition module, a conveying data processing module, a conveying status analysis module, an equipment operation data acquisition module, an equipment operation status analysis module, a conveying safety detection module, a conveying speed adjustment module, and an early warning feedback module. The system detects whether there is a risk of explosion transmission by segmented monitoring, acquisition, and analysis of perlite conveying production data. The system detects whether there is a safety risk of the fan equipment by analyzing the acquired operation data of the fan equipment. Based on the results of conveying analysis and equipment analysis, the system selects conveying monitoring sections with safety risks and separately adjusts the sections. This facilitates segmented monitoring and acquisition of perlite conveying production data, can accurately and early detect safety risks during conveying, and improves the safety and stability of the conveying system.

Description

Technical Field

[0001] The present invention relates to the technical field of perlite transportation, and more particularly to a perlite pneumatic transportation system for an emulsion explosive production line. Background Art

[0002] With the increasing automation and intelligence levels of emulsion explosives production lines, as well as increasingly stringent production safety and environmental protection requirements, traditional perlite conveying methods have gradually exposed some problems. For example, manual conveying is not only inefficient but also poses safety risks; some mechanical conveying methods may be unsuitable for emulsion explosives production lines due to complex equipment and high maintenance costs. Therefore, pneumatic conveying systems have emerged, which usually include key components such as storage tanks, conveying pipelines, and fans. The storage tanks are used to store perlite raw materials, and the conveying pipelines are responsible for transporting the perlite from the storage tanks to the designated location on the production line. Through information technology, remote monitoring and early warning can be achieved.

[0003] However, the above process still has the following disadvantages:

[0004] First, the existing pneumatic conveying system has a relatively simple pipeline monitoring process during the conveying process and lacks segmented monitoring of the conveying pipeline, resulting in inaccurate monitoring of the conveying data in the conveying pipeline, which often leads to errors in the monitoring process;

[0005] Second, the existing wind conveying system lacks specific segmented safety risk analysis from the two aspects of conveying status and fan equipment operation. It is unable to accurately and early detect safety risks during transportation, and lacks automatic segmented adjustment of the conveying speed based on the analysis results of safety risks. It is unable to intelligently improve the safety and stability of the conveying system, resulting in optimization of production efficiency and increased costs. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, the present invention provides a perlite pneumatic conveying system for an emulsion explosive production line to solve the problems existing in the above-mentioned background technology.

[0007] The present invention provides the following technical solution: a perlite pneumatic conveying system for an emulsion explosive production line, comprising:

[0008] Transportation data acquisition module: By dividing the transportation pipeline into several transportation monitoring sections, the perlite transportation production data can be monitored and collected in sections;

[0009] Transportation data processing module: processes the transportation production data of each transportation monitoring section during the perlite transportation process, including pressure processing unit, flow processing unit and temperature processing unit;

[0010] Conveying status analysis module: Based on the processed conveying production data, the conveying status risk analysis module obtains the conveying status risk assessment index to detect whether there is an explosion risk;

[0011] Equipment operation data acquisition module: used for real-time monitoring and collection of fan equipment operation data during perlite transportation;

[0012] Equipment operation status analysis module: By analyzing the operating status data of the fan equipment during the perlite conveying process, the equipment safety risk assessment index is obtained to detect whether there are safety risks during the operation of the fan equipment;

[0013] Transportation safety detection module: used to analyze the results of transportation status risks and equipment operation status risks, calculate the safety detection coefficient, and screen out all transportation monitoring sections with safety risks;

[0014] Conveying speed adjustment module: The conveying speed of the conveying monitoring section with safety risks is individually adjusted through the conveying safety detection coefficient;

[0015] Early warning feedback module: automatically generates a monitoring report based on the monitoring results of the entire transportation monitoring process, and sends the monitoring report to the management personnel terminal.

[0016] Preferably, the specific collection method of the transport data collection module is:

[0017] According to the overall layout of the production line, the conveying pipeline is divided into several conveying monitoring sections. Then, based on the actual conveying requirements of the perlite, the length of each conveying monitoring section is set, and the divided conveying monitoring sections are numbered in sequence according to the order in which the perlite is blown into the pipe, namely 1, 2, 3, ... n. Then, corresponding sensors are installed in each conveying monitoring section to monitor and collect the conveying operation data of each conveying monitoring section in real time. The conveying operation data includes the flow rate, pressure and temperature of the perlite.

