8761results about "Vehicle testing" patented technology

An autonomous driving test platform based on virtual-real integration technology, which platform belongs to the technical field of autonomous car testing. On the basis of cloud-edge-end three-level linkage, the platform combines real environment testing and sand table environment testing with virtual simulation technology. A vehicle-end real scene is an actual environment in which an autonomous vehicle is applied; and environmental information is collected, and feedback is provided for the environmental information and virtual-real fusion information. In a cloud-end virtual environment, in addition to building an autonomous driving virtual scene, data fusion is also performed on information from a real scene and a sand table scene, so as to generate virtual-real fusion data. A sand table environment is used as an edge portion to provide a relay space, which is used for bridging the cloud-end virtual environment to a vehicle-end real environment, digitally twinning the autonomous vehicle in the actual environment to a virtual simulation environment, and transmitting the virtual-real fusion information to the autonomous vehicle. The sand table environment, the virtual environment and the real environment fully interact with one another to implement data enhancement, thereby obtaining an optimal test effect.

The present disclosure relates to a method and apparatus for detecting anomalous shaking of a vehicle, a device, a vehicle, a medium, and a program product, the method comprising: acquiring a target time sequence corresponding to an original time sequence signal, the original time sequence signal being a time sequence signal corresponding to a vehicle status signal, and the target time sequence being a stable time sequence obtained from preprocessing the original time sequence signal; randomly selecting a plurality of sample points from the target time sequence, constructing a plurality of isolation trees, selecting from the target time sequence a data point to be detected, traversing isolation trees among the plurality of isolation trees according to said data point, and, on the basis of the depths of said data point in the isolation trees, determining anomaly scores of said data point; on the basis of the anomaly scores of said point, determining an anomalous point list composed of anomalous points that have been detected; and, according to a time interval between the anomalous points in the anomalous point list, identifying an anomalous shaking interval. According to the present method, the problem of missed detection during anomaly detection on vehicle status information can be reduced.

The invention relates to the technical field of testing of structural components or equipment, in particular to a method and a device for testing mechanical durability of a wheel hub motor angle module and electronic equipment, and the method comprises the following steps: calculating the mechanical durability of the wheel hub motor angle module on the basis of actual driving data and whole vehicle parameters of a vehicle carrying the wheel hub motor angle module; a whole vehicle multi-body dynamics model and a whole vehicle multi-body dynamics-control joint simulation platform of a vehicle are constructed, a whole vehicle durability simulation working condition of the vehicle is established in combination with test field condition constraints, a test driving file is iterated based on a simulation analysis result, a tool clamp is designed by utilizing the rim size of a hub motor angle module and the position of a suspension mounting point, and a test result is obtained. Therefore, a target test bench is constructed, and the target test bench is used for executing the durability test task of the wheel hub motor angle module. Therefore, the technical problem that in the related technology, a vehicle carrying a wheel hub motor angle module can collect less data and does not have the real vehicle spectrum collection condition under the long-term and severe road condition, so that the durability test is difficult to carry out is solved.

The invention relates to the field of vehicle braking fault detection, in particular to a real-time fault detection method for a vehicle electronic braking system, which comprises the following steps of: acquiring vehicle driving state data through a vehicle-mounted sensor network and an electronic control unit, calculating filtered residual data of a target wheel speed sensor, and calculating the filtered residual data of the target wheel speed sensor; establishing calibration reference parameters of the health state; performing conjoint analysis on the acceleration data and the residual fluctuation data of the vehicle to obtain a dynamic response adaptive adjustment factor of the vehicle; obtaining a tiny drift confirmation factor of the vehicle through the candidate residual error in the low dynamic interference state of the vehicle; continuous fault judgment is performed by combining the dynamic response adjustment factor and the tiny drift confirmation factor of the vehicle, and the fault judgment result of the wheel speed sensor is obtained, so that the accuracy and sensitivity of fault detection when tiny systematic deviation occurs to the wheel speed sensor are improved.

