CN117656094A - Charging station inspection robot with emergency charging function and inspection method - Google Patents
Charging station inspection robot with emergency charging function and inspection method Download PDFInfo
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Abstract
The invention relates to a charging station inspection robot with an emergency charging function and an inspection method, wherein the inspection robot comprises an inspection robot part and an emergency charging part which are in communication connection through a wireless network; the inspection robot component comprises a power management unit, a sensor unit, a network connection unit, a control unit, a human-computer interface, a motion signal adjusting unit, a servo motor driving unit, a three-phase BLDC motor driving unit, a motion motor and an operation motor; the emergency charging component consists of an information processing and control unit and a charging power unit; the information processing and control unit is used for receiving a wireless instruction of the inspection robot component, automatically moving to a specified position on the track, and has an active obstacle avoidance function, and after the inspection robot component moves to the specified position, the electric automobile is provided with charging service according to the operation of a user through the charging controller of the charging power unit. The invention improves the inspection reliability, the charging efficiency and the field utilization rate of the charging pile.
Description
Technical Field
The invention belongs to the technical field of charging station inspection equipment, and particularly relates to a charging station inspection robot with an emergency charging function and an inspection method.
Background
The charging equipment inspection mode of the electric automobile charging station generally relies on manpower to carry out inspection, the labor intensity of the inspection mode is high, the inspection efficiency is low, the problems of insufficient inspection quality and non-uniform inspection standard are easily caused by adopting manual inspection, the quantity of the charging equipment of the electric automobile is large, the electric automobile is widely dispersed, the manual inspection is very difficult, the equipment inspection is quite unreliable by relying on the sense and experience of inspection personnel, and the personnel can hardly judge the equipment objectively, comprehensively and accurately, so that danger and hidden danger are brought to the safe operation of the equipment. Charging station inspection robot with emergency charging function can improve the reliability of charging equipment operation, reduces operation and maintenance cost, is one of the key directions of intelligent charging station inspection technology development.
The charging station inspection robot is derived from the power equipment inspection robot, and the inspection robot is firstly applied in the power industry in the countries such as the United states, canada and the like in the middle and later 20 th century internationally. By the end of the 80 s, the united states has gradually used an autonomous line inspection robot that can autonomously detect and process line faults and the like. In the early 21 st century, researchers in japan first proposed a scheme of performing substation inspection by using robots instead of manual work, but development was stopped after only a few of substations were tried due to technical and financial problems. The university of holly and Paul in Brazil starts the study of inspection robots in 2008, and successfully develops a substation inspection robot in the same year, and the developed robot operates along a high-altitude walking track. After 2010, new zealand national electric company and new zealand university developed inspection robots suitable for all terrain of transformer substations, the robots were equipped with inspection cameras for transmitting back images and videos of power equipment in the transformer substations, and special sensors were also installed on the robots for emergency obstacle avoidance when the robots were operated.
Until the end of the 20 th century, there has been no research on power equipment robots in China. In 2002, china starts to develop a special study of inspection robots for substations, and establishes an electric robot technical laboratory of a national power grid company, and proposes an 863 plan. In 2009, the national grid company issued a "robust smart grid" development plan indicating that no human operation for domestic grid inspection work was to be achieved in 2020. The national network company discovers more than 1500 potential safety hazards for users from the time of operation of the inspection robot of the transformer substation to the present, related personnel early warn the potential safety hazards in advance through the robot, process the potential safety hazards in time, avoid serious electric power accidents, improve the automation level of electric power production and ensure the safe and reliable operation of the power grid. The intelligent planning guidelines of the national electricity 2015-2020 power grid indicate that in 2018, application test points of the miniaturized and tool-oriented robots are developed, and a robot inspection information management related system is established; by 2020, the robot is comprehensively popularized and miniaturized and tool-shaped in China, and all the robots are provided in a power transformation operation and maintenance team of a company system. With the proliferation of electric automobile charging equipment in recent years at home and abroad, an electric automobile charging equipment inspection robot is developed on the basis of an electric inspection robot, and some charging stations are provided with the inspection robot.