[0018] Preferably, the transport data processing module collects the pressure data of each transport monitoring section within a period of time through the pressure processing unit, and processes and analyzes the pressure change data of each transport monitoring section to calculate the pressure fluctuation value. , thereby monitoring the pressure changes of each transmission monitoring section over a period of time, and distinguishing abnormally high-pressure areas from low-pressure areas;

[0019] The flow processing unit collects the perlite gas flow data of each transmission monitoring section within a period of time, processes and analyzes the flow change data of each transmission monitoring section, and calculates the flow stability value , thereby monitoring the fluctuation of the perlite gas blowing flow rate in each transmission monitoring section over a period of time, and detecting whether the flow fluctuation is too large;

[0020] The temperature processing unit collects the temperature data of each transport monitoring section and the external environment temperature data within a period of time, processes and analyzes the temperature data of each transport monitoring section and the external environment temperature data, and calculates the temperature change rate , thereby monitoring the temperature change trend of each conveying monitoring section over a period of time, and detecting whether there are abnormal temperature areas.

[0021] Preferably, the delivery state analysis module is based on the analyzed pressure fluctuation value , flow stability value and the temperature change rate Conduct comprehensive analysis and calculate the transportation status risk assessment index: ,in, represents the transport status risk assessment index of the i-th transport monitoring section, is the weight coefficient, and the specific value is set by the management based on experience;

[0022] By setting a transport status risk threshold , the transport status risk assessment index and transport status risk threshold Comparison is used to determine whether there is an explosion risk in the transport monitoring section; if the transport status risk assessment index Transport status risk threshold , it is considered that there is no explosion risk in the transportation monitoring section, and the transportation status of the transportation monitoring section will continue to be monitored. If the transportation status risk assessment index Transport status risk threshold , it is considered that there is an explosion risk in the transportation monitoring section, and the analysis results of the transportation status are immediately transmitted to the transportation safety detection module.

[0023] Preferably, the equipment operation data acquisition module collects the speed of the fan during operation, the vibration frequency of the fan bearing, the motor winding temperature, the bearing temperature, the cooling medium temperature, the motor current and the power in real time through the speed sensor, vibration sensor, temperature sensor, current sensor and power sensor inside the fan equipment, and uses the programmable logic controller as the core of data acquisition, which is connected to various sensor interfaces to execute the data acquisition program, set a fixed acquisition cycle to automatically collect data, and input the collected equipment operation status data into the computer terminal through the wireless network.

[0024] Preferably, the equipment operation status analysis module pre-processes the collected wind turbine equipment operation status data, wherein the specific operation process of the pre-processing includes: data cleaning, data conversion and data integration, and then comprehensively analyzes the pre-processed wind turbine equipment operation status data and calculates the equipment safety risk assessment index, and monitors the safety risks of the equipment during operation in real time through the equipment safety risk assessment index;

[0025] The specific analysis method of the equipment safety risk assessment index is as follows:

[0026] Step S511: Calculate the deviation ratio of each pre-processed device operating parameter, including the fan speed, fan bearing vibration frequency, motor winding temperature, bearing temperature, cooling medium temperature, motor current and power. The specific calculation formula is: ,in, represents the deviation ratio of the kth device operating parameter, represents the actual measured value of the kth device operating parameter, represents the minimum allowable value of the kth device operating parameter, Indicates the maximum allowable value of the kth device operating parameter;

[0027] Step S512: Perform a comprehensive analysis on the deviation ratio of each device operating parameter and calculate the device safety risk assessment index: ,in, represents the equipment safety risk assessment index of the i-th transmission monitoring section, and K represents the total number of equipment operating parameters collected;

[0028] By setting a device security risk threshold , the equipment security risk assessment index Q and the equipment security risk threshold The comparison is used to determine whether there is a safety risk during the operation of the wind turbine equipment; if the equipment safety risk assessment index Q Device security risk threshold , it is considered that there is no safety risk in the equipment operation status during the perlite transportation process, and the equipment operation status will continue to be monitored. If the equipment safety risk assessment index Q Device security risk threshold , it is considered that there is a safety risk in the operation status of the fan equipment, and the analysis results of the equipment operation status are immediately transmitted to the transportation safety detection module.

[0029] Preferably, the transportation safety detection module is used to receive the analysis results of the transportation status and the analysis results of the equipment operation status. When the analysis results of the transportation risk and the equipment operation risk are received, the module immediately performs a comprehensive analysis and detection on the safety of each transportation monitoring section during the transportation of the perlite, and screens out all transportation monitoring sections with safety risks.

