Coal unloading car parking position detection and early warning system and method

Abstract

The invention provides a coal unloading vehicle parking position detection and early warning system and method, and relates to the technical field of coal unloading, and the system comprises a data collection module which obtains the position data of a coal unloading vehicle in real time through preset monitoring equipment, and outputs initial data; the preprocessing module is used for preprocessing the initial data to obtain first data; the data processing module receives and verifies the first data, outputs the first data meeting a preset verification condition as to-be-analyzed data, and processes and analyzes the to-be-analyzed data to obtain a first analysis result; and the early warning analysis module performs early warning analysis on the first analysis result to obtain an early warning analysis result, selects a coping strategy and a control instruction matched with the early warning analysis result from a preset result-strategy-instruction database, and regulates and controls the operation parameters of the coal unloading vehicle. The position data of the coal unloading vehicle is monitored in real time, the abnormal position and the abnormal dynamic state of the coal unloading vehicle are found in time, management and control measures are taken, and safe coal unloading operation is guaranteed.

Description

Technical Field

[0001] The present invention relates to the technical field of coal unloading, and in particular to a parking position detection and early warning system and method for a coal unloading vehicle. Background Art

[0002] Coal unloading trucks are special types of trucks used to transport and unload coal, such as dump trucks, train unloading trucks, port unloading trucks, etc., which are usually used in coal mines, thermal power plants, ports, etc. These vehicles are specially designed to transport large quantities of coal to meet the energy needs of different industries and play an important role in the transportation and unloading of coal. In the process of coal unloading trucks transferring coal, coal unloading truck positioning systems are often used to locate and query the coal unloading trucks in real time.

[0003] At present, the positioning system of coal unloading trucks generally adopts satellite positioning methods. Although the real-time position information of the coal unloading truck during operation can be obtained, the accuracy of its positioning data is low, and it is difficult to identify the abnormal small-range movement of the coal unloading truck during operation, and it is difficult to take timely remedial measures, which poses certain safety hazards.

[0004] Therefore, the present invention provides a coal unloading vehicle parking position detection and early warning system and method. Summary of the invention

[0005] The present invention provides a coal unloading vehicle parking position detection and early warning system and method, which are used to monitor the position data of the coal unloading vehicle in real time, promptly discover the abnormal position and abnormal dynamics of the coal unloading vehicle, and take control measures to ensure the safety of coal unloading operations.

[0006] On the one hand, the present invention provides a coal unloading vehicle parking position detection and early warning system, comprising: The data acquisition module is used to obtain the position data of the coal unloading vehicle in real time through the preset monitoring equipment and output the initial data; A preprocessing module, used to preprocess the initial data using a preset preprocessing method to obtain first data; a data processing module, configured to receive and verify the first data, output the first data satisfying a preset verification condition as data to be analyzed, and process and analyze the data to be analyzed using a preset data analysis model to obtain a first analysis result; The early warning analysis module is used to perform early warning analysis on the first analysis result to obtain the early warning analysis result, and select the response strategy and control instruction matching the early warning analysis result from the preset result-strategy-instruction database, and adjust the operating parameters of the coal unloading vehicle based on the response strategy and control instruction.

[0007] Preferably, the data acquisition module comprises: A demand acquisition submodule, used to acquire monitoring demand information, and acquire preset monitoring equipment matching the monitoring demand information based on a preset demand-equipment matching table; The data acquisition submodule is used to collect the position data of the coal unloading vehicle in real time based on the preset monitoring equipment and output the initial data.

[0008] Preferably, the data acquisition submodule includes: An image data acquisition unit, configured to acquire image data of the coal unloading vehicle in a preset area in real time based on the preset monitoring device, and output first monitoring data; A motion data monitoring unit, configured to obtain the motion data of the coal unloading vehicle in the preset area in real time based on the preset monitoring device, and output second monitoring data; A data aggregation unit is used to aggregate and output initial data based on the first monitoring data and the second monitoring data.

[0009] Preferably, the preprocessing module comprises: A method matching submodule, used for performing feature extraction on the initial data, constructing a first feature set, and acquiring a preset preprocessing method matching the first feature set based on a preset feature-method matching table; The preprocessing submodule is used to preprocess the initial data based on the preset preprocessing method to obtain the data to be extracted, and output the data to be extracted that meets the preset threshold condition as the first data.

[0010] Preferably, the preprocessing submodule includes: A denoising unit, used to denoise the initial data using a preset denoising method to obtain denoised data; A preprocessing unit, used for preprocessing the noise reduction data based on the preset preprocessing method to obtain data to be extracted; The data output unit is used to output the data to be extracted that meets the preset threshold condition as the first data.

