370 results about "Axle load" patented technology

The invention discloses a heavy traffic asphalt pavement damage evolution prediction system, and relates to the technical field of road engineering, and the system comprises a data acquisition module which is used for obtaining continuous multi-frame time sequence images of pavement cracks, a vehicle-mounted axle load spectrum and environment temperature and humidity data; the image processing and space-time modeling module is used for performing multi-scale fractal processing and dynamic time warping on the time sequence image and calculating a cross-scale fractal dimension sequence; the material performance association module is used for establishing and updating a probability association model of the fractal dimension and the shear modulus in real time according to the test data of the dynamic shear rheometer; the multi-physics field data fusion module is used for performing multi-physics field feature fusion through the fractal attention network to generate a multi-physics field collaborative damage correction factor; and the damage prediction and early warning module is used for predicting a fractal dimension growth trend through a fractal domain adaptive transfer learning algorithm, and outputting damage evolution early warning based on a viscoelasticity phase consistency verification result.

The invention relates to the field of locomotive power battery electric quantity control, and particularly discloses a locomotive power battery electric quantity hysteresis equalization control method, which comprises the following steps that: a traction force exerting mode is reset into an axle load transfer mode, and the initial value of an electric quantity equalization compensation coefficient K is a rack axle load transfer coefficient corresponding to zero speed; judging whether the current mode is a power battery power supply mode; if yes, the TCU receives the electric quantity of a front power battery and the electric quantity of a rear power battery in real time according to the current locomotive working mode, calculates the electric quantity average value difference value, monitors the auxiliary load power and the traction motor power and calculates the power difference value; entering a hysteresis control logic process; calculating a dynamic traction force compensation coefficient, ensuring that the traction force compensation amount is matched with the actual load characteristic of the system, correcting the traction characteristic curve in real time, and dynamically compensating the electric quantity difference of the battery; and performing traction distribution control according to the locomotive speed and outputting corresponding traction.

The invention relates to the technical field of road damage detection, in particular to an intelligent road damage recognition method and system based on image analysis, and the method comprises the following steps: obtaining road images, screening out substandard images, extracting local features of the images, executing enhancement processing, converting structural parameters, and matching a type template; and combining the vehicle axle load and the damage index to calculate a structure expansion trend, and generating damage expansion risk information. According to the method, the accuracy of damage type identification is improved by combining geometric parameters such as edge length, curvature range and closed region area value and performing scale conversion based on pixel resolution, and an evaluation mechanism of the influence of vehicle load on the damaged region is established by combining traffic flow and vehicle axle load data. The expansion trend is judged through the traffic frequency and the impact weight, the damage development situation is effectively predicted, the accident frequency, the speed limit information and the traffic obstruction factor are introduced into priority ranking calculation, and the urgency recognition capability of road maintenance is enhanced.

The invention provides a front and rear axle load estimation method and system and a steer-by-wire vehicle, and the method comprises the steps: (1) when the vehicle is in a longitudinal stable and straight driving state, updating the mass of the whole vehicle; (2) establishing a least square recursion equation with a forgetting factor based on the dynamic motion equation of the vehicle on the ramp, and calculating the gradient of the current ramp; and (3) calculating a front axle load and a rear axle load based on the whole vehicle mass and the current gradient. The whole vehicle mass estimation is started under the working conditions of longitudinal stability and straight driving, so that the reliability and the stability of the whole vehicle mass calculation process are ensured; besides, vehicle dynamics and kinematics models are fused, recursive calculation is performed by applying a least square method with a forgetting factor, the road gradient can be estimated in real time at high frequency and high precision under various driving working conditions of the vehicle, and the limitation of a traditional fixed parameter model is broken through.

A computer system has processing circuitry to selectively operate the powertrain system in at least a freewheeling mode, in which an output shaft of the engine is non-rotating, and the engine is disconnected from the one or more drive wheels. The processing circuitry is further configured to: determine an opportunity for the freewheeling mode by predicting a feasibility of restarting the engine along an intended route by using a controllable clutch. Predicting the feasibility of restarting the engine by using the controllable clutch includes determining fulfillment of any one of a first restarting condition and a second restarting condition. Determining fulfillment of the first restarting condition includes comparing current total weight of the vehicle with a threshold value indicative of a minimum total weight for avoiding excessive braking of the vehicle during restarting at a high friction road condition with a given total gear ratio. Determining fulfillment of the second restarting condition includes comparing a current drive axle load with a corresponding threshold value indicative of a minimum drive axle load on a drive axle for avoiding excessive wheel slip during restarting at a low friction road condition with a given total gear ratio. The powertrain system is controlled into the freewheeling mode upon the fulfillment of any one of the first restarting condition and the second restarting condition.