The invention belongs to the field of data processing, and discloses a test method for pedestrian trajectory prediction and emergency braking in an automatic driving platform. Comprising the steps of segmenting a real road environment in advance, obtaining grades of small road segments according to calculation of segmentation coefficients, carrying out resource allocation on the small segments according to the grades, and collecting multi-source heterogeneous data; importance optimization is introduced into a Transform model, possible prediction trajectories of individuals are generated, graph data are constructed by using the possible prediction trajectories, an Autoencoder anomaly detection mechanism is introduced, high-risk trajectories are screened out, and high-risk scenes are output; combining the road geometric model with the high-risk scene to form a scene library, loading the scene in a simulation platform, carrying out automatic driving test, carrying out virtual-real data cross validation in combination with real vehicle test data, and obtaining performance evaluation of an algorithm; pedestrian track prediction and emergency braking in the automatic driving process are achieved.

Disclosed is a digital twin-based fault diagnosis method for logistics mobile equipment, capable of achieving online monitoring of equipment state and fault diagnosis by means of fusion of digital twin technology and sensor data, thereby allowing for proactive fault prevention and precise maintenance, improving the reliability and operation efficiency of logistics equipment and prolonging the service life thereof. The technical solution of the method comprises: step 1, on the basis of logistics mobile equipment, establishing a corresponding digital twin model; step 2, acquiring real-time data of a battery entity for adaptive model updating; step 3, inputting fault information into a bidirectional GRU model having a multi-head attention mechanism; step 4, performing outlier detection on the basis of an improved fuzzy isolation forest algorithm, comprising introducing a type-2 fuzzy theory into a fuzzy isolation forest algorithm and making improvements; and step 5, using the obtained fault data to implement corrective measures on the basis of risk levels.

The invention provides an abnormal sound test bench capable of rapidly switching modes. The abnormal sound test bench comprises a base, a first test unit, a second test unit and a power device arranged between the first test unit and the second test unit. The power device comprises two vibration exciters arranged in the y direction. The first test unit can make a to-be-tested part generate single-degree-of-freedom vibration in x, y and z directions, and the second test unit can make the part generate pitching and side-tipping composite-degree-of-freedom vibration. The first test unit and the second test unit can be respectively driven by the same group of power device, only the tested part needs to be transferred in a short distance during mode conversion, the same group of power device is used in the two test modes, and the test efficiency is greatly improved during the test of the rear half part. The relevant parameters between the tested part and the power device are acquired in the first half part, so that the debugging time between the part and the power device is greatly saved, and the testing efficiency is improved.

The invention relates to an online multi-dimensional comprehensive test evaluation method for an automatic driving test. The method comprises the following steps: constructing a test scene library; constructing a test scene complexity model; building an intelligent driving joint simulation test platform, and embedding the intelligent driving algorithm into the intelligent driving joint simulation test platform; constructing an automatic driving test multi-dimensional evaluation index system for performing multi-dimensional performance evaluation on the automatic driving vehicle; an intelligent driving joint simulation test platform is utilized to obtain vehicle test data, an evaluation index system and a test scene complexity model are combined to calculate objective evaluation index weights, then comprehensive performance quantitative scores are calculated, and finally an automatic evaluation report is output and obtained. Compared with the prior art, the subjectivity of manual evaluation can be reduced, and the evaluation efficiency of the automatic driving vehicle is improved; comprehensive and objective quantitative scoring can be carried out on the multi-dimensional performance of the automatic driving vehicle, and the influence of different test scenes on the scoring difference of the automatic driving vehicle is reduced.

The invention relates to the technical field of transmission system fault diagnosis, in particular to an operation fault monitoring method and system applied to an automobile transmission system. Determining the vibration characteristic coefficient of each period according to the amplitude difference of the vibration sequence in different frequency regions on the frequency domain; and a fault trend coefficient is constructed based on the data fluctuation frequency of the vibration signals of all periods and the change trend of the vibration characteristic coefficients of all periods so as to adjust the abnormal proportion, and based on the adjusted abnormal proportion, the operation fault monitoring of the automobile transmission system is carried out in combination with an isolated forest algorithm. The method improves the sensitivity of abnormal detection at the initial stage of a fault or during a slight fault, guarantees the dynamic balance of the false alarm rate and the missing report rate of the fault detection of the transmission system, and improves the quality of the fault detection of the automobile transmission system.

