A molten iron transport capping device operation monitoring system and monitoring method thereof

Abstract

The present invention relates to the technical field of molten iron transportation, and in particular to an operation monitoring system and a monitoring method for a molten iron transportation capping device, which are intended to monitor the working status of the molten iron transportation capping device in real time during the entire operation process. Through advanced scientific and technological technologies such as sensor technology, Internet of Things technology, and artificial intelligence technology, a capping device operation status monitoring module monitors the status parameters of key components in vehicle-mounted equipment and fixed-point ground equipment. A data processing and analysis module performs intelligent diagnosis and prediction on possible faults. Through a remote monitoring platform, measures are automatically taken to ensure the safe operation of the capping device, and functions such as remote monitoring, data analysis, fault diagnosis, and remote control of the opening / closing of the capping device are realized, thereby improving the emergency response speed and processing efficiency. The implementation of the present invention can realize comprehensive, real-time, and accurate monitoring of the operation status of the molten iron transportation capping device, and effectively prevent safety accidents caused by failures of the capping device.

Description

Technical Field

[0001] The invention relates to the technical field of molten iron transportation, and in particular to an operation monitoring system and a monitoring method of a molten iron transportation capping device. Background Art

[0002] In the steel smelting industry, molten iron transportation is an important part of the production process, and the safety and efficiency issues in the molten iron transportation process are increasingly valued. In the traditional molten iron transportation process, due to the extremely high temperature of the molten iron and the easy generation of harmful substances such as smoke, steam, etc., it poses a threat to the transportation environment, personnel safety and equipment life; there are many ways to cover the molten iron for transportation. The current non-powered covering technology is to use the vehicle-mounted equipment to pass through the fixed ground equipment, and the rollers of the vehicle-mounted equipment are under the action of the ground slope track to realize the automatic opening and closing of the tank cover. The vehicle-mounted equipment is a four-bar linkage. The rollers of the vehicle-mounted equipment drive the tank cover to open and close through the four-bar linkage under the action of the ground equipment. Driven by the locomotive, the vehicle-mounted equipment passes through the ground device fixed next to the rail at a certain speed to implement the closing and opening of the tank cover. For example, the applicant's previous research and development results, namely the invention patent with authorization publication number CN115722660 B, named a fixed-point ramp-driven molten iron tank cover-adding and uncovering device and method, the invention concept of the patented fixed-point ramp-driven molten iron tank cover-adding and uncovering device is to adopt non-powered cover-adding technology, and its actuator, fixed frame seat, connecting rod mechanism and support constitute the vehicle-mounted equipment, and the ramp is the fixed-point ground equipment. When the vehicle-mounted equipment is towed by the locomotive, it drives the driving wheel to pass through the slope of the fixed-point ground equipment ramp, and the cover is added and closed when going uphill, and the cover is opened when going downhill. When the onboard equipment has a mechanical failure, the tank cover installed on the support arm will not move, and the opening and closing of the cover cannot be achieved; for example, the tank cover has been crushed by a plate hook in a steel plant, and interfered with the tank body when closing the cover, and could not be closed. If the cover continues to operate, it will cause the vehicle to be derailed, and the ground device and the cover device to be damaged; the support arm will deform during operation, affecting the closing effect and increasing the lifting force; the tripod will deform during operation, causing the cover to be unable to be opened and closed; when there is slag accumulation at the tank mouth, the opening and closing of the tank cover cannot be completed. When the tank cover cannot be closed, the onboard equipment will lift up the vehicle under the action of the ground equipment, causing the vehicle to be derailed.

[0003] To avoid the above accidents, the vehicle capping device is required to stop once before passing the ground equipment during operation, and the shunting personnel should monitor the running status of the rollers and the status of the tank cover beside the ground equipment. If the tank cover is found to be abnormal, the vehicle should be stopped immediately to check the cause and deal with it. This seriously affects the efficiency of molten iron transportation.

[0004] Therefore, developing a system and a monitoring method thereof that can monitor the operating status of a molten iron transport covering device in real time is of great significance for improving the safety and efficiency of molten iron transportation. Summary of the invention

[0005] In order to solve the above technical problems, the present invention provides a molten iron transport covering device operation monitoring system and a monitoring method thereof, which can monitor the operating status of the covering device in real time, promptly detect and handle abnormal situations, thereby improving the safety and efficiency of molten iron transportation.

