21599 results about "Truck" patented technology

The invention relates to the technical field of software systems, and particularly discloses a vehicle matching and positioning system and method based on comprehensive characteristics of a vehicle and a container, and the system comprises a multi-mode perception and intelligent identification module, a dynamic task matching and scheduling optimization module, an intelligent decision and automatic execution module, and a user interaction and operation module. According to the system, the states of a container and a container truck are sensed in a fusion mode through multiple sensors, cross-modal data feature learning is carried out through a Transform-VIM self-attention mechanism, and high-precision container recognition in a complex environment is achieved; meanwhile, based on multi-dimensional feature matching and a Hungary optimization algorithm, a dynamic task matching mechanism is constructed, and it is ensured that the container trucks and the containers are in accurate butt joint; the system optimizes a scheduling strategy through reinforcement learning, dynamically adjusts an operation process, and is linked with automatic equipment, so that intelligent and efficient port container transportation management is finally realized, the risks of wrong loading, neglected loading and operation delay are effectively reduced, and the overall throughput and operation efficiency of a port are improved.

The invention provides an intelligent obstacle avoidance and operation range planning method and system for a manual telescopic arm of a truck-mounted crane, and relates to the technical field of truck-mounted crane obstacle avoidance, and the method comprises the following steps: collecting environment point cloud data, truck-mounted crane attitude data and obstacle distance data, constructing a dynamic environment map, and identifying obstacle features; dividing operation areas based on the dynamic environment map and the obstacle state data, and establishing an operation space safety level model; in combination with the working space safety level model and the obstacle state data, an obstacle avoidance candidate path meeting load constraints is generated, an optimal path is selected and converted into an obstacle avoidance track and a control instruction, and finally cantilever crane obstacle avoidance is achieved; by monitoring the distance between the boom and the obstacle in real time, hierarchical control is executed, and the safety and efficiency of operation of the manual telescopic boom of the truck-mounted crane are effectively improved.

The invention discloses a long downhill section truck brake pad high temperature detection and cooling method and system, and the method comprises the steps: collecting the surface temperature data of a truck brake pad in real time according to high-precision infrared temperature sensor arrays and thermal imagers disposed at the two sides of a long downhill section, and generating a time-space correlation temperature field distribution diagram; based on the temperature field distribution diagram, dynamically adjusting a temperature safety threshold curve through reinforcement learning, and outputting a dynamic early warning trigger signal; according to the dynamic early warning trigger signal, a corresponding spraying instruction is generated so as to drive a piezoelectric ceramic microvalve array of a roadside spraying device to conduct spraying cooling on the brake pad; and according to the temperature attenuation rate and infrared thermal image feedback data of the brake pad after spraying, the temperature safety threshold curve and the spraying instruction are corrected through a Bayesian optimization algorithm, and closed-loop safety regulation and control are formed. According to the embodiment of the invention, the temperature of the brake pad can be monitored in real time, accurate spraying cooling control is realized, and safe and stable braking performance of a truck is ensured.

A tonneau cover for a bed of a truck is provided. The tonneau cover includes several improvements including but not limited to a bulkhead panel that is secured to the truck. A first cover panel section pivotably attached to the bulkhead panel. A first intermediate panel section pivotably attached to the first cover panel section and a second panel section. A second intermediate panel section pivotably attached to the second cover panel section and a third panel section. The first cover panel section, the second cover panel section, and the third cover panel section fold to form a stack of cover panel sections which is pivoted upright onto the bulkhead panel which supports the stack of cover panel sections in an upright position. The second intermediate panel section sets upon the bulkhead panel when the stack of cover panel sections is pivoted upright onto the bulkhead panel.