The embodiment of the invention provides a vehicle suspension control method and system, a vehicle and a computer readable storage medium, and the method comprises the steps that in the vehicle driving process, a road section in front of the vehicle is detected, target road section data is obtained, and the target road section data at least comprises curve data and / or slope data of the road section in front; based on the target road section data and the current state parameters of the vehicle, control parameters of a suspension in the vehicle are determined, the control parameters comprise suspension rigidity corresponding to the curve data and / or axle loads corresponding to the slope data, the axle loads act on axles of the vehicle, and the axles are connected with a vehicle body of the vehicle through the suspension; according to the control parameters, the initial damping force of the suspension is adjusted to the target damping force, and the initial height of the vehicle body is adjusted to the target height; the suspension is controlled according to the target damping force and the target height so that the vehicle can run to the front road section. The technical problem that the suspension control efficiency is low is solved.

The invention provides a loading safety monitoring method and system for a rear-loading vehicle and the vehicle. The method comprises the following steps that the arc height variable quantity of a plate spring of the vehicle in the current loading state is collected; based on the arc height variable quantity, a vehicle total weight estimated value is obtained through calculation; based on the axle load estimation values of the front axle and the rear axle and the axle distance of the vehicle, estimating the current gravity center height of the vehicle, and dynamically compensating the gravity center height according to the dynamic state parameters; and calculating a stability risk coefficient of the vehicle according to the total weight estimated value of the vehicle and the compensated gravity center height so as to carry out early warning. Displacement sensors are arranged on a front plate spring and a rear plate spring of a vehicle to collect arc height variation in real time, an axle load and a vehicle total weight estimated value are calculated based on a pre-calibrated plate spring rigidity coefficient, the gravity center height of the vehicle is estimated to evaluate the stability of the vehicle, and meanwhile the gravity center height is dynamically compensated based on dynamic parameters in the driving process. The evaluation precision under complex working conditions is improved, and the transportation safety is guaranteed.

The invention relates to the field of power control, and particularly discloses an electric four-wheel drive torque distribution method based on a climbing working condition, which comprises the following steps: defining vehicle state parameters, power system parameters, vehicle real-time driving state parameters and road condition parameters; carrying out torque calculation by utilizing Julia, considering shaft load, friction coefficient, motor efficiency and yaw velocity correction, obtaining a comprehensive weight of a front shaft and a rear shaft, and carrying out normalized torque distribution; and establishing model simulation through Modelica, and verifying the effectiveness of the distribution scheme. According to the invention, the climbing performance of the vehicle can be improved, the control flexibility and driving stability of the vehicle are improved, the energy consumption is reduced, the dynamic stability is enhanced, and the method is suitable for power control of the electric four-wheel-drive vehicle under the climbing working condition.

The invention relates to the technical field of highway bridge safety monitoring, in particular to a bridge dynamic weighing algorithm based on Bayesian maximum posterior probability. Obtaining influence lines through a bridge calibration test, and calculating an influence line matrix, a mean value and a covariance; using a Moses algorithm to obtain the vehicle axle load as the axle load of the initial main cycle i = 0; initial axle load distribution is set, the covariance of load response is obtained through the influence line covariance, the measurement noise and the axle load of the main cycle, and an axle load mean vector and a stable value of the covariance are iterated together with the influence line matrix, the initial axle load distribution and the load response to serve as the axle load distribution of the main cycle; according to the axle load distribution, the influence line matrix, the load response and the covariance thereof, the posterior probability of the axle load is obtained, and the axle load when the probability is the maximum serves as the axle load corresponding to the (i + 1) th main cycle; and repeating until the axle load update difference value is smaller than the preset value, and outputting the axle load result, thereby solving the problem of low axle load identification precision of the existing bridge dynamic weighing system.

