Simulation control practical training system and method based on DF4D railway locomotive

Abstract

The invention discloses an analogue simulation control practical training system and method based on a DF4D railway locomotive, and relates to the technical field of railway locomotive practical training, the system comprises a simulation operation subsystem, a practical training simulation subsystem and a data management subsystem; the simulation operation subsystem interacts with the practical training simulation subsystem in real time through a data interface, and the data management subsystem stores, analyzes and visually presents practical training whole process data. According to the invention, the three-dimensional visual system and the multi-mass-point dynamic model are constructed based on real line data, the influence of complex line conditions, special weather and sudden faults can be accurately simulated, the blank of critical scene training in real vehicle practical training is filled up, students can accumulate experience for dealing with unconventional conditions in a safe environment, and the training efficiency is improved. And the proficiency and accuracy of emergency disposal are fundamentally improved.

Description

Technical Field

[0001] This invention relates to the field of railway locomotive training technology, and more specifically, to a simulation operation training system and method based on the DF4D railway locomotive. Background Technology

[0002] The DF4D diesel locomotive, as an important piece of equipment in my country's railway transportation sector, is widely used in mainline freight transport, shunting operations, and some branch line passenger transport. Its power transmission system, braking control logic, and operational safety regulations have distinct technical characteristics, placing stringent demands on the operational proficiency and emergency judgment of locomotive crew members. Traditional DF4D locomotive training methods heavily rely on actual locomotive resources. Limited by locomotive scheduling priorities, line operation arrangements, and site safety regulations, training time is often fragmented, making it difficult to form a systematic skills training loop. During actual locomotive drills, crew members focus more on repetitive practice of routine operating procedures. They lack effective training platforms for handling critical scenarios such as complex line conditions, continuous gradients, small-radius curve combinations, special weather conditions (strong crosswinds, low visibility), and sudden equipment failures (running unit noises, control system communication interruptions). This leads to delays or operational deviations when facing unconventional situations in actual operation.

[0003] Existing simulation training equipment has significant limitations in technical adaptability: some equipment only achieves a simplified imitation of the control panel, failing to reproduce the DF4D locomotive's unique stepless speed regulation characteristics and the air circuit response logic of the JZ-7 brake system, resulting in a significant difference in operating feel compared to the real vehicle and greatly diminishing the training effect; another type of equipment, while possessing basic train operation simulation functions, mostly uses general track models for its visual system, failing to customize modeling for the track characteristics of the DF4D locomotive's commonly operating areas, such as tunnel groups on mountain railways and densely populated turnout areas on mining-specific lines, and lacks linkage simulation with key components such as the locomotive's mechanical parts and running gear, thus failing to meet the full-chain skill training needs of train crew members in "operation, feedback, and fault location." Furthermore, traditional training assessments rely on instructors' subjective observation, making it difficult to quantify operational details, such as the timing of traction level adjustment and the precision of brake pressure reduction control, resulting in a lack of objective basis for evaluating training effectiveness and hindering personalized skills enhancement guidance.

[0004] Therefore, building a simulation system that fits the technical characteristics of the DF4D locomotive, covers all training scenarios, and has accurate evaluation capabilities has become a key technological breakthrough for improving the quality of crew training. Summary of the Invention

[0005] In response to the problems in related technologies, this invention proposes a simulation operation training system and method based on DF4D railway locomotives to overcome the aforementioned technical problems existing in the existing related technologies.

[0006] The technical solution of this invention is implemented as follows: One aspect of the present invention: A simulation operation training system based on a DF4D railway locomotive includes: a simulation operation subsystem, a training simulation subsystem, and a data management subsystem; the simulation operation subsystem and the training simulation subsystem interact in real time through a data interface, and the data management subsystem stores, analyzes, and visualizes the data throughout the training process. The simulation operation subsystem includes: a simulated driving console, a three-dimensional visual display device, a teacher's console, several student consoles, a large splicing screen, and sound simulation equipment. The simulated driving console adopts a 1:1 replica of the DF4D locomotive console structure and integrates a TKS9 type stepless gearless driver controller, a JZ-7 type air brake, an LKJ2000 control host and display, a dual-needle speedometer, and eight locomotive signal lights. The training simulation subsystem includes: a train operation simulation module, a three-dimensional visual simulation module, an emergency response module for abnormal train operation, a brake test module, a shunting operation simulation module, a virtual vehicle interaction module, and a signal simulation module; the train operation simulation module is based on a multi-mass coupling train dynamics model and is used to simulate the effects of track gradient, curve radius, wheel-rail adhesion coefficient, and braking characteristics on train operation; The data management subsystem includes a cloud platform data management system and an instructor management system. The cloud platform data management system is used to manage training plans, monitor data dashboards, and perform multi-dimensional data analysis and early warning. The instructor management system is used for course editing, grade statistics, student information management, and real-time intervention in the training process.