[0011] Preferably, the data processing module includes: A data verification submodule, used for receiving the first data and performing data verification, and outputting the first data that meets the preset verification condition as data to be analyzed; A feature extraction submodule, used for extracting features from the data to be analyzed, and constructing a second feature set based on the extracted features; A factor matching submodule, used to obtain a model screening factor that matches each data feature in the second feature set in combination with a preset feature-factor matching table, and construct a screening factor set; A model matching submodule, used to select at least two first models matching the screening factor set in the model database in combination with a preset factor-model comparison table, and construct a model candidate library; The model selection submodule is used to obtain the self-selection instructions generated by the system and the input manual selection instructions, and select the preset data analysis model from the model candidate library in combination with the priority information corresponding to each instruction; A target recognition submodule, configured to perform recognition analysis on the data to be analyzed based on the preset data analysis model, and obtain a first recognition result corresponding to the coal unloading vehicle and a second recognition result corresponding to the surrounding environment of the coal unloading vehicle; A position data acquisition submodule, used to perform real-time analysis on the first recognition result and the second recognition result based on the preset data analysis model to obtain real-time position data of each coal unloading vehicle in a preset area; A prediction analysis submodule, configured to perform prediction analysis on the first recognition result and the second recognition result based on the preset data analysis model, and obtain predicted position data of each coal unloading vehicle in a preset area within a preset time period in the future; The comparison and analysis submodule is used to obtain the standard position data and the warning position data of each coal unloading vehicle, and compare and analyze the real-time position data and the predicted position data corresponding to each coal unloading vehicle, and summarize to obtain the first analysis result.

[0012] Preferably, the early warning analysis module includes: A data analysis submodule, used to analyze the first analysis result to obtain image position data and sensor position data of the coal unloading vehicle; A frame image acquisition submodule, used for dividing the image position data into frames, obtaining frame images, and constructing a frame image set; A frame analysis submodule, used for analyzing the position data of each coal unloading vehicle in the frame image set to obtain a frame image analysis result; A node data acquisition submodule is used to divide the sensor location data into time segments according to the time series characteristics in combination with the timestamp corresponding to the sensor location data, obtain the sensor location time node data corresponding to each time node, and construct a node data set; A node analysis submodule is used to analyze the position data of each coal unloading vehicle in the node data set to obtain a sensor time node analysis result; A trigger determination submodule is used to analyze the frame image analysis result and the sensor time node analysis result in combination with a preset warning trigger determination condition, and when any one of the frame image analysis result and the sensor time node analysis result meets the preset warning trigger determination condition, trigger a warning, and at the same time, output the frame image analysis result and the sensor time node analysis result as data to be warned; The early warning analysis submodule is used to perform early warning analysis on the data to be warned within a preset period of time and output the early warning analysis results; ; in, Indicates the warning analysis result; represents an image positioning error adjustment factor corresponding to the frame image analysis result; represents the sensor positioning error adjustment factor corresponding to the sensor time node analysis result; represents the logarithmic function; represents the consensus initial position of the coal unloading vehicle within a preset time period obtained based on the frame image analysis results and the sensor time node analysis results; Indicates the consensus real-time position of the coal unloading truck within a preset time period; represents the consensus predicted position of the coal unloading truck within a preset time period; Indicates that the coal unloading car starts from the consensus initial position To consensus real-time position The time difference between Indicates the real-time position of the coal unloading truck from the consensus To the consensus forecast position The time difference between Indicates that the coal unloading car starts from the consensus initial position To the consensus forecast position The time difference between Represents the initial position of the coal unloading car from the consensus To consensus real-time position The warning weight factor corresponding to the unit time position offset between ; Real-time position of coal unloading truck from consensus To the consensus forecast position The warning weight factor corresponding to the unit time position offset between ; Represents the initial position of the coal unloading car from the consensus To the consensus forecast position The warning weight factor corresponding to the unit time position offset between ; A strategy-instruction matching submodule, used to select a response strategy and a control instruction that matches the warning analysis result from the preset result-strategy-instruction database; The instruction execution submodule is used to adjust the operating parameters of the coal unloading vehicle and the operating parameters of related control equipment based on the response strategy and control instructions.

[0013] On the other hand, the present invention also provides a method for detecting and warning the parking position of a coal unloading vehicle, comprising: Step 1: Obtain the location data of the coal unloading vehicle in real time through the preset monitoring equipment and output the initial data; Step 2: preprocessing the initial data using a preset preprocessing method to obtain first data; Step 3: receiving and verifying the first data, outputting the first data that meets the preset verification condition as data to be analyzed, and processing and analyzing the data to be analyzed using a preset data analysis model to obtain a first analysis result; Step 4: Perform a warning analysis on the first analysis result to obtain a warning analysis result, and select a response strategy and control instruction that matches the warning analysis result from the preset result-strategy-instruction database, and adjust the operating parameters of the coal unloading vehicle based on the response strategy and control instruction.