This invention is applicable to the field of vehicle stability control technology and provides a coordinated stability control method and system for distributed, drive-by-wire vehicles. The method comprises the following steps: constructing a vehicle dynamics model; collecting vehicle state information based on a state recognition layer and a driving intention recognition layer, calculating and correcting the ideal yaw rate and ideal center-of-mass sideslip angle; allocating control variable weights using a KDPC algorithm; calculating the values ​​of the vehicle's control variables, namely, the rear wheel angle and the additional yaw moment; and allocating wheel drive torque based on the vehicle force, the additional yaw moment, the ratio of front and rear axle loads, the wheel radius, and the wheelbase. Through its electronic and dynamic control strategy, the invention achieves multi-dimensional advantages in flexibility, stability, energy efficiency, and intelligence, extending the vehicle chassis' extreme performance and vehicle handling stability.

The invention provides a low-frequency excitation and high-frequency impact coupled void lining test device and method, and belongs to the technical field of tunnel instability monitoring, and the device comprises a lining loading system, a low-frequency excitation system and a high-frequency impact system. The loading mechanism simulates the surrounding rock load borne by the lining in the circumferential direction, and the surrounding rock load borne by the lining can be simulated by adjusting parameters such as the magnitude and the direction of loading force. The vibration exciter is matched with the power amplifier, low-frequency and high-amplitude vibration matched with the axle load characteristics of the train can be generated, and the fatigue damage effect on the lining caused by long-term running of the train is simulated. When the electric detacher controls the drop hammer to be separated from the truss and fall freely, high-frequency transient impact force can be generated, and the transient load effect of a lining impacted by falling rocks is simulated. According to the test device, through multi-physics field coupling loading, the problems that a void lining damage mechanism is unclear and prediction means are deficient are solved, a complete technical chain is provided for railway tunnel structure safety, and the test device has academic value and engineering popularization significance.

The invention provides an energy recovery control method and system for improving the stability of a rear-wheel-driven vehicle, and the method and system are suitable for a new energy vehicle with a rear-wheel-driven belt for recovering sliding energy and braking energy, and the method comprises the following steps: under the working conditions that the driving torque is smaller than 0 and the turning angle of a vehicle steering wheel or the change rate of the turning angle of the steering wheel is larger than a preset threshold value, the steering wheel is started; the real-time rear axle load of the vehicle is obtained; when the rear axle load is lower than a first preset threshold value, braking energy recovery is quitted, and sliding energy recovery is reserved; and when the rear axle load is lower than a second preset threshold value, sliding energy recovery is quitted. The method is suitable for the working condition that the lateral acceleration of a vehicle is large during large-angle steering or rapid steering in the high-speed deceleration process of a rear-drive vehicle, and the method is used for solving the problem of excessive steering drifting caused by insufficient energy recovery rear axle adhesion of a new energy vehicle.

The invention discloses a tire control performance index coefficient automatic generation method and system, and the method comprises the steps: employing vehicle dynamics simulation software to generate a tire dynamics model, and obtaining a model file; obtaining a load parameter input by a user; the load parameters comprise a front axle load and a rear axle load; reading the model file, and obtaining a first calculation coefficient of the tire from the model file; substituting the first calculation coefficient into a magic formula to obtain a first fitting function; calling a first fitting function, calculating according to the load parameters to obtain force and torque of each working condition, and obtaining a first calculation result; according to the first calculation result and the load parameter, calculating a tire control index coefficient under each working condition through an index calculation formula; and outputting the tire control index coefficient to a preset result file, and generating a tire control performance index coefficient result report. According to the method, the tire control performance index coefficient can be accurately and efficiently generated, so that the tire modeling standardization is improved, and the method can be widely applied to the technical field of computers.

The invention provides a vehicle reversing control method and device, a vehicle and a storage medium, the method is applied to the field of vehicles, and the method comprises the steps that under the condition that the vehicle backs down on a ramp, the gradient of the ramp and the total braking force of the vehicle are obtained; first braking force of a front axle of the vehicle and second braking force of a rear axle of the vehicle are determined based on the gradient and the total braking force, the first braking force is used for braking the front wheels, and the second braking force is used for braking the rear wheels of the vehicle; under the condition that the first braking force is larger than the second braking force, target braking force of a rear axle is determined based on the total braking force and the rear axle load of the vehicle, the target braking force is used for meeting the braking requirement of the vehicle and maintaining rotation of front wheels, and the rear axle load is the load borne by the rear axle. According to the method, under the condition that the first braking force of the vehicle is larger than the second braking force, the braking force is distributed to the rear axle again based on the rear axle load and the total braking force, so that the braking requirement of the vehicle is met, and front wheels of the vehicle are prevented from being locked.