[0030] The specific calculation formula of the safety detection coefficient is: ,in, represents the safety detection coefficient calculated for the i-th transport monitoring section, represents the transport status risk assessment index of the i-th transport monitoring section, represents the equipment safety risk assessment index of the i-th transmission monitoring section, Indicates the transport status risk threshold, represents the device security risk threshold, a represents the proportional constant, and e represents the constant;

[0031] Pass the safety test factor and safety threshold For comparison, if the safety detection factor Safety threshold , it is considered that there is no safety risk problem in the transportation of perlite. If the safety detection coefficient Safety threshold , it is considered that there is a safety risk in the transportation process of perlite, and all monitoring sections detected to have safety risks are screened out and marked.

[0032] Preferably, the conveying speed adjustment module determines the risk level of the monitoring section marked as having safety risks according to the safety detection coefficient value, including low risk, medium risk and high risk, and slightly reduces the conveying speed of the low-risk conveying monitoring section, moderately reduces the conveying speed of the medium-risk conveying monitoring section, and suspends the conveying speed of the high-risk conveying monitoring section; and calculates the new conveying speed according to the risk level to formulate a conveying speed adjustment strategy, the specific calculation formula of which is: ,in, Indicates the new conveying speed of the conveying monitoring section, v indicates the current conveying speed of the conveying monitoring section, represents the adjustment factor, and The specific value is adjusted according to the safety detection coefficient value.

[0033] Preferably, the early warning feedback module automatically generates a monitoring report based on the safety risk monitoring results of the conveying status and equipment operation status of each conveying monitoring section, and issues early warning prompts for the monitoring sections marked with safety risks, thereby prompting management personnel to perform maintenance operations on them. At the same time, the speed reduction adjustment results are displayed to the management personnel terminal in a visual manner.

[0034] The technical effects and advantages of the present invention are as follows:

[0035] The present invention divides the conveying pipeline into several conveying monitoring sections through the conveying data acquisition module to monitor and collect the perlite conveying production data in sections. The conveying production data of each conveying monitoring section in the perlite conveying process is processed and analyzed by the conveying data processing module by the pressure processing unit, the flow processing unit and the temperature processing unit. The various production data in the perlite conveying process can be efficiently processed, which helps to improve the availability and accuracy of the data. The conveying state analysis module performs a conveying state risk analysis on the processed conveying production data to detect whether there is an explosion risk. The equipment operation data acquisition module monitors and collects the fan equipment operation data during perlite conveying in real time to the equipment operation state analysis module to analyze the fan equipment operation state data in the perlite conveying process to detect whether there is a safety risk when the fan equipment is running. The conveying safety detection module analyzes the conveying state risk and the equipment operation state risk. The safety detection coefficient is obtained based on the analysis results, and all transportation monitoring sections with safety risks are screened out. The transportation speed of the transportation monitoring sections with safety risks is adjusted separately through the transportation speed adjustment module. The early warning feedback module automatically generates a monitoring report based on the monitoring results of the entire transportation monitoring process, and sends the monitoring report to the management personnel terminal; by dividing the transportation pipeline into several transportation monitoring sections, the segmented monitoring and collection of perlite transportation production data can be realized, which is conducive to improving the accuracy and pertinence of data collection and monitoring, and providing a solid foundation for subsequent data processing and analysis; by conducting specific segmented safety risk analysis from the two aspects of transportation status and fan equipment operation, the safety risks during transportation can be detected accurately and early, and the transportation speed can be automatically adjusted in segments according to the analysis results of the safety risks, which is conducive to intelligently improving the safety and stability of the transportation system, thereby further improving production efficiency and reducing production costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a system structure diagram of the present invention.

[0037] Figure 2 1 is a diagram of the method steps in this embodiment.

[0038] Figure 3 Schematic diagram of the conveying system structure in this embodiment.

[0039] The numbers in the figure represent: 1. First dust collector; 2. Dust removal system for feeding operation; 3. Feeder; 4. Positive pressure feeding pipe; 5. Air volume detection; 6. Separator; 7. Temporary storage tank; 8. Material level switch; 9. Feeder with falling material flow control; 10. Material guide pipe; 11. Second dust collector; 12. Automatic feeding dust collection system. DETAILED DESCRIPTION

[0040] The technical solutions of the present invention will be described clearly and completely below in conjunction with the accompanying drawings of the present invention. In addition, the forms of the various structures described in the following embodiments are merely examples. The perlite pneumatic conveying system for the emulsion explosive production line involved in the present invention is not limited to the various structures described in the following embodiments. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0041] like Figure 1 The embodiment shown provides a perlite pneumatic conveying system for an emulsion explosive production line, comprising:

[0042] Transportation data acquisition module: By dividing the transportation pipeline into several transportation monitoring sections, the perlite transportation production data can be monitored and collected in sections.