[0006] To achieve the above object, the present invention is implemented by adopting the following technical solutions:

[0007] A first aspect of the present invention provides an operation monitoring system for a molten iron transport capping device, comprising a remote monitoring platform and:

[0008] The operating status monitoring module of the capping device is used to collect the operating status parameters of the molten iron transport capping device in real time;

[0009] A sensor assembly, which is in communication connection with the capping device operation status monitoring module, and is used to monitor the operation status of each component of the molten iron transport capping device and transmit signals to the capping device operation status monitoring module;

[0010] A data processing and analysis module is connected to the capping device operation status monitoring module in communication, and uses a machine learning algorithm and a fault tree analysis model to perform real-time processing and analysis on the data received from the capping device operation status monitoring module, perform intelligent fault diagnosis and prediction on the operation status of the capping device, and identify whether the operation status of the capping device is normal;

[0011] A control module, which is in communication with the data processing and analysis module and is used to provide suitable operating parameters for the capping device according to the analysis results of the data processing and analysis module;

[0012] An early warning and alarm module, which is in communication with the data processing and analysis module, and is used to automatically trigger an early warning or alarm signal to stop the locomotive when the analysis result is abnormal;

[0013] The display module is used to display the operating status, fault information or suggested handling measures of the capping device.

[0014] In a possible technical solution, the operating status parameters include the open / closed state of the covering device, whether the cover plate is deformed, whether the support arm is deformed, whether the tripod is deformed, the temperature inside the molten iron tank, the travel speed, and the pressure of the ground ramp.

[0015] In a possible technical solution, the sensor assembly includes a photoelectric sensor, a position sensor, a temperature sensor, an acceleration sensor and a pressure sensor. The photoelectric sensor is used to monitor the open / closed state of the capping device; the position sensor is respectively arranged on the cover plate, the support arm and the tripod, and is used to monitor whether the cover plate, the support arm and the tripod are deformed; the temperature sensor is used to monitor the temperature inside the molten iron ladle, and the acceleration sensor is used to monitor the travel speed of the capping device; the pressure sensor is used to monitor the pressure changes of the ground ramp of the capping device.

[0016] In a possible technical solution, the data processing and analysis module includes:

[0017] Analysis rule knowledge base, used to store machine learning training models or fault tree analysis models;

[0018] The data analysis submodule is used to receive the data sent by the capping device operation status monitoring module, analyze the data according to the rule algorithm in the analysis rule knowledge base, obtain the analysis result of whether the data is normal, and transmit the analysis result to the control module; if the analysis result is an abnormal situation, the analysis result is transmitted to the early warning and alarm module and the fault location submodule;

[0019] The fault location submodule is used to receive the abnormal situation data sent by the data analysis submodule, extract the abnormal data, and locate the fault of the abnormal data according to the fault tree analysis model stored in the analysis rule knowledge base.

[0020] In a possible technical solution, the machine learning algorithm adopted by the data processing and analysis module is a neural network. The neural network is constructed according to historical fault data, and the initial parameters of the neural network are set. The neural network is trained based on the historical fault data and the initial parameters of the neural network to obtain a neural network model group that predicts possible faults of the capping device. The neural network model has a three-layer structure, and the neural network model includes an input layer, a hidden layer, and an output layer.

[0021] In a possible technical solution, the method in which the data processing and analysis module determines whether the operating status parameter is normal is:

[0022] The opening / closing state of the capping device is normal, which means that when entering the opening / closing area through the ground device, the can lids on both sides can be opened / closed normally and the opening / closing process is smooth and without obstruction; abnormal means that it is half open and half closed or not opened / closed in place, among which, abnormal noise and non-smoothness during the opening and closing of the cover are primary abnormalities; obstruction during the opening and closing of the cover but not affecting the opening and closing of the cover is moderate abnormality; obstruction during the opening and closing of the cover affects the opening and closing of the cover and is severe abnormality;

[0023] A normal cover plate means that the cover plate has no deformation. If the cover plate is uneven, it is considered deformed. If the unevenness is greater than 10mm, it is considered a primary abnormality; if the unevenness is greater than 20mm, it is considered a moderate abnormality; if the unevenness is greater than 30mm, it is considered a serious abnormality.