[0014] The present invention provides a coal unloading vehicle parking position detection and early warning system and method, which can realize comprehensive monitoring and early warning analysis of the operation status of the coal unloading vehicle by real-time monitoring of the position data of the coal unloading vehicle and analyzing the vehicle status by using data processing and analysis models. Through the work of the early warning analysis module, the present invention can timely discover potential problems and take corresponding control measures, thereby improving the operation safety and efficiency of the coal unloading vehicle, reducing accident risks and improving production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are 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.

[0016] Figure 1 It is a schematic diagram of the framework of a coal unloading vehicle parking position detection and early warning system provided by an embodiment of the present invention; Figure 2 It is a flow chart of a method for detecting and warning the parking position of a coal unloading vehicle provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] like Figure 1As shown, a coal unloading vehicle parking position detection and early warning system provided by an embodiment of the present invention includes: The data acquisition module is used to obtain the position data of the coal unloading vehicle in real time through the preset monitoring equipment and output the initial data; A preprocessing module, used to preprocess the initial data using a preset preprocessing method to obtain first data; A data processing module is used to receive and verify the first data, output the first data that meets the preset verification condition as data to be analyzed, and use a preset data analysis model to process and analyze the data to be analyzed to obtain a first analysis result; The early warning analysis module is used to perform early warning analysis on the first analysis result, obtain the early warning analysis result, and select the response strategy and control instruction matching the early warning analysis result from the preset result-strategy-instruction database, and adjust the operating parameters of the coal unloading vehicle based on the response strategy and control instruction.

[0019] In this embodiment, the monitoring device is preset: a device for obtaining the position data of the coal unloading vehicle in real time, such as a camera, a Beidou / GPS positioning system, a laser rangefinder or other sensor device; In this embodiment, the position data: the current position coordinate information of the coal unloading vehicle, which is used to describe the specific position of the vehicle; In this embodiment, initial data refers to original position data obtained from a preset monitoring device, which has not been processed in any way; In this embodiment, the pre-processing method is preset: a method for processing the initial data, which may include data filtering, denoising, interpolation and other techniques to prepare the data for further analysis; In this embodiment, first data: data obtained after being processed by the preprocessing method, i.e., data ready for further analysis; In this embodiment, the preset verification condition is used to verify the condition of the first data to ensure the accuracy and reliability of the data; In this embodiment, the data to be analyzed: first data that meets the preset verification condition, data to be analyzed; In this embodiment, the preset data analysis model: a model or algorithm used to process and analyze the data to be analyzed, and used to generate a first analysis result; In this embodiment, the first analysis result: the result obtained by processing the data analysis model, including but not limited to information such as position offset, velocity, acceleration, etc.; In this embodiment, the early warning analysis result: further analyzing the first analysis result to determine whether there is an abnormal situation or a situation that requires early warning; In this embodiment, the preset result-strategy-instruction database: this is a database storing the response strategies and control instructions corresponding to different early warning analysis results; In this embodiment, the response strategy and control instructions: response measures and operation instructions selected from the database according to the early warning analysis results are used to adjust the operating parameters of the coal unloading vehicle to ensure safety and efficiency; In this embodiment, operating parameters are parameters used to describe and control the operating state of the coal unloading vehicle, such as speed, steering angle, acceleration, etc.

[0020] Implementation principle and beneficial effects of this embodiment: The present invention can realize comprehensive monitoring and early warning analysis of the operation status of the coal unloading vehicle by real-time monitoring of the position data of the coal unloading vehicle and analyzing the vehicle status by using data processing and analysis models. Through the work of the early warning analysis module, the present invention can timely discover potential problems and take corresponding control measures, thereby improving the operation safety and efficiency of the coal unloading vehicle, reducing accident risks and improving production efficiency.

[0021] The embodiment of the present invention provides a coal unloading vehicle parking position detection and early warning system, a data acquisition module, including: The demand acquisition submodule is used to acquire monitoring demand information and acquire preset monitoring equipment that matches the monitoring demand information based on the preset demand-equipment matching table; The data acquisition submodule is used to collect the position data of the coal unloading vehicle in real time based on the preset monitoring equipment and output the initial data.

[0022] In this embodiment, monitoring requirement information: the specific description or requirements of the user or system for monitoring requirements, including but not limited to requirements for monitoring frequency, accuracy, scope, etc.; In this embodiment, the preset requirement-equipment matching table is used to record the preset monitoring equipment corresponding to different monitoring requirements. Through the matching table, the system can automatically select the appropriate monitoring equipment according to the monitoring requirements.

[0023] The implementation principle and beneficial effects of this embodiment: The present invention can automatically match appropriate monitoring equipment according to the monitoring requirements of the user or system through the demand acquisition submodule and the preset demand-equipment matching table, thereby ensuring the accuracy and effectiveness of data collection. The present invention can save the user's time and energy through this automatic matching mechanism, while improving the intelligence level of the monitoring system. Through effective data collection and matching, it can better meet the user's monitoring needs and improve the practicality and efficiency of the coal unloading car parking position detection and early warning system.