A Level IV fuel-saving robot system for ACE HDTs of the present disclosure focuses on the minimization of actual fuel consumption (L / 100 km) for long-haul freight at first based on an electrical power split device (ePSD) and a mixed hybrid powertrain architecture. A basic model Level I fuel-saving robot realizes a longitudinal L1 automatic driving function through a predictive adaptive cruise (PACC) technology within an Operational Design Domain (ODD) for highways and reduces the actual fuel consumption of an ACE HDT by more than 20% compared with modern diesel HDTs, and the energy-saving and emission-reducing effect of the basic model Level I fuel-saving robot is decoupled from both the technical level of a vehicle engine and the driving level of a driver; an advanced Level IV fuel-saving robot has a L4 automatic driving function within the ODD for highways, operates in a “shadow mode” or “detached mode”, automatically generates a discrepancy report or detachment report, completes the “3R” batch validation for an L4 system on a billion mile scale quickly with high cost effectiveness on the premise of ensuring the traffic safety of existing road users and reduces the total validation expense by more than 65% compared with the modern HDT with internal combustion engine equipped with the L4 system, promoting the early commercialization of the Level IV fuel-saving robot.

The invention discloses a scheduling information management method and system based on fire fighting of a fire fighting truck, and relates to the technical field of intelligent fire fighting scheduling, and the method comprises the steps: receiving fire alarm information, and collecting real-time fire scene data based on a preliminary fire behavior evaluation result; combining the collected real-time fire scene data with historical fire data, and analyzing a fire spreading trend through an AI fire prediction model; according to the fire behavior spreading trend and the equipment state of the fire fighting truck, dynamically allocating fire fighting truck resources, and planning an optimal driving route; the driving state of the fire fighting truck is monitored in real time, dynamic adjustment is performed based on road conditions and equipment information, and task allocation of the fire fighting truck is updated according to the real-time fire scene situation; in the fire extinguishing process, resources are dispatched in real time for supply according to the material consumption condition of the fire fighting truck. By monitoring the material consumption condition of the fire fighting truck in real time, the supply resources are intelligently dispatched, and the continuity and high efficiency of the fire extinguishing action are ensured.

The present invention relates to an intelligent material distribution and material taking device and method for solid fermentation of powdery and granular fertilizers, comprising at least one production line, the production line comprising: a longitudinal conveyor belt parallel to the length direction of the fermentation tank; a transverse conveyor belt arranged above the fermentation tank along the width direction of the fermentation tank; a discharge vehicle, including a longitudinal discharge vehicle and a transverse discharge vehicle; a material distribution conveyor belt for receiving the fermentation raw materials scattered by the longitudinal discharge vehicle; a longitudinal receiving hopper; a mobile spiral material taking machine, which is longitudinally slidably arranged in the fermentation tank to collect the intermediate products in the fermentation tank; a controller, which controls the intelligent material distribution and material taking device for solid fermentation of powdery and granular fertilizers to switch between the two working states of distribution and material taking, and controls the transverse conveyor belt and the longitudinal discharge vehicle to keep synchronous longitudinal movement. The controller is used to switch the working state of the material distribution and material taking device, so as to realize intelligent and automatic material distribution and material taking, so as to meet the needs of solid fermentation of powdery and granular fertilizers.

Embodiments of the present invention disclose a portable folding wagon, comprising wheel components, four damping elements, a foldable load-bearing bottom frame, a foldable main frame, a telescopic handle assembly and a cloth basket; the wheel components comprise two fixed wheels arranged at a rear part of the portable folding wagon and two universal wheels arranged at a front part of the portable folding wagon; the foldable load-bearing bottom frame comprise two lower rear connectors, two lower front connectors and an X-shaped folding load-bearing frame; the fixed wheels are arranged below the lower rear connectors through the damping elements, and the universal wheels are arranged below the lower front connectors 14 through the damping elements; the damping elements comprise one or more of damping springs, cylinder dampers or variable damping force shock absorbers; the portable folding wagon provided by the present invention has excellent shock absorption performance, and is very suitable for conditions where there exists rugged roads and large vibration in the camp sites; and an overall volume of the portable folding wagon in the present invention is larger than the overall volume of a conventional cart, while a size of the portable folding wagon after being folded is smaller.

