582 results about "Speedometer" patented technology

The invention provides a quad-rotor unmanned aerial vehicle trajectory tracking control method and device, equipment and a storage medium, and belongs to the technical field of unmanned aerial vehicle control, and the method comprises the steps: determining a translation system state variable and an attitude system state variable of an unmanned aerial vehicle based on the real-time trajectory data of the quad-rotor unmanned aerial vehicle; calculating a translation disturbance estimated value based on the translation system state variable, the disturbance observer constant and the expected speed; thrust data is determined based on the translation system state variable, the translation disturbance estimated value, the expected speed, the expected position and outer ring controller parameters of the unmanned aerial vehicle; determining a desired attitude angle based on the thrust data and the desired yaw angle; calculating a control moment based on the expected attitude angle, the attitude system state variable and an inner ring controller parameter of the unmanned aerial vehicle; and based on the thrust data, the control torque and the physical parameters of the unmanned aerial vehicle, calculating to obtain a rotor expected rotating speed, and controlling the unmanned aerial vehicle based on the rotor expected rotating speed. The accuracy of flight control of the unmanned aerial vehicle can be improved.

System and method for monitoring vehicular traffic on a bridge, including receiving digital data representing the response of the bridge to a traffic event, where the digital data has been collected during the traffic event, from displacement sensors and accelerometers mounted on the superstructure of the bridge, wherein the digital data from the displacement sensors embody bending responses of the bridge, the digital data from the accelerometers embody acceleration responses of the bridge, and the digital data from the sensor are synchronised in the same time space, providing a parametric model which uses modal parameters to simulate generalized boundary conditions and two-dimensional behaviour of the bridge; using the parametric model to process the digital data to solve for deformation of the bridge and characteristics of the vehicle traffic, and generating an output that describes the deformation of the bridge and characteristics of the vehicle traffic.

The invention provides a train attitude precision keeping method and system based on inertial quaternion modeling, and belongs to the technical field of train operation positioning. Through a quaternion modeling train attitude feedback compensation model, auxiliary calibration of a gyroscope is realized by using an accelerometer, and calculation of an inertial attitude is realized; converting the acquired wheel speed sensor information into three-dimensional speed under a navigation coordinate system through attitude information resolved by a quaternion modeling train attitude feedback compensation model, and further integrating to obtain a position; and fusing the speed and position information of the wheel speed sensor after attitude conversion with the speed and position information obtained by inertial navigation dead reckoning to realize error correction of the inertial navigation system. According to the method, the problem that the train state sensing precision is degraded due to the fact that a satellite navigation / inertial navigation system positioning model is difficult to overcome inertial device error accumulation when a satellite fails is solved, the train attitude precision is kept, and then error divergence of a combined positioning system during satellite signal denial is effectively restrained.

The invention discloses a method for calculating a vehicle speed based on a moving unmanned aerial vehicle video, and belongs to the technical field of vehicle speed calculation methods through videos, and the method comprises the steps: extracting global feature points of a video frame through employing an SIFT operator, calculating a homography matrix H through combining with an RANSAC algorithm, projecting a previous frame image to a current frame, and carrying out the calculation of the current frame image; the method effectively eliminates the interference of the motion (such as flight attitude change and displacement) of the unmanned aerial vehicle on the vehicle speed calculation, solves the problem of speed measurement failure caused by the deviation of the motion directions of the unmanned aerial vehicle and the vehicle in the traditional method, enables the algorithm to be suitable for complex scenes such as curves and multi-angle flight of the unmanned aerial vehicle, improves the adaptability of the system in a dynamic environment, and improves the reliability of the system. According to the method, the YOLOv5-1 model is combined with the DeepSORT algorithm, high-precision detection and stable tracking of the vehicle are achieved, even under the complex conditions that the vehicle is partially shielded, illumination changes and the like, continuous detection frame association can still be kept, and reliable time sequence data support is provided for vehicle displacement calculation.

The invention discloses a road condition early warning method and system based on an automobile data recorder, and relates to the technical field of road condition early warning, and the method comprises the steps: starting a vehicle, recording the driving road condition through the automobile data recorder, collecting the driving speed of the vehicle, and detecting the recorded video data to recognize road condition obstacles; the actual distance and speed of an obstacle are calculated based on the recognized road condition obstacle, the movement track of the obstacle is predicted, and the dynamic TTC is calculated through the predicted movement track of the obstacle in combination with the vehicle running speed. According to the method, the motion state vector of the obstacle is constructed, and the attention mechanism and the LSTM model are combined to predict the trajectory and calculate the dynamic TTC value, so that the future position and relative trend of the obstacle can be accurately judged, the potential collision risk can be recognized in advance and graded early warning can be realized, and the accuracy of road condition early warning can be effectively improved.