[0024] The embodiment of the present invention provides a coal unloading vehicle parking position detection and early warning system, the data collection submodule includes: An image data acquisition unit, configured to acquire image data of the coal unloading vehicle in a preset area in real time based on a preset monitoring device, and output first monitoring data; A motion data monitoring unit, used for acquiring the motion data of the coal unloading vehicle in a preset area in real time based on a preset monitoring device, and outputting second monitoring data; The data aggregation unit is used to aggregate and output initial data based on the first monitoring data and the second monitoring data.

[0025] In this embodiment, preset area: a monitoring area preset by the system, which is used to limit the scope of the parking position detection and monitoring of the coal unloading vehicle; In this embodiment, the image data: image information of the coal unloading vehicle in a preset area acquired by a camera or other image acquisition device; In this embodiment, the first monitoring data refers to the data output by the image data acquisition unit, which is usually the image data of the coal unloading vehicle in a preset area; In this embodiment, motion data refers to various data generated by the coal unloading vehicle during its motion, such as speed, acceleration, steering angle, etc.; In this embodiment, the second monitoring data refers to the data output by the motion data monitoring unit, which is usually the motion data of the coal unloading vehicle in a preset area.

[0026] The implementation principle and beneficial effects of this embodiment: The present invention can simultaneously obtain the image data and motion data of the coal unloading vehicle in the preset area through the image data acquisition unit and the motion data monitoring unit, so as to comprehensively monitor the position and state of the vehicle, and then summarize the first monitoring data and the second monitoring data through the data summary unit, so as to provide more comprehensive information for further analysis and processing. The present invention can improve the monitoring precision and accuracy of the parking position of the coal unloading vehicle by the system, thereby improving the early warning effect and safety of the system, and helping to reduce potential safety risks.

[0027] The embodiment of the present invention provides a coal unloading vehicle parking position detection and early warning system, a preprocessing module, including: A method matching submodule, used to extract features from the initial data, construct a first feature set, and obtain a preset preprocessing method that matches the first feature set based on a preset feature-method matching table; The preprocessing submodule is used to preprocess the initial data based on a preset preprocessing method to obtain data to be extracted, and output the data to be extracted that meets a preset threshold condition as the first data.

[0028] In this embodiment, the first feature set refers to a feature set in the initial data extracted by the method matching submodule, which is used to describe the features and attributes of the data; In this embodiment, the preset feature-method matching table records the matching relationship between the preset features and the preprocessing methods. According to the first feature set, the system can select an appropriate preprocessing method from the matching table. For example, if the data feature is vehicle speed, the corresponding preprocessing method is smoothing filtering; if the data feature is vehicle position, the corresponding preprocessing method is coordinate conversion; if the data feature is load weight, the corresponding preprocessing method is peak monitoring. In this embodiment, the data to be extracted: data that meets the preset threshold condition after being processed by the preprocessing submodule can be used as input data for subsequent analysis and processing; In this embodiment, the preset threshold condition is a condition or restriction preset by the system, which is used to screen and filter the data to be extracted. Only the data satisfying these conditions will be output as the first data.

[0029] The implementation principle and beneficial effects of this embodiment: The present invention can select a suitable preprocessing method according to the feature set of the initial data through the method matching submodule and the preprocessing submodule, so as to extract the data to be extracted that meets the preset threshold conditions. The present invention helps to optimize the data quality and accuracy through the preprocessing process, improve the efficiency of subsequent analysis and processing, and at the same time, by setting the preset threshold conditions, it can effectively screen and extract important data, help to find problems in time and take corresponding early warning measures, thereby improving the practicality and reliability of the coal unloading car parking position detection and early warning system.

[0030] The embodiment of the present invention provides a coal unloading vehicle parking position detection and early warning system, the preprocessing submodule includes: A denoising unit, used to denoise the initial data using a preset denoising method to obtain denoised data; A preprocessing unit, used to preprocess the noise reduction data based on a preset preprocessing method to obtain data to be extracted; The data output unit is used to output the data to be extracted that meets the preset threshold condition as the first data.

[0031] In this embodiment, the preset noise reduction method: a method preset by the system for removing or reducing noise in the data to improve the quality and accuracy of the data; In this embodiment, denoised data refers to data obtained after being processed by a denoising unit, i.e., data with noise or interference removed. For example, the preset denoising method includes mean filtering and median filtering. The system can perform denoising on the initial data according to the preset denoising method. For example, for vehicle speed data, if there are some outliers or noise, the data can be smoothed by mean filtering or median filtering to remove outliers and obtain more reliable denoised data.