However, the inspection robots on the market at present have very limited functions and are very easily influenced by external factors, so that the detection result is inaccurate; the navigation mode adopted by the inspection robots sold in the market is generally magnetic track navigation, the method leads to the fact that the robots can hardly realize autonomous obstacle avoidance, and when the robots meet the obstacle with larger magnetism, the robots are very easy to damage by the obstacle. Therefore, the current situation of the inspection robot is analyzed, the situation is summarized, the functional positioning and the requirements of the inspection robot are met according to the charging equipment suitable for the charging station, the core technology is added and improved, and the charging station inspection robot with an emergency charging function is designed.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a charging station inspection robot with an emergency charging function and an inspection method, which can efficiently and accurately complete various inspection tasks of charging equipment, automatically deploy an emergency charging component to temporarily replace a fault charging pile to provide charging service for a user during manual maintenance of the fault charging equipment, so as to improve charging efficiency and field utilization rate.
One of the above objects of the present invention is achieved by the following technical solutions:
a charging station inspection robot with an emergency charging function comprises an inspection robot component and an emergency charging component which are in communication connection through a wireless network;
the inspection robot component comprises a power management unit, a sensor unit, a network connection unit, a control unit, a human-computer interface, a motion signal adjusting unit, a servo motor driving unit, a three-phase BLDC motor driving unit, a motion motor and an operation motor;
the power management unit is used for providing reliable power for each unit of the inspection robot component;
the sensor unit is used for collecting the position and the speed of the robot in real time, operating the pressure data applied by the motor arm and the video image, and providing the pressure data and the video image for the control unit;
the control unit is used for analyzing, calculating and processing to judge whether the real-time operation data of the charging pile are normal or not, and calculating to obtain correct movement and operation signals of the robot;
the motion signal adjusting unit is used for adjusting motion and operation signals, generating command signals which respectively control the servo motor driver and the three-phase BLDC motor to drive and meet the EtherCAT protocol, and sending the command signals to the servo motor driving unit and the three-phase BLDC motor driving unit through the EtherCAT bus;
the servo motor driving unit and the three-phase BLDC motor driving unit are used for respectively modulating driving signals for controlling the operation motor and the motion motor according to the received control instructions so as to enable the corresponding motors to operate correctly, wherein the operation motor is used for controlling a mechanical arm of a touch display screen of the touch charging pile, and the motion motor is used for controlling a motion wheel of the robot to walk;
the man-machine interface is used for displaying robot data and man-machine interaction;
the network connection module is used for realizing the access of the cloud platform and the local area network and realizing the interaction and maintenance of remote and local data;
the emergency charging component consists of an information processing and control unit and a charging power unit; the information processing and control unit is used for receiving the wireless instruction of the inspection robot component, controlling the emergency charging component to move to a specified position on the track independently, having an active obstacle avoidance function, and providing charging service for the electric automobile according to the operation of a user through the charging controller of the charging power unit after moving to the specified position.
The sensor unit comprises an inertial module, an electronic compass, a machine vision module, a laser ultrasonic radar, an infrared sensor and a pressure sensor;
the inertial module is used for measuring the angular speed and the acceleration of the robot moving in the three-dimensional space, feeding back the values of the angular speed and the acceleration to the control unit to form closed-loop control, so that the movement of the robot is stable and accurate; the electronic compass is used for ensuring stable posture of the robot in the motion and operation states; the machine vision module is used for identifying the content of the touch screen of the charging pile by robot movement obstacle avoidance and obstacle detouring; the laser ultrasonic radar and the infrared sensor are used for more accurately completing movement obstacle avoidance and obstacle avoidance on the basis of a visual mode by robot ranging; and the pressure sensor is used for feeding back the acting force of the operation probe of the robot to prevent the damage of the touch display screen of the charging pile.
The second object of the present invention is achieved by the following technical scheme:
the inspection method of the charging station inspection robot based on the emergency charging function comprises the steps that the inspection task of the charging station inspection robot is divided into an automatic task and a manual task, and the automatic task is a timing task arranged in a system; the manual task is a manually issued inspection task; the method comprises the following steps:
step 1, a patrol robot part waits for a patrol task;
step 2, triggering a task when the time set by the automatic task is up or a manual task is input through a human-computer interface, and moving the inspection robot part to the position of the detected charging equipment according to the inspection sequence set by the task to detect the position;
step 3, continuously detecting the residual charging piles in the task when the detected charging piles are not abnormal until all the charging piles are detected, recording inspection data if the detected charging piles are not abnormal and the emergency charging parts of the robot are not started, finishing the automatic charging task, otherwise, entering the next step;
step 4, if the charging pile is detected to be abnormal in the automatic task, the inspection robot part judges whether the charging pile is restarted after the charging pile is abnormal, if the charging pile is not restarted, the charging pile is restarted by controlling a cloud switch in the charging pile through wireless encryption communication immediately, then the inspection task is continued, if the charging pile is restarted and the abnormality still exists, whether an emergency charging part of the robot is not started or not is inquired, if the charging pile is not started, the emergency charging part is immediately notified to move to a fault charging pile position and starts to be started, and then a charging pile fault signal is sent out through a network to wait for manually repairing the fault charging pile; if the emergency charging component is in an enabling state, sending a charging pile fault signal through a network to wait for manually repairing the fault charging pile, then carrying out other inspection tasks, and after the repair is completed, issuing a manual task to inspect the charging pile; when the charging pile is in a good and fault-free state and the emergency charging component is started to be in an idle state, the emergency charging component automatically moves back to the original position.
