CN102115010A - Intelligent crane with machine vision and localization system - Google Patents

Abstract

The invention discloses an intelligent crane with a machine vision and localization system. The intelligent crane consists of the machine vision and localization system and an intelligent control system. The machine vision and localization system consists of a mechanical system and an electric control system, wherein, the mechanical part mainly consists of a traveling cart, a traveling trolley, a main beam, end beams, an upright column, a base and the like; and the electric control system is shown as follows: an industrial CCD (charge coupled device) acquires an image, inputs the obtained image analog voltage signal into an image acquisition card, and then converts the signal into a digital signal which can be processed conveniently by a computer. The intelligent control system consists of a mechanical system and an electric control system, and can realize rapid and accurate localization of the system of the crane by utilizing an improved PID (proportional-integral-derivative) control strategy. The intelligent crane has the advantages of higher automation degree, high efficiency and high precision.

Description

A kind of intelligent hoisting crane that has machine vision, position fixing system

One, technical field

The present invention relates to a kind of intelligent hoisting crane that has machine vision, position fixing system.

Two, background technology

At present, there is the problem that degree of automation is low, efficient is not high, precision is relatively poor in hoisting crane.For example: the switching that the power supply of 200910119264.8 patent intelligent controller for crane handle micro controller systems is supplied with button switch (1-8) by receptor sends instruction to (12-19) of micro controller system, encode by 2 with micro controller system, 3 to 11 of receipt transmission block, 12 to 10 of the micro controller system of receptor, the coding of 11 transmission is decoded, resistor chain R1 is the pull-up resistor of micro controller system, (1-8) pin by micro controller system sends instruction to the input end of (1-8) of photoelectrical coupler pin, resistor chain R2 is that the pull-up resistor R0-R6 of photoelectrical coupler is that the silicon controlled current-limiting resistance is controlled the transwitch action with the break-make of photoelectrical coupler, the switch receptor of control contactor and the power supply of handle are all supplied with by receptor, are they to be with a diameter 0.12m at receptor with the 5V DC supply handle of voltage transformer rectifying and wave-filtering and three-terminal voltage-stabilizing output and the wiring of controller? m2 * 4 core shielded cables connect, their Based Intelligent Control is all by micro controller system and software program control, the spacing input end that directly is connected in P521 that rises and descend.200910064321.7 patent relates to a kind of hoisting crane ac motor speed control control setup, comprise housing, intelligent command controller is installed in housing, intelligent command controller is connected with the crane rotor speed regulation intelligent controller, be connected with the paraphase controller, be connected with the drg contactless switch, be connected with the drg contactless switch, the drg contactless switch is connected with drg, the paraphase controller is connected with main supply switch, the paraphase controller is connected with motor stator, the rotor of electrical motor is connected with the high speed governing intelligent controller of crane rotor, main supply switch is connected with external power supply, is connected with the drg contactless switch, be connected with the paraphase controller.Its advantage is: alleviate the electric fault rate of crane motor cal val, reduction hoisting crane, the electric cost of compression lifting improves installation rate, improves the intelligence controlling device of the crane motor speed governing of crane intelligentization.Hoisting crane moment intelligence killer 200420092952.2 patents relate to a kind of hoisting crane intelligence monitoring and controlling device that is used for, and it mainly is applicable to the control monitor unit of control and the work of monitoring hoisting crane.And a kind of parameter that can accurately obtain in the hoisting crane work process is provided, and control highly sensitively, can realize monitoring in real time directly perceived, improve the hoisting crane moment intelligence killer of operation accuracy and work efficiency.Compared with prior art has following beneficial effect: reasonable in design, by weight sensor and amplitude sensor device are set, main control box, telltale, and main control box is connected with telltale with weight sensor device, amplitude sensor device by shielded cable respectively, hoisting capacity, work range, hoisting moment are clearly shown such as arm of force length, hoisting capacity and hoisting moment, the operating mode that can reflect hoisting crane simultaneously intuitively, installation, debugging, easy to detect; Detection architecture can show at random, printing, long-range transmission, can realize multi-level supervision and management.200710056919.2 a kind of method of detecting and controlling crane safety system of patent disclosure included as the next stage: start hoisting crane and judge system's normal stage whether; Judge the stage whether current hoisting crane operating mode of having established and required operating mode conform to; Detection constantly, mould/number conversion and the current load parameter of demonstration hoisting crane, and the stage of comparing with the hoisting crane nominal parameter; Bus control signal receives the stage of the signal of mould/number conversion; The stage that the result who compares with the hoisting crane nominal parameter according to the current load parameter of hoisting crane shows and reports to the police; When the hoisting crane overload, stop the stage of hoisting crane work.Not only intuitively but also accurate, the operation driver came into plain view in the present invention, and in addition, crane safety system of the present invention has also increased the bus controllable function, makes crane safety system and crane control system carry out data exchange, and intelligent degree is higher.Make hoisting crane operate in optimum regime.Control is accurate more, fuel oil consumption is more economical rationally.