[0032] The implementation principle and beneficial effects of this embodiment: The present invention removes noise from the data through a noise reduction unit to improve the quality and reliability of the data. Then, the noise reduction data is further processed by the preprocessing unit according to a preset preprocessing method to obtain the data to be extracted. Finally, the data to be extracted that meets the preset threshold condition is output as the first data through the data output unit. The present invention helps to optimize the data quality, reduce the impact of interference and noise on the system, and improve the accuracy and reliability of the data. By setting the preset threshold condition, the system can effectively screen and extract important data.

[0033] The embodiment of the present invention provides a coal unloading vehicle parking position detection and early warning system, a data processing module, including: A data verification submodule, used for receiving the first data and performing data verification, and outputting the first data that meets the preset verification condition as data to be analyzed; A feature extraction submodule, used for extracting features from the data to be analyzed and constructing a second feature set based on the extracted features; A factor matching submodule is used to obtain a model screening factor that matches each data feature in the second feature set by combining a preset feature-factor matching table, and construct a screening factor set; A model matching submodule is used to select at least two first models matching the screening factor set in the model database in combination with a preset factor-model comparison table to construct a model candidate library; The model selection submodule is used to obtain the self-selection instructions generated by the system and the input manual selection instructions, and select the preset data analysis model from the model candidate library in combination with the priority information corresponding to each instruction; A target recognition submodule, used for performing recognition analysis on the data to be analyzed based on a preset data analysis model, and obtaining a first recognition result corresponding to the coal unloading vehicle and a second recognition result corresponding to the surrounding environment of the coal unloading vehicle; A position data acquisition submodule is used to perform real-time analysis on the first recognition result and the second recognition result based on a preset data analysis model to obtain real-time position data of each coal unloading vehicle in a preset area; A prediction analysis submodule, used to perform prediction analysis on the first recognition result and the second recognition result based on a preset data analysis model, and obtain the predicted position data of each coal unloading vehicle in a preset area within a preset time period in the future; The comparison and analysis submodule is used to obtain the standard position data and the warning position data of each coal unloading vehicle, and compare and analyze the real-time position data and the predicted position data corresponding to each coal unloading vehicle, and summarize to obtain the first analysis result.

[0034] In this embodiment, data verification: verifying the first data to ensure the integrity and accuracy of the data, and only outputting data that meets the preset verification conditions as the data to be analyzed; In this embodiment, the second feature set: a feature set extracted from the data to be analyzed, used to describe data features and data attributes of the data to be analyzed; In this embodiment, the preset feature-factor matching table is a table that records the matching relationship between the preset features and the model screening factors, which is preset. For example, the second feature set includes data features about vehicle speed and position information. The system selects acceleration and direction angle as model screening factors according to the preset feature-factor matching table. In this embodiment, the model screening factor: a model screening factor matched according to the data feature in the second feature set, used to select a suitable data analysis model in the model database; In this embodiment, the screening factor set refers to the set of model screening factors constructed; In this embodiment, the preset factor-model comparison table: a table recording the matching relationship between the preset factors and the data analysis model, which is preset; In this embodiment, the model database: a database storing various data analysis models; In this embodiment, the first model: a data analysis model selected from a model candidate library; In this embodiment, the model candidate library: a database including a plurality of first models; In this embodiment, self-selection instructions: instructions generated by the system, used to automatically select a model from the preset data analysis models, these instructions are generated based on system algorithms or logic; In this embodiment, manual selection instruction: an instruction input by a user, used to manually select a model from the preset data analysis models, and the user can select according to specific needs or situations; In this embodiment, priority information: the priority level of each instruction, used to determine the selection order of the system among multiple instructions; In this embodiment, the first recognition result: that is, the recognition result of the corresponding coal unloading vehicle obtained after the data to be analyzed is recognized and analyzed; In this embodiment, the second recognition result is the recognition result of the surrounding environment of the coal unloading vehicle obtained after the data to be analyzed is recognized and analyzed, for example, other mechanical equipment, staff, ground guide lines in a preset area, and obstacles around the coal unloading vehicle. In this embodiment, the real-time position data refers to the position data of the coal unloading vehicle obtained through real-time analysis; In this embodiment, the predicted position data refers to the position data of the coal unloading vehicle that may appear in a preset time period in the future obtained through predictive analysis; In this embodiment, standard position data: reference data used for comparative analysis, the standard position data represents the ideal or normal position data of the coal unloading vehicle when operating in a preset area; In this embodiment, warning position data: represents position data that requires attention or vigilance. It is assumed that the system selects a certain model according to the preset data analysis model, and after identification and analysis, the first identification result is "coal unloading truck A", and the second identification result is "the surrounding environment of coal unloading truck A is normal". The real-time position data shows that the coal unloading truck A is located at position B in the specified area, and the predicted position data shows that the coal unloading truck A will move westward from position B in the next 30 minutes. The standard position data requires that the coal unloading truck A should stop at position B, and the warning position data shows that there is a safety hazard in the range of 2 meters beyond position B.