The invention belongs to the field of intelligent transportation, and discloses a large transport vehicle violation detection method and system based on multi-dimensional data matching, and the method comprises the steps: carrying out the data segmentation of the data information of the axle load and axle distance of a special multi-axle large vehicle measured by a dynamic weighing system, and forming a one-dimensional discrete data graph, and according to the formed one-dimensional discrete data graph, establishing a mapping relation between the axle load wheelbase and the total load of the large transport vehicle, and judging whether the large transport vehicle is overloaded or not based on the relation. An image of a large transport vehicle is collected through a highway camera, a point cloud model of the large transport vehicle is generated by adopting an SLAM algorithm, geometric parameters of the large transport vehicle are extracted, and the obtained point cloud model is matched with a preset contour template so as to judge whether the large transport vehicle is loaded illegally or not. According to the invention, one-dimensional data and two-dimensional data are fused in detection of overweight and illegal loading of the vehicle, so that violation detection of the large transport vehicle is realized.

The invention discloses a wheel rail vibration boundary condition testing method and device and a medium. Relates to the field of high-speed trains, and solves the problem of testing wheel-rail vibration boundary conditions on a scaling wheel-rail vibration test bench. According to the invention, from the collection of the real-time axle load value, the real-time torque and the six-component data, the interaction and vibration characteristics between the wheel rails can be reflected more accurately. Through comprehensive processing and analysis of data, feedback control data is finally generated and used for adjusting operation parameters of the test bench. Based on the real-time adjustment of feedback control data, the intelligent and automatic level of the test bench is improved, and the dynamic control of the test process is realized. Compared with a full-scale test bench, the scaling rolling test bench has lower operation and maintenance cost, and can meet the research requirements on the vibration characteristics of the high-speed train.

The invention discloses an anti-skid control method for a high-speed train at a higher speed, which comprises the following steps of: firstly, acquiring basic information such as the speed and the axle load of the high-speed train in real time through a sensor, establishing a real-time analysis model by virtue of data, then calculating a real-time adhesion coefficient, and further judging the rail surface state of wheel-rail contact of the high-speed train; the optimal creep rate under the current rail surface condition is calculated based on the information, the traction or braking torque is adjusted through a control strategy by comparing the optimal creep rate with the actual creep rate in real time, anti-skid control adjustment is conducted, and the adhesion utilization rate and operation safety are improved. According to the method, for a high-speed train at a higher speed, the torque is changed through adhesion control, so that anti-skid control is carried out, the adhesion utilization rate and the operation safety are improved, and wheel skid and abnormal abrasion can be effectively restrained.

The invention relates to the technical field of bridge monitoring, in particular to a medium and small span bridge strain intelligent verification and diagnosis method and system combined with refined space axle load. According to the method, a space-time distribution matrix of the vehicle axle load of the actual traffic flow on the multi-beam medium and small bridges is established based on a data driving method, an implementation process for converting time-discontinuous discrete dynamic weighing monitoring data into a time sequence of the vehicle axle load is provided, and reference is provided for engineering application. According to the method, the bridge is innovatively divided according to the longitudinal area to achieve linkage calculation of the time sequence of the vehicle axle load and the theoretical strain value of the key section of any main beam of the small and medium-sized bridge, and the strain-based safety condition evaluation index of the small and medium-sized bridges is established by combining the strain monitoring data of the key section of the small and medium-sized span bridge. According to the method, the bridge health monitoring data are effectively mined, the value of the multi-source monitoring data is fully utilized, and the rationality and reliability of bridge safety evaluation are effectively improved.

The invention provides a lateral movement sensing method and a vehicle, the method is applied to the technical field of vehicle control, and the method comprises the steps that a tire slip angle value at the current moment is obtained in response to a target calculation instruction of the vehicle; calculating an actual lateral force value at the current moment based on the tire slip angle value and the current wheel slip rate of the vehicle; and calculating the actual lateral motion acceleration of the vehicle according to the actual lateral force value, and evaluating the axle load transfer amount in the vehicle steering process according to the actual lateral motion acceleration. According to the method, the actual lateral force can be calculated in real time according to the tire slip angle and the wheel slip rate in various running states of the vehicle, then the actual lateral motion acceleration of the vehicle is accurately output, different working conditions can be adapted, and the real-time performance and accuracy of vehicle dynamics control are improved.