Three, summary of the invention

Purpose of the present invention is exactly that a kind of intelligent hoisting crane that has machine vision, position fixing system that overcomes above shortcoming will be provided; A kind of intelligent hoisting crane that has machine vision, position fixing system is characterized in that: be made up of machine vision, position fixing system and intelligence control system; Machine vision, position fixing system are made up of mechanical system and electric-control system: mechanics mainly is made up of walking cart, walking dolly, girder, end carriage, column, base etc., it is the scaled down model of actual hoisting crane, in order to the operating various states of simulation hoisting crane, the traveling gear of big dolly adopts driven by servomotor; Size parking stall shift measurement adopts the code-disc signal to servomotor to carry out frequency division and counting, and frequency division can realize that counting can be realized by the data collecting card in the electric-control system by certain parameter is set in motor servo driver; The position limiting and protecting device of big dolly adopts reflective photoelectric switch, the spacing alarm function of the big dolly of realizing walking, and it detects distance is 0～30cm; Electric-control system is: image acquisition is utilized the industrial CCD images acquired, the image simulation voltage signal that obtains is input in the image pick-up card, be converted to the digital signal of being convenient to Computer Processing, image pick-up card is installed in the pci bus slot of industrial control computer, image sampling speed was 25 frame/seconds, satisfied the real-time requirement of system's control; Selected AC servo motor and the actuator of AC servo drive system has full cut-off ring controllable function, the coder of being furnished with 3 kinds of precision can be for selecting for use, can the strobe pulse amount carry out position control, analog quantity carries out multiple control modes such as speed control and torque control, have perfect overvoltage, overload, excess current protective function, it is an open AC servo motor system, can adjust the parameter of electric machine according to actual needs; Control platform based on industrial computer: the hoisting crane object locating system based on vision is the control core with the industrial computer, its the most outstanding characteristic is to possess performance-oriented arithmetic capability and memory capacity, there is a large amount of application software to use, is applicable to the processing of complicated applications and mass data.By installation data capture card and image pick-up card etc. in industrial computer, just can the kinematic parameter of crane system be gathered, and produce the various control signals of servomotor;

Intelligence control hoisting crane is made up of mechanical system and electric-control system, adopts improved PID control policy to realize the location quick and precisely of the system of hoisting crane; Intelligence control elevator machinery part with mainly forms large and small garage and walks mechanism and adopt servomotor (4) driving by the big mechanism of car (3) of the hard arm dolly (2) of structure (1); The cart displacement measurement adopts the hard disk signal to servomotor to carry out step by step and counting, and counting is realized by the data truck in the electric-control system (piece number 5);

Electric-control system at first is an image acquisition, by CCD camera (6) images acquired, is handled by image pick-up card (7), is converted to the generation digital signal and sends into computing machine; Industrial computer (8) control core can be gathered the also various control signals of output servomotor to the kinematic coefficient of crane system by data collecting card and image pick-up card; Electric-control system adopts the PID controller (9) of neural network, has self study, self organizing function and associative memory, and by oneself;

