Mine elimination simulation training method and system based on acousto-optic combination

Abstract

The invention discloses a mine clearance simulation training method and system based on acousto-optic combination, and relates to the technical field of mine clearance training, an interference analysis module calculates a signal interference degree coefficient Gcxs by analyzing the signal interference conditions of trainees in different detection states, and can timely mark the signal interference degree coefficient Gcxs as wrong detection when the signal interference degree coefficient Gcxs exceeds a preset threshold value, thereby improving the detection accuracy. By means of the function, the system can rapidly recognize serious interference signals caused by misoperation. The capability evaluation module inputs the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs into a comprehensive evaluation model, carries out linear normalization processing on the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs, and then fits a comprehensive comparison index Zbzs, and the model can accurately evaluate the processing capability of trainees in mine clearance simulation training, and can also compare the processing capability with a preset evaluation threshold value Q, so that the processing capability of the trainees in mine clearance simulation training can be accurately evaluated. The system helps a teacher to make a scientific comprehensive judgment on the ability level of the student, and generates a corresponding teaching guide according to a judgment result.

Description

Technical Field

[0001] The invention relates to the technical field of mine clearance training, and in particular to a mine clearance simulation training method and system based on the combination of sound and light. Background Art

[0002] Mine clearance simulation training belongs to the field of military training and safety engineering, involving the cultivation and evaluation of skills in detecting and identifying mines, and operating mine clearance equipment. Traditional mine clearance training mostly uses physical models and simulated scenarios, but with the development of technology, mine clearance simulation training based on multiple sensory feedback has gradually become the mainstream trend. The mine clearance simulation training system based on the combination of sound and light further improves the accuracy of mine clearance operations and the students' response capabilities. This system uses sound and light combined feedback technology, and uses buzzers, voice prompts, LED indicators, display screens and other devices to provide real-time feedback on the students' detection behavior, making the training more vivid and realistic, and deepening the students' understanding and response capabilities of different signal interferences during mine detection.

[0003] In the process of demining simulation training based on the combination of sound and light, the analysis and judgment of the trainees' signal interference processing ability during training is an important part of the system design. However, the current demining simulation training system still has some shortcomings in practical applications. Traditional systems often lack detailed analysis of trainees' performance under signal interference conditions, making it difficult to accurately measure and provide feedback on trainees' detection capabilities under different interference environments. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a mine clearance simulation training method and system based on the combination of sound and light, which solves the problems in the above-mentioned background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a mine clearance simulation training system based on the combination of sound and light, including a training simulation module, a training monitoring module, a data processing module, an interference analysis module, an sound and light feedback module and a capability evaluation module; The training simulation module is used to simulate and deploy a mine clearance training area in advance, deploy several groups of mines and interference components in the mine clearance training area, and obtain the mine signals detected under the standard state; The training monitoring module is used to arrange trainees to enter the mine clearance training area for mine clearance training, monitor the trainees' behavior data through monitoring equipment, and based on the trainees' behavior data, monitor the relevant signal status data presented by the trainees using detectors at different locations; The data processing module is used to pre-process the behavior data and related signal state data of the trainees, and after linear normalization, map the corresponding data values ​​to the interval [0,1]; The interference analysis module is used to analyze the interference of the signals of each student under different detection states according to the student's behavior data and related signal state data, so as to analyze and calculate the signal interference degree coefficient Gcxs. If the signal interference degree coefficient Gcxs exceeds a preset threshold, it is marked as an error detection; The acoustic and optical feedback module is used to monitor the trainees' feedback on the corresponding detection behavior through voice prompts and optical signals according to the signal frequency characteristics detected by the trainees using the detector, so as to obtain relevant trainee feedback data, and analyze the feedback status of the trainees under different signal interference conditions according to the relevant trainee feedback data, so as to construct the judgment coefficient Pdxs; The capability evaluation module is used to input the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs into the trained comprehensive evaluation model, and after linear normalization processing, fit the comprehensive comparison index Zbzs, and compare the comprehensive comparison index Zbzs with the preset evaluation threshold Q to comprehensively judge the processing ability of the corresponding trainees in the mine clearance simulation training process, and generate corresponding training teaching orientation based on the corresponding judgment results.

[0006] Preferably, the training simulation module includes an environment simulation unit and a standard signal acquisition unit; The environmental simulation unit is used to preselect a simulated mine clearance training area, deploy various mine laying scenarios in the mine clearance training area, and lay several groups of mines and interference components, while recording the setting positions and burial depths of the mines and interference components at each position, wherein the interference components include metal waste, stones, underground pipes, shrapnel and jammers; The standard signal acquisition unit is used to perform standard detection of various mines based on the environment simulation unit using a detector according to the mine clearance instructor to detect the mine signals at the corresponding mines and perform statistics to generate a standard signal set.

[0007] Preferably, the training monitoring module includes a first data acquisition unit and a second data acquisition unit; The first data acquisition unit is used to monitor the trainees' behavior data in real time using monitoring equipment during the trainees' mine clearance training, wherein the behavior data includes the detection time of each trainee at each mine in the mine training area, the distance between the detection point and the specific location of the mine, and the detection angle; The second data acquisition unit is used to monitor the relevant signal status data presented by the trainees using the detector at different locations based on the behavioral data, wherein the relevant signal status data includes the mine signals detected by the trainees using the detector at different locations due to environmental interference delays.

[0008] Preferably, the data processing module includes a preprocessing unit and a standardization unit; The preprocessing unit is used to preprocess the behavior data and related signal state data of the trainees, the preprocessing includes removing noise, filling missing values ​​and data smoothing operations, and generating a training data set from the preprocessed behavior data and related signal state data of the trainees, wherein the missing value filling methods include mean filling, median filling, interpolation filling and regression filling; The standardization unit is used to scale the information in the training data set using a dimensionless processing technique so that the range of the information in the training data set falls between 0 and 1.