[0043] In this embodiment, the specific collection method of the transport data collection module is:

[0044] According to the overall layout of the production line, the conveying pipeline is divided into several conveying monitoring sections. Then, based on the actual conveying requirements of the perlite, the length of each conveying monitoring section is set, and the divided conveying monitoring sections are numbered in sequence according to the order in which the perlite is blown into the pipe, namely 1, 2, 3, ... n. Then, corresponding sensors are installed in each conveying monitoring section to monitor and collect the conveying operation data of each conveying monitoring section in real time. The conveying operation data includes the flow rate, pressure and temperature of the perlite.

[0045] It should be specifically explained that by analyzing the overall layout of the generation line, including the direction, bends and elevation of the pipeline, the starting point and end point of the conveying pipeline are determined, and the conveying pipeline is divided into several monitoring sections according to the length and layout of the pipeline. The length of each conveying monitoring section is set according to the conveying requirements of the perlite, including flow and pressure, for example, every 50 meters or 100 meters is a monitoring section. Each conveying monitoring section is then numbered according to the order in which the perlite is blown in for easy identification and monitoring, and corresponding sensors, including pressure sensors, flow sensors and temperature sensors, are installed at the starting point and end point of each monitoring section. Before starting data collection, all sensors are calibrated. After calibration, the sensors are started to collect the flow rate, pressure and temperature data of the perlite in each conveying monitoring section in real time, and the collected data is transmitted to the computer terminal via a wireless network.

[0046] Transportation data processing module: It processes the transportation production data of each transportation monitoring section during the perlite transportation process, including pressure processing unit, flow processing unit and temperature processing unit.

[0047] In this embodiment, the transport data processing module collects the pressure data of each transport monitoring section within a period of time through the pressure processing unit, and processes and analyzes the pressure change data of each transport monitoring section to calculate the pressure fluctuation value. , thereby monitoring the pressure changes of each transmission monitoring section over a period of time, and distinguishing abnormally high-pressure areas from low-pressure areas;

[0048] The flow processing unit collects the perlite gas flow data of each transmission monitoring section within a period of time, processes and analyzes the flow change data of each transmission monitoring section, and calculates the flow stability value , thereby monitoring the fluctuation of the perlite gas blowing flow rate in each transmission monitoring section over a period of time, and detecting whether the flow fluctuation is too large;

[0049] The temperature processing unit collects the temperature data of each transport monitoring section and the external environment temperature data within a period of time, processes and analyzes the temperature data of each transport monitoring section and the external environment temperature data, and calculates the temperature change rate , thereby monitoring the temperature change trend of each conveying monitoring section over a period of time, and detecting whether there are abnormal temperature areas.

[0050] It should be noted that the specific calculation formula for the pressure fluctuation value is: ,in, represents the pressure fluctuation value of the i-th transmission monitoring section, represents the pressure value collected at the jth time point of the i-th transport monitoring section, It represents the average pressure value of the i-th transport monitoring section over a period of time, and m represents the number of collection time points within a period of time;

[0051] The specific calculation formula for the flow stability value is: ,in, represents the flow stability value of the i-th transmission monitoring section, represents the gas blowing flow value collected at the jth time point of the i-th transmission monitoring section, Indicates the gas inflow flow rate values collected from 1, 2...m time points;

[0052] The specific analysis method for the temperature difference value is:

[0053] Step 1: The temperature data of each transport monitoring section is collected through the sensors for a period of time. At the same time, the external environment temperature is collected through the smart thermometer ;

[0054] Step 2: Used to calculate the absolute difference between the temperature of a single conveying monitoring section and the external ambient temperature at the same time ;

[0055] Step 3: Further analyze the absolute temperature difference between two adjacent time points in each transport monitoring section and calculate the temperature change rate. ,in, represents the temperature change rate of the i-th transport monitoring section, Indicates the first transmission monitoring section of the i-th The absolute temperature difference at each time point, Indicates the first transmission monitoring section of the i-th The absolute temperature difference at each time point, and Represents two different time points.