Hoisting crane object locating system software based on visual servo adopts the VC++ language to design and develop, software interface mainly is divided into the parameter setting, and state shows, automatic guidance, manually control waits the page, wherein controls to comprise video acquisition image and correlation parameter demonstration in the page.Introduce two cores of this software below:

1. the Fast Recognition Algorithm of cylindrical shape target

What native system need be located is the cylindrical shape specific objective, from a different perspective, it is oval that the cylindrical shape target can be approximately, and parameters such as the oval center of circle and ellipse degree have been reacted the position of target, this is the main foundation of hoisting crane location, so the Fast Recognition Algorithm of ellipse target is based on the emphasis of the hoisting crane object locating system of vision, also be the innovation part of this project.The standard ellipse equation is:

$\frac{{[(x-x_0)\cos \left(\mathrm{\θ}\right)+(y-y_0)\sin \left(\mathrm{\θ}\right)]}^2}{a^2}+\frac{{[(x-x_0)\sin \left(\mathrm{\θ}\right)+(y-y_0)\cos \left(\mathrm{\θ}\right)]}^2}{b^2}=1---\left(1\right)$

(x wherein ₀, y ₀) be the oval center of circle, a, b are oval major and minor axis, θ is oval degree of dip.By formula (1) as can be known, need 5 parameters to describe ellipse, this brings very big difficulty for oval identification.According to the image size and the difference of background complexity, at present some more advanced algorithms are discerned about several seconds to tens seconds time to the ellipse in the piece image in the world, this can not satisfy the real-time requirement of native system.

By deriving, obtain oval chord length and the differential formulas between the angle of contingence:

$\frac{\mathrm{dL}}{\mathrm{d\β}}=\frac{{\mathrm{ab}}^2}{a^2{\sin }^2(\mathrm{\θ}+\mathrm{\β})+b^2{\cos }^2(\mathrm{\θ}+\mathrm{\β})}\frac{1}{\sin (\mathrm{\θ}+\mathrm{\β})}\cos \left[\arctan (-\frac{b}{a}\frac{1}{\tan (\mathrm{\θ}+\mathrm{\β})})\right]---\left(2\right)$

5 parameter predigestings of this formula wushu (1) are 3 parameters: a, b and θ.With formula (2) is aim curve, by the quick match of method of steepest descent curve to be identified, by calculate residual error judge curve to be identified and aim curve and between similarity, the while estimated parameter a, b and θ.That is to say that through type (2) can be finished simultaneously to target recognition and parameter estimation, realize the quick identification of ellipse target.It is cooresponding with it that Fig. 2 is exactly a certain ellipse

Curve.

2. based on the PID position servo control algorithm of neural network

In Industry Control, traditional PID control still is in leading position so far, is particularly useful for setting up the deterministic control system of math modeling.That yet a large amount of industrial process often has is non-linear, the time become factor such as uncertainty, be difficult to set up its precise math model; In addition, the parameter in the PID controller is usually all by manually adjusting and since disposable these parameters of obtaining of adjusting be difficult to guarantee its control effect be in all the time optimum regime because of, therefore the control effect and the control accuracy of conventional PID controller are restricted.Neural network has self study, self organizing function and advantages such as associative memory, concurrent processing, makes it obtain widespread use in the Industry Control of complexity.

Native system adopts the PID based on neural network, and it mainly is made up of 3 parts:

(1) classical PID controller: directly the controlled object process is carried out closed loop control, its three parameter k _p, k _i, k _dOnline definite.Adopt increment type PID, control algorithm is:

Δu(k)＝k _p[e(k)-e(k-1)]+k _ie(k)+k _d[e(k)-2e(k-1)+e(k-2)] (3)

(2) RBF debates the knowledge network: what be used to set up controlled system debates the knowledge model, so that dynamically the output of visual control object offers the BP neural network to the sensitivity of control input, its radial basis function is a Gaussian function.Debating the performance index function of knowing device is

$J=\frac{1}{2}{(y\left(k\right)-\hat{y}\left(k\right))}^2---\left(4\right)$

According to the gradient descent method, parameters such as corrective networks weight coefficient:

$w_j\left(k\right)=w_j(k-1)+\mathrm{\η}(y\left(k\right)-\hat{y}\left(k\right)h_j)+\mathrm{\α}(w_j(k-1)-w_j(k-2))---\left(5\right)$

Wherein be the η learning rate, be the α inertia coefficient.

