CN117420752B - Strain clamp detection robot control system and control method - Google Patents
Strain clamp detection robot control system and control method Download PDFInfo
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Abstract
The invention provides a control system and a control method for a strain clamp detection robot, and belongs to the technical field of strain clamp detection. The control system comprises an Arduino controller and an upper computer, wherein the upper computer comprises a position follow-up system, controls the strain clamp detection robot through PID and RBF neural network, receives a control instruction of the upper computer and outputs the control instruction to the strain clamp detection robot, and controls the start and stop of the strain clamp robot, the sliding of a travelling wheel along a high-voltage line, the movement of a guide rail sliding seat along a detection guide rail and the rotation of a strain clamp detection module; and the image shot by the strain clamp detection module and the data returned by the sensor are also acquired and processed and transmitted to the upper computer in a wireless transmission mode. The invention realizes the omnibearing detection of the strain clamps and completes the detection of a plurality of strain clamps at one time.
Description
Technical Field
The invention relates to the technical field of strain clamp robot control, in particular to a strain clamp detection robot control system and a strain clamp detection robot control method.
Background
The strain clamp is mainly used for connecting corners, connection and terminals, plays a role of an anchor, is used for fixing a high-voltage wire or a lightning wire on a strain insulator string of a nonlinear tower, and is also used for fixing a pull wire of a pull wire tower. According to the operation and detection requirements of a power grid company, nondestructive detection of the strain clamp is required by using an X-ray detection technology at the positions of crossing railways, crossing high speeds and crossing important lines.
When the strain clamp is used for X-ray detection, based on an X-ray perspective imaging technology, according to the difference of thickness and density of internal components of an object, the difference of X-ray absorption capacity is generated, after rays penetrate through a substance, transillumination images with different intensity difference distribution are formed, and then the detector displays the difference of the X-rays in an image mode, so that nondestructive detection and high-precision imaging of a strain clamp crimping process are realized, and the defects of whether a line crimping pipe steel core is crimped in place, whether crimping is fastened, whether the crimping has cracks and the like are accurately judged. By adopting the technology, the workload of detection personnel can be effectively reduced, the working precision is improved, and the intrinsic safety level of equipment is improved.
The X-ray DR imaging system has the advantages of simple operation, wireless transmission, real-time imaging, light weight, convenience for high-altitude operation, real-time storage of nondestructive flaw detection pictures in a computer workstation, convenience for post-processing, and the like.
At present, however, strain clamp detection work is mainly finished by manpower, and a detection person carries a detection device to climb a rod to sequentially detect clamps on each high-voltage wire. The method has the advantages of prominent potential safety hazard, too much dependence on manual operation, unable standardization of the process and low detection efficiency. Therefore, robots for detecting strain clamps are urgently required to replace manual work.
The initial aim of the research on the line detection robots is to remove ice on a transmission line, and the like, the robot has the capability of walking along the line in a single gear. In order to embody the multi-purpose of a machine, improve into the detection function on the basis of its deicing function, increased the function that the cable patrols and examines. As in 1988, japan first developed a study of an overhead ground wire inspection robot, and design of ape climbing enabled the robot to work back and forth on a line. In 2000, the IREQ institute in canada developed a robot for deicing cables, which primarily functions to remove ice deposits that cover the cables, and which has the ability to travel on the cables. After the deicing season is over, the deicing function is replaced by the inspection function, so that inspection operation is realized. The research of domestic inspection robots is also increasing, in 2007, shanghai university develops a robot prototype applied to high-voltage wire inspection, the robot runs on a ground wire, has two arms with multiple degrees of freedom, and is provided with rollers and claws at the tail ends of the arms for moving. In a section with a complex working condition, the gripper is used for grabbing movement. 2011. In the year, shandong university of science and technology developed a prototype of a deicing robot for a transmission line, which has a three-arm mechanism, and arms at both ends adopt a four-bar mechanism to travel on a cable through rollers.
However, the position of the strain clamp is complex, and obstacles such as a drainage wire, a shielding ring and a damper are arranged, so that the existing line inspection robot mostly moves on a single line, the shooting position of an X-ray machine cannot be adjusted, and meanwhile, the requirement of detecting a plurality of strain clamps at one time cannot be met.
Disclosure of Invention
The invention provides a control system and a control method of a strain clamp detection robot, wherein the control system comprises an Arduino controller and an upper computer, the upper computer comprises a position follow-up system, the strain clamp detection robot is controlled by combining a PID (proportion integration differentiation) with an RBF (radial basis function) neural network, the RBF neural network is used for identifying the position change of the strain clamp detection robot in the position follow-up system to obtain jacobian matrix information required for adjusting three input parameters of the PID, and the Arduino controller is used for receiving a control instruction of the upper computer and outputting the control instruction to the strain clamp detection robot to control the start and stop of the strain clamp robot, the sliding of a travelling wheel along a high-voltage line, the movement of a guide rail sliding seat along a detection guide rail and the rotation of the strain clamp detection module; and the image shot by the strain clamp detection module and the data returned by the sensor are also acquired and processed and transmitted to the upper computer in a wireless transmission mode. The invention realizes the omnibearing detection of the strain clamps and completes the detection of a plurality of strain clamps at one time.
