CN102041824A - Automatic control system and control method of working device of excavator - Google Patents
Automatic control system and control method of working device of excavator Download PDFInfo
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- CN102041824A CN102041824A CN2010105810651A CN201010581065A CN102041824A CN 102041824 A CN102041824 A CN 102041824A CN 2010105810651 A CN2010105810651 A CN 2010105810651A CN 201010581065 A CN201010581065 A CN 201010581065A CN 102041824 A CN102041824 A CN 102041824A
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- dipper
- cylinder
- swing arm
- control
- bucket
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- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02F—DREDGING; SOIL-SHIFTING
- E02F9/00—Component parts of dredgers or soil-shifting machines, not restricted to one of the kinds covered by groups E02F3/00 - E02F7/00
- E02F9/20—Drives; Control devices
- E02F9/22—Hydraulic or pneumatic drives
Abstract
The invention discloses an automatic control system and control method of a working device of an excavator, wherein the system comprises a movable arm, a dipper handle, a dipper angle sensor, a movable arm cylinder, a dipper handle cylinder, a dipper cylinder pressure sensor, a speed sensor, a movable arm cylinder, a dipper handle cylinder, and dipper cylinder electro-hydraulic proportional valves. The system is characterized in that (1) a laser position indicator is equipped for detecting the relative positions of the working device of the excavator and an excavated object; (2) a programmable controller receives signals from the sensors, and controls the electro-hydraulic proportional valves; and (3) a BP (back propagation) neural network module is adopted for controlling. According to the invention, the position and posture of a dipper can be accurately controlled, and the automatic control on the working device of a hydraulic excavator can be realized.
Description
Technical field
The present invention relates to a kind of control method and device of excavator, relate in particular to a kind of method and apparatus that the equipment of excavator is controlled automatically.
Background technology
Hydraulic crawler excavator is a kind of engineering machinery of extensive use, its work under bad environment, and because control action is single, long working very easily causes driver fatigue.Use microcomputer control hydraulic crawler excavator, must alleviate driver's labour intensity, raise labour efficiency, save the energy, improve safety.
Because the manipulating object and the environmental change of excavator are big, digging operation will adapt to various operating modes, soil property environment, and the content of each concrete operations is all different with requirement in construction, be difficult to form rule, this requirement should have intelligentized characteristics in the selection of control mode, automatic control system should have the ability of self-adaptation manipulating object and environmental change.
In the prior art, adopting microcomputer control to realize in the research of equipment TRAJECTORY CONTROL, mostly adopt the pose Mathematical Modeling of setting up equipment, according to given bucket tooth target trajectory, through calculating, be converted to the relative rotation sequence of equipment, by the microcomputer controlled electro-hydraulic servo system, make three its target rotation angles of each autotracking of rod member, realize TRAJECTORY CONTROL.For this class engineering machinery of excavator, this control mode more complicated is difficult to adapt to various complex job environment requirement, has certain limitation in the use.
Summary of the invention
The object of the invention provides a kind of control system that is used for the autocontrol method of hydraulic digger operating device and adopts this control method, can realize that by this control system hydraulic digger operating device is in the automatic manipulation of setting under the operating mode, accurately and stably control the position and the attitude of equipment, make the orbiting motion of equipment according to expection, task fulfils assignment.
For achieving the above object, the technical solution used in the present invention is: a kind of automatic control system of digger operating device, comprise: swing arm angular transducer, dipper angular transducer, scraper bowl angular transducer, boom cylinder pressure sensor, bucket arm cylinder pressure sensor, bucket cylinder pressure sensor, speed probe, boom cylinder electro-hydraulic proportional valve, bucket arm cylinder electro-hydraulic proportional valve, bucket cylinder electro-hydraulic proportional valve
(1) is provided with the laser positioning instrument, is used to detect digger operating device and the relative position that excavates object;
(2) have the programmable logic controller of software program, the signal output part of each sensor is connected with described programmable logic controller, and the output of described programmable logic controller is connected with the control end of boom cylinder electro-hydraulic proportional valve, bucket arm cylinder electro-hydraulic proportional valve, bucket cylinder electro-hydraulic proportional valve respectively;
(3) software program in the described programmable logic controller comprises the BP neural network module of controlling swing arm, the BP neural network module of control dipper, the BP neural network module of control scraper bowl, and the electrichydraulic control module of controlling each electro-hydraulic proportional valve respectively.