[0024] A normal arm means that the arm has no bending or deformation. Bending of the arm is considered deformation. A bending degree of more than 10 mm is considered a primary abnormality; a bending degree of more than 20 mm is considered a moderate abnormality; a bending degree of more than 30 mm is considered a severe abnormality.

[0025] A normal tripod means that the tripod has no bending or deformation. A bending of the tripod is considered deformation. A bending degree of more than 10mm is considered a primary abnormality; a bending degree of more than 20mm is considered a moderate abnormality; a bending degree of more than 30mm is considered a serious abnormality.

[0026] If the temperature in the molten iron tank does not exceed the maximum allowable process temperature, it is normal. If the temperature changes by more than ±50℃, it is a primary abnormality. If it exceeds ±100℃, it is a moderate abnormality. If it exceeds ±200℃, it is a serious abnormality.

[0027] A speed of 3 km / h is normal, a speed of >3 km / h is a primary abnormality, a speed of >3.5 km / h is a medium abnormality, and a speed of >4 km / h is a serious abnormality;

[0028] A ground ramp pressure of less than 20 tons is normal, a ground ramp pressure between 20-21 tons is a primary abnormality, a ground ramp pressure of 21-25 tons is a moderate abnormality, and a ground ramp pressure of more than 25 tons is a serious abnormality.

[0029] In one possible technical solution, the early warning and alarm module sets up a multi-level early warning mechanism according to the severity of the abnormal situation monitored by the data processing and analysis module, including a yellow warning triggered by a primary abnormal situation, an orange warning triggered by a moderate abnormal situation, and a red warning triggered by a severe abnormal situation.

[0030] A possible technical solution also includes high-definition cameras arranged around the molten iron car and key positions of the molten iron transport covering device, and the high-definition cameras are communicatively connected to the remote monitoring platform.

[0031] A possible technical solution further includes a communication device arranged on the molten iron car, and the communication device communicates bidirectionally with the remote monitoring platform.

[0032] The second aspect of the present invention provides an operation monitoring method for a molten iron transport and capping device, wherein a sensor component monitors the operating status of each component of the molten iron transport and capping device and transmits a signal to a capping device operation status monitoring module, and the capping device operation status monitoring module transmits the collected effective operating status parameters of the molten iron transport and capping device to a data processing and analysis module, and the data processing and analysis module processes and analyzes the received data in real time, performs intelligent fault diagnosis and prediction on the operating status of the capping device, identifies whether the operating status of the capping device is normal, and transmits the analysis result to a control module, giving the capping device appropriate operating parameters; if the analysis result is an abnormal situation, the analysis result is transmitted to an early warning and alarm module and a fault location submodule; the fault location submodule receives the abnormal situation data sent by the data analysis submodule, extracts the abnormal data, and locates the fault of the abnormal data according to a fault tree analysis model stored in an analysis rule knowledge base; the early warning and alarm module triggers a multi-level early warning according to the severity of the abnormal situation monitored by the data processing and analysis module, and automatically triggers an early warning or alarm signal.

[0033] Compared with the prior art, the beneficial effects of the present invention are as follows: the implementation of the present invention can realize comprehensive, real-time and accurate monitoring of the operating status of the molten iron transportation capping device, and effectively prevent safety accidents and environmental pollution problems caused by the failure of the capping device by real-time monitoring of the operating status of the capping device and timely handling of abnormal situations, thereby improving the safety, efficiency and environmental protection level of molten iron transportation. At the same time, through the use of the remote monitoring platform, the cost of manual inspection can be significantly reduced and the management efficiency can be improved.

[0034] (1) Improve safety: By real-time monitoring of the molten iron transportation process, potential safety hazards can be discovered in a timely manner and the risk of accidents can be reduced.