[0035] The implementation principle and beneficial effects of this embodiment: The present invention can comprehensively analyze and predict the location data of the coal unloading vehicle through the synergy of sub-modules such as data verification, feature extraction, factor matching, and model matching, which helps the system to accurately identify the coal unloading vehicle and its surrounding environment, monitor the vehicle position in real time and perform predictive analysis to provide effective early warning and positioning information. By comparing and analyzing the real-time location data and the predicted location data, the present invention can promptly detect abnormal situations and take corresponding measures, thereby improving the accuracy and practicality of the coal unloading vehicle parking position detection and early warning system.

[0036] The embodiment of the present invention provides a coal unloading vehicle parking position detection and early warning system, and an early warning analysis module, including: A data analysis submodule, used to analyze the first analysis result to obtain image position data and sensor position data of the coal unloading vehicle; The frame image acquisition submodule is used to divide the image position data into frames, obtain frame images, and construct a frame image set; The frame analysis submodule is used to analyze the position data of each coal unloading vehicle in the frame image set to obtain the frame image analysis result; The node data acquisition submodule is used to combine the timestamp corresponding to the sensor location data, divide the sensor location data into time according to the time series characteristics, obtain the sensor location time node data corresponding to each time node, and construct a node data set; The node analysis submodule is used to analyze the position data of each coal unloading vehicle in the node data set to obtain the sensor time node analysis result; The trigger judgment submodule is used to analyze the frame image analysis results and the sensor time node analysis results in combination with the preset warning trigger judgment conditions. When any one of the frame image analysis results or the sensor time node analysis results meets the preset warning trigger judgment conditions, the warning is triggered. At the same time, the frame image analysis results and the sensor time node analysis results are comprehensively output as data to be warned. The early warning analysis submodule is used to perform early warning analysis on the data to be warned within a preset period of time and output the early warning analysis results; ; in, Indicates the warning analysis result; represents an image positioning error adjustment factor corresponding to the frame image analysis result; represents the sensor positioning error adjustment factor corresponding to the sensor time node analysis result; represents the logarithmic function; Indicates the consensus initial position of the coal unloading vehicle within a preset time period obtained based on the frame image analysis results and the sensor time node analysis results; Indicates the consensus real-time position of the coal unloading truck within a preset time period; represents the consensus predicted position of the coal unloading truck within a preset time period; Indicates that the coal unloading car starts from the consensus initial position To consensus real-time position The time difference between Indicates the real-time position of the coal unloading truck from the consensus To the consensus forecast position The time difference between Indicates that the coal unloading car starts from the consensus initial position To the consensus forecast position The time difference between Represents the initial position of the coal unloading car from the consensus To consensus real-time position The warning weight factor corresponding to the unit time position offset between ; Real-time position of coal unloading truck from consensus To the consensus forecast position The warning weight factor corresponding to the unit time position offset between ; Represents the initial position of the coal unloading car from the consensus To the consensus forecast position The warning weight factor corresponding to the unit time position offset between ; The strategy-instruction matching submodule is used to select the response strategy and control instruction that match the early warning analysis result from the preset result-strategy-instruction database; The instruction execution submodule is used to adjust the operating parameters of the coal unloading vehicle and the operating parameters of related control equipment based on the response strategy and control instructions.

[0037] In this embodiment, the image position data: that is, the image data including the position information of the coal unloading vehicle; In this embodiment, the sensor position data: that is, sensor data including position information of the coal unloading vehicle, for example, position data of the coal unloading vehicle obtained by a laser radar; In this embodiment, frame division: that is, the image position data is divided into a plurality of frames, each frame containing position information within a specific time period; In this embodiment, frame image: image data corresponding to a single frame; In this embodiment, the frame image set is a set consisting of multiple frame images within a certain time period; In this embodiment, the frame image analysis result is: the result obtained after analyzing the position data of each coal unloading vehicle in the frame image set; In this embodiment, the timestamp is used to mark the time information of the sensor location data, so as to help perform time division and comparative analysis on the sensor location data; In this embodiment, the sensor location time node data: location data at each time node obtained by dividing the sensor location data according to the timestamp; In this embodiment, the node data set is a set consisting of sensor location time node data corresponding to multiple time nodes; In this embodiment, the sensor time node analysis result: the result obtained by analyzing the position data of the coal unloading vehicle in the node data set; In this embodiment, the preset warning triggering judgment condition is used to judge whether the frame image analysis result or the sensor time node analysis result meets the condition for triggering the warning, which is preset. For example, when the position offset data of the coal unloading vehicle in 60 frames within 1 second in the frame image analysis result reaches 10 cm, the warning is triggered; In this embodiment, data to be warned: data to be analyzed for warning after the warning is triggered; In this embodiment, the regulating device is a device used to adjust the operating parameters of the coal unloading vehicle and the operating parameters of related equipment, for example, a device that controls the coal unloading vehicle to stop or change the moving direction.