[0007] Furthermore, the three-dimensional visual simulation module uses computer-generated image technology to construct a 1:1 three-dimensional model of the route based on satellite maps and elevation geographic information of the 50KM real route within the pipeline. This model is used to simulate the terrain of straight roads, curves, slopes, tunnels, and bridges, and supports the switching of environmental effects. It can also set up sudden accident scenarios such as large rocks blocking the road, livestock blocking the road, and floods and landslides.

[0008] Furthermore, the abnormal driving emergency response module includes a simulation exercise mode and a challenge assessment mode. The simulation exercise mode is used to provide operation guidance for LKJ abnormal driving scenarios. The challenge assessment mode is used to automatically record the trainee's operation process, generate a practical evaluation form, and the assessment question bank includes at least the assessment items of basic operation, abnormal driving without disclosure, abnormal driving with disclosure, ground signal failure, and driving in the opposite direction.

[0009] Furthermore, the brake test module is used to implement the seven-step brake test teaching, practice and assessment of the JZ-7 air brake. It dynamically displays the on / off status of the air circuit and the internal action process of each valve through a large splicing screen, and supports instructors to manually set mechanical faults of the brake. Trainees can judge and complete the handling operation based on the fault phenomenon.

[0010] Furthermore, the virtual vehicle interaction module is based on a 1:1 3D model of the DF4D locomotive, which allows trainees to roam the driver's cab, machine room, roof and running gear in a virtual environment. They can view the structure of parts, disassembly animations and workflows. It is also linked with the simulated driving control panel. When a malfunction occurs in the simulated driving on the control panel, trainees can locate the faulty part and handle it through the virtual vehicle module. The handling results are fed back to the control panel display system in real time.

[0011] Furthermore, the signal simulation module includes an on-board signal simulation unit and a ground signal simulation unit. The on-board signal simulation unit is used to simulate the LKJ2000 on-board signal system and can display the actual speed, speed limit, track status, and braking prompts. The ground signal simulation unit is used to simulate the interlocking system, CTC system, and train control system, simulate the light display logic of the entry, exit, shunting, and passing signals, and supports the setting of signal fault scenarios.

[0012] Furthermore, the simulation operation subsystem also includes a one-button start / stop management system, which enables the simultaneous start and stop of the simulated driving console, teacher's machine, student's machine, and splicing screen through a central control button, supporting student self-training operation in unattended mode.

[0013] Another aspect of the present invention: A simulation operation training method based on DF4D railway locomotive, used in the aforementioned simulation operation training system based on DF4D railway locomotive, includes the following steps: Step S1, training preparation stage: Instructors create training courses through the instructor management system, set training types, route scenarios, environmental conditions and assessment items, and issue course authorization to the student console. Step S2, the practical training phase, involves trainees logging into the system via fingerprint or facial recognition and operating the simulated driving control panel according to course requirements. For normal driving training, trainees operate the driver controller to adjust traction / braking levels, set train number, total weight, and length parameters via the LKJ display, and receive real-time feedback on train operation status from the 3D visual system. Simultaneously, the sound simulation equipment plays track sounds, braking sounds, and air compressor operating sounds. For abnormal handling training, the system randomly triggers preset faults, and trainees complete the handling operations according to procedures. The system automatically records the operation steps and response time. Step S3, the practical training evaluation stage, the system automatically scores students based on their operation data and generates a practical evaluation form that includes operation records, deduction points, and improvement suggestions; instructors can view the overall class performance distribution through the data dashboard and identify students' weak skills. Step S4, the data archiving stage, the cloud platform data management system stores the training data, supports multi-dimensional queries by student, class, and training type, and generates a skills improvement trend chart.