[0035] (2) Reduce environmental pollution: The covering device can effectively prevent molten iron from volatilizing or splashing during transportation, reduce environmental pollution, and meet the requirements of ecological and environmental protection.

[0036] (3) Improving transportation efficiency: The monitoring system can provide real-time feedback on transportation status, optimize transportation routes and scheduling, improve overall transportation efficiency, and reduce transportation costs.

[0037] (4) Data recording and analysis: The system can record and analyze various data during the transportation process, providing data support for subsequent improvements and optimizations.

[0038] (5) Convenient maintenance: Through the monitoring system, the operating status of the equipment can be monitored in real time and equipment failures can be discovered in time, thereby reducing maintenance time and costs and increasing the service life of the equipment.

[0039] (6) Enhance the management capabilities of operators: The monitoring system provides a visual operation interface to help operators better understand the transportation process and improve management level and decision-making ability.

[0040] (7) Improving enterprise competitiveness: By improving safety and transportation efficiency and reducing operating costs, the competitiveness of enterprises in the market is enhanced.

[0041] (8) Compliance with industry standards: The implementation of this monitoring system and method will help enterprises comply with relevant industry safety and environmental protection standards and enhance their corporate image.

[0042] In short, the implementation of this invention patent can not only improve the safety and efficiency of molten iron transportation, but also promote the sustainable development of the industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a structural schematic diagram of an operation monitoring system of a molten iron transport capping device according to an embodiment of the present invention;

[0045] Figure 2 It is a schematic diagram of the arrangement structure of the sensor assembly;

[0046] Figure 3 It is a structural diagram of the data processing and analysis module;

[0047] Figure 4 It is a control logic diagram of a method for monitoring the operation of a molten iron transport capping device according to an embodiment of the present invention;

[0048] Figure markings: 1-covering device operation status monitoring module; 2-sensor assembly; 21-photoelectric sensor; 22-position sensor one; 23-position sensor two; 24-position sensor three; 25-temperature sensor; 26-pressure sensor; 3-data processing and analysis module; 31-analysis rule knowledge base; 32-data analysis submodule; 33-fault location submodule; 4-control module; 5-early warning and alarm module; 6-display module; 7-communication module; 8-remote monitoring platform. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments.

[0050] like Figure 1 As shown, the present invention proposes an operation monitoring system for a molten iron transport capping device, comprising a remote monitoring platform 8 and:

[0051] The capping device operation status monitoring module 1 is used to collect the operation status parameters of the molten iron transport capping device in real time;

[0052] The sensor assembly 2 is connected to the capping device operation status monitoring module 1 for monitoring the operation status of each component of the molten iron transport capping device and transmitting the signal to the capping device operation status monitoring module 1;

[0053] The data processing and analysis module 3 is connected to the capping device operation status monitoring module 1 in communication, and adopts a machine learning algorithm and a fault tree analysis model to process and analyze the data received from the capping device operation status monitoring module 1 in real time, perform intelligent fault diagnosis and prediction on the operation status of the capping device, and identify whether the operation status of the capping device is normal and whether there is a potential fault;

[0054] The control module 4 is in communication with the data processing and analysis module 3 and is used to provide suitable operating parameters for the capping device according to the analysis results of the data processing and analysis module 3;

[0055] The early warning and alarm module 5 is in communication with the data processing and analysis module 3 and is used to automatically trigger an early warning or alarm signal to stop the locomotive when the analysis result is abnormal;

[0056] Display module 6, used to display the operating status of the capping device, fault information or recommended fault handling measures;

[0057] The modules exchange data via the communication module 7 .

[0058] The present invention aims to monitor the working status of the molten iron transport capping device in real time during the entire operation process. Through advanced scientific and technological technologies such as sensor technology, Internet of Things technology, and artificial intelligence technology, the capping device operation status monitoring module monitors the status parameters of key components in the vehicle-mounted equipment and fixed-point ground equipment. The data processing and analysis module performs intelligent diagnosis and prediction of possible faults, and automatically responds through the remote monitoring platform to take measures to ensure the safe operation of the capping device, thereby realizing remote monitoring, data analysis, fault diagnosis, and remote control of the opening / closing of the capping device and other functions, thereby improving the emergency response speed and processing efficiency.