[0038] The implementation principle and beneficial effects of this embodiment: Through the various submodules of the early warning analysis module, the system can comprehensively utilize image data and sensor data to analyze and warn the location information of the coal unloading vehicle, and then according to the preset early warning trigger judgment conditions, abnormal conditions can be discovered in time and early warnings can be triggered. Finally, the corresponding response strategies and control instructions are matched through the early warning analysis results to adjust the operating parameters of the coal unloading vehicle and the operating parameters of related equipment to ensure the safety and stability of the system operation. The present invention can accurately locate the position of the coal unloading vehicle in combination with image data and sensor data, and perform early warning analysis and risk response to ensure the effectiveness and reliability of the coal unloading vehicle parking position detection and early warning system.

[0039] A method for detecting and warning the parking position of a coal unloading vehicle provided by an embodiment of the present invention includes: Step 1: Obtain the location data of the coal unloading vehicle in real time through the preset monitoring equipment and output the initial data; Step 2: preprocessing the initial data using a preset preprocessing method to obtain first data; Step 3: Receive and verify the first data, output the first data that meets the preset verification condition as the data to be analyzed, and use the preset data analysis model to process and analyze the data to be analyzed to obtain a first analysis result; Step 4: Perform early warning analysis on the first analysis result to obtain the early warning analysis result, and select the response strategy and control instruction that match the early warning analysis result from the preset result-strategy-instruction database, and adjust the operating parameters of the coal unloading car based on the response strategy and control instruction.

[0040] Implementation principle and beneficial effects of this embodiment: The present invention can realize comprehensive monitoring and early warning analysis of the operation status of the coal unloading vehicle by real-time monitoring of the position data of the coal unloading vehicle and analyzing the vehicle status by using data processing and analysis models. The present invention can timely discover potential problems and risks in the location of the coal unloading vehicle through early warning analysis, and take corresponding control measures, thereby improving the operation safety and efficiency of the coal unloading vehicle, reducing accident risks and improving production efficiency.

[0041] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A coal unloading vehicle parking position detection and early warning system, characterized in that: include: The data acquisition module is used to obtain the position data of the coal unloading vehicle in real time through the preset monitoring equipment and output the initial data; A preprocessing module, used to preprocess the initial data using a preset preprocessing method to obtain first data; a data processing module, configured to receive and verify the first data, output the first data satisfying a preset verification condition as data to be analyzed, and process and analyze the data to be analyzed using a preset data analysis model to obtain a first analysis result; The early warning analysis module is used to perform early warning analysis on the first analysis result to obtain the early warning analysis result, and select the response strategy and control instruction matching the early warning analysis result from the preset result-strategy-instruction database, and adjust the operating parameters of the coal unloading vehicle based on the response strategy and control instruction.

2. A coal unloading vehicle parking position detection and early warning system according to claim 1, characterized in that: The data acquisition module comprises: A demand acquisition submodule, used to acquire monitoring demand information, and acquire preset monitoring equipment matching the monitoring demand information based on a preset demand-equipment matching table; The data acquisition submodule is used to collect the position data of the coal unloading vehicle in real time based on the preset monitoring equipment and output the initial data.

3. A coal unloading vehicle parking position detection and early warning system according to claim 1, characterized in that: The data acquisition submodule comprises: An image data acquisition unit, configured to acquire image data of the coal unloading vehicle in a preset area in real time based on the preset monitoring device, and output first monitoring data; A motion data monitoring unit, configured to obtain the motion data of the coal unloading vehicle in the preset area in real time based on the preset monitoring device, and output second monitoring data; A data aggregation unit is used to aggregate and output initial data based on the first monitoring data and the second monitoring data.

4. A coal unloading vehicle parking position detection and early warning system according to claim 1, characterized in that: The preprocessing module comprises: A method matching submodule, used for performing feature extraction on the initial data, constructing a first feature set, and acquiring a preset preprocessing method matching the first feature set based on a preset feature-method matching table; The preprocessing submodule is used to preprocess the initial data based on the preset preprocessing method to obtain the data to be extracted, and output the data to be extracted that meets the preset threshold condition as the first data.

5. A coal unloading vehicle parking position detection and early warning system according to claim 4, characterized in that: The preprocessing submodule comprises: A denoising unit, used to denoise the initial data using a preset denoising method to obtain denoised data; A preprocessing unit, used for preprocessing the noise reduction data based on the preset preprocessing method to obtain data to be extracted; The data output unit is used to output the data to be extracted that meets the preset threshold condition as the first data.