The invention discloses an intelligent AI detection method based on an infrared thermogram and automobile diagnosis, according to the technical scheme, the fireproof safety detection efficiency of an electric automobile is remarkably improved through multi-modal data fusion and intelligent analysis, and a multi-dimensional data basis is constructed through synchronous acquisition of dual-band infrared and vehicle operation parameters; secondly, a dynamic correlation model realizes accurate triggering of abnormal current on heat map enhancement, partition gradient processing is combined with dynamic threshold adjustment to optimize detection sensitivity for thermal characteristics of different parts, three-dimensional thermal field reconstruction breaks through surface detection limitation, internal potential overheat points can be identified, and the detection sensitivity is improved; and finally, closed-loop diagnosis is formed through case library intelligent matching, so that the fault positioning precision reaches a component level, and the whole scheme is coordinated through a multi-level technology, so that the problems of low infrared thermal image contrast and relatively poor detail distinguishing capability due to the fact that electric vehicle fireproof safety detection is carried out only by depending on thermal infrared images in the prior art are solved.

The invention discloses a road network abnormal event identification and risk evaluation early warning method based on vibration perception, and relates to the technical field of urban road safety monitoring. Comprising the steps of collecting road vibration data of a road network through a sensor; preprocessing the road vibration data through Kalman filtering and multi-dimensional feature extraction; abnormal event recognition is carried out on the processed road vibration data through a differentiation algorithm, wherein abnormal events comprise vehicle overload, illegal construction and road structure damage; and carrying out risk scoring on the abnormal events through dynamic weight distribution, dividing the risk scores according to the risk levels, and carrying out graded response. According to the invention, through differential algorithm design, a mixed model architecture and a hierarchical response mechanism are adopted, abnormal event identification, risk level quantitative evaluation and differential early warning processing are realized, the safety state of an urban road network is monitored in real time, and early warning information is provided.

The invention belongs to the field of automatic driving test, and provides an end-to-end automatic driving system closed-loop confrontation test method based on a world model, and the method comprises the steps: building an end-to-end automatic driving system test platform based on the world model, providing end-to-end automatic driving system perception input information, and carrying out the modeling of a camera sensor, the accurate alignment among the multi-modal scene information is realized; constructing a traffic flow module, and providing map and scene global state information; a traffic vehicle multi-agent collaborative confrontation strategy balancing strategy convergence and strategy diversity is designed, a dense reward function is constructed and matched with an agent heterogeneous strategy adaptive adjustment method, a global exploration target is planned as a whole, and the test efficiency is improved; all the modules are integrated, an end-to-end automatic driving system to be tested is integrated, and efficient closed-loop testing is achieved. According to the method, efficient testing of the performance of the end-to-end automatic driving system can be achieved, the robustness and safety of the end-to-end automatic driving system can be evaluated, and functional defects of the system can be rapidly excavated.

The invention discloses a new energy automobile fault diagnosis and early warning system based on artificial intelligence, and the system employs an advanced artificial intelligence technology, and is designed according to the fault diagnosis and early warning demands of a new energy automobile. By integrating a high-precision sensor and a real-time data acquisition module, the system can comprehensively monitor key performance parameters of the vehicle; by utilizing machine learning and deep learning algorithms, the system can automatically identify a fault mode, the diagnosis accuracy is improved, and the diagnosis time is shortened; meanwhile, based on a potential fault early warning function of big data analysis, vehicle data can be monitored in real time, potential faults can be found in advance, and measures can be taken in time to prevent the faults. The system also has a strong data processing capability, can process and analyze a large amount of vehicle data in real time, and provides powerful support for fault diagnosis and early warning. Generally speaking, the system can significantly improve the safety, reliability and maintenance efficiency of the new energy vehicle, reduce the maintenance cost of a vehicle owner, and improve the user experience.

The present invention proposes an autonomous driving testing method based on multi-alliance cluster confrontation, aiming to improve the efficiency and accuracy of autonomous driving simulation test, and comprising S1—initialization of testing environment of autonomous driving; S2—decision-making for dividing background vehicle clusters; S3—decision-making for confrontation behaviors of the background vehicles; S4—trajectory planning for the background vehicles; and S5—looping through the steps S2, S3, and S4 until cluster confrontation testing tasks are completed. The method of the present invention uses reinforcement learning and alliance games to dynamically generate testing scenarios that are highly confrontational to vehicles being tested, which can find dangerous boundary scenarios for autonomous driving more quickly and improve the efficiency of simulation testing.