[0009] Preferably, the interference analysis module includes a signal interference analysis unit and an assessment and judgment unit; The signal interference analysis unit is used to analyze the interference of the signals of each student under different detection states according to the student's behavior data and related signal state data, so as to analyze and calculate the signal interference degree coefficient Gcxs, which is obtained specifically in the following manner: ; Where j = 1, 2, 3, ..., n, n represents the end point of signal collection at the corresponding mine, It represents the mine signal detected by the mine-clearing instructor when he is at the closest distance to the corresponding mine. It is represented by the delay caused by environmental interference when the trainee is at a distance j from the corresponding mine. Detected mine signals.

[0010] Preferably, the assessment judgment unit is used to pre-set a distortion threshold W, and compare and analyze the signal interference degree coefficient Gcxs with the distortion threshold W to determine whether the trainee has a detection error when detecting the corresponding mine. The specific contents are as follows: If the signal interference degree coefficient Gcxs exceeds the distortion threshold W, it will be judged that the trainee has a detection error when detecting the corresponding mine, and the detection of the corresponding mine will be marked as an erroneous detection; If the signal interference degree coefficient Gcxs does not exceed the distortion threshold W, it will be judged that the trainee did not make any detection errors when detecting the corresponding mine.

[0011] Preferably, the acoustic-optical feedback module comprises an acoustic-optical unit, a collection unit and a feedback analysis unit; The acousto-optic unit is used to provide real-time feedback to the trainee through voice prompts and optical signals according to the signal frequency characteristics detected by the trainee using the detector; The acquisition unit is used to monitor the trainees' feedback on the corresponding detection behavior in real time during the trainees' mine clearance simulation training to obtain relevant trainee feedback data, wherein the relevant trainee feedback data includes the feedback results of mine identification by each trainee in the mine clearance training area, and the feedback results include the existence of mines at specific locations and the existence of interference components at specific locations. Based on the feedback results, the missed reporting rate of each trainee in the mine clearance training is calculated. , false alarm rate and detection reaction time .

[0012] Preferably, the feedback analysis unit is used to analyze the feedback status of the students under different signal interference conditions according to the relevant student feedback data, and construct a judgment coefficient Pdxs after linear normalization processing. The judgment coefficient Pdxs is specifically obtained in the following manner: ; In the formula, Expressed as the false alarm rate, It is expressed as the false negative rate, It is represented as the detection reaction time, Expressed as the first correction constant, and are weight values, among which, and The specific value is set by the user according to the situation.

[0013] Preferably, the capability evaluation module includes a comprehensive evaluation unit and a comparison unit; The comprehensive evaluation unit is used to construct a comprehensive evaluation model using convolutional neural network technology, and to obtain a comprehensive comparison index Zbzs by fitting the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs, which is specifically obtained in the following manner: ; In the formula, and are weight values, Expressed as the second correction constant, where and The specific value is set by the user according to the situation; The comparison unit is used to compare and analyze the comprehensive comparison index Zbzs with the preset evaluation threshold Q to comprehensively judge the processing ability of the corresponding trainees during the mine clearance simulation training. The specific judgment content is as follows: If the comprehensive comparison index Zbzs exceeds the evaluation threshold Q, it will be comprehensively judged that the corresponding trainee's processing ability during the mine clearance simulation training is at a qualified level. At this time, a No. 1 teaching instruction will be issued and fed back to the terminal of the mine clearance instructor. The mine clearance instructor will continue to change and add interference factors in the simulated training environment, set time limit requirements, and divide qualified trainees into groups to compete in mine clearance tasks; If the comprehensive comparison index Zbzs does not exceed the evaluation threshold Q, it will be comprehensively judged that the processing ability of the corresponding trainee during the mine clearance simulation training is not at a qualified level. At this time, a No. 2 teaching instruction will be issued and fed back to the terminal of the mine clearance instructor. The mine clearance instructor will conduct targeted intensive training for the trainees, focusing on training the corresponding trainees' ability to recognize common signal patterns, replaying the trainees' erroneous operations during the training process, and cooperating with the mine clearance instructor's explanation to let the trainees understand the specific reasons for their errors and improvement methods.

[0014] A mine clearance simulation training method based on the combination of sound and light, comprising the following steps: S1. Pre-simulate and deploy a mine clearance training area, deploy several groups of mines and jamming components in the mine clearance training area, and obtain the mine signals detected under standard conditions; S2. Arrange trainees to enter the mine clearance training area for mine clearance training, monitor trainees' behavior data through monitoring equipment, and based on the trainees' behavior data, monitor relevant signal status data presented by the trainees using detectors at different locations; S3, preprocessing the trainee's behavior data and related signal state data, and after linear normalization, mapping the corresponding data values ​​to the interval [0,1]; S4. Analyze the interference of the signals of each student under different detection states according to the student's behavior data and related signal state data, so as to analyze and calculate the signal interference degree coefficient Gcxs. If the signal interference degree coefficient Gcxs exceeds the preset threshold, it is marked as an error detection. S5. According to the signal frequency characteristics detected by the trainee using the detector, the trainee is fed back in real time through voice prompts and optical signals, and the trainee's feedback on the corresponding detection behavior is monitored to obtain relevant trainee feedback data, and the trainee's feedback status under different signal interference conditions is analyzed according to the relevant trainee feedback data to construct the judgment coefficient Pdxs; S6. Input the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs into the trained comprehensive evaluation model, and after linear normalization, fit the comprehensive comparison index Zbzs, and compare the comprehensive comparison index Zbzs with the preset evaluation threshold Q to comprehensively judge the processing ability of the corresponding trainees in the mine clearance simulation training, and generate corresponding training teaching orientation based on the corresponding judgment results.