The invention relates to a non-inductive FOC open-loop to closed-loop switching method and device for an electronic water pump and a vehicle. The method comprises the steps that a rotor is pre-positioned; starting an open loop I-F; switching condition judgment; estimating the rotor speed based on an observer, calculating a normalization factor, and obtaining a mixed scale factor through cubic polynomial operation; acquiring an open-loop current instruction of a q axis and a closed-loop current instruction output by a closed-loop speed PI regulator; performing weighted synthesis on the two paths of current instructions according to the mixing scale factor to obtain a temporary target current instruction, and applying a change rate limit to obtain a final current instruction output in the current period; the original angle error of the observer estimation angle and the open-loop slope angle is calculated and normalized, the allowable adjustment step length and direction of the round are dynamically determined, and the angle correction amount of the round is generated and superposed to the open-loop slope angle to update the rotor angle reference value; and closed-loop switching is completed. According to the invention, the problems of electromagnetic torque impact and rotating speed fluctuation caused by instruction step change are solved.

The embodiment of the invention provides a traffic signal-based vehicle path planning method and related equipment, and belongs to the technical field of automatic driving. The method comprises the following steps: acquiring traffic light data of each intersection of a target driving path; according to the green light time interval of the traffic light data, time constraint calculation of multi-intersection continuous passing is carried out, and a time constraint of continuous green wave passing is obtained; performing speed calculation on each road section according to the time constraint to obtain a speed interval of each road section; performing quadratic programming on the speed interval by taking the energy consumption and the driving time as optimization objectives to obtain a global speed sequence; and performing multi-dimensional constraint and multi-target optimization on a speed controller of the vehicle according to the global speed sequence so as to control the vehicle to run on the target running path. According to the embodiment of the invention, the vehicle can be guided to realize continuous green light passing, and the driving efficiency and the driving comfort are improved while the driving energy consumption of the vehicle is reduced.

The present disclosure provides a camera calibration method based on vehicle localization, mainly considering that a vehicle is not of an ideal rigid structure, and shaking of a vehicle body during operation, uneven road surfaces, or different loads will cause variations in extrinsic parameters of a camera system, resulting in perceptual information errors. Therefore, through perceptual information from a fused image, an inertial measurement unit, a speedometer, and the like, combined with the road and marking information provided by a high-definition map, the relative motion between the vehicle body and a vehicle chassis is simultaneously described with a mass-spring-damper model, so as to complete the determination of six-degree-of-freedom positions of the vehicle body and the vehicle chassis, and finally the extrinsic parameters of cameras are immediately calibrated with the vehicle chassis as reference coordinates.

The invention discloses a track non-contact intelligent detection system and method based on multi-source data fusion, relates to the technical field of track detection, and aims at efficiently completing track detection with low cost. The system comprises a frame body, a plurality of line structured light 3D cameras, a synchronous controller, a processing computer and a speedometer; the linear structured light 3D cameras are arranged on the two sides of the frame body, and the optical axes of the linear structured light 3D cameras are arranged to be perpendicular to the axis direction of the steel rail to be measured; the synchronous controller, the processing computer and the speedometer are integrated at the bottom of the frame body, and the synchronous controller and the speedometer are respectively connected with the structured light 3D camera through cables.

The invention relates to a safety constraint vehicle formation distributed sliding mode control method based on a preset performance function. Compared with the prior art, the defect that vehicle formation control is difficult to meet safety constraint, preset performance and distributed cooperative control at the same time is overcome. The method comprises the following steps: establishing a vehicle formation three-order state space model; generating a following vehicle smooth reference trajectory; a preset performance constraint of the following vehicle is designed; calculating the expected speed of the following vehicle; calculating the expected torque of the following vehicle; a following vehicle driving system is controlled; and formation cooperative control is realized. According to the invention, through a reference generation mechanism of constraint perception, a preset performance function with a self-adaptive boundary and a topological structured reaching law, high-performance tracking of the track of the pilot vehicle is realized on the premise of ensuring that all following vehicles meet the time-varying safety boundary.