The invention provides a self-adaptive control method and system for an automatic driving truck, and the method comprises the steps: carrying out the filtering and structural processing of multi-dimensional data collected by a vehicle-mounted sensor network, and generating a standardized data package containing vehicle state parameters and environment information; and according to the standardized data packet, retrieving a deep learning neural network model library, selecting a currently applicable basic model, and dynamically adjusting parameters of the basic model to generate an optimized adaptive control model. And inputting the standardized data packet into an adaptive control model for operation, generating a candidate control instruction, and generating an optimal control strategy through rapid simulation and multi-objective optimization calculation. And finally, the optimal control strategy is executed by the vehicle controller, vehicle response is monitored in real time, and controller parameters are adaptively adjusted based on deviation. According to the method, the dynamic adaptability and strategy optimization of the control model are realized, and the safety and efficiency of the automatic driving truck in a variable environment are improved.

A modular storage system of connectable, heavy-duty storage boxes, crates, rolling carts and / or dollies, work surfaces, organizers, trays, accessories is provided for internal and external item storage and organization and convenient access for use and transport, that is expandable, customizable and readily adaptable. Storage boxes have different sizes by length, width and / or height and have universal box-to-box connection system for stacking and connection to mounting accessories. Boxes have removable, customizable organization inserts (e.g., dividers, storage trays, bins, alignment trays for bins, and bins of different sizes). Box lid rib grid with bosses and undercuts expands internal organization, including cooperation with dual purpose dividers and accessories. Boxes have external mounting accessories to expand external organization. Different housing modes are provided including wall mount systems for wall or side of a truck or van, and different transport modes are provided (e.g., base box with wheels, or on a dolly or a cart).

The invention relates to the technical field of electric heavy trucks, and discloses an electric heavy truck self-adaptive positioning method and system based on multi-sensor fusion, and the method is characterized in that a sensor data preprocessing module and a space-time synchronization module are constructed to carry out the preprocessing of data obtained by sensors; performing basic positioning on the electric heavy truck based on an Apriltag label positioning algorithm and a laser slam positioning algorithm; carrying out real-time positioning and correction on the electric heavy truck in a moving state by an Apriltag-assisted laser slam correction algorithm based on ESKF; the stability of a GPS signal in a current environment is automatically detected and analyzed through an adaptive controller module, a fuzzy control selector is adopted to adaptively switch a positioning mode according to a real-time condition, and an Apriltag auxiliary laser slam positioning algorithm based on an ESKF is designed according to the difference of different sensors carried by the electric heavy truck. And then considering the operation requirements of the electric heavy truck in complex environments such as unstable GPS signals in a mining area, designing an adaptive positioning system of the electric heavy truck so as to improve the positioning precision and robustness.

The invention provides a narrow-space-oriented truck-mounted crane manual arm operation path planning method and system, and relates to the technical field of path planning, and the method comprises the steps: carrying out the multi-source information fusion through binocular vision and laser ranging, and building an operation space three-dimensional model; a convolutional neural network is adopted to identify an obstacle, a kinematics constraint is combined to establish an obstacle avoidance cost function, and a bidirectional probability sampling algorithm is utilized to generate and optimize an initial path. Afterwards, a target path is screened by considering the dynamic constraint of the load weight, and dynamic adjustment is carried out based on a comprehensive evaluation function of path length, smoothness and safety degree and a virtual spring damping model; and finally, performing polynomial fitting on the adjusted path, calculating a joint angle and performing local correction according to a kinematic model, and finally outputting a working path meeting constraint conditions. According to the invention, the working efficiency and safety of the truck-mounted crane in a narrow space are effectively improved.

The invention discloses an automatic long drilling tool loading and unloading system of a directional drilling machine and a control method. The automatic long drilling tool loading and unloading system comprises a drilling main machine, a rod loading and unloading mechanical arm and a rod supplementing device. In the drill rod loading and unloading construction process, the rod loading and unloading mechanical arm can achieve the rod loading and unloading function at different drilling angles, the rod loading and unloading action within the range of 0-90 degrees can be achieved in the mode that linear motion and rotary motion are combined, accurate positioning at multiple angles is achieved in the mode that mechanical limiting and an angle sensor are combined, and the drill rod loading and unloading efficiency and reliability are improved; during rod supplementing operation, the drilling machine has the rod bin capacity meeting the single-shift footage average value in actual construction, single-shift one-time rod supplementing can be achieved, and auxiliary personnel do not need to wait for rod supplementing basically. The drilling machine is suitable for underground coal mine automatic directional drilling machine construction, can achieve integral layout, is compact in structure, is provided with a power system, and does not need to be matched with a special power pump truck for use.