[0056] Conveying status analysis module: Based on the processed conveying production data, the conveying status risk analysis module obtains the conveying status risk assessment index, which is used to detect whether there is an explosion risk.

[0057] In this embodiment, the delivery state analysis module is based on the analyzed pressure fluctuation value , flow stability value and the temperature change rate Conduct comprehensive analysis and calculate the transportation status risk assessment index: ,in, represents the transport status risk assessment index of the i-th transport monitoring section, is the weight coefficient, and the specific value is set by the management based on experience;

[0058] By setting a transport status risk threshold , the transport status risk assessment index and transport status risk threshold Comparison is used to determine whether there is an explosion risk in the transport monitoring section; if the transport status risk assessment index Transport status risk threshold , it is considered that there is no explosion risk in the transportation monitoring section, and the transportation status of the transportation monitoring section will continue to be monitored. If the transportation status risk assessment index Transport status risk threshold , it is considered that there is an explosion risk in the transportation monitoring section, and the analysis results of the transportation status are immediately transmitted to the transportation safety detection module.

[0059] Equipment operation data acquisition module: used for real-time monitoring and acquisition of fan equipment operation data during perlite transportation.

[0060] In this embodiment, the equipment operation data acquisition module uses the speed sensor, vibration sensor, temperature sensor, current sensor and power sensor inside the fan equipment to collect the fan speed, fan bearing vibration frequency, motor winding temperature, bearing temperature, cooling medium temperature, motor current and power in real time during operation, and uses the programmable logic controller as the core of data acquisition, connected to various sensor interfaces to execute the data acquisition program, set a fixed acquisition cycle to automatically collect data, and input the collected equipment operation status data into the computer terminal through the wireless network.

[0061] Equipment operation status analysis module: By analyzing the operating status data of the fan equipment during the perlite transportation process, the equipment safety risk assessment index is obtained to detect whether there are safety risks during the operation of the fan equipment.

[0062] In this embodiment, the equipment operation status analysis module pre-processes the collected wind turbine equipment operation status data. The specific operation process of the pre-processing includes: data cleaning, data conversion and data integration. Then, the pre-processed wind turbine equipment operation status data is comprehensively analyzed and the equipment safety risk assessment index is calculated. The equipment safety risk assessment index is used to monitor the safety risks of the equipment during operation in real time.

[0063] The specific analysis method of the equipment safety risk assessment index is as follows:

[0064] Step S511: Calculate the deviation ratio of each pre-processed device operating parameter, including the fan speed, fan bearing vibration frequency, motor winding temperature, bearing temperature, cooling medium temperature, motor current and power. The specific calculation formula is: ,in, represents the deviation ratio of the kth device operating parameter, represents the actual measured value of the kth device operating parameter, represents the minimum allowable value of the kth device operating parameter, Indicates the maximum allowable value of the kth device operating parameter;

[0065] Step S512: Perform a comprehensive analysis on the deviation ratio of each device operating parameter and calculate the device safety risk assessment index: ,in, represents the equipment safety risk assessment index of the i-th transmission monitoring section, and K represents the total number of equipment operating parameters collected;

[0066] By setting a device security risk threshold , the equipment security risk assessment index Q and the equipment security risk threshold The comparison is used to determine whether there is a safety risk during the operation of the wind turbine equipment; if the equipment safety risk assessment index Q Device security risk threshold , it is considered that there is no safety risk in the equipment operation status during the perlite transportation process, and the equipment operation status will continue to be monitored. If the equipment safety risk assessment index Q Device security risk threshold , it is considered that there is a safety risk in the operation status of the fan equipment, and the analysis results of the equipment operation status are immediately transmitted to the transportation safety detection module.

[0067] Transportation safety detection module: used to analyze the results of transportation status risks and equipment operation status risks, calculate the safety detection coefficient, and screen out all transportation monitoring sections with safety risks.

[0068] In this embodiment, the transportation safety detection module is used to receive the analysis results of the transportation status and the analysis results of the equipment operation status. When the analysis results of the transportation risk and the equipment operation risk are received, the module immediately performs a comprehensive analysis and detection on the safety of each transportation monitoring section during the perlite transportation process, and screens out all transportation monitoring sections with safety risks.

