Intelligent beam transporting vehicle control method and system based on multi-network information fusion

Abstract

The invention discloses a beam transporting vehicle intelligent control method and system based on multi-network information fusion, and relates to the field of beam transporting vehicle intelligent control. The method includes the following steps that operation parameters of the beam transporting vehicle and positioning information and posture information of the vehicle are collected; according to the collected operation parameters, self-adaptive power matching speed regulation control of an engine, a pump and a motor is achieved through feedforward-feedback compound control; based on the positioning information and attitude information of the vehicle, positioning and attitude control are performed on the beam transporting vehicle by combining a Beidou high-precision differential positioning technology with a laser distance measuring sensor; and a temperature protection mechanism and a man-machine cooperative safety redundancy mechanism are utilized, so that the safety and reliability of the beam transporting vehicle are improved. By introducing a multi-network information fusion technology, the invention aims to solve the problems of low intelligent degree, high energy consumption, monitoring lag and the like of transportation and erection equipment.

Description

Technical Field

[0001] The present invention relates to the field of intelligent control of beam transport vehicles, and more particularly to an intelligent control method and system for beam transport vehicles based on multi-network information fusion. Background Art

[0002] As the core equipment for high-speed railway construction, box girder transport and erection equipment has the characteristics of heavy load and complex structure. However, in the long-term use process, its operation faces many key problems, which seriously restrict the construction efficiency and safety. The specific problems are: (1) The girder transport vehicle has insufficient control efficiency and safety. The heavy-load speed is low (≤5km / h), and long-distance transportation can easily cause driver fatigue, affecting driving safety. Under complex road conditions (such as curves and slopes), it is difficult for operators to accurately predict the line information, and there are risks such as scratching the tunnel wall and deviating from the track, which seriously threatens construction safety; (2) The power system has poor energy efficiency and adaptability. The traditional control method relies on manual adjustment of the pump / motor displacement, which is difficult to accurately match the engine power and easily causes engine overload and flameout or hydraulic system leakage. Under low-load conditions, fuel waste is serious, the overall energy efficiency is low, and construction costs increase.

[0003] In the field of intelligent engineering machinery at home and abroad, many scholars have conducted in-depth research and achieved certain results. However, there are still many deficiencies in existing research, which are specifically manifested in the following aspects: (1) Power system control. Existing research on the drive system of beam transporters focuses on the optimization control of single variables (such as engine speed, pump displacement, etc.), and lacks research on multi-degree-of-freedom collaborative control strategies such as engines, pumps, and motors. Traditional control methods are difficult to accurately match engine power and load requirements, resulting in low energy efficiency and difficulty in precise operation; (2) Positioning and attitude detection. Traditional GPS positioning accuracy is insufficient (±1m), which is difficult to meet the construction needs of narrow bridge deck environments (such as tunnel gaps of only 10cm). Summary of the Invention

[0004] In view of this, the present invention provides an intelligent control method and system for beam transport vehicles based on multi-network information fusion. By introducing multi-network information fusion technology, it aims to overcome the problems of low intelligence level, high energy consumption, and monitoring lag of transport and erection equipment.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] An intelligent control method for a beam transport vehicle based on multi-network information fusion includes the following steps:

[0007] Collect the operating parameters of the beam transport vehicle, as well as the vehicle's positioning information and posture information;

[0008] Based on the collected operating parameters, adaptive power matching and speed control of the engine, pump and motor are achieved through feedforward-feedback composite control;

[0009] Based on the vehicle's positioning and attitude information, the beam transport vehicle is positioned and its attitude controlled using Beidou high-precision differential positioning technology combined with a laser ranging sensor.

[0010] The safety and reliability of the beam transport vehicle are improved by utilizing the temperature protection mechanism and the human-machine collaborative safety redundancy mechanism.

[0011] Optionally, the operating parameters include engine speed, variable pump control current, and variable motor control current.

[0012] Optionally, adaptive power matching speed control specifically includes the following steps:

[0013] According to the input signal from the operating handle, the engine speed, variable pump displacement and motor displacement are pre-adjusted to achieve fast response and preliminary matching;

[0014] Monitor the load changes of the hydraulic system in real time through pressure sensors, and dynamically correct the control amount to achieve precise matching;

[0015] Limit the maximum displacement of the variable pump and the minimum displacement of the variable motor to prevent engine overload and flameout and hydraulic system leakage;

[0016] Taking the lowest engine fuel consumption rate as the criterion, the optimization algorithm is used to achieve stepless speed regulation and power adaptive matching.