The invention provides a strain clamp detection robot control system, which is used for detecting a strain clamp connected with a high-voltage line and comprises a detection robot body, a walking module and a detection module, wherein the detection robot body is connected with the high-voltage line;
the walking module comprises a detection guide rail and a walking wheel which are respectively connected with the detection robot body, and the detection guide rail consists of two semicircular guide rails which can be opened and closed; the walking wheels are arranged on two sides of the detection robot body, the detection guide rail is arranged at one end of the detection robot body, the symmetry axis of the walking wheels is perpendicular to the plane where the detection guide rail is located, and the walking wheels can walk along a high-voltage line connected with the strain clamp;
the detection module comprises a detection support and a strain clamp detection module, wherein the strain clamp detection module is arranged on the detection support and comprises imaging equipment;
the detection guide rail is provided with a guide rail sliding seat which is fixedly connected with the detection support, and the guide rail sliding seat can slide along the detection guide rail and drive the detection support to move together;
a speed reduction stepping motor, a stepping motor driving circuit and a sensor are arranged in the detection robot body;
the control system comprises an Arduino controller and an upper computer, wherein the upper computer comprises a position follow-up system, an RBF neural network is used for identifying the position change of the strain clamp detection robot in the position follow-up system to obtain jacobian matrix information required for adjusting three input parameters of a PID, the strain clamp detection robot is controlled by combining the PID with an RBF (Radial Basis Function radial basis function) neural network, neurons of an input space and an hidden space of the RBF neural network are determined by the position follow-up system, and an output space is formed by the neurons.
The Arduino controller receives a control instruction of the upper computer and outputs the control instruction to the strain clamp detection robot, and controls starting and stopping of the strain clamp robot, sliding of the travelling wheel along the high-voltage line, movement of the guide rail sliding seat along the detection guide rail and rotation of the strain clamp detection module;
the Arduino controller is used for collecting and processing images shot by the strain clamp detection module and data returned by the sensor, and transmitting the images and the data to the upper computer in a wireless transmission mode;
the upper computer receives the data transmitted by the Arduino controller, detects whether the strain clamp detection robot reaches a working position, detects whether the guide rail is closed, detects whether the strain clamp detection module reaches a detection position, and outputs a control instruction for the state of the strain clamp detection robot.
Arduino has the advantages of high operation speed, short development period, more I/O ports, convenience in carrying a plurality of sensors and the like, and the strain clamp detection robot control system disclosed by the invention needs to detect the positions of the strain clamp detection robot, the strain clamp detection module and the damper through the plurality of sensors, so that Arduino is combined with the upper computer, and the control of the strain clamp detection robot can be better realized.
The RBF neural network is a three-layer forward network, wherein the first layer is an output layer and consists of signal source nodes; the second layer is an implicit layer, and the node basis function is a locally distributed non-negative nonlinear function which is attenuated symmetrically in the radial direction of the center; the third layer is an output layer.
Preferably, the position follow-up system adopts a closed-loop negative feedback system, an Ardunio control board is used as a control core, a deceleration stepping motor is used as an executing element, the rotating speed and the position of the detection robot are used as controlled objects, and an encoder is used as a detection unit.
Preferably, the wireless communication mode is WIFI wireless transmission, and compared with traditional cable transmission, the robot moving flexibility and expandability are improved, and the maintenance and detection cost of the robot is reduced.
Preferably, the upper computer controls the opening and closing of the two semi-circles of the detection guide rail through the reduction gearbox, and the strain clamp detection module comprises an X-ray machine and a reflecting plate.
Preferably, the detection robot body is provided with a proximity switch sensor, the walking wheels are matched to complete the movement of the strain clamp detection robot across the damper, the detection guide rail is provided with a limit switch sensor, and the upper computer is matched to complete the position detection of the strain clamp detection module.
Preferably, the detection robot body can be further provided with an anti-roll mechanical rotating arm, so that the occurrence of overturning under special conditions can be prevented.
Preferably, a steering engine for controlling the anti-roll mechanical rotating arm is arranged on the detection robot body.
Preferably, the upper computer generates a start-stop instruction of the strain clamp detection robot according to the current start-stop state and start-stop requirement of the strain clamp detection robot.
Preferably, before detection, the strain clamp detection robot is carried away from the ground by an unmanned aerial vehicle and released on a high-voltage wire, and the high-voltage wire is clamped into the travelling wheel.