The invention relates to an unmanned surface vehicle formation control method and device, and belongs to the technical field of unmanned surface vehicle automatic driving, and the unmanned surface vehicle formation control method comprises the steps: building a mathematical model of each unmanned surface vehicle in an unmanned surface vehicle formation based on the initial position and initial speed of each unmanned surface vehicle in the unmanned surface vehicle formation; estimating the real-time speed and disturbance of each unmanned ship in the unmanned ship formation based on the mathematical model and a preset extended state observer; based on a preset relative threshold event triggering mechanism, calculating a measurement error between the unmanned ships in combination with the initial position information and the real-time speed of each unmanned ship in the unmanned ship formation; and calculating a generalized dynamic error of the unmanned ship formation based on the measurement error between the unmanned ships, and calculating control input of the unmanned ship formation by adopting a preset sliding mode algorithm based on the generalized dynamic error. According to the invention, the unmanned ship formation can be accurately and stably controlled.

The invention provides a vehicle travel calculation method and device, electronic equipment and a storage medium, and the method comprises the steps: marking a travel starting point and setting an activation state if a vehicle enters a travel starting stage; if the vehicle in the activated state is in a static state, determining idling duration based on time information of an idling starting point corresponding to a static moment and time information of a target track point corresponding to an idling judgment moment; if the idle speed lasting time meets the preset time condition, a track point between the idle speed starting point and a target track point serves as an idle speed track point, and whether the vehicle enters a travel ending stage or not is determined based on the actual driving speed at each speed calculation moment and the current state of the travel state; and if yes, marking the track point at the travel ending moment as a travel ending point, setting the travel state as an inactive state, and determining a vehicle travel result based on the travel starting point, the idle speed track point and the travel ending point. According to the invention, the accuracy of stroke calculation is improved.

The invention relates to the technical field of intelligent driving, in particular to a vehicle collision risk dynamic assessment method based on multi-modal perception. In the vehicle driving process, driving information and environment characteristic information of a vehicle are collected through a sensor array, and vehicle increment movement prediction is carried out according to the environment characteristic information; acquiring a second driving speed of the vehicle, performing vehicle incremental movement identification, and acquiring an identified vehicle incremental movement distance; according to the first driving speed and the second driving speed, calculating to obtain a fusion driving speed, and carrying out weighted calculation on the predicted vehicle increment moving distance and the identified vehicle increment moving distance to obtain a vehicle increment moving distance; according to the first monitoring distance and the vehicle increment moving distance, a second monitoring distance is obtained through calculation, correction is conducted through the fused driving speed, a third monitoring distance is obtained, collision risk assessment is conducted, and an assessment result is obtained. The technical effect of accurately and quickly evaluating the collision risk is achieved.

The application discloses a road condition early warning method and system based on a driving recorder, relates to the technical field of road condition early warning, and comprises the following steps: starting a vehicle, recording a driving road condition by using a driving recorder, collecting a vehicle driving speed, and detecting and identifying road condition obstacles from video data; calculating actual distances and speeds of the obstacles based on the identified road condition obstacles, predicting motion trajectories of the obstacles, and calculating a dynamic TTC by combining the predicted motion trajectories of the obstacles with the vehicle driving speed. The application can accurately determine future positions and relative trends of the obstacles by constructing a motion state vector of the obstacles and predicting the trajectories by combining an attention mechanism and an LSTM model, and can calculate a dynamic TTC value, so that early identification and graded early warning of potential collision risks are realized, and the accuracy of road condition early warning is effectively improved.

Various implementations include audio systems and related approaches for providing road noise cancelation (RNC). Certain implementations include a method of training a machine learning (ML) based road noise cancelation (RNC) system for a vehicle, the method including: providing inputs to the ML based RNC system, the inputs obtained from: a set of ear-mounted microphones on a user of the vehicle, at least one transducer, an accelerometer, a set of cabin microphones in the vehicle, and a controller area network (CAN) bus, wherein the inputs from the set of ear-mounted microphones on the user approximate detected road noise by the user; adapting a set of parameters defining noise cancelation signals in the ML based RNC system based on the inputs; and generating noise cancelation signals for output by the at least one transducer based on the adapted set of parameters.