Embodiments of the current disclosure provide for a mobile system interface device that translates between agnostic mobile system data and adapted mobile system data. Embodiments of the current disclosure also provide for remote active diagnostics of a mobile system using the mobile system interface device. Embodiments of the current disclosure also provide for testing of mobile systems using the mobile system interface device.

The invention discloses quality inspection equipment for automobile thermostat production, and belongs to the technical field of automobile part quality inspection, the quality inspection equipment comprises a rotary detection table and a center column rotatably arranged at the center of the interior of the rotary detection table, and the side wall of the rotary detection table is rotatably provided with a mounting sliding rail playing a supporting role. The top end of the rotary detection table is provided with circumferentially distributed detection grooves, the top end of the rotary detection table is provided with indicating lamps at the detection grooves, and the inner walls of the detection grooves are fixedly connected with mounting rings. By arranging the rotary detection table, the detection mechanism and the water circulation mechanism, the detection mechanism is matched with the water circulation mechanism, the principle of variable control is utilized, interference of other factors is eliminated, hot water is injected into the detection groove in batches, and whether various indexes of the thermostat are qualified or not is judged by monitoring whether the opening and closing distance of a main valve is qualified or not; therefore, the fault reason of the thermostat can be accurately determined, and an indication effect is achieved for factory return overhaul and process improvement of subsequent defective thermostats.

The invention discloses a new energy automobile safe driving detection method and system, and relates to the technical field of safe driving detection, and the method comprises the steps: collecting vehicle state data, and carrying out the preprocessing of the vehicle state data; constructing a health state evaluation model, and predicting a vehicle health state score; dynamically adjusting scene detection parameters according to the vehicle health state score; environment data are collected in real time through the adjusted scene detection parameters, and a scene risk score is evaluated based on the environment data; and according to the vehicle health state score and the scene risk score, generating an optimal driving strategy, and executing an active safety linkage mechanism. According to the invention, the health state evaluation model is constructed, the multi-dimensional state data of the vehicle is comprehensively analyzed, and the health state of the vehicle is accurately quantified; the environment detection parameters are dynamically adjusted according to the health state score, the detection sensitivity and frequency are improved when the health state is poor, and the adaptability to complex road conditions and severe weather is enhanced.

A system for accidentology-based measuring of accident risk-indexing score values for a motor vehicle to be tested providing a measured accident probability value for an occurrence of an accident event having a physical impact to the tested motor vehicle. The system includes a driving scenario module, a test setting module, and a scoring module. The driving scenario module is configured for determining various driving scenarios for the motor vehicle by defining a set of measurable scenario characteristics, which include at least one ADAS variable. The test setting module is configured for determining a test setting in form of a multi-dimensional test matrix, which includes testing protocols for each of the measurable scenario characteristics for providing measured values of measurable scenario characteristics of the various driving scenarios. The scoring module is configured for generating the risk-indexing score by receiving the multi-dimensional test result signal and a historical data information signal.

Provide are a method for evaluating a human-machine interaction of a vehicle, a system, an edge computing device, and a medium. The method includes: acquiring, in a target driving test scenario, human-factor interaction data and external data, in which the human-factor interaction data is generated based on an interaction between a tester and a human-machine interaction system of the vehicle, and the external data is associated with driving of the vehicle; and evaluating an interaction element in the human-machine interaction system based on the human-factor interaction data and the external data to obtain evaluation data for the interaction element.

The invention provides a compound degree-of-freedom excited abnormal sound test bench. The compound degree-of-freedom excited abnormal sound test bench comprises a base, a supporting frame, an objective table, a first limiting piece, a second limiting piece and a driving mechanism, the supporting frame is provided with a first mounting part, the bottom of the objective table is provided with a second mounting part and two driving connecting parts, and one side edge of the objective table is provided with a third mounting part; the first limiting piece comprises a rod body and two first elastic parts, and the first mounting part and the second mounting part are connected with the two ends of the rod body through the first elastic parts correspondingly; the second limiting piece comprises an extension arm and a mounting seat, the mounting seat comprises a second elastic part, and the two ends of the extension arm are connected with the second elastic part and the third mounting part respectively; the driving mechanism comprises two driving end heads, and each driving end head is connected with one driving connecting part. The first limiting piece and the second limiting piece are used for supporting, limiting and guiding the objective table, composite degree-of-freedom excitation can be achieved only through z-direction exciting force, operation is convenient, and the testing effect is good.