(3) BP neural network: adopt three layers of BP network,, pid control parameter is regulated, to reach the optimum of controller performance index by adjusting self weight coefficient.

This hoisting crane has that degree of automation is higher, efficient is high, advantage of high precision.

Four, description of drawings

Fig. 1 is to be a kind of intelligent hoisting crane system structure principle chart that has machine vision, position fixing system.

Five, the specific embodiment

Specifically introduce below in conjunction with accompanying drawing: in Fig. 1,1 is physical construction; 2 is hard arm dolly; 3 is big mechanism of car; 4 is servomotor; 5 is the data truck; 6 is the CCD camera; 7 is image pick-up card; 8 is industrial computer; 9 is the PID controller of electric-control system neural network.A kind of intelligent hoisting crane that has machine vision, position fixing system is characterized in that: be made up of machine vision, position fixing system and intelligence control system; Machine vision, position fixing system are made up of mechanical system and electric-control system: mechanics mainly is made up of walking cart, walking dolly, girder, end carriage, column, base etc., it is the scaled down model of actual hoisting crane, in order to the operating various states of simulation hoisting crane, the traveling gear of big dolly adopts driven by servomotor; Size parking stall shift measurement adopts the code-disc signal to servomotor to carry out frequency division and counting, and frequency division can realize that counting can be realized by the data collecting card in the electric-control system by certain parameter is set in motor servo driver; The position limiting and protecting device of big dolly adopts reflective photoelectric switch, the spacing alarm function of the big dolly of realizing walking, and it detects distance is 0～30cm; Electric-control system is: image acquisition is utilized the industrial CCD images acquired, the image simulation voltage signal that obtains is input in the image pick-up card, be converted to the digital signal of being convenient to Computer Processing, image pick-up card is installed in the pci bus slot of industrial control computer, image sampling speed was 25 frame/seconds, satisfied the real-time requirement of system's control; Selected AC servo motor and the actuator of AC servo drive system has full cut-off ring controllable function, the coder of being furnished with 3 kinds of precision can be for selecting for use, can the strobe pulse amount carry out position control, analog quantity carries out multiple control modes such as speed control and torque control, have perfect overvoltage, overload, excess current protective function, it is an open AC servo motor system, can adjust the parameter of electric machine according to actual needs; Control platform based on industrial computer: the hoisting crane object locating system based on vision is the control core with the industrial computer, its the most outstanding characteristic is to possess performance-oriented arithmetic capability and memory capacity, there is a large amount of application software to use, is applicable to the processing of complicated applications and mass data.By installation data capture card and image pick-up card etc. in industrial computer, just can the kinematic parameter of crane system be gathered, and produce the various control signals of servomotor;

Intelligence control hoisting crane is made up of mechanical system and electric-control system, adopts improved PID control policy to realize the location quick and precisely of the system of hoisting crane; Intelligence control elevator machinery part with mainly forms large and small garage and walks mechanism and adopt servomotor (4) driving by the big mechanism of car (3) of the hard arm dolly (2) of structure (1); The cart displacement measurement adopts the hard disk signal to servomotor to carry out step by step and counting, and counting is realized by the data truck in the electric-control system (piece number 5);

Electric-control system at first is an image acquisition, by CCD camera (6) images acquired, is handled by image pick-up card (7), is converted to the generation digital signal and sends into computing machine; Industrial computer (8) control core can be gathered the also various control signals of output servomotor to the kinematic coefficient of crane system by data collecting card and image pick-up card; Electric-control system adopts the PID controller (9) of neural network, has self study, self organizing function and associative memory, and by oneself;

Hoisting crane object locating system software based on visual servo adopts the VC++ language to design and develop, software interface mainly is divided into the parameter setting, and state shows, automatic guidance, manually control waits the page, wherein controls to comprise video acquisition image and correlation parameter demonstration in the page.Introduce two cores of this software below:

1. the Fast Recognition Algorithm of cylindrical shape target

What native system need be located is the cylindrical shape specific objective, from a different perspective, it is oval that the cylindrical shape target can be approximately, and parameters such as the oval center of circle and ellipse degree have been reacted the position of target, this is the main foundation of hoisting crane location, so the Fast Recognition Algorithm of ellipse target is based on the emphasis of the hoisting crane object locating system of vision, also be the innovation part of this project.The standard ellipse equation is:

$\frac{{[(x-x_0)\cos \left(\mathrm{\θ}\right)+(y-y_0)\sin \left(\mathrm{\θ}\right)]}^2}{a^2}+\frac{{[(x-x_0)\sin \left(\mathrm{\θ}\right)+(y-y_0)\cos \left(\mathrm{\θ}\right)]}^2}{b^2}=1---\left(1\right)$

(x wherein ₀, y ₀) be the oval center of circle, a, b are oval major and minor axis, θ is oval degree of dip.By formula (1) as can be known, need 5 parameters to describe ellipse, this brings very big difficulty for oval identification.According to the image size and the difference of background complexity, at present some more advanced algorithms are discerned about several seconds to tens seconds time to the ellipse in the piece image in the world, this can not satisfy the real-time requirement of native system.

By deriving, obtain oval chord length and the differential formulas between the angle of contingence:

$\frac{\mathrm{dL}}{\mathrm{d\β}}=\frac{{\mathrm{ab}}^2}{a^2{\sin }^2(\mathrm{\θ}+\mathrm{\β})+b^2{\cos }^2(\mathrm{\θ}+\mathrm{\β})}\frac{1}{\sin (\mathrm{\θ}+\mathrm{\β})}\cos \left[\arctan (-\frac{b}{a}\frac{1}{\tan (\mathrm{\θ}+\mathrm{\β})})\right]---\left(2\right)$

5 parameter predigestings of this formula wushu (1) are 3 parameters: a, b and θ.With formula (2) is aim curve, by the quick match of method of steepest descent curve to be identified, by calculate residual error judge curve to be identified and aim curve and between similarity, the while estimated parameter a, b and θ.That is to say that through type (2) can be finished simultaneously to target recognition and parameter estimation, realize the quick identification of ellipse target.

2. based on the PID position servo control algorithm of neural network

In Industry Control, traditional PID control still is in leading position so far, is particularly useful for setting up the deterministic control system of math modeling.That yet a large amount of industrial process often has is non-linear, the time become factor such as uncertainty, be difficult to set up its precise math model; In addition, the parameter in the PID controller is usually all by manually adjusting and since disposable these parameters of obtaining of adjusting be difficult to guarantee its control effect be in all the time optimum regime because of, therefore the control effect and the control accuracy of conventional PID controller are restricted.Neural network has self study, self organizing function and advantages such as associative memory, concurrent processing, makes it obtain widespread use in the Industry Control of complexity.

A kind of dynamic cognition neural network and implementation method, it is made of input layer, hidden layer, Structural layer, memory layer and output layer.This cognition neural network has ratio, integration, differential dynamic characteristics, will accelerate convergence rate when being used for that system carried out identification, and described neural network is followed the tracks of better by identification system.It is equivalent to a PID controller that becomes the structure variable element in fact when being used to control.When the number of hidden nodes is r, it is equivalent to r output stack that becomes the PID controller of structure variable element, be r PID controller parallel connection that becomes the structure variable element, at this moment, only change weights coefficient w3, then be equivalent to expert Intelligence Control or fuzzy intelligence and be controlled at and select in the r bar control control law or make up.Different with other neural network maximum, the weights of described new neural network have physical significance, and initial value is selected and can be carried out the understanding of physical process according to people, thereby can avoid may making the disturbance that controlled system is unstable and cause at the training initial stage.