In step 2, the inspection robot part adopts an autonomous obstacle avoidance algorithm of an immune genetic fuzzy neural network to carry out obstacle avoidance movement during inspection.
In step 2, detecting the item includes obtaining charging pile display data, performing touch point pressing operation on a charging pile display screen, and performing infrared temperature measurement on the charging pile.
In step 2, the method for detecting the fuzzy edge of the charging device display data of the detected charging device by adopting the immune genetic RANSAC comprises the following steps:
2.1, the inspection robot component firstly utilizes a SIFT feature extraction core algorithm to select random points of a shot image, and utilizes a genetic random sampling consistency algorithm to perform feature matching on the selected random points, so as to obtain angle and position feature deviation points obtained by converting corresponding matching points;
2.2, obtaining feature points of the image display content by adopting a feature matching algorithm, wherein the feature matching algorithm adopts a genetic random sampling consensus algorithm combining a genetic algorithm and a RANSAC algorithm;
2.3, combining the deblurring by using a tri-spline interpolation method with an immune genetic edge detection method, comparing and screening the characteristic points and the deviation characteristic points, ensuring the precision of the characteristic points and the deviation characteristic points, and removing the blurred edges caused by shadows and reflection in the image; obtaining a building module by acquiring data points and removing abnormal data points;
and 2.4, carrying out morphological edge detection on the sub-graph modeling modules by utilizing a morphological self-adaptive structural element generation algorithm based on an immune genetic algorithm, combining the sub-graph modeling module grouping results, and finally realizing image target boundary extraction.
In the step 2, a touch screen mechanical arm is adopted for performing touch point pressing operation on a charging pile display screen, and the touch screen mechanical arm is controlled by adopting an adaptive neural network algorithm based on extreme learning; in the walking process of the inspection robot part, the touch screen mechanical arm is hidden in the robot; when the touch screen operation is needed, the touch screen mechanical arm touches the charging pile screen through rotation and telescopic movement and through the flexible contact; the touch screen mechanical arm is internally provided with a touch induction sensor, and when a charging pile screen is touched, the touch induction sensor generates signals, so that timely retraction control of the touch screen mechanical arm is realized.
In addition, in the step 4, the emergency charging component adopts a magnetic driving flexible rail in a moving mode.
The invention has the advantages and positive effects that:
1. when the inspection robot detects that the inspected charging pile has a fault and can not continuously provide charging service and needs manual maintenance, the emergency stop button for stopping work is immediately pressed, and the emergency charging component is automatically deployed to temporarily replace the fault charging pile to provide charging service for users, so that the charging efficiency and the field utilization rate are improved.
2. Aiming at the core problems of the traditional and current edge detection algorithms applied to the actual inspection scene, a set of fuzzy edge detection technology is designed and applied in an image recognition system; the system adopts a method combining immune inheritance, cubic spline interpolation and random sampling consistency, is used for detecting the fuzzy edge of the display content of the charging pile display screen, improves the identification processing efficiency and the detection precision, and ensures the reliability of the inspection system.
3. The invention processes the sensor data by using an immune genetic fuzzy neural network algorithm, and solves the problem of poor autonomy of the sensor by using the fuzzy neural network with an autonomous learning function. The application of the algorithm effectively solves the problems that the charging station inspection robot with the emergency charging function has long obstacle avoidance time, unreasonable avoidance mode and the like in the inspection process of charging equipment, and achieves the function of quickly and timely completing the inspection task by avoiding and avoiding the obstacle when the equipment is required to be used.