[0015] The present invention provides a mine clearance simulation training method and system based on the combination of sound and light, which has the following beneficial effects: (1) Through the training simulation module, the system can pre-deploy several groups of mines and interference components in the mine clearance training area, providing a training scenario that is highly similar to the actual operation environment. This realistic simulation environment helps trainees adapt to the complex situations that may be encountered in real mine clearance operations more quickly, and improves the trainees' adaptability and operation level. The training monitoring module uses monitoring equipment to track the trainees' behavior data and the signal status when using the detector in different locations in real time. This precise behavior monitoring can help instructors understand the trainees' detection behavior in a timely manner, thereby providing trainees with more targeted guidance, avoiding ineffective training repetitions, improving training efficiency, and facilitating testing of trainees' signal recognition and interference filtering capabilities. The interference analysis module calculates the signal interference degree coefficient Gcxs by analyzing the signal interference of trainees under different detection states, and can promptly mark it as an error detection when it exceeds the preset threshold. This function enables the system to quickly identify serious interference signals caused by incorrect operations. The sound and light feedback module provides real-time feedback on the trainees' responses to different signals during the detection process in the form of voice prompts and light signals. This multimodal feedback can not only intuitively guide the trainees to perform correct detection behaviors, but also analyze the trainees' responses when they are interfered with by signals, which helps to improve the trainees' ability to identify abnormal signals. The ability evaluation module inputs the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs into the comprehensive evaluation model, and after linear normalization, it fits the comprehensive comparison index Zbzs. This model can not only accurately evaluate the trainees' processing ability in the mine clearance simulation training, but also compare it with the preset evaluation threshold Q, helping the instructor to make a scientific and comprehensive judgment on the trainees' ability level, and generate corresponding teaching guidance based on the judgment results. According to the comparison results of the comprehensive comparison index Zbzs, the system can generate targeted teaching instructions for trainees of different levels. This personalized training guidance helps to improve the trainees' weaknesses in a targeted manner, so that each trainee can make progress in the simulation training. Overall, the system further realizes a closed-loop training process from training simulation to capability assessment through multi-level data analysis, intelligent feedback mechanism and personalized teaching guidance, thereby maximizing the accuracy and effectiveness of mine clearance simulation training.

[0016] (2) The interference analysis module can quantify the signal interference coefficient of the trainees under different detection conditions through the calculation of the signal interference analysis unit, thereby identifying the signal interference caused by environmental factors (such as metal waste, stones, underground pipes and other interference objects). This quantitative analysis enables the system to more accurately evaluate the impact of interference on the trainees' detection ability and provide reliable data support for subsequent judgments. Through the distortion threshold set by the assessment judgment unit, the system can quickly determine whether the trainees have made detection errors during the detection process. When the signal interference coefficient exceeds the distortion threshold, the system will automatically mark it as an error detection. This judgment mechanism ensures that the trainees' erroneous detection behavior can be identified and corrected in time during the simulation training, improving the effectiveness of the training process and the accuracy of judgment. When the trainees make erroneous detection behaviors during the detection process, the training content can be designed in a targeted manner according to the numerical difference of their interference coefficients to help the trainees gradually improve their detection capabilities in complex environments. This dynamic adjustment mechanism can not only optimize the trainees' learning path, but also significantly improve the trainees' comprehensive response capabilities in actual mine clearance tasks.

[0017] (3) The acoustic and optical feedback module can help trainees quickly identify the detection status under different signal interference conditions through multi-dimensional analysis of detection behavior. Through repeated training, trainees can develop a keen judgment ability for specific frequencies and signal characteristics. This ability is extremely critical for rapid decision-making and response in actual mine clearance tasks, and can further enhance trainees' response and handling capabilities in actual combat.

[0018] (4) By calculating the comprehensive comparison index and comparing it with the pre-set evaluation threshold, the training content can be adjusted in real time according to the trainee's performance. When it exceeds the threshold, the trainee's ability is assessed as qualified and they are divided into groups to carry out competition tasks to stimulate teamwork and competition awareness. For trainees who do not meet the standards, personalized intensive training will be implemented, accompanied by detailed explanations and playback analysis by the mine clearance instructor. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a block diagram of a mine clearance simulation training system based on the combination of sound and light in the present invention; Figure 2 The present invention is a flowchart of a mine clearance simulation training method based on the combination of sound and light. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions 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. 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.

[0021] Example 1: Please refer to Figure 1 , the present invention provides a mine clearance simulation training system based on the combination of sound and light, a training simulation module, a training monitoring module, a data processing module, an interference analysis module, an sound and light feedback module and a capability evaluation module; The training simulation module is used to simulate and deploy a mine clearance training area in advance, deploy several groups of mines and interference components in the mine clearance training area, and obtain the mine signals detected under the standard state; The training monitoring module is used to arrange trainees to enter the mine clearance training area for mine clearance training, monitor the trainees' behavior data through monitoring equipment, and based on the trainees' behavior data, monitor the relevant signal status data presented by the trainees using detectors at different locations; The data processing module is used to pre-process the behavior data and related signal state data of the trainees, and after linear normalization, map the corresponding data values ​​to the interval [0,1]; The interference analysis module is used to analyze the interference of the signals of each student under different detection states according to the student's behavior data and related signal state data, so as to analyze and calculate the signal interference degree coefficient Gcxs. If the signal interference degree coefficient Gcxs exceeds a preset threshold, it is marked as an error detection; The acoustic and optical feedback module is used to monitor the trainees' feedback on the corresponding detection behavior through voice prompts and optical signals according to the signal frequency characteristics detected by the trainees using the detector, so as to obtain relevant trainee feedback data, and analyze the feedback status of the trainees under different signal interference conditions according to the relevant trainee feedback data, so as to construct the judgment coefficient Pdxs; The capability evaluation module is used to input the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs into the trained comprehensive evaluation model, and after linear normalization processing, fit the comprehensive comparison index Zbzs, and compare the comprehensive comparison index Zbzs with the preset evaluation threshold Q to comprehensively judge the processing ability of the corresponding trainees in the mine clearance simulation training process, and generate corresponding training teaching orientation based on the corresponding judgment results.