[0069] The specific calculation formula of the safety detection coefficient is: ,in, represents the safety detection coefficient calculated for the i-th transport monitoring section, represents the transport status risk assessment index of the i-th transport monitoring section, represents the equipment safety risk assessment index of the i-th transmission monitoring section, Indicates the transport status risk threshold, represents the device security risk threshold, a represents the proportional constant, and e represents the constant;

[0070] Pass the safety test factor and safety threshold For comparison, if the safety detection factor Safety threshold , it is considered that there is no safety risk problem in the transportation of perlite. If the safety detection coefficient Safety threshold , it is considered that there is a safety risk in the transportation process of perlite, and all monitoring sections detected to have safety risks are screened out and marked.

[0071] Conveying speed adjustment module: The conveying speed of the conveying monitoring section with safety risks is adjusted separately through the conveying safety detection coefficient.

[0072] In this embodiment, the conveying speed adjustment module determines the risk level of the monitoring section marked as having safety risks according to the safety detection coefficient value, including low risk, medium risk and high risk. The conveying speed of the low-risk conveying monitoring section is slightly reduced, the conveying speed of the medium-risk conveying monitoring section is moderately reduced, and the conveying speed of the high-risk conveying monitoring section is suspended. The new conveying speed is calculated according to the risk level to formulate a conveying speed adjustment strategy. The specific calculation formula is: ,in, Indicates the new conveying speed of the conveying monitoring section, v indicates the current conveying speed of the conveying monitoring section, represents the adjustment factor, and The specific value is adjusted according to the safety detection coefficient value.

[0073] Early warning feedback module: automatically generates a monitoring report based on the monitoring results of the entire transportation monitoring process, and sends the monitoring report to the management personnel terminal.

[0074] In this embodiment, the early warning feedback module automatically generates a monitoring report based on the safety risk monitoring results of the conveying status and equipment operation status of each conveying monitoring section, and issues an early warning prompt for the monitoring section marked with safety risks, thereby prompting the management personnel to perform maintenance operations on it. At the same time, the speed reduction adjustment results are displayed to the management personnel terminal in a visual manner.

[0075] like Figure 2 This embodiment provides a method for analyzing and processing network routing failures, including the following steps:

[0076] S1: By dividing the transportation pipeline into several transportation monitoring sections, the perlite transportation production data is monitored and collected in sections;

[0077] S2: Processing the production data of each transport monitoring section during the perlite transport process, including pressure processing unit, flow processing unit and temperature processing unit;

[0078] S3: Based on the processed transportation production data, a transportation status risk analysis is performed to obtain a transportation status risk assessment index to detect whether there is an explosion risk;

[0079] S4: used for real-time monitoring and collection of fan equipment operation data during perlite transportation;

[0080] S5: By analyzing the operating status data of the fan equipment during the perlite transportation process, an equipment safety risk assessment index is obtained to detect whether there is a safety risk during the operation of the fan equipment;

[0081] S6: Analyzes the results of the transportation status risk and equipment operation status risk, calculates the safety detection coefficient, and screens out all transportation monitoring sections with safety risks;

[0082] S7: The conveying speed of the conveying monitoring section with safety risks is adjusted separately through the conveying safety detection coefficient;

[0083] S8: Automatically generate a monitoring report based on the monitoring results of the entire transportation monitoring process, and send the monitoring report to the management personnel terminal.

[0084] like Figure 3 The figure shows a schematic diagram of the conveying system structure of this embodiment, which includes a first dust collector 1, a feeding operation dust removal system 2, a feeder 3, a positive pressure feeding pipe 4, an air volume detector 5, a separator 6, a temporary storage tank 7, a material level switch 8, a falling material flow control feeder 9, a material guide pipe 10, a second dust collector 11 and an automatic feeding dust collection system 12;

[0085] Among them, the first dust collector 1 and the second dust collector 11 are used to filter and collect the dust generated during feeding, and uniformly treat the finer dust in a water bath; the feeding operation dust removal system 2 is connected to the exhaust dust collector through the cyclone separator to isolate and collect dust to prevent dust from entering the atmosphere, and the collected dust is returned to the perlite storage tank; the feeder 3 can be frequency-controlled to achieve stable and controllable air flow speed and feed volume; the positive pressure feeding pipe 4 is used to achieve positive pressure transportation of materials; the air volume detection 5 is used to determine whether the pipeline is blocked. If there is a blockage, the control program in the monitoring room will alarm and maintenance personnel can be arranged to go to the site for timely treatment; the separator 6 causes the perlite to sink and accumulate at the bottom, The two separators 6 alternately intake air and discharge material, causing the perlite material to fall into the temporary storage tank 7; the temporary storage tank 7 is provided with two high and low liquid level switches to automatically control the material level in the tank; the material level switch 8 is used to automatically detect and control the material level in the temporary storage tank. When the material level reaches the preset limit value, the material level switch will send a signal to trigger the corresponding control logic to stop or start the material transportation; the material flow control feeder 9 is used to accurately control the material transportation volume to ensure that the material can enter the conveying pipeline stably and continuously according to the predetermined flow rate; the material guide pipe 10 is used to automatically transmit the material to the automatic feeding and dust collection system 12; the automatic feeding and dust collection system 12 automatically feeds the material into the wind conveying system.