4. According to the invention, the self-adaptive neural network algorithm based on extreme learning is used for simulating the manual operation of the charging pile touch screen, so that the state of the charging pile is further detected, and the problem of touch accuracy reduction caused by the conditions of vibration, shake and the like brought by the movement or operation of the robot is successfully solved. Thereby further improving the operability and the safety of the device
In summary, the charging station inspection robot with the emergency charging function is based on an Artificial Intelligence (AI) theory, combines technologies such as computer vision, motion control and the like, particularly applies a method combining immunogenetics, cubic spline interpolation and random sampling consistency to accurately identify various data displayed by charging equipment, applies an immunogenetics fuzzy neural network algorithm and applies an adaptive neural network algorithm based on extreme learning, so that various inspection tasks of the charging equipment can be completed efficiently and accurately by perfectly winding a barrier and avoiding the barrier in the running process and perfectly operating a touch display screen of the charging equipment, and emergency charging components are deployed automatically to temporarily replace a fault charging pile to provide charging service for users during manual maintenance of the fault charging equipment, thereby improving the charging efficiency and the field utilization rate.
Drawings
FIG. 1 is a system diagram of a charging pile inspection robot with an emergency charging function;
FIG. 2 is a flow chart of the charging pile inspection robot with the emergency charging function;
FIG. 3 is a schematic diagram of an electromagnetically driven flexible track system employed in the present invention;
FIG. 4 is a flow chart of a fuzzy algorithm of the immune genetic RANSAC employed in the present invention;
FIG. 5 is an autonomous motion obstacle avoidance reference map based on an immune genetic fuzzy neural network employed in the present invention;
FIG. 6 is a flow chart of the operation of a touch display screen based on an extreme learning machine adaptive neural network employed in the present invention.
Detailed Description
The structure of the present invention will be further described by way of examples with reference to the accompanying drawings. It should be noted that the present embodiments are illustrative and not restrictive.
As shown in fig. 1, the charging station inspection robot with the emergency charging function is composed of two large parts, namely an inspection robot part and an emergency charging part, which form a system through a wireless network. The inspection robot component comprises a power management unit, a sensor unit, a network connection unit, a control unit, a human-computer interface, a motion signal adjusting unit, a servo motor driving unit, a three-phase BLDC motor driving unit, a motion motor and an operation motor.
The power management unit provides a reliable power supply for each unit of the inspection robot component. The sensor unit collects important data such as position and speed of the robot, pressure image applied by an arm of an operation motor and the like, and video images are provided for the control unit, the control unit analyzes, calculates and processes whether real-time operation data of the charging pile are normal or not and obtains correct motion and operation signals of the robot, the motion and operation signals generate command signals meeting EtherCAT protocol, which can respectively control a servo motor driver and a three-phase BLDC motor driver, through an EtherCAT bus, and send the command signals to the servo motor driver and the three-phase BLDC motor driver, the servo motor driver and the three-phase BLDC motor driver respectively modulate driving signals for controlling the operation motor and the motion motor according to the received control commands to enable the motor to operate correctly, wherein the operation motor is used for controlling a mechanical arm of a touch display screen of the touch charging pile, and the motion motor is used for controlling motion wheels of the robot to walk. The automatic routing and obstacle detouring robot part is controlled by the accurate sensor data, the accurate control unit algorithm and the real-time motor, so that the automatic routing and obstacle detouring function of the charging pile is realized, and the charging pile touch screen and the display data thereof are accurately operated and identified.
The emergency charging component mainly comprises an information processing and control unit and a charging power unit. The information processing and control unit receives a wireless instruction of the inspection robot component, automatically moves to a designated position on a track, has an active obstacle avoidance function, and then starts a charging controller of the charging power unit to provide charging service for the electric automobile according to the operation of a user.
The charging station inspection robot with the emergency charging function, which is composed of the inspection robot component and the emergency charging component, can not only finish inspection of charging equipment, but also automatically deploy the emergency charging component according to whether the charging pile equipment fails, thereby improving inspection efficiency and accuracy and improving charging experience of users.