The invention relates to a calibration method of a vehicle transmission assembly, in particular to a transmission shaft calibration rack and a transmission shaft torque test method in the whole vehicle operation process, and aims to solve the problem that an existing transmission calibration method cannot meet the torque test requirements of a whole vehicle under various complex operation conditions. The output torque strength of the transmission shaft cannot be accurately obtained, and the problems of whole vehicle NVH and strength are difficult to solve. The method comprises the following steps: 1) installing a transmission shaft to be calibrated; (2) torque is loaded to the driving motor and the load motor; 3) calibrating to obtain ri and ui; 4) obtaining a single calibration process ri-alpha i-Si corresponding relation; 5) obtaining a three-dimensional calibration data set; 6) obtaining a plurality of three-dimensional calibration data sets, and sorting to obtain a four-dimensional calibration data set; (7) the calibrated transmission shaft is assembled to the vehicle; and 8) calculating the output torque Tx of the transmission shaft at any moment. According to the method, forward and reverse torque loading is performed by using the driving motor and the load motor, and the calibration precision is high.

The invention relates to the technical field of obstacle prediction, and provides a vehicle fault real-time diagnosis method based on multi-source heterogeneous data and a dynamic stream processing system, and the method comprises the steps: obtaining multi-source heterogeneous operation data from a vehicle sensor, a vehicle-mounted bus and an external environment; based on historical fault samples, determining a parameter critical value interval of each fault for each historical fault sample through reverse reasoning, and constructing a fault critical value library; performing dynamic streaming processing on the multi-source heterogeneous operation data, extracting time sequence features, comparing the time sequence features with a fault critical value library in real time, and outputting early warning through a multi-source voting mechanism; and when the operation data is close to or exceeds the corresponding critical value interval, outputting a fault prediction result, and triggering a dynamic updating mechanism to correct the critical value library. According to the method, the accuracy, timeliness and interpretability of fault identification are improved, meanwhile, the system resource consumption and real-time requirements are considered, and the method is suitable for long-term health state monitoring of large-scale vehicles.

The invention discloses a truck hub maintenance-free bearing all-condition simulation testing machine, which comprises a tool table, a servo driving system, a servo hydraulic system and a temperature control simulation system, and is characterized in that the tool table is provided with a tool seat and a main shaft movably arranged on the tool seat, and a to-be-tested bearing is detachably connected between the main shaft and the tool seat; the servo driving system is in linkage fit with the main shaft to simulate the actual operation condition of the bearing, the tool table is provided with a special-shaped load plate and a mandrel, the special-shaped load plate is in linkage fit with the mandrel, and the mandrel is inserted into an inner ring shaft hole of the bearing to be tested and is detachably connected with the inner ring shaft hole of the bearing to be tested. The servo driving system is in linkage cooperation with the special-shaped load plate to simulate the load working condition of the bearing during actual operation, and the temperature control simulation system is in linkage cooperation with the bearing to be tested to simulate the actual temperature working condition of the bearing. According to the invention, the problem that a test device for carrying out a multi-working-condition simulation test on a truck hub bearing is lacked in the prior art is solved.

The invention provides a vehicle window test system and a vehicle window test method, and the vehicle window test system not only samples the operation parameters of a vehicle window motor through a sampling module, but also samples the pressure information of the upper edge of a vehicle window through a pressure sensor, and samples the displacement information of vehicle window glass through a displacement sensor. Therefore, the electronic equipment can perform multi-angle analysis on the vehicle window system according to the multi-path sampling information corresponding to each sampling moment, and abnormal vehicle window parts and / or regulation and control methods in the vehicle window can be determined more accurately.