The invention discloses a meter weight control device and method for a cable crosslinking procedure, and belongs to the technical field of cable manufacturing, the meter weight control device comprises an extruder and a weighing unit, the extruder adopts a three-layer co-extrusion system and comprises a feeding device, a traction device and an extrusion device, and the meter weight control device further comprises a speed detection unit, a calculation unit and a control unit. The speed detection unit can detect the production line traction speed of the extruder, and the calculation unit can receive a speed signal and calculate a real-time meter weight value and an actual glue thickness value; the control unit controls the working parameters of the extruder according to the comparison between the data calculated by the calculation unit and the set data; the weighing unit, the speed detection unit, the calculation unit and the control unit work cooperatively to control the weight per meter of the extruder. According to the invention, the weighing unit is arranged, and the weight of the extruded material entering the extruder is adjusted through the cooperation of the speed detection unit, the calculation unit and the control unit. The situation that the thickness exceeds the standard can be avoided, and trial production and starting waste products are remarkably reduced.

The invention discloses a dynamic pressure-based carrier rocket grid rudder control method, which comprises the following steps of: according to a pre-launch binding wind field and the speed of a carrier rocket at the current moment, calculating to obtain the relative airflow speed of the carrier rocket at the current moment; according to the current relative airflow velocity of the carrier rocket, calculating to obtain a current dynamic pressure estimated value; according to the dynamic pressure estimation value at the current moment, solving a control law parameter in the grid rudder online variable gain control law to obtain an optimal control law parameter at the current moment; according to the optimal control law parameters at the current moment, a grid rudder swing angle control instruction at the current moment is obtained through calculation, and real-time control over the grid rudder of the carrier rocket is completed. The method can effectively adapt to the rapid change pneumatic environment of the reentry flight section, remarkably reduces the flight deviation, is suitable for various carrier rocket reentry recovery scenes, and has the advantages of being high in engineering practicability, high in control efficiency and the like.

A vehicle employs a method of towing a trailer. A speedometer measures a current velocity of the vehicle. A hitch length sensor obtains a current trailer length of the trailer. A steering angle sensor measures a steering wheel angle of a steering wheel of the vehicle. A processor determines a velocity difference between the current velocity of the vehicle and a nominal velocity of the vehicle, determines a length difference between the current trailer length and a nominal trailer length, calculates a dynamic steering ratio based on the length difference and the velocity difference, determines a road wheel angle for the vehicle from the steering wheel angle and the dynamic steering ratio, and controls a road wheel actuator to obtain the road wheel angle to steer the vehicle.

The invention discloses an improved M method for improving the speed measurement precision of a servo motor, and the method comprises the steps: storing the information of each collected position through the application of an array, calculating the maximum length of the array according to the maximum speed and the resolution of a position encoder, and finally calculating the speed measurement precision of the servo motor under the condition that the speed calculation frequency is not changed by using the latest updated position value and the next to-be-updated position value of the array. Meanwhile, compared with a traditional M method, the method provided by the invention has the advantages that the modification is small, and the implementation of various main control chips is facilitated.

The invention discloses a method for detecting abnormal parking of an unmanned aerial vehicle on a highway under a relatively large inclined view angle. The method comprises the following steps: extracting a road mask and a vehicle detection frame through a road segmentation model and a vehicle detection model; a unique ID is distributed to each vehicle detection frame, and each vehicle detection frame is tracked; extracting image feature points from the expressway video data stream collected by the unmanned aerial vehicle; constructing a view angle conversion matrix, and converting the road mask, the vehicle detection frame and the feature points from an inclined view angle to an aerial view view angle; calculating the background speed of the unmanned aerial vehicle; calculating the relative movement speed of each vehicle between the two frames; calculating the actual moving speed of the vehicle; when the actual moving speed of the vehicle is zero within a certain threshold time, the vehicle is in a parking state; and when the overlap ratio of the vehicle detection frame and the common lane mask is higher than a preset threshold value, the vehicle is in an abnormal parking state. The accuracy and the reliability of the detection method are further improved.

The embodiment of the invention provides a vehicle control method, electronic equipment and a vehicle. The method comprises the following steps: acquiring driving state information of a vehicle and unit slip rates and unit speeds corresponding to a plurality of driving units in the vehicle; based on the unit slip rate, the unit speed and the judgment threshold condition, slip judgment is conducted on the vehicle, and a judgment result is obtained; if the judgment result shows that the target driving unit in the plurality of driving units slips, determining a target slip rate according to the current driving mode and a road adhesion coefficient; calculating a request torque of the target driving unit based on the target slip rate and the unit speed; according to the vehicle speed and the slip type of the target driving unit, the request torque is distributed, and torque transfer information is obtained; and according to the torque transfer information, performing torque control on the driving motors corresponding to the plurality of driving units. The technical problem of how to realize effective anti-skid control so as to improve the driving safety of the vehicle under the slipping condition is solved.