The work flow of the charging station inspection robot with the emergency charging function is as follows:
the charging station inspection robot with the emergency charging function is divided into an automatic task and a manual task, wherein the automatic task is a timing task arranged in the system. The manual task is a manually issued inspection task. Firstly, waiting for an inspection task, if the time reaches to trigger the automatic task, moving the inspection robot part to the position of the detected charging equipment according to the inspection sequence set by the automatic task to detect the automatic task, wherein the detection items mainly comprise charging equipment display data, a charging pile touch display screen function, infrared temperature measurement and the like, continuously detecting the residual charging piles in the automatic task when the detected charging piles are not abnormal until all the detection is finished, and recording inspection data if no abnormality exists and an emergency charging part of the robot is not started, so as to finish the automatic charging task. If the charging pile is detected to be abnormal in the automatic task, the inspection robot component judges whether the charging pile is restarted after the charging pile is abnormal (most of the charging pile is not abnormal and can be recovered to be normal through restarting after power failure), if the charging pile is not restarted, the charging pile is restarted by controlling a cloud switch in the charging pile through wireless encryption communication immediately, then the inspection task is continued, if the charging pile is restarted and the abnormality still exists, whether an emergency charging component of the robot is not started is inquired, if the charging pile is not started, the emergency charging component is immediately informed to move to the position of the fault charging pile and starts to be started, and then a charging pile fault signal is sent through a network to wait for manually repairing the fault charging pile. If the emergency charging component is in an enabling state, a charging pile fault signal is sent out through a network to wait for manual repair of the fault charging pile, then other automatic inspection tasks are carried out, and a manual task can be issued to inspect the charging pile after repair is completed. The manual task flow of the charging station inspection robot with the emergency charging function is similar to the automatic flow, the robot moves to the position of the manually appointed charging pile, the data and the functions of the manually appointed charging pile are detected, the abnormal situation is found, the charging pile is restarted according to the restarting condition and the state of the emergency charging component, the emergency charging component is started, the manual repairing fault charging pile is notified, and the like, and the manual task is completely completed, such as the inspection data is recorded without abnormality, so that the manual charging task is completed. The recharging device moves back to the original position by itself when the recharging device is in a good state and the recharging device is enabled in an idle state.
The charging station inspection robot with the emergency charging function has the functions of infrared temperature measurement, screen content identification, operation touch screen, video monitoring, environment monitoring and the like, can carry out the inspection operation of charging station equipment in a full-automatic or manual mode, can accurately provide relevant data of the running condition of the charging station equipment, reduces the influence of various factors under different environments when the equipment is used for detection, and enhances the fault diagnosis capability, the image identification capability and the autonomous obstacle avoidance and obstacle avoidance capability of the robot. And when the charging equipment is manually maintained, the rail type emergency charging component is independently deployed to provide charging service for a user when the charging service cannot be provided, so that the safety operation reliability of the charging equipment is improved, and the practicability of the inspection equipment is practically improved.
1. Electromagnetically driven flexible track system
The emergency charging part movement mode of the charging station inspection robot with the emergency charging function adopts a magnetic drive flexible track, and is an orbital movement technology based on the principle of a long stator linear motor. The permanent magnet rotor is composed of a control system, a bearing guide rail, a long stator module (motor module) embedded with a driving module and an electromagnetic coil, and a permanent magnet rotor slider provided with a guide and support pulley. And the power output of the driving module can enable the stator coil to generate a group of alternating magnetic fields on the surface of the track, and the permanent magnet mover on the track is driven to move under the control of the control system, so that the autonomous movement of the emergency charging component on the guide rail is realized.
The device adopts the electromagnetism to drive flexible track system and can make its emergent charging member follow the guide rail circulation motion of installing on motor module under the traction of passive active cell to every active cell independent control is free to move on the track, provides convenience for this charging station with emergent charging function patrols and examines the robot and be equipped with a plurality of emergent charging members. The electromagnetic driving technology breaks through the bottleneck of the traditional mechanical track, changes rigidity into softness, can meet the personalized customization of inspection of different charging stations, greatly improves the efficiency of deploying emergency charging components, and provides better charging experience for users.
2. Fuzzy edge detection based on immune genetic RANSAC
Aiming at the problem that the charging station environment light is complex and unstable, the actual display content of the charging pile is caused to have fuzzy edge detection precision, a set of fuzzy edge detection technology is designed and applied in the image recognition system, the recognition and detection of fuzzy edges in a charging station scene are realized, the fuzzy edge detection capability of detected equipment, instruments and a screen is improved, and the recognition speed and precision of the charging station inspection robot with an emergency charging function are improved.
Because of the variation of shooting angles and light rays, the shadow overlapping deviation of the object in the display content of the table is often caused, so that the precision and performance in deblurring and edge detection are affected. The robot firstly performs random point selection on a shot image, uses SIFT feature stability, uses SIFT as a feature extraction core algorithm, and uses a genetic random sampling consistency technology as a feature matching technology, so as to obtain angle and position feature deviation points obtained by conversion of corresponding matching points.