[0017] Optionally, positioning and posture control specifically includes the following steps:

[0018] Two sets of differential positioning devices are arranged at the front and rear ends of the vehicle body to monitor the lateral deviation of the vehicle relative to the centerline of the bridge deck in real time and dynamically adjust the driving trajectory based on the real-time positioning data;

[0019] A third differential positioning device is added to the middle of the vehicle body as an independent verification unit to compare the three sets of positioning data in real time. When the data are consistent, the positioning reliability is confirmed. If there is a deviation, the early warning mechanism is immediately triggered and the error correction program is started.

[0020] Laser ranging sensors are used to achieve seamless positioning switching inside and outside the tunnel, ensuring positioning continuity and accuracy;

[0021] The oblique and figure-eight steering modes are selected based on the measurement values ​​of the front-end and rear-end positioning modules, and the PID control strategy is used to determine the tire steering angle. At the same time, the maximum steering angle of the tire during autonomous driving is limited.

[0022] Optionally, the temperature protection mechanism is: when the hydraulic system temperature exceeds the preset warning value, the system actively reduces the engine speed and operating speed to control the hydraulic system temperature and ensure the safe operation of the hydraulic system.

[0023] Optional human-machine collaborative safety redundancy mechanism is: when the driver's foot pressure value is lower than the threshold, the system immediately activates the safety response program, the engine speed drops to idle state, and the full disc brake is activated within the set time to achieve emergency stopping.

[0024] An intelligent control system for beam transport vehicles based on multi-network information fusion, including:

[0025] Operation parameter acquisition module: used to collect the operation parameters of the beam transport vehicle, as well as the vehicle's positioning information and posture information;

[0026] Adaptive power matching speed control module: used to achieve adaptive power matching speed control of the engine, pump and motor through feedforward-feedback composite control based on the collected operating parameters;

[0027] Adaptive power matching speed control module: Based on the vehicle's positioning and attitude information, it uses Beidou high-precision differential positioning technology combined with laser ranging sensors to position and control the beam transport vehicle's attitude;

[0028] Safety assurance module: used to improve the safety and reliability of the beam transport vehicle by utilizing the temperature protection mechanism and the human-machine collaborative safety redundancy mechanism.

[0029] It can be seen from the above technical solutions that, compared with the prior art, the present invention provides an intelligent control method and system for beam transport vehicles based on multi-network information fusion, which has the following beneficial effects:

[0030] 1. Improve the intelligence level of equipment: By building an adaptive power matching control system, an assisted driving system, and a posture monitoring system, intelligent control and management of equipment can be achieved, thereby improving construction efficiency and safety.

[0031] 2. Reduce energy consumption and costs: By optimizing the power system control strategy, accurate matching of engine power and load is achieved, reducing fuel consumption and construction costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0033] Figure 1This is a schematic diagram of the adaptive power matching speed regulation control principle of the present invention;

[0034] Figure 2 This is a schematic diagram of the multi-operating condition experimental test principle of the present invention;

[0035] Figure 3 This is a schematic diagram of the Beidou positioning technology of the present invention;

[0036] Figure 4 This is a diagram showing the actual installation of the Beidou positioning system sensor of the present invention;

[0037] Figure 5 This is a diagram showing the posture of the beam transport vehicle of the present invention relative to the bridge deck;

[0038] Figure 6 This is a block diagram of the tire steering angle control of the automatic driving system of the present invention;

[0039] Figure 7 This is a comparison chart of the fuel consumption rate of the beam transport vehicle under no-load conditions of the present invention;

[0040] Figure 8 This is a comparison chart of the fuel consumption rate of the engine under heavy load conditions of the present invention;

[0041] Figure 9 This is a diagram showing the optimal temperature operating range of the hydraulic oil of the present invention;

[0042] Figure 10 This is a graph showing changes in control parameters of the beam transport vehicle under no-load and slope-level working conditions according to the present invention;

[0043] Figure 11 This is a diagram showing the changes in the control parameters of the heavy-loaded, flat-slope working beam transport vehicle of the present invention. DETAILED DESCRIPTION

[0044] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0045] The embodiment of the present invention discloses an intelligent control method for a beam transport vehicle based on multi-network information fusion, comprising the following steps:

[0046] Collect the operating parameters of the beam transport vehicle, as well as the vehicle's positioning information and posture information;

[0047] Based on the collected operating parameters, adaptive power matching and speed control of the engine, pump and motor are achieved through feedforward-feedback composite control;

[0048] Based on the vehicle's positioning and attitude information, the beam transport vehicle is positioned and its attitude controlled using Beidou high-precision differential positioning technology combined with a laser ranging sensor.