[0022] During the operation of this system, the system pre-simulates and deploys the mine clearance training area in the training simulation module, deploys mines and interference components, and obtains mine signals under standard conditions, so that trainees can conduct mine clearance training in an environment that highly restores the real scene. This simulation environment not only improves the authenticity of the training, but also helps trainees to exercise their detection capabilities and coping skills under complex and changing conditions. Through the design of the training monitoring module, the system can collect the trainees' behavior data and signal status data in real time, and pre-process and normalize these data in combination with the data processing module to ensure the consistency and standardization of the data, so that the trainees' detection behavior data during the training process can more accurately reflect their actual operation conditions, and analyze their performance in detail under different detection conditions; the interference analysis module effectively identifies the trainees' erroneous detection behavior when the signal is interfered by calculating the signal interference degree coefficient Gcxs, thereby improving the system's judgment accuracy on the detection behavior. The sound and light feedback module provides instant feedback to trainees through sound prompts (such as voice prompts) and light signals (such as LED indicators), so that they can understand the accuracy of their detection in real time during the detection process and make adjustments based on the feedback. This diversified feedback method not only improves the trainees' sensitivity to detection signals, but also helps them make faster and more accurate responses in complex interference environments. Finally, the ability evaluation module comprehensively considers the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs, and inputs them into the trained comprehensive evaluation model to generate a comprehensive comparison index Zbzs. The system compares this index with the preset evaluation threshold Q to accurately evaluate the trainees' processing capabilities during the mine clearance simulation training and generate corresponding training and teaching guidance. This comprehensive evaluation process can adjust the training strategy in a timely manner according to the trainees' actual detection performance, help trainees improve their mine clearance skills in a targeted manner, and further improve the effectiveness and efficiency of mine clearance training.

[0023] Example 2: Please refer to Figure 1 ,Specifically: the training simulation module includes an environment simulation unit and a standard signal acquisition unit; The environmental simulation unit is used to pre-select a simulated mine clearance training area, and deploy various mine laying scenarios in the mine clearance training area, such as sand, grass, soil, concrete ground and other environments, and bury several groups of mines and interference components, and record the setting position and burial depth of the mines and interference components at each position, wherein the interference components include metal waste, stones, underground pipes, shrapnel and jammers; The standard signal acquisition unit is used to perform standard detection of various mines based on the environment simulation unit using a detector according to the mine clearance instructor to detect the mine signals at the corresponding mines and perform statistics to generate a standard signal set.

[0024] The training monitoring module includes a first data acquisition unit and a second data acquisition unit; The first data acquisition unit is used to monitor the trainees' behavior data in real time using monitoring equipment during the trainees' mine clearance training, wherein the behavior data includes the detection time of each trainee at each mine in the mine training area, the distance between the detection point and the specific location of the mine, and the detection angle; The second data acquisition unit is used to monitor the relevant signal status data presented by the trainees using the detector at different locations based on the behavioral data, wherein the relevant signal status data includes the mine signals detected by the trainees using the detector at different locations due to environmental interference delays.

[0025] The data processing module includes a preprocessing unit and a standardization unit; The preprocessing unit is used to preprocess the behavior data and related signal state data of the trainees, the preprocessing includes removing noise, filling missing values ​​and data smoothing operations, and generating a training data set from the preprocessed behavior data and related signal state data of the trainees, wherein the missing value filling methods include mean filling, median filling, interpolation filling and regression filling; The standardization unit is used to scale the information in the training data set using a dimensionless processing technique so that the range of the information in the training data set falls between 0 and 1.

[0026] In this embodiment, the environment simulation unit in the training simulation module can deploy various mine laying scenes in the simulated mine clearance training area according to actual operation requirements, including sand, grass, soil and concrete ground, and bury mines and interference components at the same time. The simulated deployment of different ground conditions and interference objects (such as metal scraps, stones, underground pipes, etc.) helps trainees experience a variety of complex operating environments during training, which effectively improves the adaptability and processing ability of trainees in mine clearance in different scenarios. The standard signal acquisition unit generates a standard signal set through standard detection by the mine clearance instructor using a detector. This process ensures that the signal acquisition in different simulation environments has consistency and standardization, so that the signals detected by the trainees in training can be compared with the standard signals, and the success rate and error of mine clearance detection can be accurately judged, which helps to improve the trainees' ability to identify the detection signal and reduce the misjudgment and missed judgment during the detection process. The first data acquisition unit in the training monitoring module can monitor the trainees' behavior data in real time, such as detection time, the distance between the detection point and the mine position, and the detection angle. Through the precise collection of these behavioral data, the system can comprehensively analyze the detection efficiency and operation mode of the trainees during the training process, and provide accurate data support for subsequent ability evaluation and training improvement. The second data acquisition unit monitors the signal state data detected by the trainees due to environmental interference when using the detector at different locations. These data include detection delay signals caused by interference. By analyzing these data, the degree of influence of different environmental interference on the detection effect of the trainees can be clarified, so as to identify the ability of each trainee to make correct judgments under different interference environments. The preprocessing unit in the data processing module efficiently preprocesses the trainees' behavioral data and signal state data by removing noise, filling missing values, and smoothing data. These data processing methods (such as mean filling, median filling, interpolation filling, regression filling, etc.) significantly improve the integrity and quality of the data, and provide a more reliable data basis for subsequent data analysis and model training. The standardization unit in the data processing module uses dimensionless processing technology to scale all training data sets so that the data range falls between 0 and 1. This standardization process can eliminate the scale differences between different data sources and ensure that the training model has consistency and comparability in processing different input data, thereby improving the generalization ability and prediction accuracy of the model. In short, the system achieves refined and standardized management of the training process through multi-level environmental simulation, multi-dimensional data monitoring and efficient data processing. The system can not only further identify the trainees' mine detection capabilities in complex environments, but also prepare for later training to reduce false alarms and misjudgments, thereby improving training efficiency and ultimately providing demining personnel with more scientific and accurate skills training.