[0059] In this embodiment, based on the experience of failures that occurred during the actual implementation of molten iron transportation covering devices for many years, the operating status parameters include the open / closed state of the covering device, whether the cover plate is deformed, whether the support arm is deformed, whether the tripod is deformed, the temperature inside the molten iron tank, the travel speed, and the pressure of the ground ramp.

[0060] Accordingly, the sensor assembly 2 includes a photoelectric sensor, a position sensor, a temperature sensor, an acceleration sensor and a pressure sensor, such as Figure 2 As shown, the photoelectric sensor 21 is arranged on the support arm, and is used to monitor the open / closed state of the capping device; the position sensor 1 22, the position sensor 23, and the position sensor 3 24 are respectively arranged on the cover plate, the support arm and the tripod, and are used to monitor whether the cover plate, the support arm and the tripod are deformed; the temperature sensor 25 is arranged on the cover plate, and is used to monitor the temperature in the molten iron ladle to ensure its normal operation and prevent overheating; the acceleration sensor is arranged on the molten iron car or the capping device (not shown in the figure), and is used to monitor the travel speed of the capping device, so as to detect the vibration of the capping device; the pressure sensor 26 is arranged on the tripod, and is used to monitor the pressure change of the ground ramp of the capping device.

[0061] like Figure 3 As shown, the data processing and analysis module 3 includes:

[0062] An analysis rule knowledge base 31, used to store a machine learning training model or a fault tree analysis model;

[0063] The data analysis submodule 32 is used to receive the data sent by the capping device operation status monitoring module 1, analyze the data according to the rule algorithm in the analysis rule knowledge base 31, obtain the analysis result of whether the data is normal, and transmit the analysis result to the control module 4; if the analysis result is an abnormal situation, the analysis result is transmitted to the early warning and alarm module 5 and the fault location submodule 33;

[0064] The fault location submodule 33 is used to receive the abnormal situation data sent by the data analysis submodule 32, extract the abnormal data, and locate the fault of the abnormal data according to the fault tree analysis model stored in the analysis rule knowledge base 31; take the abnormal data as the top event in the fault tree, find the minimum cut set of all possible fault modes that cause the top event of parameter abnormality, that is, find the cause of the parameter abnormality and locate the fault.

[0065] The machine learning algorithm adopted by the data processing and analysis module is a neural network. Specifically, a BP neural network can be used to construct a neural network based on historical fault data, and the initial parameters of the neural network are set. The initial parameters specifically include initial weights, initial thresholds, number of hidden layer nodes, learning rate, maximum iteration step size and expected value of error performance; the neural network is trained based on historical fault data and the initial parameters of the neural network to obtain a neural network model group that predicts possible faults of the capping device. The neural network model has a three-layer structure, and the neural network model includes an input layer, a hidden layer and an output layer.

[0066] The method by which the data processing and analysis module determines whether the operating status parameters are normal is:

[0067] The opening / closing state of the capping device is normal, which means that when entering the opening / closing area through the ground device, the can lids on both sides can be opened / closed normally and the opening / closing process is smooth and without obstruction; abnormal means that it is half open and half closed or not opened / closed in place, among which, abnormal noise and non-smoothness during the opening and closing of the cover are primary abnormalities; obstruction during the opening and closing of the cover but not affecting the opening and closing of the cover is moderate abnormality; obstruction during the opening and closing of the cover affects the opening and closing of the cover and is severe abnormality;

[0068] A normal cover plate means that the cover plate has no deformation. If the cover plate is uneven, it is considered deformed. If the unevenness is greater than 10mm, it is considered a primary abnormality; if the unevenness is greater than 20mm, it is considered a moderate abnormality; if the unevenness is greater than 30mm, it is considered a serious abnormality.

[0069] A normal arm means that the arm has no bending or deformation. Bending of the arm is considered deformation. A bending degree of more than 10 mm is considered a primary abnormality; a bending degree of more than 20 mm is considered a moderate abnormality; a bending degree of more than 30 mm is considered a severe abnormality.