In the technique scheme, the output of each BP neural network module connects the electrichydraulic control module of corresponding electro-hydraulic proportional valve respectively.
A kind of autocontrol method of digger operating device adopts above-mentioned automatic control system to realize, comprises the following steps:
(1) obtaining of training sample: under the setting operating mode, repeatedly repeat to excavate action earlier by the driver, sample by pre-set time interval: the relative position e of recording scheduled excavation object of laser positioning instrument and equipment, each angular transducer is the acquisition and recording swing arm respectively, the relative rotation sample information θ of dipper and scraper bowl, each pressure sensor is the acquisition and recording boom cylinder respectively, the pressure sample information p of bucket arm cylinder and bucket cylinder, speed probe is gathered engine speed sample information n, and the sampling swing arm, dipper, bucket cylinder electro-hydraulic proportional valve control signal u;
(2) training BP neural network module:
The sample data that step (1) is gathered is respectively as the training sample of the BP neural network module of controlling swing arm, dipper, scraper bowl, through the BP ANN (Artificial Neural Network) Control program of finishing in the controller, train by its adaptive learning functionality, be met the neural network weight and the threshold value of precision, thus the BP neutral net that acquisition trains;
(3) measure the station-keeping data e (t) of current excavation object and swing arm, dipper, scraper bowl with the laser positioning instrument, each angular transducer is gathered the relative rotation θ (t) of current swing arm, dipper and scraper bowl respectively, each pressure sensor is measured the pressure sample information p (t) of boom cylinder, bucket arm cylinder and bucket cylinder respectively, and speed probe is gathered engine speed sample information n (t);
(4) data that step (3) is obtained are as the input of each the BP neural network module that trains, output is the control input quantity u (t) of the electrichydraulic control module of swing arm, dipper and bucket cylinder, through each electrichydraulic control module, control the stroke of swing arm, dipper, bucket cylinder respectively, obtain next constantly swing arm, dipper and scraper bowl position e (t+1), relatively rotate angle θ (t+1), oil cylinder working-pressure p (t+1), engine speed n (t+1);
(5) data that step (3) and step (4) are obtained are compared, calculating location difference DELTA e (t+1), and constitute next system's input quantity constantly jointly with other data of step (4);
(6) repeating step (3), is finally realized the TRAJECTORY CONTROL of equipment in whole mining process by the loop iteration of The whole control system to (5).
Because the technique scheme utilization, the present invention compared with prior art has following advantage:
1. the present invention has adopted the BP neural network control technique, each sensor parameters when sampling true driver's operation is trained the BP neutral net, more simulation true driver's manipulation strategy, realization is to the compliance of excavator work under the different operating modes, controller basis and pressure, engine speed information, after data processing section calculating, send controlled quentity controlled variable, drive the swing arm hydraulic cylinder respectively, dipper hydraulic cylinder and the action of scraper bowl hydraulic cylinder, thereby control the position and the attitude of scraper bowl exactly, realize the automatic manipulation of hydraulic digger operating device.
2. the present invention is implemented in the automatic job of setting excavator under the operating mode by to the automatic control of equipment movement locus, alleviate the driver working strength, increase work efficiency and safety, energy conservation; Owing to used the BP nerual network technique, shortcomings such as employing traditional PID control method complexity, precision are low, poor stability have been avoided, control strategy obfuscation, intellectuality with equipment, and have self adaptation, a learning functionality, can be according to the operation demonstration of experienced driver, learning training obtain ripe control strategy, thereby the equipment mining track that is implemented under the different operating modes is controlled automatically then and there.