[0027] Example 3: Please refer to Figure 1,Specifically: the interference analysis module includes a signal interference analysis unit and an assessment and judgment unit; The signal interference analysis unit is used to analyze the interference of the signals of each student under different detection states according to the student's behavior data and related signal state data, so as to analyze and calculate the signal interference degree coefficient Gcxs, which is obtained specifically in the following manner: ; Where j = 1, 2, 3, ..., n, n represents the end point of signal collection at the corresponding mine, It represents the mine signal detected by the mine-clearing instructor when he is at the closest distance to the corresponding mine. It is represented by the delay caused by environmental interference when the trainee is at a distance j from the corresponding mine. Detected mine signals.

[0028] The assessment judgment unit is used to pre-set the distortion threshold W, and compare and analyze the signal interference degree coefficient Gcxs with the distortion threshold W to determine whether the trainee has a detection error when detecting the corresponding mine. The specific contents are as follows: If the signal interference degree coefficient Gcxs exceeds the distortion threshold W, it will be judged that the trainee has a detection error when detecting the corresponding mine, and the detection of the corresponding mine will be marked as an erroneous detection; If the signal interference degree coefficient Gcxs does not exceed the distortion threshold W, it will be judged that the trainee did not make any detection errors when detecting the corresponding mine.

[0029] In this embodiment, through the signal interference analysis unit, the system can analyze the signal interference conditions of each student under different detection states according to the signal state data and behavior data collected by the students during the mine clearance process. The signal interference degree coefficient Gcxs is calculated by the formula, and the coefficient can accurately reflect the degree of interference of the detection signal. This accurate analysis method enables the system to identify the detection interference encountered by the students in a complex environment and help the students improve their detection ability. The assessment judgment unit can effectively judge whether there is a detection error when the students detect landmines by setting a distortion threshold and comparing the signal interference degree coefficient with the threshold. When it exceeds the threshold, the system can quickly identify the detection error and mark it as an error detection. This judgment method based on quantitative analysis can reduce the influence of human subjective factors on the judgment results and ensure that the judgment process is more objective and accurate. By analyzing the signal interference degree of the students in the detection process in real time, the system can provide timely and effective feedback to the students. In the case of detection errors, the students can understand the causes of the detection errors and the degree of interference according to the feedback information provided by the system, so as to adjust their own detection methods and strategies. This feedback mechanism helps the students to better master the mine clearance skills in actual operation and improve their ability to cope with complex interference environments.

[0030] Example 4: Please refer to Figure 1 , specifically: the acousto-optic feedback module includes an acousto-optic unit, a collection unit and a feedback analysis unit; The sound and light unit is used to provide real-time feedback to the trainees through voice prompts and light signals (such as LED indicator lights, display screens) based on the frequency characteristics of the signal detected by the trainees using the detector. This feedback mechanism helps the trainees to understand their detection status in real time and judge whether they have successfully detected mines or whether there are interfering components. The frequency characteristics of the detected signal can help judge the size and type of the target object. Specific frequencies may be associated with certain types of mines or metal objects. When the detector approaches the target mine, the sound of the buzzer will become louder and more rapid. If the signal strength detected by the detector is large, the buzzer will continue to emit high-frequency sounds.

[0031] The acquisition unit is used to monitor the trainees' feedback on the corresponding detection behavior in real time during the trainees' mine clearance simulation training to obtain relevant trainee feedback data, wherein the relevant trainee feedback data includes the feedback results of mine identification by each trainee in the mine clearance training area, and the feedback results include the existence of mines at specific locations and the existence of interference components at specific locations. Based on the feedback results, the missed reporting rate of each trainee in the mine clearance training is calculated. , false alarm rate and detection reaction time .

[0032] The feedback analysis unit is used to analyze the feedback status of the students under different signal interference conditions according to the relevant student feedback data, and construct a judgment coefficient Pdxs after linear normalization processing. The judgment coefficient Pdxs is specifically obtained in the following manner: ; In the formula, Expressed as the false alarm rate, It is expressed as the false negative rate, It is represented as the detection reaction time, Expressed as the first correction constant, and are weight values, among which, and The specific value is set by the user according to the situation.

[0033] The false positive rate mentioned above It refers to the ratio of the number of times the trainees incorrectly judged the interference components as mines to the total number of non-mine objects; False negative rate It refers to the ratio of the number of actual mines that trainees failed to detect to the number of mines actually laid during training; Detection reaction time It refers to the length of time it takes for students to give feedback when sound and light information is presented to them; In this embodiment, the sound and light unit uses voice prompts and light signals to provide real-time feedback on the detection situation of the trainees, helping the trainees understand the signal frequency characteristics detected by the detector. This feedback mechanism can provide a louder and more rapid beep when the trainees think they are close to the target mine. At the same time, when the signal strength is large, the buzzer will emit a high-frequency sound. This instant feedback helps the trainees to timely judge the existence of mines or interference components and improve the detection accuracy and efficiency. The collection unit monitors the feedback data of the trainees in the mine clearance training, including the missed alarm rate, the false alarm rate and the detection reaction time, so as to help evaluate the performance of the trainees in different scenarios. Through the collection of these specific data, the system can identify the deficiencies of the trainees in the mine clearance process and provide targeted training guidance. The comprehensive statistical analysis of the feedback data helps to quantify the detection ability of the trainees and find out the weak links that may exist in the actual operation. According to the feedback status of the trainees in the mine clearance simulation training, the feedback analysis unit constructs the judgment coefficient Pdxs through the analysis of the false alarm rate, the missed alarm rate and the detection reaction time to quantify the detection accuracy of the trainees in the face of different signal interference. By introducing correction constants and weight values, the system can flexibly adjust parameters according to actual training needs, so as to more accurately evaluate the detection level of trainees. This process is processed by linear normalization, making the evaluation data between different trainees more comparable, further improving the accuracy and objectivity of data evaluation. Through comprehensive analysis of the judgment coefficient Pdxs, the sound and light feedback module can further reduce the false alarm and missed alarm rate of trainees during the detection process. This refined data processing and feedback mechanism not only improves the judgment ability of trainees in mine clearance simulation training, but also effectively reduces the detection error rate in actual operation. Trainees can continuously adjust the detection strategy based on real-time feedback and gradually optimize the training results. In general, the sound and light feedback module further improves the detection ability and decision-making level of trainees in complex environments through multi-level interaction of real-time feedback, precise data collection and analysis, ensuring relatively good learning results in mine clearance simulation training, and providing scientific data support for training guidance.