[0070] A normal tripod means that the tripod has no bending or deformation. A bending of the tripod is considered deformation. A bending degree of more than 10mm is considered a primary abnormality; a bending degree of more than 20mm is considered a moderate abnormality; a bending degree of more than 30mm is considered a serious abnormality.

[0071] If the temperature in the molten iron tank does not exceed the maximum allowable process temperature, it is normal. If the temperature changes by more than ±50℃, it is a primary abnormality. If it exceeds ±100℃, it is a moderate abnormality. If it exceeds ±200℃, it is a serious abnormality.

[0072] A speed of 3 km / h is normal, a speed of >3 km / h is a primary abnormality, a speed of >3.5 km / h is a medium abnormality, and a speed of >4 km / h is a serious abnormality;

[0073] A ground ramp pressure of less than 20 tons is normal, a ground ramp pressure between 20-21 tons is a primary abnormality, a ground ramp pressure of 21-25 tons is a moderate abnormality, and a ground ramp pressure of more than 25 tons is a serious abnormality.

[0074] like Figure 4 As shown, the data processing and analysis module 3 performs intelligent fault diagnosis and prediction on the operating status of the capping device. When it is determined that the current operating status parameters are normal or within the adjustable range (such as below the intermediate abnormality level), a signal is sent to the control module 4. For some faults that can be automatically adjusted (such as poor sealing), the control module 4 can try to repair them by automatically adjusting the operating parameters to reduce the time of manual intervention.

[0075] When the analysis result of the early warning and alarm module 5 is an abnormal situation, it automatically triggers an early warning or alarm signal to remind the operator to pay attention, and triggers the sound and light alarm function when necessary (such as excessive temperature, cover not closed, etc.), notifying relevant personnel to take emergency measures; the early warning and alarm module 5 sets a multi-level early warning mechanism according to the severity of the abnormal situation monitored by the data processing and analysis module 3, including a yellow warning triggered by a primary abnormal situation, an orange warning triggered by a moderate abnormal situation, and a red warning triggered by a serious abnormal situation; preferably, the early warning and alarm module can also customize the early warning threshold, allowing the user to customize the early warning threshold of various monitoring parameters according to actual needs, increasing the flexibility and applicability of the system. When a serious abnormality is found (such as the complete failure of the capping device), the early warning and alarm module automatically triggers the emergency braking system to stop the operation of the transport vehicle to prevent the accident from expanding.

[0076] The display module 6 can be a touch screen or an LED display screen to display the operating status information of the capping device in real time, which is convenient for operators to monitor.

[0077] The communication module 7 can use wireless communication technology, such as Wi-Fi, Bluetooth, etc., to exchange data with other module devices to achieve remote monitoring and control.

[0078] Preferably, the remote monitoring platform 8 has an intuitive and easy-to-use interface, and designs an intuitive and easy-to-use human-computer interaction interface so that operators can quickly get started and operate accurately; the remote monitoring platform 8 supports a variety of terminal devices (such as computers, tablets, mobile phones, etc.) to facilitate usage needs in different scenarios.

[0079] As a preferred implementation scheme of the present invention, high-definition cameras are arranged around the molten iron car and at key positions of the molten iron transport covering device. The high-definition cameras are communicated with the remote monitoring platform 8 to realize real-time video monitoring and provide intuitive picture information for the remote monitoring platform.

[0080] As a preferred embodiment of the present invention, a communication device is installed on the molten iron car, and the communication device communicates with the remote monitoring platform 8 in a two-way manner. The operator can send instructions to the site through the remote monitoring platform 8, and the site personnel can also report the situation to the remote monitoring platform 8 through the communication device.

[0081] As a preferred implementation scheme of the present invention, the monitoring system is also provided with a data recording module to record all historical information such as monitoring data, early warning records, fault handling records, etc., to facilitate subsequent analysis and tracing; further, the data recording module adopts data encryption, backup and other measures to ensure the security and stability of the data; the monitoring system performs redundant design on key components and system modules to ensure that the system can still operate normally when some equipment fails; the monitoring system is also provided with a report generation module, which provides functions such as automatic generation of monitoring reports and fault analysis reports to help managers quickly understand the system operation status.