[0049] The safety and reliability of the beam transport vehicle are improved by utilizing the temperature protection mechanism and the human-machine collaborative safety redundancy mechanism.

[0050] In order to solve the problem of poor energy efficiency and adaptability of the beam transport vehicle power system, the present invention proposes an adaptive power matching speed control scheme based on feedforward-feedback composite control. The principle is as follows: Figure 1 The scheme works as follows:

[0051] Feedforward control: Based on the input signals from the operating handle (such as accelerator pedal position, steering wheel angle, etc.), the engine speed, variable pump displacement and motor displacement are pre-adjusted to achieve rapid response and preliminary matching.

[0052] Feedback compensation: The pressure sensor monitors the load changes of the hydraulic system in real time and dynamically corrects the control amount to achieve precise matching. The specific restrictions are as follows:

[0053] Limit the maximum displacement of the variable pump: q p,max =p s η pm T e,max , where T e,max is the maximum torque of the engine, p s is the system pressure, η pm is the pump motor efficiency. This limit prevents the engine from stalling due to overload.

[0054] Limiting the minimum displacement of variable motors: Ensures that system pressure does not exceed the set threshold, preventing hydraulic system leakage and failure.

[0055] Optimization goal: Taking the lowest engine fuel consumption rate as the criterion, achieve stepless speed regulation and power adaptive matching through optimization algorithm.

[0056] To achieve trajectory control for the beam transport vehicle under complex road conditions, this invention uses three sets of Beidou high-precision differential positioning technology. By placing two sets of differential positioning devices at the front and rear ends of the vehicle body, the lateral deviation of the vehicle relative to the bridge deck centerline is monitored in real time. The system dynamically adjusts the driving trajectory based on real-time positioning data to ensure that the vehicle strictly follows the predetermined path. The positioning accuracy can reach the centimeter level. The working principle diagram is shown below. Figure 3 shown.

[0057] To improve system reliability, a third differential positioning device is added in the middle of the vehicle body as an independent verification unit. The system compares the three sets of positioning data in real time. When the data are consistent, the positioning reliability is confirmed. When there is a deviation, the early warning mechanism is immediately triggered and the error correction program is started. This triple verification mechanism effectively guarantees the accuracy of the positioning data. Figure 4 This positioning solution, through multi-sensor data fusion and real-time verification, not only achieves high-precision trajectory control of the beam transporter, but also significantly improves the system's fault tolerance, providing reliable technical support for safe autonomous driving in complex construction environments.

[0058] The specific design process is as follows:

[0059] Tunnel external positioning module: Based on Beidou positioning technology, the control system measures the distance between the four corners of the vehicle body (left front, right front, left rear, right rear) and the bridge deck, and uses a differential algorithm to calculate the position of the beam transport vehicle relative to the bridge deck. By defining the front offset and rear offset Two key parameters can fully describe the spatial posture of the beam transport vehicle on the bridge deck, such as Figure 5 shown.

[0060] The specific design process is as follows:

[0061] Tunnel external positioning module: Based on Beidou positioning technology, the control system measures the distance between the four corners of the vehicle body (left front, right front, left rear, right rear) and the bridge deck, and uses a differential algorithm to calculate the position of the beam transport vehicle relative to the bridge deck. By defining the front offset and rear offset These two key parameters can fully describe the spatial posture of the beam transport vehicle on the bridge deck.

[0062] Positioning switching in the tunnel: A laser ranging sensor (accuracy ±10mm) is used to achieve seamless positioning switching inside and outside the tunnel, ensuring positioning continuity and accuracy.

[0063] To achieve precise steering and trajectory control of the beam transport vehicle, this study proposes the following steering control strategy:

[0064] Mode selection: Based on the measurement values ​​of the front-end and back-end positioning modules The specific expression of the selected steering modes such as oblique and figure eight is shown in formula (1).

[0065]

[0066] PID angle control: with attitude deviation d F ,d B As input, PID control strategy is used to determine the tire steering angle. At the same time, in order to avoid system oscillation and improve system response speed, the maximum steering angle of the tire in autonomous driving is limited. The block diagram of tire steering angle control based on PID is shown in the figure. Figure 6 shown.