The invention provides an air-ground cooperative intelligent emergency material scheduling and electric power configuration optimization method and system, and the method comprises the steps: constructing an air-ground cooperative emergency resource joint scheduling frame which integrates heterogeneous resources, such as future emergency trucks, unmanned aerial vehicles, unmanned and manned new energy vehicles; the objective of the invention is to jointly optimize post-disaster emergency material distribution and power recovery processes so as to improve the overall emergency response efficiency and cooperative capability. Secondly, aiming at the complexity of air-ground cooperative scheduling under the framework, a two-stage optimization model is designed, and the objective of the two-stage optimization model is to maximize the emergency power supply capability of the key area in the first stage and minimize the material distribution time of the unmanned aerial vehicle taking off from the large power supply vehicle based on the two-stage optimization model in the second stage. And finally, in order to efficiently solve the model, a GRASP algorithm and an ALNS algorithm are respectively developed. Through simulation analysis based on actual scene data, the feasibility and potential of the whole method for realizing quick response of emergency materials and electric power under a real disaster background are proved.

A vertical-bar connection assembly for a collapsible wagon and a collapsible wagon is provided. The vertical-bar connection assembly has an extended state and a folded state. The vertical-bar connection assembly comprises at least one vertical-bar connection member comprising a first connecting bar and a second connecting bar. Each of the first connecting bar and the second connecting bar has a proximal end and a distal end. The proximal ends of the first connecting bar and the second connecting bar are hinged with each other. The distal ends of the first connecting bar and the second connecting bar are respectively adapted to be hinged with the adjacent vertical bars of the collapsible wagon, and are rotatable about their respective proximal ends to move away from or close to each other, so as to allow the vertical-bar connection assembly to be in the extended state or in the folded state.

The invention provides a heavy truck battery compartment guiding method and system based on visual perception. The method and system are used for automatic battery replacement operation in a complex industrial environment. According to the system, a multi-camera fusion visual perception platform is constructed, a plurality of industrial cameras arranged on the ground or ceiling of a battery swap station are used for collecting local images of different visual angles of a battery compartment, and a complete visual field image is generated through feature matching and image splicing. A battery compartment is coarsely positioned by adopting a YOLO series model, a bounding box region is extracted, pixel-level contour segmentation is realized by introducing SAM, and the complex background and multi-interference environment recognition capability is enhanced. And after segmentation, calculating a minimum enclosing rectangle of the battery compartment, obtaining a center coordinate and a deviation angle, and transmitting a pose parameter to an upper computer control system. According to the method, the defects of the laser radar are avoided, image processing, the deep neural network and multi-view information are fused, the recognition precision and stability are improved, the battery replacement efficiency and the unmanned level of the electric heavy truck can be remarkably improved, and reliable support is provided for green traffic.

Provided are an electric wagon and an electronically power assisted wagon. The electric wagon includes a wagon body including at least a foldable frame; a handle device connected to the wagon body; a walking assembly including at least driving wheels; a drive motor configured to drive the driving wheels to rotate; a power supply connection portion configured to be detachably connected to a battery pack for supplying power to the drive motor, and a controller electrically connected to at least the drive motor to control the drive motor to rotate.

The invention discloses an engineering vehicle multi-area environment control system based on AI, and particularly relates to the technical field of engineering vehicle environment control. Humidity, electric field, air pressure and dust multi-mode sensing arrays are arranged in multiple areas of an engineering vehicle, dust particle deposition distribution time sequence characteristics are extracted, and a deposition acceleration coefficient and a humidity response coefficient are calculated; calculating a dust deposition risk coefficient, comparing the dust deposition risk coefficient with a preset value, and marking a region exceeding a threshold value as a region in a dust deposition abnormal state; analyzing a deposition trend based on a time sequence prediction model, inputting environmental parameters, and predicting a dust deposition velocity curve of each area of the engineering vehicle in a future set time; according to the method, the static electricity, humidity, air pressure and dust coupling deposition risk is assessed in a prospective mode, a collaborative intervention strategy is triggered through a dynamic early warning threshold function, the effect of rapidly restraining the risk is achieved, and the problem that traditional single-parameter monitoring lags behind, and ventilation efficiency is suddenly reduced due to the fact that a coupling mechanism cannot be captured is effectively solved.