[0082] A method for monitoring the operation of a molten iron transport and capping device according to an embodiment of the present invention, wherein a sensor component 2 monitors the operating status of each component of the molten iron transport and capping device and transmits a signal to a capping device operating status monitoring module 1, wherein the capping device operating status monitoring module 1 transmits the collected effective operating status parameters of the molten iron transport and capping device to a data processing and analysis module 3, wherein the data processing and analysis module 3 processes and analyzes the received data in real time, performs intelligent fault diagnosis and prediction on the operating status of the capping device, identifies whether the operating status of the capping device is normal, and transmits the analysis result to a control module 4, giving the capping device suitable operating parameters; if the analysis result is an abnormal situation, the analysis result is transmitted to an early warning and alarm module 5 and a fault location submodule 33; the fault location submodule 33 receives the abnormal situation data sent by the data analysis submodule 32, extracts the abnormal data, and locates the fault of the abnormal data according to the fault tree analysis model stored in the analysis rule knowledge base 31; the early warning and alarm module 5 triggers a multi-level early warning according to the severity of the abnormal situation monitored by the data processing and analysis module 3, and automatically triggers an early warning or alarm signal.

[0083] The system is widely used in the iron and steel enterprises in the process of molten iron transportation, especially for enterprises that use open torpedo tank cars or ladles to transport molten iron. Through this system, enterprises can realize comprehensive monitoring and management of the molten iron transportation process, improve transportation efficiency, reduce energy consumption, reduce carbon emissions and ensure production safety.

[0084] The above is only a preferred specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed by the present invention should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A molten iron transport capping device operation monitoring system, characterized in that: Includes remote monitoring platform (8) and: A capping device operation status monitoring module (1) is used to collect operation status parameters of the molten iron transport capping device in real time; The operating state parameters include the open / closed state of the capping device, whether the cover plate is deformed, whether the support arm is deformed, whether the tripod is deformed, the temperature in the molten iron ladle, the travel speed, and the pressure of the ground ramp; A sensor assembly (2) is communicatively connected to the capping device operation status monitoring module (1) and is used to monitor the operation status of various components of the molten iron transport capping device and transmit signals to the capping device operation status monitoring module (1); The sensor assembly (2) comprises a photoelectric sensor, a position sensor, a temperature sensor, an acceleration sensor and a pressure sensor. The photoelectric sensor is used to monitor the open / closed state of the capping device. The position sensor is arranged on the cover plate, the support arm and the tripod respectively, and is used to monitor whether the cover plate, the support arm and the tripod are deformed. The temperature sensor is used to monitor the temperature in the molten iron tank. The acceleration sensor is used to monitor the travel speed of the capping device. The pressure sensor is used to monitor the pressure change of the ground ramp of the capping device. A data processing and analysis module (3) is connected to the capping device operation status monitoring module (1) in communication, and uses a machine learning algorithm and a fault tree analysis model to perform real-time processing and analysis on the data received from the capping device operation status monitoring module (1), perform intelligent fault diagnosis and prediction on the operation status of the capping device, and identify whether the operation status of the capping device is normal; The data processing and analysis module (3) uses a neural network as the machine learning algorithm. The neural network is constructed based on the historical fault data, the initial parameters of the neural network are set, and the neural network is trained based on the historical fault data and the initial parameters of the neural network to obtain a neural network model group for predicting possible faults of the capping device. The neural network model has a three-layer structure, and the neural network model includes an input layer, a hidden layer, and an output layer; A control module (4) is connected to the data processing and analysis module (3) for providing suitable operating parameters for the capping device according to the analysis results of the data processing and analysis module (3); An early warning and alarm module (5) is connected to the data processing and analysis module (3) for automatically triggering an early warning or alarm signal and stopping the locomotive when the analysis result is abnormal; The display module (6) is used to display the operating status of the capping device, fault information or suggested handling measures for the fault.