Preferably, the upper computer generates an instruction for controlling the travelling wheels to advance and retreat according to the current position of the strain clamp detection robot and the current working position required to be detected, and after receiving the instruction, the Arduino controller outputs the instruction to the stepping motor driving circuit to control the stepping motor to drive the travelling wheels to move and drive the strain clamp detection robot to move to the required working position along the high-voltage line.
Preferably, when the upper computer judges that the strain clamp detection robot moves to a required working position, the upper computer detects whether the detection guide rail is closed or not, and when the detection guide rail is not closed, the upper computer generates an instruction to control the detection guide rail to be closed, and if the detection guide rail is not closed yet, an alarm is sent.
Preferably, when the upper computer judges that the detection guide rail is closed, the upper computer generates an instruction for controlling the guide rail slide seat to slide along the detection guide rail according to the position of the strain clamp detection module and the position to be detected of the strain clamp, and after receiving the instruction, the Arduino controller outputs the instruction to the stepping motor driving circuit to control the stepping motor to drive the guide rail slide seat to slide along the detection guide rail, so that the strain clamp detection module moves to the position to be detected of the strain clamp.
Preferably, when the strain clamp detection module slides to the detection position of the strain clamp, the upper computer further generates an instruction for controlling the strain clamp detection module to rotate, and the instruction is used for adjusting the shooting angle of the imaging device.
Preferably, the upper computer judges that the strain clamp detection robot has completed one strain clamp detection according to the received image of the detection process of the strain clamp detection robot sent by the Arduino controller, and generates an instruction for controlling the strain clamp detection robot to move to the working position of the next strain clamp, and sends the instruction to the Arduino controller for controlling the strain clamp detection robot to move to the working position of the next strain clamp.
The invention provides a strain clamp detection robot control method used by the strain clamp detection robot control system, which comprises the following steps:
step S1: detecting whether the strain clamp detection robot reaches a working position or not and adjusting the position of the strain clamp detection robot;
step S2: detecting whether the detection guide rail is closed or not, if not, generating an instruction by the upper computer to control the detection guide rail to be closed, and if not, sending an alarm to end the detection; otherwise, executing the step S3;
step S3: detecting whether the strain clamp detection robot reaches a detection position or not and adjusting the position of the guide rail sliding seat;
step S4: according to the position to be detected of the strain clamp, controlling the strain clamp detection module to rotate, and completing image shooting of different positions of the strain clamp;
step S5: judging whether the detection of one strain clamp is finished, if so, generating an instruction, controlling the strain clamp detection robot to move to the working position of the next strain clamp, and repeating the steps S1-S5 until the detection of six strain clamps of the high-voltage line is finished.
Preferably, before step S1, the method further includes performing state detection of the strain clamp detection robot, and displaying self state information and electric quantity conditions of the strain clamp detection robot.
Preferably, step S1 is specifically: the upper computer judges whether the strain clamp detection robot reaches a working position according to the current position of the strain clamp detection robot sent by the Arduino controller, if not, the upper computer generates an instruction for controlling the travelling wheels to move forwards and backwards according to the current position of the strain clamp detection robot and the working position required to work currently, and after receiving the instruction, the Arduino controller outputs the instruction to the stepping motor driving circuit to control the stepping motor to drive the travelling wheels to move and drive the strain clamp detection robot to move to the working position required to work along the high-voltage wire.
Preferably, step S2 is specifically: when the strain clamp detection robot reaches a required working position, a detection signal is introduced into one semicircular guide rail end part of the detection guide rail, the detection signal is detected on the other semicircular guide rail of the detection guide rail, if the detection signal can be received, the detection guide rail is closed, if the detection signal can not be received, the detection guide rail is not closed, the upper computer controls the detection guide rail to be closed through a reduction gearbox connected with the detection guide rail, and if the detection signal is still not closed, an alarm is sent out, and the detection is ended.
Preferably, step S3 is specifically: when the upper computer judges that the detection guide rail is closed, the upper computer receives the signals of the limit switch sensor to obtain the position of the guide rail sliding seat, generates an instruction for controlling the guide rail sliding seat to slide along the detection guide rail according to the position of the strain clamp detection module and the position to be detected of the strain clamp, sends the instruction to the Arduino controller, after receiving the instruction, outputs the instruction to the driving circuit of the stepping motor, controls the stepping motor to drive the guide rail sliding seat to slide along the detection guide rail, enables the strain clamp detection module to move to the position to be detected of the strain clamp, and when the movement is finished, sends the position of the strain clamp detection module to the upper computer through the Arduino controller, judges whether the strain clamp detection module reaches the detection position according to the received position of the strain clamp detection module measured by the limit switch sensor on the detection guide rail, and adjusts the position to the strain clamp detection module if the signal does not reach the detection position again.
Preferably, step S4 is specifically: when the strain clamp detection module reaches a detection position, the upper computer controls the strain clamp detection module on the detection support to rotate according to the received position of the strain clamp detection module and the position to be detected of the strain clamp, so that image shooting of different positions of the strain clamp is completed.