Native system adopts the PID based on neural network, and it mainly is made up of 3 parts:

(1) classical PID controller: directly the controlled object process is carried out closed loop control, its three parameter k _p, k _i, k _dOnline definite.Adopt increment type PID, control algorithm is:

Δu(k)＝k _p[e(k)-e(k-1)]+k _ie(k)+k _d[e(k)-2e(k-1)+e(k-2)] (3)

(2) RBF debates the knowledge network: what be used to set up controlled system debates the knowledge model, so that dynamically the output of visual control object offers the BP neural network to the sensitivity of control input, its radial basis function is a Gaussian function.Debating the performance index function of knowing device is

$J=\frac{1}{2}{(y\left(k\right)-\hat{y}\left(k\right))}^2---\left(4\right)$

According to the gradient descent method, parameters such as corrective networks weight coefficient:

$w_j\left(k\right)=w_j(k-1)+\mathrm{\η}(y\left(k\right)-\hat{y}\left(k\right)h_j)+\mathrm{\α}(w_j(k-1)-w_j(k-2))---\left(5\right)$

Wherein be the η learning rate, be the α inertia coefficient.

(3) BP neural network: adopt three layers of BP network,, pid control parameter is regulated, to reach the optimum of controller performance index by adjusting self weight coefficient.

Claims (1)

1. an intelligent hoisting crane that has machine vision, position fixing system is characterized in that: be made up of machine vision, position fixing system and intelligence control system; Machine vision, position fixing system are made up of mechanical system and electric-control system: mechanics mainly is made up of walking cart, walking dolly, girder, end carriage, column, base etc., it is the scaled down model of actual hoisting crane, in order to the operating various states of simulation hoisting crane, the traveling gear of big dolly adopts driven by servomotor; Size parking stall shift measurement adopts the code-disc signal to servomotor to carry out frequency division and counting, and frequency division can realize that counting can be realized by the data collecting card in the electric-control system by certain parameter is set in motor servo driver; The position limiting and protecting device of big dolly adopts reflective photoelectric switch, the spacing alarm function of the big dolly of realizing walking, and it detects distance is 0～30cm; Electric-control system is: image acquisition is utilized the industrial CCD images acquired, the image simulation voltage signal that obtains is input in the image pick-up card, be converted to the digital signal of being convenient to Computer Processing, image pick-up card is installed in the pci bus slot of industrial control computer, image sampling speed was 25 frame/seconds; Selected AC servo motor and the actuator of AC servo drive system has full cut-off ring controllable function, is furnished with coder, can the strobe pulse amount carry out position control, analog quantity carries out multiple control modes such as speed control and torque control, having perfect overvoltage, overload, excess current protective function, is an open AC servo motor system; Control platform based on industrial computer: the hoisting crane object locating system based on vision is the control core with the industrial computer, by installation data capture card and image pick-up card and related system in industrial computer, just can gather, and produce the various control signals of servomotor the kinematic parameter of crane system; Hoisting crane object locating system software based on visual servo adopts the VC++ language to design and develop, software interface mainly is divided into the parameter setting, and state shows, automatic guidance, the manual control page is wherein controlled and is comprised the video acquisition image in the page and correlation parameter shows; Software is respectively: the Fast Recognition Algorithm of cylindrical shape target; PID position servo control algorithm based on neural network.

Intelligence control system is made up of mechanical system and electric-control system, adopts improved PID control policy to realize the location quick and precisely of the system of hoisting crane; Intelligence control elevator machinery part with mainly forms large and small garage and walks mechanism and adopt servomotor (4) driving by the big mechanism of car (3) of the hard arm dolly (2) of structure (1); The cart displacement measurement adopts the hard disk signal to servomotor to carry out step by step and counting, and counting is realized by the data truck (5) in the electric-control system; Electric-control system at first is an image acquisition, by CCD camera (6) images acquired, is handled by image pick-up card (7), is converted to the generation digital signal and sends into computing machine; Industrial computer (8) control core can be gathered the also various control signals of output servomotor to the kinematic coefficient of crane system by data collecting card and image pick-up card; Electric-control system adopts the PID controller (9) of neural network, is made of input layer, hidden layer, Structural layer, memory layer and output layer; Have self study, self organizing function and associative memory, and by oneself.

Images