[0014] Furthermore, step S2 also includes the train operation simulation module receiving trainee operation data and line parameters in real time, calculating train acceleration, braking distance and speed change through a multi-mass coupling model, and feeding the calculation results back to the dual-needle speedometer and the three-dimensional visual system.

[0015] Furthermore, the system automatically scores trainees based on their operational data using evaluation indicators, including standardized operation, fault handling capability, LKJ operation accuracy, and emergency response time. For abnormal handling training, if a trainee fails to complete the handling within the specified time, the system automatically marks it as unqualified and displays a prompt for the correct handling procedure.

[0016] The beneficial effects of this invention are: This invention achieves high-fidelity reproduction and full-process coverage of the DF4D locomotive training scenario, significantly breaking through the limitations of traditional training modes. Through a 1:1 replica of the simulated driving control panel, it accurately reproduces the stepless speed regulation characteristics of the TKS9 driver controller, the air circuit response logic of the JZ-7 brake system, and the interaction mode of the LKJ2000 system, ensuring that the operating feel and equipment linkage are consistent with the real vehicle. This allows trainees to directly transfer the muscle memory developed in the simulation environment to real-vehicle operations. Simultaneously, the 3D visual system and multi-mass dynamic model built based on real track data can accurately simulate the impact of complex track conditions, special weather, and sudden faults, filling the gap in critical scenario training in real-vehicle training. This allows trainees to accumulate experience in dealing with unconventional situations in a safe environment, fundamentally improving their proficiency and accuracy in emergency response.

[0017] Furthermore, the integration of the cloud platform data management system and the instructor management system in this invention enables precise delivery of training plans, full recording of the operation process, and multi-dimensional analysis of skill data. Instructors can intuitively grasp the weaknesses of trainees in traction control, brake adjustment, and fault diagnosis through data dashboards, and develop targeted retraining plans, avoiding the drawbacks of traditional training assessments that rely on subjective experience. The linkage between the virtual vehicle interaction module and the brake test module also constructs a cognitive closed loop of operation, fault phenomena, and component principles, helping trainees deepen their understanding from simple process imitation to understanding the principles of equipment. This not only improves the effectiveness of short-term training but also lays the foundation for the long-term professional development of flight attendants. In addition, the system does not rely on actual vehicles and real line resources, allowing for flexible scheduling of training time and content, significantly reducing the interference of training on operational scheduling, and eliminating safety risks in actual vehicle operation, thus achieving an efficient, safe, and sustainable skills training model. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of a simulation operation training system based on a DF4D railway locomotive according to an embodiment of the present invention. Figure 2 This is a flowchart illustrating a simulation operation training method based on a DF4D railway locomotive according to an embodiment of the present invention. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention are within the scope of protection of the present invention.

[0021] According to an embodiment of the present invention, a simulation operation training system based on a DF4D railway locomotive is provided.

[0022] like Figure 1As shown, the simulation operation training system based on the DF4D railway locomotive according to an embodiment of the present invention includes: a simulation operation subsystem 1, a training simulation subsystem 2, and a data management subsystem 3. The simulation operation subsystem 1 and the training simulation subsystem 2 interact in real time through a data interface. The data management subsystem 3 stores, analyzes, and visualizes the data of the entire training process. Among them, the simulation operation subsystem 1 uses a 1:1 replica of the core operating components of the DF4D locomotive as its core, ensuring that the size, appearance, and operating logic are completely consistent with the actual vehicle, as detailed below: The simulated driving control console integrates a TKS9 continuously variable driver controller, a JZ-7 air brake, an LKJ2000 control host, a 10.4-inch TFTLCD display, a dual-needle speedometer for displaying real speed and speed limit, a dual-needle pressure gauge for displaying brake pipe pressure, and eight locomotive signal indicator lights for dual-sided display, as well as buttons, indicator lights, and toggle switches. The driver controller allows for locomotive operating conditions and speed adjustment, and the brake valves support both normal braking and emergency braking operations.