Description of drawings
Fig. 1 is the control structure schematic diagram of control system in the embodiment of the invention.
Fig. 2 is the structural representation of current control module among the embodiment.
Fig. 3 is installation and the interactively schematic diagram of control system on excavator.
The specific embodiment
Below in conjunction with drawings and Examples the present invention is further described:
Embodiment one: a kind of automatic control system of digger operating device, comprise: swing arm angular transducer, dipper angular transducer, scraper bowl angular transducer, boom cylinder pressure sensor, bucket arm cylinder pressure sensor, bucket cylinder pressure sensor, speed probe, boom cylinder electro-hydraulic proportional valve, bucket arm cylinder electro-hydraulic proportional valve, bucket cylinder electro-hydraulic proportional valve, wherein, the programmable logic controller that has a software program comprises that drive simulating person controls the BP neural network module c1 of swing arm, dipper, scraper bowl, c2, c3 and electrichydraulic control module c4, c5, c6.Swing arm, dipper, scraper bowl control system are similar, the system architecture schematic diagram as shown in Figure 1, electrichydraulic control modular structure schematic diagram is as shown in Figure 2.
Referring to Fig. 3, the inventive system comprises, swing arm 1, dipper 2, scraper bowl 3, boom cylinder a1, bucket arm cylinder a2, bucket cylinder a3, swing arm angular transducer s1, dipper angular transducer s2, scraper bowl angular transducer s3, boom cylinder pressure sensor s4, bucket arm cylinder pressure sensor s5, bucket cylinder pressure sensor s6, engine speed sensor s7, laser positioning instrument 4, controller 5, wherein:
1) swing arm angular transducer s1 is installed in swing arm 1 peaceful platform hinged place, and dipper angular transducer s2 is installed in swing arm 1 and dipper 2 hinged places, and scraper bowl angular transducer s3 is installed in dipper 2 and scraper bowl 3 hinged places;
2) boom cylinder pressure sensor s4 is installed in the boom cylinder a1 hydraulic circuit, and bucket arm cylinder pressure sensor s4 is installed in the bucket arm cylinder a1 hydraulic circuit, and bucket cylinder pressure sensor s4 is installed in the bucket cylinder a1 hydraulic circuit;
3) engine speed sensor s7 is installed in engine interior;
4) laser positioning instrument 4 is installed in the driver's cabin front end;
5) controller 5 is integrated with excavator ECU.
The control method of present embodiment is as follows:
1) be the manual drive pattern with default, the driver carries out the repetition digging operation according to operating mode under stable state, each sensor sample is noted corner, pressure signal, excavation object relative position signal, engine rotational speed signal and each operating cylinder electrichydraulic control proportional valve control signal of swing arm, dipper, scraper bowl;
2) step 1 is gathered sample storage to controller 5,, through program running, be met the BP neutral net of requirement, its system control strategy as the equipment motion as the training sample of BP network control module c1, c2, c3 wherein;
3) be automatic driving mode with default, sensor is measured corner, pressure signal, excavation object relative position signal, engine rotational speed signal and the oil cylinder electrichydraulic control proportional valve control input signal of current swing arm, dipper, scraper bowl;
4) with the step 3) measured signal as controller 5 input quantities, through BP ANN (Artificial Neural Network) Control module c1, c2, c3, obtain next instantaneous each operating cylinder electrichydraulic control proportional valve control signal;
5) control signal that step 4) is obtained is as system's input quantity of electrohydraulic control system module c4, c5, c6, through power amplifier and electro-hydraulic proportional valve, the signal of telecommunication is converted into pressure signal, control each operating cylinder pressure and fuel delivery, thereby control the stroke of each operating cylinder, obtain the relative position of next instantaneous swing arm, dipper, scraper bowl, convert, be output as the relative position of next instantaneous excavation object and swing arm, dipper, scraper bowl through program;
6) data that step 3) and step 5) are obtained are compared, and obtain the relative position difference of adjacent moment swing arm, dipper and scraper bowl and excavation object, and feed back to system input;
7) repeating step 3-6 finishes expection until equipment and excavates action.