[0034] Example 5: Please refer to Figure 1 ,Specifically: the capability evaluation module includes a comprehensive evaluation unit and a comparison unit; The comprehensive evaluation unit is used to construct a comprehensive evaluation model using convolutional neural network technology, and to obtain a comprehensive comparison index Zbzs by fitting the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs, which is specifically obtained in the following manner: ; In the formula, and are weight values, Expressed as the second correction constant, where and The specific value is set by the user according to the situation; The comparison unit is used to compare and analyze the comprehensive comparison index Zbzs with the preset evaluation threshold Q to comprehensively judge the processing ability of the corresponding trainees during the mine clearance simulation training. The specific judgment content is as follows: If the comprehensive comparison index Zbzs exceeds the evaluation threshold Q, it will be comprehensively judged that the corresponding trainee's processing ability in the demining simulation training is at a qualified level. At this time, a No. 1 teaching instruction will be issued and fed back to the terminal of the demining instructor. The demining instructor will continue to change and add interference factors in the simulated training environment, such as different types of mines, metal fragments or non-metallic materials, to enhance the trainee's detection ability, and set time limit requirements to force the trainee to make correct detection decisions in a shorter time to improve their quick judgment ability. At the same time, qualified trainees will be divided into groups to compete in demining tasks to stimulate their sense of cooperation and competition; If the comprehensive comparison index Zbzs does not exceed the evaluation threshold Q, it will be comprehensively judged that the processing ability of the corresponding trainee during the mine clearance simulation training is not at a qualified level. At this time, a No. 2 teaching instruction will be issued and fed back to the terminal of the mine clearance instructor. The mine clearance instructor will conduct targeted intensive training for the trainees, focusing on training the corresponding trainees to recognize common signal patterns, replay the trainees' erroneous operations during the training process, and cooperate with the mine clearance instructor's explanation to let the trainees understand the specific reasons for their errors and improvement methods. The instructor will provide one-on-one individual counseling for trainees who have not met the standards, explain the details and techniques that should be paid attention to during the detection process, introduce a phased evaluation mechanism in the training, regularly provide feedback on the trainees' training progress, and adjust the training content according to their performance.

[0035] In this embodiment, the comprehensive evaluation unit uses convolutional neural network technology to construct an evaluation model, and calculates the comprehensive comparison index Zbzs by fitting the judgment coefficient and the signal interference degree coefficient. This evaluation method combined with artificial intelligence technology can not only process complex nonlinear data, but also automatically adjust the weight parameters through the deep learning model, accurately capture the performance details of the trainees in the mine clearance simulation training, and thus achieve a higher precision evaluation of the trainees' abilities. The comparison unit divides the trainees into two groups, qualified and unqualified, according to the comparison results of the comprehensive comparison index and the preset evaluation threshold, and conducts different training instructions respectively. For qualified trainees, the system will issue a No. 1 teaching instruction to guide the mine clearance instructor to increase the difficulty of training, enhance the trainees' ability to cope with complex environments, and stimulate their cooperation and competition awareness through group competitions. For unqualified trainees, a No. 2 teaching instruction will be issued to arrange targeted intensive training and gradually improve under the guidance of the mine clearance instructor. The personalized training method can accurately improve the trainees' weaknesses, shorten their learning curve, and significantly improve their detection skills. Through the No. 1 instruction, the system encourages demining instructors to introduce more interference factors in the simulated training environment, such as different types of mines, metal fragments or non-metallic materials, and set time limits. This pressure environment can force trainees to make correct detection decisions in a shorter time and improve their ability to make quick judgments. This dynamic adaptive training method can enhance trainees' ability to cope with emergencies and psychological qualities in actual tasks, making them more calm when facing high-pressure environments. For trainees who do not meet the standards, the system arranges one-on-one individual counseling, combining the playback of incorrect operations during training with the explanations of demining instructors to help trainees identify and correct their shortcomings in the detection process. At the same time, a phased evaluation mechanism is introduced to regularly provide feedback on the progress of trainees' training and adjust the training content according to their performance. This not only helps trainees understand their own learning status in a timely manner, but also allows them to flexibly adjust the training plan according to actual conditions, thereby ensuring that each trainee can be targeted at each stage. Improvement. For qualified trainees whose comprehensive comparison index exceeds the threshold, the system further trains their cooperation ability and competitive awareness in actual operations through group competitions. This team competition not only improves the tacit understanding between trainees, but also promotes each trainee's active learning and positive progress in a fierce competitive atmosphere. The practical experience in team competitions will help trainees to collaborate with their peers more efficiently to complete detection tasks when performing actual tasks in the future. Through in-depth analysis of trainee performance data, the system can provide more scientific training guidance and decision-making support for demining instructors.In summary, the application of the capability evaluation module in mine clearance simulation training not only realizes the accurate assessment of trainees' capabilities through the intelligent evaluation model, but also comprehensively improves the trainees' detection skills and comprehensive response capabilities through personalized training guidance and feedback mechanism. The multi-dimensional analysis and dynamic adjustment capabilities of this module enable trainees to respond to complex situations more agilely in actual combat, thereby improving the overall success rate of mine clearance tasks.