[0086] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

[0087] The above description is merely a specific embodiment of the present application, but the scope of protection of the present application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. Perlite pneumatic conveying system for emulsion explosive production line, characterized by: include: Transportation data acquisition module: By dividing the transportation pipeline into several transportation monitoring sections, the perlite transportation production data can be monitored and collected in sections; Transportation data processing module: processes the transportation production data of each transportation monitoring section during the perlite transportation process, including pressure processing unit, flow processing unit and temperature processing unit; Conveying status analysis module: Based on the processed conveying production data, the conveying status risk analysis module obtains the conveying status risk assessment index to detect whether there is an explosion risk; Equipment operation data acquisition module: used for real-time monitoring and collection of fan equipment operation data during perlite transportation; Equipment operation status analysis module: By analyzing the operating status data of the fan equipment during the perlite conveying process, the equipment safety risk assessment index is obtained to detect whether there are safety risks during the operation of the fan equipment; Transportation safety detection module: used to analyze the results of transportation status risks and equipment operation status risks, calculate the safety detection coefficient, and screen out all transportation monitoring sections with safety risks; Conveying speed adjustment module: The conveying speed of the conveying monitoring section with safety risks is individually adjusted through the conveying safety detection coefficient; Early warning feedback module: automatically generates a monitoring report based on the monitoring results of the entire transportation monitoring process and sends the monitoring report to the management terminal; The transport data processing module collects the pressure data of each transport monitoring section within a period of time through the pressure processing unit, processes and analyzes the pressure change data of each transport monitoring section, and calculates the pressure fluctuation value ; The flow processing unit collects the perlite gas flow data of each transmission monitoring section within a period of time, processes and analyzes the flow change data of each transmission monitoring section, and calculates the flow stability value ; The temperature processing unit collects the temperature data of each transport monitoring section and the external environment temperature data within a period of time, processes and analyzes the temperature data of each transport monitoring section and the external environment temperature data, and calculates the temperature change rate ; The delivery state analysis module is based on the analyzed pressure fluctuation value , flow stability value and the temperature change rate Conduct comprehensive analysis and calculate the transportation status risk assessment index: ,in, represents the transport status risk assessment index of the i-th transport monitoring section, is the weight coefficient; The equipment operation status analysis module pre-processes the collected wind turbine equipment operation status data. The specific operation process of the pre-processing includes: data cleaning, data conversion and data integration. Then, the pre-processed wind turbine equipment operation status data is comprehensively analyzed and the equipment safety risk assessment index is calculated. The equipment safety risk assessment index is used to monitor the safety risks of the equipment during operation in real time. The specific analysis method of the equipment safety risk assessment index is as follows: The deviation ratio is calculated by pre-processing the operating parameters of each device, including the fan speed, fan bearing vibration frequency, motor winding temperature, bearing temperature, cooling medium temperature, motor current and power. The specific calculation formula is: ,in, represents the deviation ratio of the kth device operating parameter, represents the actual measured value of the kth device operating parameter, represents the minimum allowable value of the kth device operating parameter, Indicates the maximum allowable value of the kth device operating parameter; By comprehensively analyzing the deviation ratio of each equipment operating parameter, the equipment safety risk assessment index is calculated as follows: ,in, represents the equipment safety risk assessment index of the i-th transmission monitoring section, and K represents the total number of equipment operating parameters collected.

2. The perlite pneumatic conveying system for emulsion explosive production line according to claim 1, characterized in that: The specific collection method of the transport data collection module is: According to the overall layout of the production line, the conveying pipeline is divided into several conveying monitoring sections. Then, based on the actual conveying requirements of the perlite, the length of each conveying monitoring section is set, and the divided conveying monitoring sections are numbered in sequence according to the order in which the perlite is blown into the pipe, namely 1, 2, 3, ... n. Then, corresponding sensors are installed in each conveying monitoring section to monitor and collect the conveying operation data of each conveying monitoring section in real time. The conveying operation data includes the flow rate, pressure and temperature of the perlite.