Preferably, in step S5, when the strain clamp detection robot moves to the working position of the next strain clamp, a proximity switch sensor on the detection robot body detects a damper, the detection result is transmitted to the upper computer, and when the damper is detected, the upper computer receives the result and controls the travelling wheel to complete the movement of the strain clamp detection robot across the damper. Specifically, when the anti-vibration hammer is crossed, the travelling wheel is controlled to slow down, and the anti-vibration hammer is crossed slowly, so that falling is prevented. The anti-rolling rotating arms can be arranged on two sides of the detection robot body and correspond to the walking wheels, when the anti-rolling rotating arms span the anti-vibration hammer, the anti-rolling rotating arms rotate to the outer sides of the walking wheels, the auxiliary strain clamp detection robot stably spans the anti-vibration hammer, and the strain clamp detection robot is prevented from falling.
Preferably, when the upper computer detects that all six strain clamps are detected, the upper computer sends an instruction, controls the guide rail sliding seat to a preset position, controls the strain clamp detection robot to move to a preset hanging-off position, controls the two semicircular guide rails of the detection guide rails to open, and controls the unmanned aerial vehicle to carry out hanging-off of the strain clamp detection robot.
Preferably, when the detection starts, the stepping motor drives the guide rail sliding seat to drive the strain clamp detection module to do circular motion around the detection guide rail, and the strain clamps of the six high-voltage wires are sequentially detected according to a preset detection sequence. When encountering the damper in the rotation process, the anti-vibration device is matched with an upper computer to control the travelling wheel to move so as to realize the action of crossing the damper, and when encountering other obstacles, the strain clamp detection robot can emergently brake and send out an alarm signal.
Preferably, the rotational speed of the rail carriage on the detection rail is detected by: two magnetic steel sheets are arranged on the detection guide rail, a Hall element sensor is arranged on the guide rail sliding seat, and when the guide rail sliding seat moves around the detection guide rail with the strain clamp detection module, the Hall element sensor sends out a receivable pulse when detecting the magnetic field of the magnetic steel sheets. The time interval between the two ending pulses is the time when the guide rail sliding seat rotates around the detection guide rail for one circle.
Preferably, the rotational speedThe calculation formula is as follows:
（1）
wherein:
c, detecting the pulse number sent by the Hall element sensor within the perimeter distance of the guide rail;
——detecting the circumference of the guide rail, and measuring the circumference in mm;
——detecting the radius of the guide rail, and measuring the mm;
t——two pulse intervals, s.
Preferably, the PID controller in the control system adopts an incremental mode, and the control error is as follows:
the three inputs to the PID are:
the incremental PID control algorithm is as follows:
setting a performance index function:
three parameter adjustment formulas of the PID regulator:
in the method, in the process of the invention,the information of the jacobian matrix of the controlled object can be obtained through RBF neural network identification. In the invention, the controlled object is the strain clamp detection robotIs provided, and the rotational speed of the rail carriage.
Compared with the prior art, the invention has the following beneficial effects:
(1) The invention combines the traditional PID control and the RBF neural network, is used for controlling the position of the strain clamp detection robot and the rotating speed of the guide rail slide seat, and when the position of the strain clamp detection robot in the position follow-up system changes, the radial basis neural network can identify the strain clamp detection robot in time, so that the Jacobian matrix information required for adjusting three input parameters of the PID is obtained, and the control of the robot is more timely and accurate.
(2) The detection robot disclosed by the invention adopts the two closable arc-shaped guide rails, so that the moving positions of the guide rail sliding seat on the guide rails can be more comprehensively covered, images of strain clamps with more angles can be acquired, and the occurrence of missed detection is avoided;
(3) According to the control system disclosed by the invention, after the robot reaches the working position, before detection starts, a test signal is input into one semicircular guide rail, and the test signal is received into the other semicircular guide rail to judge whether the detection guide rail is closed, so that the detection guide rail is prevented from falling off or being blocked when the detection guide rail slides are moved due to the fact that the detection guide rail is not closed, and the detection is smoothly carried out.
(4) The limit switch sensor provided by the invention can be matched with an upper computer algorithm to ensure that the strain clamp detection module of the robot accurately reaches the detection position, and the proximity switch sensor can be matched with the upper computer algorithm to accurately control the travelling wheel to span the damper.
(5) The control system can control the strain clamp detection robot to detect a plurality of strain clamps at one time, and detection is faster and more convenient.