[0023] The three-dimensional visual display device uses a 55-inch full HD LED TV as the front-facing display, and is equipped with a 2*2 LED splicing screen to simultaneously display circuit visuals, pneumatic circuit diagrams, circuit diagrams, and training and assessment interfaces.

[0024] The teacher control console consists of a host computer with an i7 processor, 16GB of RAM, a 250GB solid-state drive, and a GTX 1060 graphics card, and two 19-inch monitors. It is equipped with wall-mounted speakers, a wireless microphone, and a 5.1-channel amplifier, and is used for monitoring the training process, issuing fault reports, and voice interaction.

[0025] The student control console, consisting of six student computers, is equipped with an i7 processor, 16GB of RAM, a 250GB solid-state drive, a GTX 1060 6G graphics card, and a 20-inch monitor. It supports students in theoretical learning, virtual operation, and answering questions during assessments. It also communicates with the teacher's computer in real time to receive course instructions and performance feedback.

[0026] The sound simulation equipment is embedded inside the control panel and can simulate various sounds of the DF4D locomotive during operation, including track sounds, braking sounds, air compressor operating sounds, whistle sounds, tunnel echoes, and environmental noise. The sound intensity is automatically adjusted according to the train speed and scene changes to restore a realistic auditory experience.

[0027] The training simulation subsystem 2 is used to simulate the operation of the DF4D locomotive in different scenarios, as detailed below: The train operation simulation module is used to generate a train dynamics model based on multi-mass coupling. It can input line parameters, including gradient, curve radius, and length; train parameters, including number of trains, total weight, and length; environmental parameters, including wheel-rail adhesion coefficient, wind speed, and trainee operation commands, including driver controller level and brake valve position. It can calculate train acceleration, speed, braking distance, and traction / braking power in real time.

[0028] The 3D visual simulation module, employing CGI technology, constructs a 1:1 3D model of the 50km real railway line based on satellite maps and elevation data. This model includes track bed, sleepers, rails, signals, and features such as station entrances / exits / shunting / passing, bridges, tunnels, level crossings, and landmarks along the line, such as stations, villages, and rivers. It supports environmental effects switching, such as rain / snow / fog / nighttime. The rain and snow particle effects utilize an optimized particle system, while the fog effect achieves gradual changes in distance using LOD technology. It also allows for the setting of emergency scenarios, such as large rocks blocking the road, livestock obstructing the path, and floods / landslides.

[0029] The emergency response module for abnormal train operation includes a built-in question bank covering five categories: "Basic Operation," "Abnormal Operations Without Disclosure," "Abnormal Operations with Disclosure," "Ground Signal Deactivation," and "Reverse Direction Train Operation." It encompasses practical training content such as "Handling Train Overshooting Signals," "Train Operation During Braking System Failure," and "Handling Forced Stops in Sections." It supports two modes: simulated drills with operational guidance and challenge-based assessments without guidance, with automatic recording of operations. After the assessment, a "Practical Performance Evaluation Form" is automatically generated, marking correct and incorrect operations and the reasons for point deductions.

[0030] The brake testing module is used to simulate the entire "seven-step brake" test process for the JZ-7 air brake, including: Step 1, self-valve overcharge position; Step 2, self-valve operation position; Step 3, self-valve braking position; Step 4, self-valve pressure holding position; Step 5, self-valve release position; Step 6, single-valve braking position; and Step 7, single-valve release position. A large splicing screen dynamically displays the air circuit and the internal operation processes of each valve, such as the distribution valve and the actuating valve. Instructors can set faults, such as brake pipe leakage or distribution valve jamming. Trainees can identify the fault point and perform repairs by observing pressure gauge changes and the air circuit diagram.

[0031] The shunting operation simulation module simulates the layout of a station with three tracks, including shunting signals, track numbers, and parking car markings. Instructors can send shunting commands via the instructor's console, such as start / push / ten cars / five cars / three cars / stop. Trainees operate the control panel to complete shunting operations, such as pulling out, switching tracks, and coupling. The system automatically determines whether the trainee has confirmed the signals, controlled the speed, and ensured the accuracy of the stopping position, providing real-time prompts for operational errors.