[0067] Figure 6 In, d F0 ,d B0is the initial position setting value, which is set to 0 through calibration during use; θ, They are the PID controller output value and the value after being limited by the amplitude limiter.

[0068] The beam transporters involved in this invention are the THY900 and TY900 models; both models use L-HM46 anti-wear hydraulic oil. L-HM46 hydraulic oil typically has a high viscosity index and is suitable for operation over a wide temperature range. However, temperature fluctuations still affect its viscosity, which in turn affects the performance of the hydraulic system.

[0069] The recommended oil viscosity range is based on the hydraulic pump and hydraulic motor used. The recommended reasonable oil working direction is as follows: Figure 9 shown.

[0070] Therefore, it is recommended that the hydraulic oil temperature be controlled within the range of 30°C-70°C. According to the control principle, a temperature warning value is preset. When the hydraulic system temperature exceeds 70°C, the system actively reduces the engine speed and operating speed to control the hydraulic system temperature, thereby ensuring the safe operation of the hydraulic system.

[0071] Therefore, it is recommended that the hydraulic oil temperature be controlled within the range of 30°C-70°C. According to the control principle, a temperature warning value is preset. When the hydraulic system temperature exceeds 70°C, the system actively reduces the engine speed and operating speed to control the hydraulic system temperature, thereby ensuring the safe operation of the hydraulic system.

[0072] In order to verify the effectiveness of the adaptive power matching control system, the present invention has carried out multi-operating condition experimental tests on the THY900 beam transport vehicle. The specific principle is as follows: Figure 2 shown.

[0073] On-site testing of the control characteristics of the travel drive control system of the beam transport vehicle under different driving conditions (empty, heavy, uphill, downhill and flat slope). Figure 10 and Figure 11 The changes in the beam transporter's travel speed and command speed, engine speed, variable pump control current, and variable motor control current are given under both no-load and heavy-load conditions. Regardless of whether the beam transporter is operating under no-load or heavy-load conditions, the engine speed, variable pump control current, and variable motor control current can all effectively coordinate and change synchronously to ensure that the beam transporter's travel speed can follow the changes in the command speed in real time and maintain a certain tracking accuracy. Figure 11 It can be seen that when the beam transport vehicle encounters a large load, the variable pump control current can automatically reduce to ensure that the engine torque does not exceed the allowable torque at its current speed, avoiding the engine from slowing down and stalling due to overload.

[0074] To verify the energy-saving effectiveness of the adaptive power matching control scheme, this study compared the fuel consumption characteristics of a beam transport vehicle's drive system under two control schemes. In the original control scheme, the engine speed was set at 1300, 1500, and 1700 rpm. At each speed, the vehicle's fuel consumption was tested under different operating conditions (no load, full load) and at different speeds. To minimize the impact of speed control errors and engine transient characteristics, fuel consumption per mile was used as the evaluation metric.

[0075] Depend on Figure 7 A comparison of fuel consumption rates between the two control schemes under no-load, level-slope conditions was presented. Experimental data showed that the adaptive power matching control scheme significantly reduced fuel consumption rates, ranging from 2.8% to 68%, with an average reduction of 33%. The specific energy savings were dependent on the engine speed setting and vehicle speed. Furthermore, while the original constant speed control scheme exhibited significant fuel consumption fluctuations, the adaptive control scheme maintained a stable fuel consumption rate that was consistently lower than the original scheme.

[0076] Figure 8 The test results under heavy-load, level-slope conditions are shown. The adaptive control scheme's fuel consumption remains significantly better than the original scheme, with reductions ranging from 5% to 60%, averaging 24%. Compared to the original scheme, the adaptive scheme's fuel consumption fluctuates less and remains consistently low. Under heavy-load conditions, the relationship between fuel consumption and vehicle speed exhibits a unique pattern: at low speeds, lower engine speeds are more energy-efficient; at high speeds, higher engine speeds are more efficient. This phenomenon can be explained by the fact that engine speed corresponds to its maximum output power. When the actual power demand does not exceed this value, fuel consumption decreases as power demand increases; conversely, fuel consumption increases. Therefore, under heavy-load conditions, engine speed must be dynamically adjusted based on real-time power demand, rather than simply reducing it.