The invention discloses a gearbox fault diagnosis method based on a speed fluctuation periodic ring diagram, and the method comprises the following steps: 1, collecting a motor current signal, a motor instruction rotation speed signal and a motor rotation angle signal through an RV gearbox fault simulation experiment table, and enabling the fault type to be a sun gear single tooth crack wear fault; 2, setting a window parameter set in a certain range; 3, at a fixed moment, carrying out high-order multiple compression transformation on the fault motor current signal, and further extracting an actual current instantaneous frequency; 4, converting the actual current instantaneous frequency into an actual motor speed; 5, calculating speed fluctuation; 6, setting a speed fluctuation threshold value, and traversing all moments to obtain an optimal window parameter set; 7, self-adaptive high-order multiple compression transformation is carried out, and motor speed fluctuation is calculated in a self-adaptive mode in the complete work period; and 8, drawing a speed fluctuation periodic loop graph based on the motor rotation angle signal. According to the method, the gear box fault is visually displayed by detecting the abnormal speed fluctuation synchronous with the fault tooth meshing period, the problems that the resolution of traditional time-frequency analysis is low, distortion is caused by fixed window parameters, and the spectral analysis result is unreliable are solved, and the gear box fault can be more visually and accurately diagnosed.

The invention belongs to the technical field of intelligent traffic safety and risk prediction, and particularly relates to a traffic conflict risk spatio-temporal evolution prediction method based on a vehicle interaction relationship, and the method comprises the steps: taking a target vehicle as a main vehicle, and extracting the positions and speeds of the main vehicle and surrounding vehicles in a unified coordinate system through multi-source data; the method comprises the following steps: calculating a relative position and a relative speed, forming interaction relationship representation data, constructing a vehicle risk potential field on a space-time continuous domain on the basis, mapping a discrete interaction state into continuous and differentiable risk intensity distribution, further forming a sequence by the risk potential fields at each moment, introducing a space-time coding module based on Transform, and coding the vehicle risk potential fields at each moment by using a time-space coding module based on the Transform. And combining position coding, self-attention and graph attention to represent time sequence dependence and multi-vehicle risk propagation coupling, and outputting future risk field evolution distribution. According to the method, the problems of information loss and insufficient spatio-temporal expression of a traditional single time interval index and fixed time window method are solved, conflict risk dynamic prediction is realized, and a reliable basis is provided for traffic safety management and active intervention.

The invention provides a lane keeping control method and device for a low-adhesion road surface, and the method comprises the steps: calculating a wheel slip rate according to a wheel angular velocity and a vehicle driving speed, and judging whether the road surface is the low-adhesion road surface or not according to the wheel slip rate; when it is judged that the road surface is the low-adhesion road surface, a preset gravity center adjustment coefficient is corrected according to the road surface friction coefficient, and meanwhile a peak lateral force value in a tire model corresponding to the target wheel is corrected; according to the real-time steering state of the vehicle and the corrected preset gravity center adjustment coefficient, the vehicle body height and the vehicle gravity center position are adjusted, and meanwhile the distribution condition of the wheel braking force is adjusted to optimize the road holding force of the target wheel; after the road holding force of the target wheel is optimized, the tire lateral force is calculated according to the corrected peak lateral force value, the compensation torque is calculated according to the tire lateral force and a pre-built yawing torque balance equation, and the vehicle system state is controlled to converge along the preset sliding mode surface through the compensation torque. According to the invention, the lane keeping effect is improved, and the driving safety is improved.

In the present invention, a sensor control unit 201 uses a Doppler sensor to receive emitted microwaves and waves reflected from a moving body in a hitting area. A generation control unit 202 generates distribution data indicating the distribution of signal strength at each speed at the time of reception. An accumulation control unit 203 starts accumulation of the distribution data generated over time. A reverse reproduction control unit 204 reproduces the distribution data accumulated over time in reverse time toward the past from the time of the distribution data at which the signal strength dropped below an analysis start threshold. A BS calculation control unit 205 specifies, as a ball peak, a prescribed peak among peaks of the signal strength of the distribution data reproduced in reverse time, and calculates the speed of a golf ball. An HS calculation control unit 206: specifies, from among the distribution data reproduced in reverse time, distribution data of a time at which the ball peak disappeared; and calculates the speed of a golf club head on the basis of a prescribed head peak from among the peaks of the signal strength of the specified distribution data.