Drawings
FIG. 1 is a schematic diagram of a strain clamp inspection robot in accordance with one embodiment of the present invention;
FIG. 2 is a schematic diagram of a PID controller architecture for an RBF neural network, according to an embodiment of the present invention;
fig. 3 is a general structure diagram of a strain clamp detection robot control system according to an embodiment of the present invention, where ESP8266 is a WIFI chip;
FIG. 4 is a flowchart of a process for controlling a strain clamp detection robot (including the process of hoisting the strain clamp detection robot to and from a high-voltage wire in-line traveling wheel) according to one embodiment of the present invention;
FIG. 5 is a graph showing the comparison of RBF-PID control with conventional PID control according to an embodiment of the invention;
FIG. 6 is a block diagram of a closed loop negative feedback control system according to one embodiment of the invention;
in the figure, a 1-detection robot body, a 2-detection guide rail, a 3-detection support, a 4-guide rail sliding seat, a 5-X-ray machine, a 6-reflecting plate, a 7-travelling wheel and an 8-anti-roll rotating arm.
Detailed Description
The following describes the embodiments of the present invention in detail with reference to the drawings.
The invention provides a strain clamp detection robot control system, which is used for detecting a strain clamp connected with a high-voltage line and comprises a detection robot body 1, a walking module and a detection module;
the walking module comprises a detection guide rail 2 and a walking wheel 7 which are respectively connected with the detection robot body 1, wherein the detection guide rail 2 consists of two semicircular guide rails which can be opened and closed; the walking wheels 7 are arranged on two sides of the detection robot body 1, the detection guide rail 2 is arranged at one end of the detection robot body 1, the symmetry axis of the walking wheels 7 is perpendicular to the plane where the detection guide rail 2 is located, and the walking wheels 7 can walk along high-voltage wires connected with the strain clamps;
the detection module comprises a detection bracket 3 and a strain clamp detection module, wherein the strain clamp detection module is arranged on the detection bracket 3, and the strain clamp detection module comprises imaging equipment;
a guide rail sliding seat 4 is arranged on the detection guide rail 2, the guide rail sliding seat 4 is fixedly connected with the detection support 3, and the guide rail sliding seat 4 can slide along the detection guide rail 2 and drive the detection support 3 to move together;
a speed reduction stepping motor, a stepping motor driving circuit and a sensor are arranged in the detection robot body 1;
the control system comprises an Arduino controller and an upper computer, wherein the upper computer comprises a position follow-up system, an RBF neural network is used for identifying the position change of the strain clamp detection robot in the position follow-up system to obtain jacobian matrix information required for adjusting three input parameters of a PID, the strain clamp detection robot is controlled by combining the PID with an RBF (Radial Basis Function radial basis function) neural network, neurons of an input space and an hidden space of the RBF neural network are determined by the position follow-up system, and an output space is formed by the neurons;
the Arduino controller receives a control instruction of the upper computer and outputs the control instruction to the strain clamp detection robot, and controls starting and stopping of the strain clamp robot, sliding of the travelling wheel 7 along the high-voltage line, movement of the guide rail sliding seat 4 along the detection guide rail 2 and rotation of the strain clamp detection module;
the Arduino controller is used for collecting and processing images shot by the strain clamp detection module and data returned by the sensor, and transmitting the images and the data to the upper computer in a wireless transmission mode;
the upper computer receives data transmitted by the Arduino controller, detects whether the strain clamp detection robot reaches a working position, detects whether the guide rail 2 is closed, detects whether the strain clamp detection module reaches a detection position, and outputs a control instruction for the state of the strain clamp detection robot.
In some embodiments of the present invention, the position follower system adopts a closed-loop negative feedback system, an Ardunio control board is used as a control core, a deceleration stepper motor is used as an executing element, the rotation speed and the position of the detection robot are used as controlled objects, and an encoder is used as a detection unit.
In some embodiments of the present invention, the wireless communication mode is WIFI wireless transmission, which improves flexibility and expandability of robot movement and reduces maintenance and detection costs of the robot compared with conventional cable transmission.
In some embodiments of the present invention, the upper computer controls the opening and closing of the two semi-circles of the detection guide rail 2 through a reduction gearbox, and the strain clamp detection module includes an X-ray machine 5 and a reflecting plate 6.
In some embodiments of the present invention, the detection robot body 1 is provided with a proximity switch sensor, the walking wheel 7 is matched to complete the movement of the strain clamp detection robot across the damper, the detection guide rail 2 is provided with a limit switch sensor, and the upper computer is matched to complete the position detection of the strain clamp detection module.
In some embodiments of the present invention, the inspection robot body 1 may further be provided with an anti-roll mechanical rotation arm, so as to prevent the occurrence of capsizing under special conditions.
In some embodiments of the present invention, the steering engine for controlling the anti-roll mechanical rotation arm is disposed on the inspection robot body 1.
In some embodiments of the present invention, the upper computer generates a start-stop instruction of the strain clamp detection robot according to a current start-stop state and start-stop requirements of the strain clamp detection robot.
In some embodiments of the present invention, before the detection, the strain clamp detection robot is carried off the ground by an unmanned plane and released on a high-voltage wire, and clamps the high-voltage wire into the travelling wheel 7.