[0032] The virtual vehicle interaction module, based on a 1:1 3D model of the DF4D locomotive, allows trainees to virtually navigate the driver's cab, engine room, roof, and running gear using a mouse and keyboard. They can view the structure, dimensions, and working principles of components such as the diesel engine, generator, and brake lines. Clicking on a component plays disassembly animations and workflow videos. Simultaneously, it links with the simulated driving control console. When the console simulates a "diesel engine failure," trainees can locate the faulty cylinder in the virtual vehicle and perform a "cylinder cut-off operation." The results are fed back to the control console in real time. If the operation is correct, the fault indicator light turns off, and the training continues.

[0033] The signal simulation module is divided into two parts: the vehicle-mounted signal simulation unit and the ground signal simulation unit. The vehicle-mounted signal simulation unit simulates the LKJ2000 system, displaying information such as actual speed, speed limit, kilometer markers, tunnel / bridge / gradient, and supports the operation of special driving permits such as "specific guidance," "green permit," and "telephone block." The ground signal simulation unit simulates the interlocking system and CTC system, and can set signal malfunctions, such as lights going out, unclear displays, and track circuit malfunctions. Trainees need to confirm driving permits, such as road tickets and hand signals, based on the malfunction situation. The system judges the correctness of the permit entries and the compliance of the operating procedures.

[0034] Data Management Subsystem 3 is used to realize intelligent management and data analysis of the entire training process based on cloud computing and big data technologies, as detailed below: The cloud platform data management system integrates all training equipment and examination systems. Instructors can access the cloud platform from their offices via computer to complete training plan development, such as setting training time, class, content, and data dashboard monitoring. This allows for real-time display of each student's training progress, grades, troubleshooting status, and data analysis alerts. For example, if a class's pass rate for "brake troubleshooting" falls below 60%, an automatic alert will be issued, prompting additional training. Data export is supported, in formats such as Excel / Word, which can generate individual student skill profiles, class performance reports, and teaching improvement suggestions.

[0035] The instructor management system includes course management, grade management, student management, and monitoring authorization, as detailed below: Course management supports the creation of courses / exam papers, the addition of practical training modules such as normal driving and brake tests, the setting of assessment items and scores such as standardized operation 30 points and fault handling 40 points, and courses can be saved as templates for reuse. The performance management system automatically compiles trainees' training scores and supports queries by name, class, and training type. It displays operation records, such as "2024-XX-XX 10:30, brake failure handling timeout, deduct 10 points". It can generate a performance ranking table and a skills radar chart to show trainees' scores in dimensions such as "normal operation", "fault handling", and "shunting operation". Student management supports creating student information, such as name, employee number, ID number, and group management, such as dividing by class group. Students can import / export student lists and view students' historical training records. The system monitors and authorizes student console screens in real time, allowing remote control of student machine start-up and shutdown. It supports "real-time authorization" for students during on-site training and "long-term authorization" for students to conduct independent training within a specified time period. The authorization information is linked to the student's account to prevent proxy training and exams.

[0036] According to an embodiment of the present invention, a simulation operation training method based on DF4D railway locomotive is provided.

[0037] like Figure 2 As shown, the simulation operation training method based on the DF4D railway locomotive according to an embodiment of the present invention includes the following steps: Step S1 involves the instructor conducting pre-training preparations, including the following steps: Instructors log in to the cloud platform data management system to create training courses: select training type, such as "abnormal train operation handling training", line scenario, such as "mountain line, including two tunnels and three curves", environmental conditions, such as "rainy day, visibility 200m" and assessment items, such as "train overshoot signal handling" and "brake system failure train operation", set training time, such as 2 hours and class, such as "DF4D crew member class 1"; Instructors distribute course authorizations to six student control consoles through the instructor management system, select "real-time authorization" as the authorization type, and enable the teacher's monitoring function to view student login status in real time. Students log in to the student machine via fingerprint / facial recognition. The system automatically loads the course content and displays the training task description, such as "This training requires the completion of two abnormal handling procedures. Correct operation will earn points, while timeout / error will result in point deduction."