[0036] Example 6: Please refer to Figure 2 , specifically: A mine clearance simulation training method based on the combination of sound and light, comprising the following steps, S1. Pre-simulate and deploy a mine clearance training area, deploy several groups of mines and jamming components in the mine clearance training area, and obtain the mine signals detected under standard conditions; S2. Arrange trainees to enter the mine clearance training area for mine clearance training, monitor trainees' behavior data through monitoring equipment, and based on the trainees' behavior data, monitor relevant signal status data presented by the trainees using detectors at different locations; S3. Preprocess the student's behavior data and related signal state data, and after linear normalization, map the corresponding data values ​​to the interval Inside; S4. Analyze the interference of the signals of each student under different detection states according to the student's behavior data and related signal state data, so as to analyze and calculate the signal interference degree coefficient Gcxs. If the signal interference degree coefficient Gcxs exceeds the preset threshold, it is marked as an error detection. S5. According to the signal frequency characteristics detected by the trainee using the detector, the trainee is fed back in real time through voice prompts and optical signals, and the trainee's feedback on the corresponding detection behavior is monitored to obtain relevant trainee feedback data, and the trainee's feedback status under different signal interference conditions is analyzed according to the relevant trainee feedback data to construct the judgment coefficient Pdxs; S6. Input the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs into the trained comprehensive evaluation model, and after linear normalization, fit the comprehensive comparison index Zbzs, and compare the comprehensive comparison index Zbzs with the preset evaluation threshold Q to comprehensively judge the processing ability of the corresponding trainees in the mine clearance simulation training, and generate corresponding training teaching orientation based on the corresponding judgment results.

[0037] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A mine clearance simulation training system based on the combination of sound and light, characterized by: It includes training simulation module, training monitoring module, data processing module, interference analysis module, sound and light feedback module and capability evaluation module; The training simulation module is used to simulate and deploy a mine clearance training area in advance, deploy several groups of mines and interference components in the mine clearance training area, and obtain the mine signals detected under the standard state; The training monitoring module is used to arrange trainees to enter the mine clearance training area for mine clearance training, monitor the trainees' behavior data through monitoring equipment, and based on the trainees' behavior data, monitor the relevant signal status data presented by the trainees using detectors at different locations; The data processing module is used to pre-process the trainee's behavior data and related signal state data, and after linear normalization, map the corresponding data values ​​to the interval [0,1]; The interference analysis module is used to analyze the interference of the signals of each student under different detection states according to the student's behavior data and related signal state data, so as to analyze and calculate the signal interference degree coefficient Gcxs. If the signal interference degree coefficient Gcxs exceeds a preset threshold, it is marked as an error detection; The acoustic and optical feedback module is used to monitor the trainees' feedback on the corresponding detection behavior through voice prompts and optical signals according to the signal frequency characteristics detected by the trainees using the detector, so as to obtain relevant trainee feedback data, and analyze the feedback status of the trainees under different signal interference conditions according to the relevant trainee feedback data, so as to construct the judgment coefficient Pdxs; The capability evaluation module is used to input the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs into the trained comprehensive evaluation model, and after linear normalization processing, fit the comprehensive comparison index Zbzs, and compare the comprehensive comparison index Zbzs with the preset evaluation threshold Q to comprehensively judge the processing ability of the corresponding trainees in the mine clearance simulation training process, and generate corresponding training teaching orientation based on the corresponding judgment results.

2. The mine clearance simulation training system based on the combination of sound and light according to claim 1 is characterized by: The training simulation module includes an environment simulation unit and a standard signal acquisition unit; The environmental simulation unit is used to preselect a simulated mine clearance training area, deploy various mine laying scenarios in the mine clearance training area, and lay several groups of mines and interference components, while recording the setting positions and burial depths of the mines and interference components at each position, wherein the interference components include metal waste, stones, underground pipes, shrapnel and jammers; The standard signal acquisition unit is used to perform standard detection of various mines based on the environment simulation unit using a detector according to the mine clearance instructor to detect the mine signals at the corresponding mines and perform statistics to generate a standard signal set.

3. The mine clearance simulation training system based on the combination of sound and light according to claim 2 is characterized by: The training monitoring module includes a first data acquisition unit and a second data acquisition unit; The first data acquisition unit is used to monitor the trainees' behavior data in real time using monitoring equipment during the trainees' mine clearance training, wherein the behavior data includes the detection time of each trainee at each mine in the mine training area, the distance between the detection point and the specific location of the mine, and the detection angle; The second data acquisition unit is used to monitor the relevant signal status data presented by the trainees using the detector at different locations based on the behavioral data, wherein the relevant signal status data includes the mine signals detected by the trainees using the detector at different locations due to environmental interference delays.

4. The mine clearance simulation training system based on the combination of sound and light according to claim 3 is characterized by: The data processing module includes a preprocessing unit and a standardization unit; The preprocessing unit is used to preprocess the behavior data and related signal state data of the trainees, the preprocessing includes removing noise, filling missing values ​​and data smoothing operations, and generating a training data set from the preprocessed behavior data and related signal state data of the trainees, wherein the missing value filling methods include mean filling, median filling, interpolation filling and regression filling; The standardization unit is used to scale the information in the training data set using a dimensionless processing technique so that the range of the information in the training data set falls between 0 and 1.