The invention discloses a coal ash roadbed permanent deformation prediction method and a prediction model thereof. The method comprises the following steps: firstly, obtaining the optimal water content and the maximum dry density of fly ash through a fly ash compaction test; filling the fly ash in the state into a full-scale model according to a core-spun method, and applying dynamic loads simulating different vehicle speeds and axle loads to carry out a test to obtain permanent deformation values under different working conditions; and establishing a prediction model based on a time hardening power law criterion and a nonlinear viscoplastic constitutive theory, fitting test values to determine model parameters, and constructing the prediction model. Based on the prediction model, equivalent standard axle load action times allowed by a road structure are predicted according to a specified critical threshold, quantitative evaluation of road durability is realized, and a scientific early warning mechanism is provided for road maintenance decision. According to the technical scheme, the settling volume of the fly ash roadbed can be accurately predicted, and the road durability is effectively evaluated.

The invention discloses a method for determining an initial modulus of a semi-rigid base of an in-service asphalt pavement, and relates to the technical field of road engineering, a preset monitoring point of the in-service asphalt pavement is detected through a drop weight deflectometer, and a base modulus value is obtained through back calculation based on a deflection detection result; based on the transverse distribution coefficient of the carriageway, respectively calculating the accumulated axle load action times of the preset monitoring points; establishing a basic layer modulus damage model with basic layer initial modulus parameters by utilizing the structure behavior equation; and detecting basic layer modulus values under different accumulated axle load action times by using a drop weight deflectometer, performing regression fitting to obtain model parameters, obtaining a complete basic layer modulus damage model, and obtaining a basic layer initial modulus. According to the method, the initial modulus of the base layer is determined through the drop weight deflectometer.

The motor tricycle rear axle load adjusting device comprises a base, an adjusting arm and a load spring, two sides of the base are respectively and rotatably connected with one end of an upper rocker arm, and the other end of the upper rocker arm is respectively connected with a rear wheel steering knuckle. Two brackets and a jacking mechanism are fixedly arranged on the upper surface of the base; the jacking mechanism is located between the two supports. The adjusting arm comprises a first end part, a second end part and an arm body, a through hole is formed in the first end part and is used for being rotatably connected with the second through hole, one end of a load spring sleeves the bottom of the second end part, and the other end of the load spring sleeves the upper surface of the upper rocker arm; a third through hole is formed in an arm body of the adjusting arm and used for being rotationally connected with a hole in the top of the jacking mechanism. The adjusting arm serves as a lever, the third through hole serves as a fulcrum, the through hole in the first end serves as a force point, the jacking mechanism presses the two load springs downwards while ascending, and load support is provided for the motor tricycle.

1. The name of the design product: multifunctional detector. 2. The use of the design product: for the safety of motor vehicles, for detecting braking performance, pressure, tension, weighing, axle load performance. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: design 1 perspective view. 5. Design 1 is designated as the basic design.

The present application relates to the technical field of bridge health monitoring, in particular to a bridge health monitoring system acceleration sensor online calibration method and system. The method comprises the following steps: extracting dynamic axle load time history characteristics and environmental interference correction factors according to traffic load data and environmental monitoring data; processing standard sensor data and to-be-calibrated sensor data to obtain real vibration reference characteristics and initial deviation characteristics; using the traffic load data and the real vibration reference characteristics to obtain working condition weight characteristics; combining the dynamic axle load time history characteristics, the environmental interference correction factors, the real vibration reference characteristics, the initial deviation characteristics and the working condition weight characteristics to obtain adaptive optimization calibration values. The present application can realize calibration without disassembling sensors and blocking traffic under normal operation of the bridge, evaluate transient errors through multi-data coupling, adaptively optimize calibration values, and ensure monitoring accuracy while reducing operation and maintenance costs.

The invention discloses an axle load determination method, device and equipment, a medium and a program product. The axle load determination method comprises the following steps: acquiring a rear axle load sent by an electronically controlled air suspension system (ECAS) associated with a rear axle of a vehicle; according to the rear axle load and the mass and the deployment position of the vehicle part on the frame, the front axle load of the vehicle is calculated based on the moment balance constraint; according to the current front tire pressure of the vehicle and the corresponding relation between the front tire pressure interval and the front axle load interval, the front axle load interval corresponding to the front tire pressure is determined; and comparing the front axle load with the front axle load interval, and displaying the rear axle load and the front axle load under the condition that the front axle load belongs to the front axle load interval. According to the technical scheme provided by the embodiment of the invention, the front axle load of the front leaf spring suspension and rear air suspension tractor can be obtained without depending on external weighing equipment and adding additional sensors.