The invention provides a collaborative optimization scheduling method and system for an integrated energy system comprising an electric heavy truck. The method comprises the following steps: randomly generating key driving characteristics of the electric heavy truck; by analyzing the key features, the charging demand, the schedulable time period and the charging power range of the electric heavy truck are evaluated so as to construct an adjustable potential model of the electric heavy truck; based on the adjustable potential model and the current running state of the electric heavy truck, a daily charging load curve is generated by establishing a load prediction model of the electric heavy truck; establishing a power output model of photovoltaic power generation and a charging and discharging model of an energy storage system; an upper-layer optimization model of electric heavy truck charging scheduling based on IGDT and a lower-layer optimization model of energy storage system and power grid combined scheduling are established to generate a double-layer optimization model; and solving the double-layer optimization model by adopting an iterative solving method so as to generate a collaborative optimization scheduling strategy of the integrated energy system. According to the invention, the energy supplement problem of the new energy heavy truck is effectively solved, and the peak load shifting capability of the power grid is improved.

A rack system for a vehicle and method of operating same includes an upright support bracket and a stability bracket. The upright support bracket has upper and lower portions with the upper portion having a bracket body and a bracket channel, and the lower portion configured to removably attach to the vehicle. The stability bracket has a shelf projection and a bracket base. The shelf projection extends from the bracket base and has a shelf bottom. The bracket base of the stability bracket is configured to be removably secure to the bracket body of the upright support bracket within the bracket channel of the upright support bracket in a predetermined position such that the shelf bottom is configured to support a mounting bar thereon.

A heavy-duty truck includes a cabin, a window having an upper edge region and a lower edge region, a hinge that rotatably couples the upper edge region of the window to the cabin, and a motor-driven actuator coupled to the lower edge region of the window such that actuation of the motor-driven actuator in a first direction moves the lower edge region of the window away from the cabin, thereby opening the window to an open position, and actuation of the motor-driven actuator in a second direction opposite to the first direction moves the lower edge region of the window toward the cabin, thereby closing the window to a closed position.

A truck cover system comprises a side rail configured to be coupled to a side wall of a bed of a truck; a cover removably attached to the side rail and configured to cover the bed of the truck; a latching mechanism attached to the cover and configured to releasably engage the side rail; and a driving assembly configured to drive the latching mechanism. The driving assembly comprises a mount plate coupled with the side rail through a latch attachment; a driving cylinder rotatably coupled with the mount plate; a driving ring releasably coupled with the driving cylinder and configured to rotate together with the driving cylinder; a torsion spring interposed between the driving ring and the mount plate and configured to be driven by the driving ring; and a handle coupled with the driving cylinder and configured to rotate together with the driving cylinder and the driving ring.

The invention discloses a port container transportation full-process simulation and space planning quantification system and method under random event deduction. The system comprises a data acquisition module, a data processing module, a process simulation module, an efficiency quantification index generation module and an efficiency quantification module. The data acquisition module is used for acquiring basic data in port operation; the data processing module is used for processing the basic data; the process simulation module is used for constructing port container transportation process simulation covering the whole process of ship navigation, ship berthing, quay crane loading and unloading, storage yard storage and container truck outward transportation based on the processed basic data, and obtaining a simulation result; the efficiency quantitative index generation module is used for obtaining an efficiency quantitative index according to the container transportation characteristics and the port operation experience; and the efficiency quantification module is used for quantifying the simulation result by utilizing the efficiency quantification index. According to the invention, the current operation efficiency level of the port can be measured comprehensively and objectively.