[0038] Step S2 involves implementing the practical training, including the following steps: During the normal driving simulation phase: The trainee operates the simulated driving console, sets the driver controller to the "forward" position, adjusts the traction level, and the train starts from the station; the 3D visual system displays the track scene, such as rainy weather with a visibility of 200m, and the dual-needle speedometer displays the speed in real time, such as from 0 to 60km / h; the sound simulation equipment plays track sounds and rain sounds; the trainee needs to confirm the track speed limit according to the prompts on the LKJ display, such as the speed limit of 45km / h on curves, and adjust the traction / braking level in a timely manner to control the speed within the limit; the system judges the compliance of the operation in real time. If the speed is exceeded, such as reaching 46km / h, the LKJ system will sound an alarm and record "speeding operation, deduct 5 points".

[0039] During the abnormal handling phase: The system randomly triggers a "brake system malfunction," such as a brake pipe leak, where the pressure gauge drops from 600 kPa to 400 kPa. The trainee needs to observe the pressure gauge change, confirm the malfunction type, and operate the JZ-7 brake according to the procedure, such as closing the valve on the faulty pipeline and using the backup brake. The system records the operation steps and response time, such as "Response time 1 minute 20 seconds, operation correct, 10 points." If the trainee does not close the faulty valve, the system will prompt "The malfunction has not been resolved, and the vehicle cannot continue to operate. Please try again."

[0040] During the brake test phase: Trainees complete the "seven-step brake" test of the JZ-7 brake according to the instructor's instructions. The air circuit path is dynamically displayed on the large screen. After each step is completed, the system judges whether the operation is correct. For example, when the first step is "self-valve overcharge position", the overcharge pressure is checked to see if it rises to 650kPa. If it is correct, the system proceeds to the next step. If it is incorrect, the system prompts "insufficient overcharge pressure, please operate again" and deducts 2 points.

[0041] During the shunting operation phase: The instructor sends the shunting command "Advance to the third track for coupling and parking" via the instructor's machine. The trainee confirms the shunting signal, such as a white light, and sets the driver's controller to the "reverse" position, controlling the speed to ≤10km / h. The 3D visual system displays the shunting scene. When the distance to the parking car is 50m, the system prompts "10 cars". The trainee needs to depress the brakes and gradually reduce the speed. If coupling is successful, and the parking position deviation is ≤1m, the system records "Shunting operation correct, 8 points". If the deviation is too large, points will be deducted.

[0042] Step S3, conduct practical training evaluation, including the following steps: After the practical training, the system calculates the total score based on the trainees' operation data, such as standardized operation (30 points), fault handling (40 points), brake test (20 points), and shunting operation (10 points), and generates a "Practical Evaluation Form" which marks the scoring items, deduction items, and improvement suggestions, such as "The response time for brake fault handling is relatively long, and it is recommended to strengthen simulation training." Instructors can view class performance distribution through cloud platform data dashboards, such as "Class 1 average score 75 points, 2 students failed", and identify weak skills, such as "30% of students lost points in 'shunting operation speed control'"; for students who failed, their operation videos are retrieved, the reasons for the errors are analyzed, such as "starting without confirming the shunting signal", and personalized retraining plans are developed, such as increasing the number of shunting operation simulations; The system stores trainees' training data, such as operation records, grades, and videos, on the cloud platform, generating individual skill profiles for trainees. This supports subsequent queries and tracking, such as comparing the results of two training sessions during annual refresher training to assess skill improvement.

[0043] Step S4: Shut down the equipment. After completing the training, the trainee operates the "shutdown" button on the one-button power-on / off system, and the simulated driving control console, trainee machine, and splicing screen are simultaneously shut down. The instructor confirms that all equipment is shut down through the cloud platform, exports the training data, and completes the training summary.