6. A coal unloading vehicle parking position detection and early warning system according to claim 1, characterized in that: The data processing module comprises: A data verification submodule, used for receiving the first data and performing data verification, and outputting the first data that meets the preset verification condition as data to be analyzed; A feature extraction submodule, used for extracting features from the data to be analyzed, and constructing a second feature set based on the extracted features; A factor matching submodule, used to obtain a model screening factor that matches each data feature in the second feature set in combination with a preset feature-factor matching table, and construct a screening factor set; A model matching submodule, used to select at least two first models matching the screening factor set in the model database in combination with a preset factor-model comparison table, and construct a model candidate library; The model selection submodule is used to obtain the self-selection instructions generated by the system and the input manual selection instructions, and select the preset data analysis model from the model candidate library in combination with the priority information corresponding to each instruction; A target recognition submodule, configured to perform recognition analysis on the data to be analyzed based on the preset data analysis model, and obtain a first recognition result corresponding to the coal unloading vehicle and a second recognition result corresponding to the surrounding environment of the coal unloading vehicle; A position data acquisition submodule, used to perform real-time analysis on the first recognition result and the second recognition result based on the preset data analysis model to obtain real-time position data of each coal unloading vehicle in a preset area; A prediction analysis submodule, configured to perform prediction analysis on the first recognition result and the second recognition result based on the preset data analysis model, and obtain predicted position data of each coal unloading vehicle in a preset area within a preset time period in the future; The comparison and analysis submodule is used to obtain the standard position data and the warning position data of each coal unloading vehicle, and compare and analyze the real-time position data and the predicted position data corresponding to each coal unloading vehicle, and summarize to obtain the first analysis result.

7. A coal unloading vehicle parking position detection and early warning system according to claim 1, characterized in that: The early warning analysis module includes: A data analysis submodule, used to analyze the first analysis result to obtain image position data and sensor position data of the coal unloading vehicle; A frame image acquisition submodule, used for dividing the image position data into frames, obtaining frame images, and constructing a frame image set; A frame analysis submodule, used for analyzing the position data of each coal unloading vehicle in the frame image set to obtain a frame image analysis result; A node data acquisition submodule is used to divide the sensor location data into time segments according to the time series characteristics in combination with the timestamp corresponding to the sensor location data, obtain the sensor location time node data corresponding to each time node, and construct a node data set; A node analysis submodule is used to analyze the position data of each coal unloading vehicle in the node data set to obtain a sensor time node analysis result; A trigger determination submodule is used to analyze the frame image analysis result and the sensor time node analysis result in combination with a preset warning trigger determination condition, and when any one of the frame image analysis result and the sensor time node analysis result meets the preset warning trigger determination condition, trigger a warning, and at the same time, output the frame image analysis result and the sensor time node analysis result as data to be warned; The early warning analysis submodule is used to perform early warning analysis on the data to be warned within a preset period of time and output the early warning analysis results; ； in, Indicates the warning analysis result; represents an image positioning error adjustment factor corresponding to the frame image analysis result; represents the sensor positioning error adjustment factor corresponding to the sensor time node analysis result; represents the logarithmic function; represents the consensus initial position of the coal unloading vehicle within a preset time period obtained based on the frame image analysis results and the sensor time node analysis results; Indicates the consensus real-time position of the coal unloading truck within a preset time period; represents the consensus predicted position of the coal unloading truck within a preset time period; Indicates that the coal unloading car starts from the consensus initial position To consensus real-time position The time difference between Indicates the real-time position of the coal unloading truck from the consensus To the consensus forecast position The time difference between Indicates that the coal unloading car starts from the consensus initial position To the consensus forecast position The time difference between Represents the initial position of the coal unloading car from the consensus To consensus real-time position The warning weight factor corresponding to the unit time position offset between ; Real-time position of coal unloading truck from consensus To the consensus forecast position The warning weight factor corresponding to the unit time position offset between ; Represents the initial position of the coal unloading car from the consensus To the consensus forecast position The warning weight factor corresponding to the unit time position offset between ; A strategy-instruction matching submodule, used to select a response strategy and a control instruction that matches the warning analysis result from the preset result-strategy-instruction database; The instruction execution submodule is used to adjust the operating parameters of the coal unloading vehicle and the operating parameters of related control equipment based on the response strategy and control instructions.

8. A method for detecting and warning the parking position of a coal unloading vehicle, characterized in that: include: Step 1: Obtain the location data of the coal unloading vehicle in real time through the preset monitoring equipment and output the initial data; Step 2: preprocessing the initial data using a preset preprocessing method to obtain first data; Step 3: receiving and verifying the first data, outputting the first data that meets the preset verification condition as data to be analyzed, and processing and analyzing the data to be analyzed using a preset data analysis model to obtain a first analysis result; Step 4: Perform a warning analysis on the first analysis result to obtain a warning analysis result, and select a response strategy and control instruction that matches the warning analysis result from the preset result-strategy-instruction database, and adjust the operating parameters of the coal unloading vehicle based on the response strategy and control instruction.

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