In some embodiments of the present invention, the upper computer generates an instruction for controlling the traveling wheel 7 to advance and retreat according to the current position of the strain clamp detection robot and the current working position to be detected, and after receiving the instruction, the Arduino controller outputs the instruction to the stepper motor driving circuit to control the stepper motor to drive the traveling wheel 7 to move, and drives the strain clamp detection robot to move to the required working position along the high-voltage line.
In some embodiments of the present invention, when the upper computer determines that the strain clamp detection robot moves to a required working position, the upper computer detects whether the detection guide rail 2 is closed, and when the detection guide rail 2 is not closed, the upper computer generates an instruction to control the detection guide rail 2 to be closed, and if the detection guide rail 2 is not closed, an alarm is sent.
In some embodiments of the present invention, when the upper computer determines that the detection rail 2 is closed, the upper computer generates an instruction for controlling the rail slide 4 to slide along the detection rail 2 according to the position of the strain clamp detection module and the position to be detected of the strain clamp, and after receiving the instruction, the Arduino controller outputs the instruction to the stepper motor driving circuit to control the stepper motor to drive the rail slide 4 to slide along the detection rail 2, so that the strain clamp detection module moves to the position to be detected of the strain clamp.
In some embodiments of the present invention, when the strain clamp detection module moves to the detection position of the strain clamp, the upper computer further generates an instruction for controlling the strain clamp detection module to rotate, so as to adjust the shooting angle of the imaging device.
In some embodiments of the present invention, after the upper computer determines that the strain clamp detection robot has completed detection of one strain clamp according to the received image of the process of detecting the strain clamp by the Arduino controller, the upper computer generates an instruction for controlling the strain clamp detection robot to move to the working position of the next strain clamp, and sends the instruction to the Arduino controller, so as to control the strain clamp detection robot to move to the working position of the next strain clamp.
The invention provides a strain clamp detection robot control method used by the strain clamp detection robot control system, which comprises the following steps:
step S1: detecting whether the strain clamp detection robot reaches a working position or not and adjusting the position of the strain clamp detection robot;
step S2: detecting whether the detection guide rail 2 is closed or not, if not, generating an instruction by the upper computer to control the detection guide rail 2 to be closed, and if not, giving an alarm and ending the detection; otherwise, executing the step S3;
step S3: detecting whether the strain clamp detection robot reaches a detection position or not and adjusting the position of the guide rail sliding seat 4;
step S4: according to the position to be detected of the strain clamp, controlling the strain clamp detection module to rotate, and completing image shooting of different positions of the strain clamp;
step S5: judging whether the detection of one strain clamp is finished, if so, generating an instruction, controlling the strain clamp detection robot to move to the working position of the next strain clamp, and repeating the steps S1-S5 until the detection of six strain clamps of the high-voltage line is finished.
In some embodiments of the present invention, before step S1, the method further includes performing state detection of the strain clamp detection robot, and displaying self state information and an electric quantity condition of the strain clamp detection robot.
In some embodiments of the present invention, step S1 is specifically: the upper computer judges whether the strain clamp detection robot reaches a working position according to the current position of the strain clamp detection robot sent by the Arduino controller, if not, the upper computer generates an instruction for controlling the traveling wheel 7 to advance and retreat according to the current position of the strain clamp detection robot and the working position required to work currently, and after receiving the instruction, the Arduino controller outputs the instruction to the stepping motor driving circuit to control the stepping motor to drive the traveling wheel 7 to move and drive the strain clamp detection robot to move to the working position required to work along the high-voltage wire.
In some embodiments of the present invention, step S2 is specifically: when the strain clamp detection robot reaches a required working position, a detection signal is introduced into one semicircular guide rail end part of the detection guide rail 2, the detection signal is detected on the other semicircular guide rail of the detection guide rail 2, if the detection signal can be received, the detection guide rail 2 is closed, if the detection signal can not be received, the detection guide rail 2 is not closed, the upper computer controls the detection guide rail 2 to be closed through a reduction gearbox connected with the detection guide rail 2, and if the detection signal is still not closed, an alarm is sent out, and the detection is ended.
In some embodiments of the present invention, step S3 is specifically: when the upper computer judges that the detection guide rail 2 is closed, the upper computer receives the signals of the limit switch sensor to obtain the position of the guide rail sliding seat 4, generates an instruction for controlling the guide rail sliding seat 4 to slide along the detection guide rail 2 according to the position of the strain clamp detection module and the position to be detected of the strain clamp, sends the instruction to the Arduino controller, after receiving the instruction, outputs the instruction to the stepping motor driving circuit, controls the stepping motor to drive the guide rail sliding seat 4 to slide along the detection guide rail 2, so that the strain clamp detection module moves to the position to be detected of the strain clamp, and when the movement is finished, the limit switch sensor on the detection guide rail 2 sends the position of the strain clamp detection module to the upper computer through the Arduino controller, judges whether the detection module reaches the position to be detected of the strain clamp detection module according to the received position of the limit switch sensor on the detection guide rail 2, and adjusts whether the signal reaches the position to the strain clamp detection module again.