And then, the image is used for obtaining characteristic points of display contents by using a genetic random sampling consistent technology combining a genetic algorithm and a RANSAC as a characteristic matching technology, and the technology optimizes the loop calculation of the RANSAC in iteration. Because the feature points near the feature points of the target match still have a larger probability of matching, a new sample group is generated on a subset which is matched by a genetic algorithm, and single extraction samples of the new sample group are generated and screened. Meanwhile, the rapidness and accuracy of the system matching are improved, and the guarantee is provided for the application of the system.
And then, combining the three spline interpolation deblurring and the immune genetic edge detection technology, comparing and screening the characteristic points and the deviation characteristic points, ensuring the precision of the characteristic points and the deviation characteristic points, and removing the blurred edge caused by shadow and reflection in the image. And obtaining the building module by acquiring data points and removing abnormal data points. For an image with over-bright or over-dark illumination in a charging station scene, a region with zero continuity appears in a gray histogram of the image after gray stretching, if the number of pixels corresponding to gray values in one threshold step is 0, two adjacent data points in a modeling group are equal to each other, so that the selection of a final optimal threshold value is affected, and therefore the robustness of the algorithm to illumination is increased by eliminating abnormal data points in the algorithm. The effects of removing shadows and reflecting light are achieved.
Finally, morphological self-adaptive structural element generation algorithm based on immune genetic algorithm is utilized, morphological edge detection can be carried out on the subgraph by each structural element, then segmentation results of each subgraph are combined, and finally the image target boundary extraction function is achieved.
In summary, the immune genetic edge detection technology applied by the equipment aims at the problem of blurred edges caused by motion shaking and recognition angles, and adopts the SIFT algorithm to perform feature detection, matching and correction on the shot image before recognition, so that the influence of the two types of blur is eliminated; aiming at the core problem of detecting the shadow edge of the pointer in practical application, the immune tri-spline deblurring edge detection technology is designed and applied, and the fuzzy problem caused by shadow and reflection is eliminated by combining the tri-spline interpolation deblurring with an immune genetic edge detection core algorithm, so that the reading precision and accuracy are ensured.
3. Autonomous obstacle avoidance based on immune genetic fuzzy neural network
The charging station inspection robot with the emergency charging function collects external environment and obstacle information through a plurality of ultrasonic waves and laser sensors carried on equipment, the system is developed and applied to process data transmitted back by the sensors through an immune genetic fuzzy neural network algorithm, and the problem of poor autonomy of the ultrasonic sensors is solved through the fuzzy neural network with an autonomous learning function. The immune algorithm principle, the fuzzy logic and the genetic algorithm idea are combined, and the obstacle avoidance fuzzy controller designed for most inspection robots does not analyze or recognize the functions of intersection and variation in the dynamic process, or only takes the change of fitness as the standard for adjusting the intersection and variation rate, so that the problems of actual change of population diversity and the requirement of self-adaptive adjustment in the evolution process are not considered. Aiming at the problems, the system adopts the obstacle avoidance fuzzy controller which is suitable for binary and real number coding and comprehensively considers the adaptability change and population distribution.
The improved obstacle avoidance fuzzy control algorithm can enable the inspection diagnosis and control robot to be timely adjusted according to the running process and the requirement on diversity, and the obstacle avoidance algorithm is guaranteed to always run in an optimal state and to be globally converged. The system effectively solves the problems that the patrol diagnosis and control robot has long obstacle avoidance time and unreasonable avoidance mode in the patrol process of the charging equipment, realizes that the patrol diagnosis and control robot can automatically stop patrol to avoid and bypass when a user needs to use equipment, does not need to reload patrol tasks after the user or the obstacle leaves an alarm range, not only further enhances the rationality of overall motion attitude control of the patrol robot, but also improves the patrol efficiency.
4. Touch display screen operating mechanism based on extreme learning machine self-adaptive neural network
The charging station inspection robot with the emergency charging function utilizes the adaptive neural network algorithm based on extreme learning to operate the touch screen mechanical arm, and successfully solves the problem that the touch precision is reduced due to the conditions of vibration, shake and the like caused by the movement or operation of the robot. And the touch mechanical device of the inspection diagnosis and control robot equipment is hidden inside the robot in the walking process. When touch screen operation is required, the touch device touches the charging pile screen through rotation and telescopic movement. The touch device is internally provided with the contact induction sensor, when the screen of the charging pile is touched, the contact induction sensor generates signals, the touch device is retracted in time, and the probe is flexible, so that the probe is not damaged or plastically deformed even if the robot advances a certain distance after contacting an object, and meanwhile, the touch screen operated by the robot is not damaged, deformed, vibrated or moved. Therefore, the touch point pressing operation can be rapidly and effectively performed on the premise of not affecting the inspection speed.