This invention discloses a method and system for acquiring pantograph contactor images, belonging to the field of railway power supply contact network detection technology. It uses a photoelectric sensor signal as a trigger. When the photoelectric sensor module detects an approaching train, it controls the pantograph imaging module to take a picture based on a system-preset speed and the radar's measured speed. After the train passes, the image's stretching / compression ratio is calculated based on the radar's final detected speed and the system-preset speed. The identified pantograph contactor image is then stretched, compressed, and segmented to obtain the final pantograph contactor image. By introducing a photoelectric sensor, both the sensor and radar can identify approaching trains. Furthermore, by combining the imaging process based on real-time radar speed measurement and a system-preset speed, even if a train is missed by the radar, the entire image acquisition process can be completed based on the photoelectric sensor's identification and the system-preset speed, avoiding the problem of missed trains by the radar.

According to the peeling expansion analysis method, whether the raceway ring is peeled or not and the shape of a peeling part are acquired, and the peeling expansion analysis is performed at least according to the acquired shape of the peeling part, the specification of the rolling bearing and the operation condition of the rolling bearing. The rolling element load acting on the rolling element when the rolling element passes through the exit portion of the peeling portion of the raceway ring is calculated in consideration of the shape of the peeling portion during degradation, the peeling expansion speed obtained in consideration of the shape of the peeling portion during degradation is calculated on the basis of the rolling element load at the exit portion of the peeling portion, and the rolling element load acting on the rolling element when the rolling element passes through the exit portion of the peeling portion during degradation is calculated on the basis of the peeling expansion speed. The relationship between the elapsed time and the shape of the peeling portion is calculated.

The invention relates to a hydrogen fuel cell unmanned aerial vehicle flight control system. The system comprises a dual-redundancy STM32 main control chip (one main chip and one standby chip), a fuel cell system, a super capacitor and a multi-sensor cooperation module. The main control chip integrates flight control and fuel cell management through an I2C / SPI / CAN bus, and receives data of a gyroscope, an accelerometer, a barometer, a magnetometer, a temperature / pressure sensor and a CVM in real time; the super capacitor dynamically buffers rapid acceleration / deceleration energy, and overload of the fuel cell is avoided; the dual-chip redundancy switching ensures continuous control when the system fails; and the electromagnetic valve and the fan are controlled by the main chip through I / O / PWM ports. According to the system, the problems of control splitting and response lag of a traditional hydrogen energy unmanned aerial vehicle are solved, the endurance is improved by 3-10 times, stable operation in the environment of-40 DEG C to 60 DEG C is achieved, and the emergency braking energy recovery efficiency reaches 90% or above.

To provide a measurement method with which it is possible to calculate a passage section that a railway vehicle has passed through a bridge with good accuracy.SOLUTION: Provided is a measurement method including: a first acceleration calculation step for calculating, on the basis of acceleration data outputted from an acceleration sensor provided at a measurement point of a bridge, a first acceleration including a response to action on the measurement point of a railway vehicle traveling the bridge; a second acceleration calculation step for smoothing the first acceleration and calculating a second acceleration; a threshold calculation step for calculating a threshold on the basis of the amplitude of the second acceleration; and a passage section calculation step for calculating a section whose amplitude of second acceleration is greater than or equal to the threshold as a passage section that the railway vehicle has passed through the bridge.SELECTED DRAWING: Figure 14

The invention provides a simulation system of train vehicle equipment and vehicle-mounted controller interface equipment, which can realize simulation of the train vehicle equipment and the vehicle-mounted controller interface equipment through a simulation control module, and a speed sensor simulation module realizes calculation of a speed sensor signal simulation value and generates a corresponding speed sensor signal. The PWM signal acquisition module is used for acquiring train traction / braking force output by a vehicle-mounted controller in a PWM signal form, the accelerometer simulation module is used for generating accelerometer signals, and the train line signal simulation module is used for driving / acquiring train line signals; the signal conditioning module realizes conversion and adaptation between output / input signals of the multiple functional modules and input / output signals of the vehicle-mounted controller module, can reduce coupling among the functional modules, improves real-time performance of simulation data calculation, reduces calculation load of simulation data calculation, and improves simulation data calculation efficiency. The accuracy of simulation data and the verisimilitude of changes are improved, and the sufficiency and effectiveness of injection faults can also be improved.