5. The mine clearance simulation training system based on the combination of sound and light according to claim 4 is characterized by: The interference analysis module includes a signal interference analysis unit and an assessment and judgment unit; The signal interference analysis unit is used to analyze the interference of the signals of each student under different detection states according to the student's behavior data and related signal state data, so as to analyze and calculate the signal interference degree coefficient Gcxs, which is obtained specifically in the following manner: ; Where j = 1, 2, 3, ..., n, n represents the end point of signal collection at the corresponding mine, It represents the mine signal detected by the mine-clearing instructor when he is at the closest distance to the corresponding mine. It is represented by the delay caused by environmental interference when the trainee is at a distance j from the corresponding mine. Detected mine signals.

6. The mine clearance simulation training system based on the combination of sound and light according to claim 5 is characterized by: The assessment judgment unit is used to pre-set the distortion threshold W, and compare and analyze the signal interference degree coefficient Gcxs with the distortion threshold W to determine whether the trainee has a detection error when detecting the corresponding mine. The specific contents are as follows: If the signal interference degree coefficient Gcxs exceeds the distortion threshold W, it will be judged that the trainee has a detection error when detecting the corresponding mine, and the detection of the corresponding mine will be marked as an erroneous detection; If the signal interference degree coefficient Gcxs does not exceed the distortion threshold W, it will be judged that the trainee did not make any detection errors when detecting the corresponding mine.

7. The mine clearance simulation training system based on the combination of sound and light according to claim 6 is characterized by: The acoustic-optic feedback module includes an acoustic-optic unit, a collection unit and a feedback analysis unit; The acousto-optic unit is used to provide real-time feedback to the trainee through voice prompts and optical signals according to the signal frequency characteristics detected by the trainee using the detector; The acquisition unit is used to monitor the trainees' feedback on the corresponding detection behavior in real time during the trainees' mine clearance simulation training to obtain relevant trainee feedback data, wherein the relevant trainee feedback data includes the feedback results of mine identification by each trainee in the mine clearance training area, and the feedback results include the existence of mines at specific locations and the existence of interference components at specific locations. Based on the feedback results, the missed reporting rate of each trainee in the mine clearance training is calculated. , false alarm rate and detection reaction time .

8. The mine clearance simulation training system based on the combination of sound and light according to claim 7 is characterized by: The feedback analysis unit is used to analyze the feedback status of the students under different signal interference conditions according to the relevant student feedback data, and construct a judgment coefficient Pdxs after linear normalization processing. The judgment coefficient Pdxs is specifically obtained in the following manner: ; In the formula, Expressed as the false alarm rate, It is expressed as the false negative rate, It is represented as the detection reaction time, Expressed as the first correction constant, and is the weight value, where and The specific value is set by the user according to the situation.

9. The mine clearance simulation training system based on the combination of sound and light according to claim 1 is characterized by: The capability evaluation module includes a comprehensive evaluation unit and a comparison unit; The comprehensive evaluation unit is used to construct a comprehensive evaluation model using convolutional neural network technology, and to fit the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs to obtain the comprehensive comparison index Zbzs, which is specifically obtained in the following manner: ; In the formula, and are weight values, Expressed as the second correction constant, where and The specific value is set by the user according to the situation; The comparison unit is used to compare and analyze the comprehensive comparison index Zbzs with the preset evaluation threshold Q to comprehensively judge the processing ability of the corresponding trainees during the mine clearance simulation training. The specific judgment content is as follows: If the comprehensive comparison index Zbzs exceeds the evaluation threshold Q, it will be comprehensively judged that the corresponding trainee's processing ability during the mine clearance simulation training is at a qualified level. At this time, a No. 1 teaching instruction will be issued and fed back to the terminal of the mine clearance instructor. The mine clearance instructor will continue to change and add interference factors in the simulated training environment, set time limit requirements, and divide qualified trainees into groups to compete in mine clearance tasks; If the comprehensive comparison index Zbzs does not exceed the evaluation threshold Q, it will be comprehensively judged that the processing ability of the corresponding trainee during the mine clearance simulation training is not at a qualified level. At this time, a No. 2 teaching instruction will be issued and fed back to the terminal of the mine clearance instructor. The mine clearance instructor will conduct targeted intensive training for the trainees, focusing on training the corresponding trainees' ability to recognize common signal patterns, replaying the trainees' erroneous operations during the training process, and cooperating with the mine clearance instructor's explanation to let the trainees understand the specific reasons for their errors and improvement methods.

10. A mine clearance simulation training method based on the combination of sound and light, used to implement the mine clearance simulation training system based on the combination of sound and light as described in any one of claims 1 to 9, characterized in that: The following steps are included: S1. Pre-simulate and deploy a mine clearance training area, deploy several groups of mines and jamming components in the mine clearance training area, and obtain the mine signals detected under standard conditions; S2. Arrange trainees to enter the mine clearance training area for mine clearance training, monitor trainees' behavior data through monitoring equipment, and based on the trainees' behavior data, monitor relevant signal status data presented by the trainees using detectors at different locations; S3, preprocessing the trainee's behavior data and related signal state data, and after linear normalization, mapping the corresponding data values ​​to the interval [0,1]; S4. Analyze the interference of the signals of each student under different detection states according to the student's behavior data and related signal state data, so as to analyze and calculate the signal interference degree coefficient Gcxs. If the signal interference degree coefficient Gcxs exceeds the preset threshold, it is marked as an error detection. S5. According to the signal frequency characteristics detected by the trainee using the detector, the trainee is fed back in real time through voice prompts and optical signals, and the trainee's feedback on the corresponding detection behavior is monitored to obtain relevant trainee feedback data, and the trainee's feedback status under different signal interference conditions is analyzed according to the relevant trainee feedback data to construct the judgment coefficient Pdxs; S6. Input the judgment coefficient Pdxs and the signal interference degree coefficient Gcxs into the trained comprehensive evaluation model, and after linear normalization, fit the comprehensive comparison index Zbzs, and compare the comprehensive comparison index Zbzs with the preset evaluation threshold Q to comprehensively judge the processing ability of the corresponding trainees in the mine clearance simulation training, and generate corresponding training teaching orientation based on the corresponding judgment results.

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