[0044] Using the above technical solution, and taking the pre-job training of DF4D train attendants as the implementation scenario, a railway bureau conducted a 7-day pre-job training for 20 newly recruited DF4D train attendants, divided into 3 groups. The training was carried out using the system of this invention, and the specific implementation schedule is as follows: Day 1-Day 2: Normal driving simulation, such as route familiarization, speed control, LKJ operation; Day 3-Day 4: Abnormal handling, namely signal failure, brake failure, and section stop; Day 5: Brake testing and shunting operations; Day 6-Day 7: Comprehensive assessment, including full-scenario practical training; Specific implementation process: Instructors create daily courses through the cloud platform and set up a "newbie guidance mode" to prompt the correct steps when operating errors occur; students take turns operating the simulated driving control console in groups, with each group having 40 minutes, while the remaining students watch the live training broadcast and conduct theoretical learning through their student devices; Training results: The comprehensive assessment after 7 days showed that the pass rate for "normal driving operation" was 100%, the pass rate for "abnormal handling" increased from 20% before training to 85%, and the correct operation rate for "brake test" reached 90%, which was significantly better than traditional on-vehicle training.

[0045] In addition, taking the annual refresher training of DF4D crew members as an example, a certain locomotive depot conducted annual refresher training for 50 in-service DF4D crew members, focusing on strengthening their "emergency fault handling" capabilities. The specific implementation is as follows: Refresher training content: Set up 10 high-frequency fault scenarios such as "diesel engine failure", "brake line leakage" and "signal light failure", and adopt a "challenge assessment mode"; Implementation process: Instructors randomly assign faults through the instructor management system, and trainees must complete the handling within a specified time of 3-5 minutes; the system automatically records the operation steps and scores, and generates an individual skill radar chart; Retraining results: After retraining, the average response time for flight attendants to handle faults was reduced from 8 minutes to 3.5 minutes, and the accuracy rate of operation increased from 70% to 92%, effectively reducing the risk of fault handling in actual train operation.

[0046] In summary, by utilizing the above-mentioned technical solutions of the present invention, the simulation operation training system and method based on the DF4D railway locomotive provided by the present invention solves the pain points of traditional training through the combination of high-fidelity hardware, full-scene software and intelligent data management, and provides an efficient, safe and low-cost solution for the training of DF4D locomotive crew members, which has important practical application value and promotion prospects.

[0047] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Those skilled in the art, upon considering the disclosure in the specification and embodiments, will readily conceive of other embodiments of this disclosure. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the claims.

[0048] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A simulation and control training system based on DF4D railway locomotive, characterized in that, The utility model relates to a real training simulation system, which comprises a simulation operation subsystem (1), a real training simulation subsystem (2) and a data management subsystem (3); the simulation operation subsystem (1) and the real training simulation subsystem (2) are in real-time interaction through a data interface, and the data management subsystem (3) stores, analyzes and visually presents real training full-process data. The simulation operation subsystem (1) comprises a simulated driving console, a three-dimensional visual display device, a teacher console, a plurality of student consoles, a large screen and sound simulation equipment; the simulated driving console is a 1:1 copy of a DF4D locomotive console structure, and is integrated with a TKS9 type stepless gear controller, a JZ-7 type air brake, an LKJ2000 control host and a display, a double-needle speedometer and eight visible lights of a locomotive signal. The real training simulation subsystem (2) comprises a train operation simulation module, a three-dimensional visual simulation module, an abnormal operation emergency disposal module, a brake test module, a shunting operation simulation module, a virtual locomotive interaction module and a signal simulation module; the train operation simulation module is based on a multi-particle coupled train dynamics model and is used for simulating the influence of line slope, curve radius, wheel-rail adhesion coefficient and brake characteristics on train operation. The data management subsystem (3) comprises a cloud platform data management system and a teacher management system; the cloud platform data management system is used for realizing real training plan management, data dashboard monitoring and multi-dimensional data analysis and early warning; and the teacher management system is used for course editing, score statistics, student information management and real-time intervention in the real training process. The three-dimensional visual simulation module adopts a computer-generated image technology, is based on satellite maps and elevation geographic information of 50 km real lines in a pipeline, and constructs a line three-dimensional model in a 1:1 mode, which is used for simulating straight, curved, sloping, tunnel and bridge terrains and supports environment special effect switching, and can set up sudden accident scenes such as line large stone blockage, livestock blockage and flood landslides.

2. The simulation and operation training system based on the DF4D railway locomotive according to claim 1, characterized in that, The abnormal operation emergency disposal module comprises a simulation drill mode and a challenge assessment mode; the simulation drill mode is used for providing operation guidance for LKJ abnormal operation scenes; the challenge assessment mode is used for automatically recording the operation process of students, generating a practical identification table, and an assessment item bank at least contains basic operation, non-revealing abnormality, revealing abnormality, ground signal stoppage and reverse direction operation.