[0077] This embodiment also discloses an intelligent control system for a beam transport vehicle based on multi-network information fusion, including:

[0078] Operation parameter acquisition module: used to collect the operation parameters of the beam transport vehicle, as well as the vehicle's positioning information and posture information;

[0079] Adaptive power matching speed control module: used to achieve adaptive power matching speed control of the engine, pump and motor through feedforward-feedback composite control based on the collected operating parameters;

[0080] Adaptive power matching speed control module: Based on the vehicle's positioning and attitude information, it uses Beidou high-precision differential positioning technology combined with laser ranging sensors to position and control the beam transport vehicle's attitude;

[0081] Safety assurance module: used to improve the safety and reliability of the beam transport vehicle by utilizing the temperature protection mechanism and the human-machine collaborative safety redundancy mechanism.

[0082] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0083] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An intelligent control method for beam transport vehicles based on multi-network information fusion, characterized in that: The following steps are involved: Collect the operating parameters of the beam transport vehicle, as well as the vehicle's positioning information and posture information; Based on the collected operating parameters, adaptive power matching and speed control of the engine, pump and motor are achieved through feedforward-feedback composite control; Based on the vehicle's positioning and attitude information, the beam transport vehicle is positioned and its attitude controlled using Beidou high-precision differential positioning technology combined with a laser ranging sensor. The safety and reliability of the beam transport vehicle are improved by utilizing the temperature protection mechanism and the human-machine collaborative safety redundancy mechanism.

2. The intelligent control method for beam transport vehicles based on multi-network information fusion according to claim 1 is characterized in that: The operating parameters include engine speed, variable pump control current, and variable motor control current.

3. The intelligent control method for beam transport vehicles based on multi-network information fusion according to claim 1 is characterized in that: Adaptive power matching speed control specifically includes the following steps: According to the input signal from the operating handle, the engine speed, variable pump displacement and motor displacement are pre-adjusted to achieve fast response and preliminary matching; Monitor the load changes of the hydraulic system in real time through pressure sensors, and dynamically correct the control amount to achieve precise matching; Limit the maximum displacement of the variable pump and the minimum displacement of the variable motor to prevent engine overload and flameout and hydraulic system leakage; Taking the lowest engine fuel consumption rate as the criterion, the optimization algorithm is used to achieve stepless speed regulation and power adaptive matching.

4. The intelligent control method for beam transport vehicles based on multi-network information fusion according to claim 1 is characterized in that: Positioning and posture control specifically include the following steps: Two sets of differential positioning devices are arranged at the front and rear ends of the vehicle body to monitor the lateral deviation of the vehicle relative to the centerline of the bridge deck in real time and dynamically adjust the driving trajectory based on the real-time positioning data; A third differential positioning device is added to the middle of the vehicle body as an independent verification unit to compare the three sets of positioning data in real time. When the data are consistent, the positioning reliability is confirmed. If there is a deviation, the early warning mechanism is immediately triggered and the error correction program is started. Laser ranging sensors are used to achieve seamless positioning switching inside and outside the tunnel, ensuring positioning continuity and accuracy; The oblique and figure-eight steering modes are selected based on the measurement values ​​of the front-end and rear-end positioning modules, and the PID control strategy is used to determine the tire steering angle. At the same time, the maximum steering angle of the tire during autonomous driving is limited.

5. The intelligent control method for beam transport vehicles based on multi-network information fusion according to claim 1 is characterized in that: The temperature protection mechanism is: when the hydraulic system temperature exceeds the preset warning value, the system actively reduces the engine speed and operating speed to control the hydraulic system temperature and ensure the safe operation of the hydraulic system.

6. The intelligent control method for beam transport vehicles based on multi-network information fusion according to claim 1 is characterized in that: The human-machine collaborative safety redundancy mechanism is: when the driver's foot pressure value is lower than the threshold, the system immediately activates the safety response program, the engine speed drops to idle state, and the full disc brake is activated within the set time to achieve emergency stopping.

7. An intelligent control system for beam transport vehicles based on multi-network information fusion, characterized in that: include: Operation parameter acquisition module: used to collect the operation parameters of the beam transport vehicle, as well as the vehicle's positioning information and posture information; Adaptive power matching speed control module: used to achieve adaptive power matching speed control of the engine, pump and motor through feedforward-feedback composite control based on the collected operating parameters; Adaptive power matching speed control module: Based on the vehicle's positioning and attitude information, it uses Beidou high-precision differential positioning technology combined with laser ranging sensors to position and control the beam transport vehicle's attitude; Safety assurance module: used to improve the safety and reliability of the beam transport vehicle by utilizing the temperature protection mechanism and the human-machine collaborative safety redundancy mechanism.

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