The embodiment of the invention discloses a double-truck-crane cooperative hoisting monitoring method and device, electronic equipment and a storage medium. The method comprises the steps that component parameters and operation environment parameters of hoisting operation are collected, a reference data model is constructed, and an action expected value and a safety control threshold value are set; state acquisition devices are arranged on the two truck cranes to acquire multi-source data in real time and transmit the multi-source data to a central control system so as to realize synchronous sensing of the two trucks; processing multi-source data based on a data fusion algorithm, and constructing a dynamic attitude model and a collaborative operation state model; a state prediction correction value in the model is compared with the reference data model in real time, deviation is judged, and safety early warning is triggered; and generating a feedback control instruction, dynamically adjusting the hoisting operation, correcting the coordination deviation, and realizing the coordination control of the hoisting posture. In this way, through multi-source data fusion and real-time feedback control, the safety and coordination of cooperative lifting operation of the double truck cranes are remarkably improved.

The invention discloses an automobile hoisting device, and belongs to the technical field of engineering hoisting. The problems that the gravity center of a component is difficult to accurately determine, the position and posture control of a cargo boom is inaccurate, and the load cannot be adaptively adjusted exist in the hoisting process of an existing automobile crane. The device comprises a truck crane body, a cargo boom tail end execution module, a cargo boom body sensing module, an environment sensing module and a control module. The control module is internally provided with a dynamic gravity center correction unit, a multi-sensor fusion unit and a self-adaptive load control unit, processes related sensor data based on Kalman filtering, extended particle filtering and a model prediction control algorithm, and outputs an adjustment instruction. The method is mainly used for improving the accuracy, safety and efficiency of automobile hoisting operation.

Provided is a path planning method of a handling device, a handling device, and an electronic device. The method includes: based on position information of a target goods placement area in a truck bed and an initial position, determining a handling path corresponding to the target goods placement area, where the handling path includes a first handling path including a turn-around position and a loading-unloading position corresponding to the target goods placement area; sending the handling path to a target handling device such that the target handling device, based on the first handling path, travels to the turn-around position in a forward mode, and rotates at the turn-around position to enable a bearing assembly of the rotated target handling device to face toward the target goods placement area, and then travels, in a backward mode, to the loading-unloading position to perform goods loading or unloading operations.

The invention relates to the technical field of data processing, and discloses a truck scale anomaly detection method, device and equipment and a storage medium, and the method comprises the steps: obtaining the operation state data and peripheral image data of a truck scale when a to-be-weighed vehicle drives onto the truck scale; processing the operation state data and the peripheral image data by using a preset target detection model, and performing cross validation and correlation analysis on a processing result to obtain a preliminary abnormality diagnosis result and a potential fault prediction result; and generating a target anomaly detection report according to the preliminary anomaly diagnosis result and the potential fault prediction result. And when the to-be-weighed vehicle is driven into the truck scale, the running state data and the peripheral image data are processed by using a preset target detection model, then cross validation and correlation analysis are performed, and a target anomaly detection report is generated. Abnormal conditions in the running process of the truck scale can be found more timely and accurately, a detailed basis is provided for subsequent maintenance and repair, and stable running of the truck scale is effectively guaranteed.

The invention discloses a garbage truck real-time monitoring and remote scheduling method based on the Internet of Things, and the method comprises the following steps: S1, collecting the real-time data of the operation state of a garbage truck, and carrying out the preprocessing of the real-time data; s2, constructing a task prediction model based on an improved adaptive graph neural network, and generating a preliminary task distribution matrix and a path planning scheme; s3, optimizing the preliminary task allocation matrix and the path planning scheme by adopting an improved PPO algorithm; s4, the optimized task allocation matrix and the path planning scheme are sent to a garbage truck vehicle-mounted terminal, and the task completion rate and the path deviation value are calculated; s5, the operation state of the garbage truck is monitored in real time, and the monitoring result and the operation state data are transmitted to the cloud Internet of Things platform; and S6, dynamically updating the scheduling instruction. According to the method, the Internet of Things, the adaptive graph neural network and the improved PPO algorithm are fused, intelligent scheduling and real-time optimization of the garbage truck are realized, and the method has the advantages of high efficiency, stability and low-cost operation.