This invention discloses a test apparatus and method for train disc brakes considering wheel-rail creep. The apparatus includes a test bench base, a fixed gantry, a track simulation system, an axle load system, a disc brake system, and a control system. The fixed gantry is fixedly mounted on the test bench base, the axle load system is fixedly mounted above the test bench base via the fixed gantry, the disc brake system is fixedly mounted on the axle load system, and the track simulation system is mounted on the test bench base and rolls in contact with the axle load system. This invention enables the analysis of the braking performance of the disc brake system under wheel-rail creep conditions, as well as the dynamic response when multiple brake discs brake simultaneously. It thus provides an in-depth exploration of the braking characteristics of the disc brake system under wheel-rail creep conditions and the complex coupling mechanism between the braking system and the wheel and rail.

The invention discloses a road fatigue damage prediction method, system and device, a medium and a program product, and relates to the technical field of road surface damage prediction.The method comprises the steps that according to obtained road surface traffic load data, each axle load of each vehicle is converted into the equivalent axle number of standard axle loads, the equivalent axle numbers of all vehicles at the current moment are summarized, and the equivalent axle numbers of all vehicles at the current moment are obtained; obtaining a multi-axle load accumulated value at the current moment, and obtaining an accumulated damage degree according to the multi-axle load accumulated value; according to the multi-axle load accumulated value at the current moment, the proportion of various vehicle types, the average vehicle speed at the current moment and the accumulated damage degree at the previous moment, the evolution trend of the accumulated damage degree is predicted, set damage degree predicted values at multiple moments in the future are obtained, and an early warning signal is pushed when the damage degree predicted values exceed a set threshold value. High-frequency and multi-axle load data are accumulated according to time periods, the road damage degree is quantified more truly, and the potential damage risk of the road surface is reduced through rolling prediction of the damage degree.

The application discloses a hydraulic weighing system for heavy-load vehicles at high-speed intersections, and belongs to the technical field of heavy-load transportation, which comprises a plurality of pits evenly spaced along the longitudinal direction of a road, a road panel arranged at the opening of the pit, an oil cylinder corresponding to the road panel arranged in the pit, a middle partition plate of the oil cylinder separating the inner side of the oil cylinder into an upper oil cylinder groove and a lower storage groove, a piston fixed at the bottom of the road panel and slidingly arranged in the oil cylinder groove, and an oil bag arranged between the piston and the middle partition plate; a pressure measuring instrument is installed in the storage groove, and the output end of the pressure measuring instrument is connected to the oil bag; the pressure measuring instrument can convert the current actual axle load according to the pressure change amount, and the weighing data information of each road panel is returned to a central control computer, and the computer outputs the size of each axle load and the axle spacing. The application can be used for accurately calculating the total weight of vehicles and goods, and can also consider more detailed load factors such as the axle load and the wheelbase.

The application provides a four-wheel vertical load dynamic estimation system and simulation method of a variable load working condition commercial vehicle, relates to the field of vehicle motion characteristic simulation, and is composed of a nonlinear three-degree-of-freedom vehicle body model, a tire model, a four-wheel side slip angle / slip rate calculation model, a four-wheel vertical load solving model and a mass center position and spring mass estimation model. The mass center position and spring mass estimation model can be combined with the vehicle static axle load to estimate the mass center and mass related information, and correct the parameters in the vehicle body model and the vertical load solving model. The four-wheel vertical load and load transfer rate of the commercial vehicle can be obtained under the premise that the wheels are not additionally modified.

This application relates to the field of lifting equipment technology, specifically providing a hoisting machine and a support adjustment method. The hoisting machine includes a chassis, which comprises a frame, a first front axle, and a second front axle connected to the frame. The first and second front axles are independently mounted on the frame, or the first and second front axles form a modular front axle assembly connected to the frame. Increasing the load capacity generally requires increasing the frame and axle dimensions to meet load-bearing and stability requirements, but this easily leads to exceeding specifications and limitations. The hoisting machine provided in this application uses multi-axle support at the front end of the frame. By increasing the number of front axles, it significantly increases the machine's load-bearing capacity and load capacity without increasing the size or requirements of the axles and the frame itself, thus at least partially solving the problem of insufficient front axle load-bearing capacity in existing front-end hoisting cranes.