In some embodiments of the present invention, step S4 is specifically: when the strain clamp detection module reaches a detection position, the upper computer controls the strain clamp detection module on the detection support 3 to rotate according to the received position of the strain clamp detection module and the position to be detected of the strain clamp, so that image shooting of different positions of the strain clamp is completed.
In some embodiments of the present invention, in step S5, when the strain clamp detection robot moves to the working position of the next strain clamp, a proximity switch sensor on the detection robot body 1 detects a damper, and transmits a detection result to the upper computer, and when the damper is detected, the upper computer receives the result and controls the travelling wheel 7 to complete the movement of the strain clamp detection robot across the damper.
In some embodiments of the present invention, when the upper computer detects that all six strain clamps have been detected, the upper computer sends an instruction, controls the rail slide seat 4 to a preset position, controls the strain clamp detection robot to move to a preset hanging-off position, controls the two semicircular rails of the detection rail 2 to open, and controls the unmanned aerial vehicle to carry out hanging-off of the strain clamp detection robot.
In some embodiments of the present invention, when the detection starts, the stepper motor drives the rail slide 4 to drive the strain clamp detection module to do circular motion around the detection rail 2, and the strain clamps of the six high-voltage wires are sequentially detected according to a preset detection sequence. When encountering the damper in the rotation process, the anti-vibration device is matched with an upper computer to control the traveling wheel 7 to move so as to realize the action of crossing the damper, and when encountering other obstacles, the strain clamp detection robot can emergently brake and send out an alarm signal.
In some embodiments of the invention, the rotational speed of the rail carriage 4 on the detection rail 2 is detected by: two magnetic steel sheets are arranged on the detection guide rail 2, a Hall element sensor is arranged on the guide rail sliding seat 4, and when the guide rail sliding seat 4 moves around the detection guide rail 2 with the strain clamp detection module, the Hall element sensor sends out a receivable pulse when detecting the magnetic field of the magnetic steel sheets. The time interval between the two ending pulses is the time when the guide rail slide seat 4 rotates around the detection guide rail 2 for one circle.
In some embodiments of the invention, the rotational speedThe calculation formula is as follows:
（1）
wherein:
c, detecting the pulse number sent by the Hall element sensor within the peripheral distance of the guide rail 2;
——detecting the circumference of the guide rail 2 mm;
——detecting the radius of the guide rail 2, and measuring mm;
t——two pulse intervals, s.
In some embodiments of the present invention, the PID controller in the control system adopts an incremental type, as shown in fig. 2, and the RBF-PID regulator adopted in the present invention has a schematic structure, and the control error is:
the three inputs to the PID are:
the incremental PID control algorithm is as follows:
setting a performance index function:
three parameter adjustment formulas of the PID regulator:
in the method, in the process of the invention,the information of the jacobian matrix of the controlled object can be obtained through RBF neural network identification. In the present invention, the controlled object is the position of the strain clamp detection robot and the rotation speed of the rail slider 4.
In order to verify the effect of the RBF-PID control method, simulation is carried out, in a simulation model, a higher-order signal is used as input, 0.2s is used as a sampling period, a dark curve is a traditional PID control strategy, and a light curve represents the RBF-PID control strategy. Two control strategy response curves can be obtained from the simulation results shown in FIG. 5, RBF-PID control is stabilized about 0.4s, and conventional PID is stabilized about 1.2 s; compared with the traditional PID control, the RBF-PID control strategy can effectively reduce the overshoot of the system, shortens the response time of the system, and shows better robustness and stability in the robot control system.
The above is only a preferred embodiment of the present invention, and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are included in the protection scope of the present invention.