2. The operation monitoring system of the molten iron transport capping device according to claim 1, characterized in that: The data processing and analysis module (3) comprises: An analysis rule knowledge base (31) for storing a machine learning training model or a fault tree analysis model; A data analysis submodule (32) is used to receive data sent by the capping device operation status monitoring module (1), analyze the data according to the rule algorithm in the analysis rule knowledge base (31), obtain an analysis result of whether the data is normal, and transmit the analysis result to the control module (4); if the analysis result is an abnormal situation, transmit the analysis result to the early warning and alarm module (5) and the fault location submodule (33); The fault location submodule (33) is used to receive the abnormal situation data sent by the data analysis submodule (32), extract the abnormal data, and locate the fault of the abnormal data according to the fault tree analysis model stored in the analysis rule knowledge base (31).

3. The operation monitoring system of the molten iron transport capping device according to claim 2, characterized in that: The method by which the data processing and analysis module (3) determines whether the operating status parameters are normal is: The opening / closing state of the capping device is normal, that is, when entering the cap opening / closing area through the ground device, the can lids on both sides can be opened / closed normally and the cap opening / closing process is smooth without obstruction; Abnormal means half open and half closed or not fully open / closed. Among them, abnormal noise and unevenness during the operation of the switch cover are primary abnormalities; obstruction during the operation of the switch cover but not affecting the operation of the switch cover is moderate abnormality; obstruction during the operation of the switch cover affecting the operation of the switch cover is severe abnormality; A normal cover plate means that the cover plate has no deformation. If the cover plate is uneven, it is considered deformed. If the unevenness is greater than 10mm, it is considered a primary abnormality; if the unevenness is greater than 20mm, it is considered a moderate abnormality; if the unevenness is greater than 30mm, it is considered a serious abnormality. A normal arm means that the arm has no bending or deformation. Bending of the arm is considered deformation. A bending degree of more than 10 mm is considered a primary abnormality; a bending degree of more than 20 mm is considered a moderate abnormality; a bending degree of more than 30 mm is considered a severe abnormality. A normal tripod means that the tripod has no bending or deformation. A bending of the tripod is considered deformation. A bending degree exceeding 10mm is considered a primary abnormality; a bending degree exceeding 20mm is considered a moderate abnormality; and a bending degree exceeding 30mm is considered a serious abnormality.

4. The operation monitoring system of the molten iron transport capping device according to claim 3, characterized in that: The early warning and alarm module (5) sets a multi-level early warning mechanism according to the severity of the abnormal situation detected by the data processing and analysis module (3), including a yellow warning triggered by a primary abnormal situation, an orange warning triggered by a moderate abnormal situation, and a red warning triggered by a severe abnormal situation.

5. The operation monitoring system for the molten iron transport capping device according to claim 4, characterized in that: It also includes high-definition cameras arranged around the molten iron car and key parts of the molten iron transport and covering device, and the high-definition cameras are communicatively connected to the remote monitoring platform (8).

6. The operation monitoring system for the molten iron transport capping device according to claim 5, characterized in that: It also includes a communication device arranged on the molten iron car, wherein the communication device communicates bidirectionally with the remote monitoring platform (8).

7. A method for monitoring the operation of a molten iron transport capping device, characterized in that: The invention is realized by the operation monitoring system of the molten iron transport and capping device according to any one of claims 1 to 6, wherein the sensor component (2) monitors the operation status of each component of the molten iron transport and capping device and transmits the signal to the capping device operation status monitoring module (1), the capping device operation status monitoring module (1) transmits the collected effective operation status parameters of the molten iron transport and capping device to the data processing and analysis module (3), the data processing and analysis module (3) processes and analyzes the received data in real time, performs intelligent fault diagnosis and prediction on the operation status of the capping device, identifies whether the operation status of the capping device is normal, and divides the data into the data processing and analysis module (3). The analysis result is transmitted to the control module (4), and suitable operating parameters are given to the capping device; if the analysis result is an abnormal situation, the analysis result is transmitted to the early warning and alarm module (5) and the fault location submodule (33); the fault location submodule (33) receives the abnormal situation data sent by the data analysis submodule (32), extracts the abnormal data, and locates the fault of the abnormal data according to the fault tree analysis model stored in the analysis rule knowledge base (31); the early warning and alarm module (5) triggers a multi-level early warning according to the severity of the abnormal situation monitored by the data processing and analysis module (3), and automatically triggers an early warning or alarm signal.

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