Thus, present embodiment has been realized the automatic control of digger operating device.
Claims (3)
1. the automatic control system of a digger operating device, comprise: swing arm angular transducer, dipper angular transducer, scraper bowl angular transducer, boom cylinder pressure sensor, bucket arm cylinder pressure sensor, bucket cylinder pressure sensor, speed probe, boom cylinder electro-hydraulic proportional valve, bucket arm cylinder electro-hydraulic proportional valve, bucket cylinder electro-hydraulic proportional valve is characterized in that:
(1) is provided with the laser positioning instrument, is used to detect digger operating device and the relative position that excavates object;
(2) have the programmable logic controller of software program, the signal output part of each sensor is connected with described programmable logic controller, and the output of described programmable logic controller is connected with the control end of boom cylinder electro-hydraulic proportional valve, bucket arm cylinder electro-hydraulic proportional valve, bucket cylinder electro-hydraulic proportional valve respectively;
(3) software program in the described programmable logic controller comprises the BP neural network module of controlling swing arm, the BP neural network module of control dipper, the BP neural network module of control scraper bowl, and the electrichydraulic control module of controlling each electro-hydraulic proportional valve respectively.
2. the automatic control system of digger operating device according to claim 1 is characterized in that: the output of each BP neural network module connects the electrichydraulic control module of corresponding electro-hydraulic proportional valve respectively.
3. the autocontrol method of a digger operating device adopts the described automatic control system of claim 1 to realize, it is characterized in that, comprises the following steps:
(1) obtaining of training sample: under the setting operating mode, repeatedly repeat to excavate action earlier by the driver, sample by pre-set time interval: the relative position e of recording scheduled excavation object of laser positioning instrument and equipment, each angular transducer is the acquisition and recording swing arm respectively, the relative rotation sample information θ of dipper and scraper bowl, each pressure sensor is the acquisition and recording boom cylinder respectively, the pressure sample information p of bucket arm cylinder and bucket cylinder, speed probe is gathered engine speed sample information n, and the sampling swing arm, dipper, bucket cylinder electro-hydraulic proportional valve control signal u;
(2) training BP neural network module:
The sample data that step (1) is gathered is respectively as the training sample of the BP neural network module of controlling swing arm, dipper, scraper bowl, through the BP ANN (Artificial Neural Network) Control program of finishing in the controller, train by its adaptive learning functionality, be met the neural network weight and the threshold value of precision, thus the BP neutral net that acquisition trains;
(3) measure the station-keeping data e (t) of current excavation object and swing arm, dipper, scraper bowl with the laser positioning instrument, each angular transducer is gathered the relative rotation θ (t) of current swing arm, dipper and scraper bowl respectively, each pressure sensor is measured the pressure sample information p (t) of boom cylinder, bucket arm cylinder and bucket cylinder respectively, and speed probe is gathered engine speed sample information n (t);
(4) data that step (3) is obtained are as the input of each the BP neural network module that trains, output is the control input quantity u (t) of the electrichydraulic control module of swing arm, dipper and bucket cylinder, through each electrichydraulic control module, control the stroke of swing arm, dipper, bucket cylinder respectively, obtain next constantly swing arm, dipper and scraper bowl position e (t+1), relatively rotate angle θ (t+1), oil cylinder working-pressure p (t+1), engine speed n (t+1);
(5) data that step (3) and step (4) are obtained are compared, calculating location difference DELTA e (t+1), and constitute next system's input quantity constantly jointly with other data of step (4);
(6) repeating step (3), is finally realized the TRAJECTORY CONTROL of equipment in whole mining process by the loop iteration of The whole control system to (5).
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