Because of factors such as errors in the parameters of the robot itself, observed noise, unmodeled dynamics and uncertainty external disturbances exist in the rigid robot system. Therefore, the system provides a self-adaptive nerve control algorithm based on an Extreme Learning Machine (ELM) aiming at a rigid touch mechanical arm system of the inspection diagnosis and control robot. The algorithm is characterized in that hidden layer nodes and node parameters of a single hidden layer feedforward neural network (SLFN) are randomly selected, and only the output weight of the network is regulated in the learning process, so that compared with the SLFN adopting a gradient descent algorithm to regulate all network weight parameters, the ELM improves the popularization of the SLFN and has extremely high learning speed. The operation touch display screen function of the inspection robot is realized, so that the operability and reliability of the charging station inspection robot with the emergency charging function are further improved.
In summary, the charging station inspection robot with the emergency charging function has the characteristics of accurate observation, accurate movement, stable control and complete functions, and is a multifunctional robot which can completely replace manual inspection charging station charging equipment and is more efficient and safer.
Although the embodiments of the present invention and the accompanying drawings have been disclosed for illustrative purposes, those skilled in the art will appreciate that: various substitutions, changes and modifications are possible without departing from the spirit of the invention and the appended claims, and therefore the scope of the invention is not limited to the embodiments and the disclosure of the drawings.
Claims (8)
1. Charging station inspection robot with emergent function of charging, its characterized in that: the inspection robot comprises an inspection robot component and an emergency charging component, wherein the inspection robot component and the emergency charging component are in communication connection through a wireless network;
the inspection robot component comprises a power management unit, a sensor unit, a network connection unit, a control unit, a human-computer interface, a motion signal adjusting unit, a servo motor driving unit, a three-phase BLDC motor driving unit, a motion motor and an operation motor;
the power management unit is used for providing reliable power for each unit of the inspection robot component;
the sensor unit is used for collecting the position and the speed of the robot in real time, operating the pressure data applied by the motor arm and the video image, and providing the pressure data and the video image for the control unit;
the control unit is used for analyzing, calculating and processing to judge whether the real-time operation data of the charging pile are normal or not, and calculating to obtain correct movement and operation signals of the robot;
the motion signal adjusting unit is used for adjusting motion and operation signals, generating command signals which respectively control the servo motor driver and the three-phase BLDC motor to drive and meet the EtherCAT protocol, and sending the command signals to the servo motor driving unit and the three-phase BLDC motor driving unit through the EtherCAT bus;
the servo motor driving unit and the three-phase BLDC motor driving unit are used for respectively modulating driving signals for controlling the operation motor and the motion motor according to the received control instructions so as to enable the corresponding motors to operate correctly, wherein the operation motor is used for controlling a mechanical arm of a touch display screen of the touch charging pile, and the motion motor is used for controlling a motion wheel of the robot to walk;
the man-machine interface is used for displaying robot data and man-machine interaction;
the network connection module is used for realizing the access of the cloud platform and the local area network and realizing the interaction and maintenance of remote and local data;
the emergency charging component consists of an information processing and control unit and a charging power unit; the information processing and control unit is used for receiving the wireless instruction of the inspection robot component, controlling the emergency charging component to move to a specified position on the track independently, having an active obstacle avoidance function, and providing charging service for the electric automobile according to the operation of a user through the charging controller of the charging power unit after moving to the specified position.
2. The charging station inspection robot with emergency charging function according to claim 1, wherein: the sensor unit comprises an inertia module, an electronic compass, a machine vision module, a laser ultrasonic radar, an infrared sensor and a pressure sensor;
the inertial module is used for measuring the angular speed and the acceleration of the robot moving in the three-dimensional space, feeding back the values of the angular speed and the acceleration to the control unit to form closed-loop control, so that the movement of the robot is stable and accurate; the electronic compass is used for ensuring stable posture of the robot in the motion and operation states; the machine vision module is used for identifying the content of the touch screen of the charging pile by robot movement obstacle avoidance and obstacle detouring; the laser ultrasonic radar and the infrared sensor are used for more accurately completing movement obstacle avoidance and obstacle avoidance on the basis of a visual mode by robot ranging; the pressure sensor is used for feeding back acting force of the robot operation probe and preventing the touch display screen of the charging pile from being damaged.