The present invention relates to a fatigue loading test mechanism for a car seat frame, comprising: a force cylinder for pushing and pulling the seat frame; a proportional valve installed at the tail of the force cylinder, the valve port of the proportional valve connected to the air vent of the force cylinder through an air pipe; a force sensor and a displacement sensor installed on the cylinder rod of the force cylinder; a control system, which controls the opening of the proportional valve according to the force value and displacement value fed back in real time by the force sensor and the displacement sensor, and adjusts the loading force, loading speed, and loading stroke of the force cylinder in real time. The present invention uses the cylinder as the actuating component for applying the load, and controls the force speed, accuracy, extreme value, and stroke of the cylinder extension and retraction process by controlling the proportional valve; the fatigue loading test of the seat frame can be realized stably and reliably for a long time with high-frequency loading cycles and high-precision loading force, so that the loading test process can be completed relatively quickly, accurately, and reliably.

An apparatus for measuring the stopping distance of a working machine is provided. The working machine includes a user interface, at least one processor, and at least one memory including a computer program code. The at least one memory and the computer code are configured to, with the at least one processor, cause the apparatus at least to: receive at least one speed parameter based on at least one user input on the user interface, receive at least one speed information value from a controller or the engine control unit of the working machine, send at least one command to the controller or the engine control unit to at least stop the working machine when the received speed information value is equal to the at least one speed parameter, and calculate the stopping distance of the working machine. A method and a system are also disclosed.

The invention discloses an electric tricycle frame welding quality evaluation method combined with vibration detection, and relates to the technical field of fault diagnosis, and the method comprises the steps: reading historical operation records of similar tricycles, collecting a welding fault event set, carrying out fault tracing, and determining a high-frequency fault source. A vibration monitoring array is arranged, a vibration test is performed on a target tricycle in a predetermined scene, and a plurality of vibration signal distributions are generated. And the welding fault probability is analyzed in combination with industrial big data, and a welding quality evaluation coefficient is obtained according to probability matching and serves as an evaluation result of the frame welding quality. The technical problems that in the prior art, welding quality detection cannot be dynamically combined with the actual use condition of the vehicle for comprehensive evaluation, so that prediction precision is low, and the evaluation process is tedious are solved, and the technical effect of improving convenience, accuracy and practicability of welding quality evaluation is achieved.

The invention provides a method for testing identification and response of an automatic driving vehicle to a signal lamp in a closed site, and belongs to the technical field of automatic driving testing. The method solves the problem that it is difficult to dynamically simulate a real signal lamp interaction scene and quantitatively evaluate the accuracy of a vehicle perception-decision chain in a closed test. According to the technical scheme, the method comprises the following steps: constructing a line segment topology network with directional attributes; deploying a three-dimensional adjustable signal lamp device at the node to dynamically adjust the pose; synchronously acquiring signal lamp identification result data and control response behavior data of the vehicle; calculating a time margin based on the vehicle positioning speed and the distance from the stop line, and triggering signal lamp state grading switching through comparison with a preset threshold value; a two-dimensional verification mechanism is adopted, and identification result data and control response behavior data are aligned through a time synchronization protocol to analyze causal relevance. The method is used for testing and verifying the recognition accuracy and response timeliness of an automatic driving vehicle on a signal lamp scene in a closed site.

The invention discloses an unmanned vehicle interaction fault analysis method and device, terminal equipment and a storage medium. The method comprises the following steps: acquiring multi-source data of a to-be-detected unmanned vehicle; wherein the multi-source data comprises state data, environment sensing data, system data and fault recording data; generating fusion data of the to-be-detected unmanned vehicle according to the state data, the environment perception data, the system data and the fault record data; inputting the fusion data of the to-be-detected unmanned vehicle into an unmanned vehicle interaction fault analysis model, so that the unmanned vehicle interaction fault analysis model outputs fault data of the to-be-detected unmanned vehicle; wherein the fault data comprises a fault type, a fault priority and a fault probability. According to the invention, the accuracy of interaction fault analysis of the unmanned vehicle can be improved.

An electronic system for controlling vibrations and / or inertial forces occurring at a plurality of areas of interest within an operating vehicle. The electronic device comprises circuitry configured to receive input data comprising sensor data from one or more environment sensors and / or one or more internal sensors; convert, by means of a machine learning system, the input data into actuator settings; and transmit the actuator settings to one or more actuators to control vibrations and / or inertial forces occurring at each of the plurality of areas of interest within the vehicle.