3. The perlite pneumatic conveying system for emulsion explosive production line according to claim 1, characterized in that: The transport state analysis module further includes setting a transport state risk threshold , the transport status risk assessment index and transport status risk threshold Comparison is used to determine whether there is an explosion risk in the transport monitoring section; if the transport status risk assessment index Transport status risk threshold , it is considered that there is no explosion risk in the transportation monitoring section, and the transportation status of the transportation monitoring section will continue to be monitored. If the transportation status risk assessment index Transport status risk threshold , it is considered that there is an explosion risk in the transportation monitoring section, and the analysis results of the transportation status are immediately transmitted to the transportation safety detection module.

4. The perlite pneumatic conveying system for emulsion explosive production line according to claim 1, characterized in that: The equipment operation data acquisition module uses the speed sensor, vibration sensor, temperature sensor, current sensor and power sensor inside the fan equipment to collect the fan speed, fan bearing vibration frequency, motor winding temperature, bearing temperature, cooling medium temperature, motor current and power in real time during operation, and uses the programmable logic controller as the core of data acquisition, connected to various sensor interfaces to execute the data acquisition program, set a fixed acquisition cycle to automatically collect data, and input the collected equipment operation status data into the computer terminal through the wireless network.

5. The perlite pneumatic conveying system for emulsion explosive production line according to claim 1, characterized in that: The equipment operation status analysis module also includes setting an equipment safety risk threshold , the equipment security risk assessment index Q and the equipment security risk threshold Comparison is performed to determine whether there are safety risks during the operation of the wind turbine equipment; If the equipment safety risk assessment index Q Device security risk threshold , it is considered that there is no safety risk in the equipment operation status during the perlite transportation process, and the equipment operation status will continue to be monitored. If the equipment safety risk assessment index Q Device security risk threshold , it is considered that there is a safety risk in the operation status of the fan equipment, and the analysis results of the equipment operation status are immediately transmitted to the transportation safety detection module.

6. The perlite pneumatic conveying system for emulsion explosive production line according to claim 1, characterized in that: The transportation safety detection module is used to receive the analysis results of the transportation status and the analysis results of the equipment operation status. When the analysis results of the transportation risk and the equipment operation risk are received, the module immediately conducts a comprehensive analysis and detection of the safety of each transportation monitoring section during the perlite transportation process, and screens out all transportation monitoring sections with safety risks. The specific calculation formula of the safety detection coefficient is: ,in, represents the safety detection coefficient calculated for the i-th transport monitoring section, represents the transport status risk assessment index of the i-th transport monitoring section, represents the equipment safety risk assessment index of the i-th transmission monitoring section, Indicates the transport status risk threshold, represents the device security risk threshold, a represents the proportional constant, and e represents the constant; Pass the safety test factor and safety threshold For comparison, if the safety detection factor Safety threshold , it is considered that there is no safety risk problem in the transportation of perlite. If the safety detection coefficient Safety threshold , it is considered that there is a safety risk in the transportation process of perlite, and all monitoring sections detected to have safety risks are screened out and marked.

7. The perlite pneumatic conveying system for emulsion explosive production line according to claim 1, characterized in that: The conveying speed adjustment module determines the risk level of the monitoring section marked as having safety risks according to the safety detection coefficient value, including low risk, medium risk and high risk. It slightly reduces the conveying speed of the low-risk conveying monitoring section, moderately reduces the conveying speed of the medium-risk conveying monitoring section, and suspends the conveying speed of the high-risk conveying monitoring section; and calculates the new conveying speed according to the risk level to formulate a conveying speed adjustment strategy. The specific calculation formula is: ,in, Indicates the new conveying speed of the conveying monitoring section, v indicates the current conveying speed of the conveying monitoring section, represents the adjustment factor, and The specific value is adjusted according to the safety detection coefficient value.

8. The perlite pneumatic conveying system for emulsion explosive production line according to claim 1, characterized in that: The early warning feedback module automatically generates a monitoring report based on the safety risk monitoring results of the conveying status and equipment operation status of each conveying monitoring section, and issues early warning prompts for the monitoring sections marked with safety risks, thereby prompting management personnel to perform maintenance operations on them. At the same time, the speed reduction adjustment results are displayed in a visual manner to the management personnel terminal.

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