3. A patrol method of the charging station patrol robot with an emergency charging function based on the claims 1 and 2, characterized in that: the inspection task of the charging station inspection robot is divided into an automatic task and a manual task, wherein the automatic task is a timing task arranged in a system; the manual task is a manually issued inspection task; the method comprises the following steps:
step 1, a patrol robot part waits for a patrol task;
step 2, triggering a task when the time set by the automatic task is up or a manual task is input through a human-computer interface, and moving the inspection robot part to the position of the detected charging equipment according to the inspection sequence set by the task to detect the position;
step 3, continuously detecting the residual charging piles in the task when the detected charging piles are not abnormal until all the charging piles are detected, recording inspection data if the detected charging piles are not abnormal and the emergency charging equipment of the robot is not started, finishing the automatic charging task, otherwise, entering the next step;
step 4, if the charging pile is detected to be abnormal in the automatic task, the inspection robot component judges whether the charging pile is restarted after the charging pile is abnormal, if the charging pile is not restarted, the charging pile is restarted by controlling a cloud switch in the charging pile through wireless encryption communication immediately, then the inspection task is continued, if the charging pile is restarted and the abnormality still exists, whether an emergency charging component of the robot is not started or not is inquired, if the charging pile is not started, the emergency charging component is immediately informed to move to a fault charging pile position and start to be started, and then a charging pile fault signal is sent through a network to wait for manually repairing the fault charging pile; if the emergency charging component is in an enabling state, sending a charging pile fault signal through a network to wait for manually repairing the fault charging pile, then carrying out other inspection tasks, and after the repair is completed, issuing a manual task to inspect the charging pile; when the charging pile is in a good and fault-free state and the emergency charging component is started to be in an idle state, the emergency charging component automatically moves back to the original position.
4. A patrol method of the charging station patrol robot with an emergency charging function according to claim 3 based on claims 1 and 2, characterized in that: in the step 2, the inspection robot part adopts an autonomous obstacle avoidance algorithm of an immune genetic fuzzy neural network to carry out obstacle avoidance movement during inspection.
5. A charging station inspection robot with emergency charging function according to claim 3, wherein: in the step 2, detecting the item comprises obtaining charging pile display data, performing touch point pressing operation on a charging pile display screen, and performing infrared temperature measurement on the charging pile.
6. A patrol method of the charging station patrol robot with an emergency charging function according to claim 3 based on claims 1 and 2, characterized in that: in step 2, the fuzzy edge detection method for acquiring the display data of the charging pile touch screen by adopting the immune genetic RANSAC comprises the following steps:
6.1, the inspection robot component firstly utilizes a SIFT feature extraction core algorithm to select random points of a shot image, and utilizes a genetic random sampling consistency algorithm to perform feature matching on the selected random points, so as to obtain angle and position feature deviation points obtained by converting corresponding matching points;
6.2, obtaining characteristic points of the image display content by adopting a characteristic matching algorithm, wherein the characteristic matching algorithm adopts a genetic random sampling consensus algorithm combining a genetic algorithm and a RANSAC algorithm;
6.3, combining the deblurring by using a tri-spline interpolation method with an immune genetic edge detection method, comparing and screening the characteristic points and the deviation characteristic points, ensuring the precision of the characteristic points and the deviation characteristic points, and removing the blurred edges caused by shadows and reflection in the image; obtaining a building module by acquiring data points and removing abnormal data points;
and 6.4, carrying out morphological edge detection on the sub-graph modeling modules by utilizing a morphological self-adaptive structural element generation algorithm based on an immune genetic algorithm, combining the sub-graph modeling module grouping results, and finally realizing image target boundary extraction.
7. A patrol method of the charging station patrol robot with an emergency charging function according to claim 3 based on claims 1 and 2, characterized in that: in the step 2, a touch screen mechanical arm is adopted for carrying out touch point pressing operation on a charging pile display screen, and the touch screen mechanical arm is controlled by adopting an adaptive neural network algorithm based on extreme learning; in the walking process of the inspection robot part, the touch screen mechanical arm is hidden in the robot; when the touch screen operation is needed, the touch screen mechanical arm touches the charging pile screen through rotation and telescopic movement and through the flexible contact; the touch screen mechanical arm is internally provided with a touch induction sensor, and when a charging pile screen is touched, the touch induction sensor generates signals, so that timely retraction control of the touch screen mechanical arm is realized.
8. A patrol method of the charging station patrol robot with an emergency charging function according to claim 3 based on claims 1 and 2, characterized in that: in step 4, the emergency charging component adopts a magnetic driving flexible track in a movement mode.
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