3. The simulation and operation training system based on the DF4D railway locomotive according to claim 1, characterized in that, The brake test module is used for realizing seven-step brake test teaching, drill and assessment of the JZ-7 type air brake, dynamically displays the on-off state of an air path and the internal operation process of each valve through a large screen, and supports manual setting of brake mechanical faults by teachers, and students judge and complete disposal operations through the fault phenomena.

4. The simulation and operation training system based on the DF4D railway locomotive according to claim 1, characterized in that, ​ 5. The simulation and operation training system based on the DF4D railway locomotive according to claim 1, characterized in that, The virtual locomotive interaction module is based on a 1:1 three-dimensional modeling of a DF4D locomotive, and is used to enable a trainee to roam a cab, a mechanical room, a roof and a running part in a virtual environment, view component structures, disassembly animations and work processes, and be linked with a simulated driving console, so that when a simulated driving fault occurs, the trainee can locate a faulty component and complete disposal through the virtual locomotive module, and a disposal result is fed back to a console display system in real time.

6. The simulation and operation training system based on the DF4D railway locomotive according to claim 1, characterized in that, The signal simulation module includes a vehicle-mounted signal simulation unit and a ground signal simulation unit, wherein; The vehicle-mounted signal simulation unit is used to simulate an LKJ2000 vehicle-mounted signal system, and can display a real speed, a speed limit, a line state and a braking prompt; and the ground signal simulation unit is used to simulate an interlocking system, a CTC system and a train control system, simulate light display logic of an entry signal, an exit signal, a shunting signal and a passing signal, and support signal fault scene setting.

7. The simulation and operation training system based on the DF4D railway locomotive according to claim 1, characterized in that, The simulation operation subsystem (1) further includes a one-key on-off management system, which realizes synchronous start and stop of the simulated driving console, the teacher machine, the trainee machine and the spliced large screen through a general control button, and supports trainee self-operation in an unattended mode.

8. A simulation-based simulation control training method for a DF4D railway locomotive, used for the simulation-based simulation control training system for the DF4D railway locomotive according to any one of claims 1-7, characterized in that, The method comprises the following steps: In step S1, a training preparation stage, a teacher creates a training course through a teacher management system, sets a training type, a line scene, an environment condition and an assessment item, and issues the course to a trainee console; In step S2, a training implementation stage, a trainee logs in the system through fingerprint or face recognition, and operates a simulated driving console according to the course; if it is normal driving training, the trainee adjusts traction / braking levels through a driver controller, sets train number, total weight and length parameters through an LKJ display, and the three-dimensional visual system feeds back a train running state in real time, and sound simulation equipment synchronously plays track sound, braking sound and air compressor running sound; if it is abnormal disposal training, the system randomly triggers a preset fault, and the trainee completes disposal operation according to regulations, and the system automatically records operation steps and response time; In step S3, a training evaluation stage, the system automatically scores according to trainee operation data, and generates a practical identification table including operation records, deduction points and improvement suggestions; a teacher checks overall performance distribution of a class through a data board, and locates weak skills of a trainee; In step S4, a data archiving stage, a cloud platform data management system stores training data, supports multi-dimensional query according to a trainee, a class and a training type, and generates a skill improvement trend chart.

9. The simulation and operation training method for the DF4D-based railway locomotive according to claim 8, characterized in that, In the step S2, a train running simulation module receives trainee operation data and line parameters in real time, calculates train acceleration, braking distance and speed change through a multi-particle coupling model, and feeds back calculation results to a double-needle speedometer and a three-dimensional visual system.

10. The simulation and operation training method for the DF4D-based railway locomotive according to claim 8, characterized in that, The evaluation indexes of the system automatic scoring according to trainee operation data include standardized operation, fault disposal ability, LKJ operation accuracy and emergency response time; for abnormal disposal training, if a trainee does not complete disposal within a specified time, the system automatically marks it as unqualified, and pops up a correct disposal process prompt.

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