Claims (9)
1. The utility model provides a strain clamp detection robot control system which characterized in that:
the strain clamp detection robot is used for detecting a strain clamp connected with a high-voltage wire and comprises a detection robot body, a walking module and a detection module;
the walking module comprises a detection guide rail and a walking wheel which are respectively connected with the detection robot body, and the detection guide rail consists of two semicircular guide rails which can be opened and closed; the walking wheels are symmetrically arranged on two sides of the detection robot body, the detection guide rail is arranged at one end of the detection robot body, the symmetry axis of the walking wheels is perpendicular to the plane where the detection guide rail is located, and the walking wheels can walk along high-voltage wires connected with the strain clamps;
the detection module comprises a detection support and a strain clamp detection module, wherein the strain clamp detection module is arranged on the detection support and comprises imaging equipment;
the detection guide rail is provided with a guide rail sliding seat which is fixedly connected with the detection support, and the guide rail sliding seat can slide along the detection guide rail and drive the detection support to move together;
a speed reduction stepping motor, a stepping motor driving circuit and a sensor are arranged in the detection robot body;
the control system comprises an Arduino controller and an upper computer, wherein the upper computer comprises a position follow-up system, an RBF neural network is used for identifying the position change of the strain clamp detection robot in the position follow-up system to obtain jacobian matrix information required for adjusting three input parameters of a PID, and the strain clamp detection robot is controlled by combining the PID with the RBF neural network;
the Arduino controller receives a control instruction of the upper computer and outputs the control instruction to the strain clamp detection robot, and controls starting and stopping of the strain clamp robot, sliding of the travelling wheel along the high-voltage line, movement of the guide rail sliding seat along the detection guide rail and rotation of the strain clamp detection module;
the Arduino controller is used for collecting and processing images shot by the strain clamp detection module and data returned by the sensor, and transmitting the images and the data to the upper computer in a wireless transmission mode;
the upper computer is used for receiving the data transmitted by the Arduino controller, detecting whether the strain clamp detection robot reaches a working position, detecting whether the guide rail is closed or not, detecting whether the strain clamp detection module reaches a detection position or not, and outputting a control instruction for the state of the strain clamp detection robot;
when the upper computer judges that the detection guide rail is closed, the upper computer generates an instruction for controlling the guide rail slide seat to slide along the detection guide rail according to the position of the strain clamp detection module and the position to be detected of the strain clamp, and after receiving the instruction, the Arduino controller outputs the instruction to the stepping motor driving circuit to control the stepping motor to drive the guide rail slide seat to slide along the detection guide rail, so that the strain clamp detection module moves to the position to be detected of the strain clamp.
2. The strain clamp detection robot control system of claim 1, wherein the upper computer controls the opening and closing of the two semi-circles of the detection guide rail through a reduction gearbox, and the strain clamp detection module comprises an X-ray machine and a reflecting plate.
3. The strain clamp detection robot control system according to claim 1, wherein a proximity switch sensor is arranged on the detection robot body, the movement of the strain clamp detection robot crossing the damper is completed by matching with the travelling wheel, a limit switch sensor is arranged on the detection guide rail, and the position detection of the strain clamp detection module is completed by matching with the upper computer.
4. The strain clamp inspection robot control system of claim 1, wherein prior to inspection, the strain clamp inspection robot is carried off the ground by an unmanned aerial vehicle and released on a high voltage wire and clamps the high voltage wire into the road wheel.
5. The control system of the strain clamp detection robot according to claim 4, wherein the upper computer generates an instruction for controlling the traveling wheels to advance and retreat according to the current position and the current working position of the strain clamp detection robot, and the Arduino controller receives the instruction and outputs the instruction to the stepping motor driving circuit to control the stepping motor to drive the traveling wheels to move and drive the strain clamp detection robot to move to the required working position along the high-voltage line.
6. The strain clamp detection robot control system of claim 5, wherein when the upper computer judges that the strain clamp detection robot moves to a required working position, the upper computer detects whether the detection guide rail is closed, and when the detection guide rail is not closed, the upper computer generates an instruction to control the detection guide rail to be closed, and if the detection guide rail is not closed, an alarm is sent.
7. The strain clamp inspection robot control system of any of claims 1-6, wherein when the strain clamp inspection module slides to the inspection position of the strain clamp, the host computer further generates an instruction to control rotation of the strain clamp inspection module for adjusting the shooting angle of the imaging device.
8. The strain clamp detection robot control system according to claim 7, wherein after the upper computer judges that the strain clamp detection robot has completed detection of one strain clamp according to the received strain clamp detection process picture sent by the Arduino controller, the upper computer generates an instruction for controlling the strain clamp detection robot to move to the working position of the next strain clamp, and sends the instruction to the Arduino controller for controlling the strain clamp detection robot to move to the working position of the next strain clamp.
9. A strain clamp inspection robot control method for use with the strain clamp inspection robot control system of any one of claims 1-8, comprising the steps of:
step S1: detecting whether the strain clamp detection robot reaches a working position or not and adjusting the position of the strain clamp detection robot;
step S2: detecting whether the detection guide rail is closed or not, if not, generating an instruction by the upper computer to control the detection guide rail to be closed, and if not, sending an alarm to end the detection; otherwise, executing the step S3;
step S3: detecting whether the strain clamp detection robot reaches a detection position or not and adjusting the position of the guide rail sliding seat;
step S4: according to the position to be detected of the strain clamp, controlling the strain clamp detection module to rotate, and completing image shooting of different positions of the strain clamp;
step S5: judging whether the detection of one strain clamp is finished, if so, generating an instruction, controlling the strain clamp detection robot to move to the working position of the next strain clamp, and repeating the steps S1-S5 until the detection of six strain clamps of the high-voltage line is finished.
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