Nothing Special   »   [go: up one dir, main page]

CN114179093A - Transformer substation inspection robot system and obstacle avoidance method thereof - Google Patents

Transformer substation inspection robot system and obstacle avoidance method thereof Download PDF

Info

Publication number
CN114179093A
CN114179093A CN202111664013.5A CN202111664013A CN114179093A CN 114179093 A CN114179093 A CN 114179093A CN 202111664013 A CN202111664013 A CN 202111664013A CN 114179093 A CN114179093 A CN 114179093A
Authority
CN
China
Prior art keywords
inspection
field intensity
inspection trolley
trolley
image
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202111664013.5A
Other languages
Chinese (zh)
Other versions
CN114179093B (en
Inventor
陈星筑
左益芳
王龙翔
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xintong Institute Innovation Center For Internet Of Vehicles Chengdu Co ltd
Original Assignee
Xintong Institute Innovation Center For Internet Of Vehicles Chengdu Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Xintong Institute Innovation Center For Internet Of Vehicles Chengdu Co ltd filed Critical Xintong Institute Innovation Center For Internet Of Vehicles Chengdu Co ltd
Priority to CN202111664013.5A priority Critical patent/CN114179093B/en
Publication of CN114179093A publication Critical patent/CN114179093A/en
Application granted granted Critical
Publication of CN114179093B publication Critical patent/CN114179093B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J11/00Manipulators not otherwise provided for
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J19/00Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
    • B25J19/02Sensing devices
    • B25J19/027Electromagnetic sensing devices
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J19/00Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
    • B25J19/02Sensing devices
    • B25J19/04Viewing devices
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00Programme-controlled manipulators
    • B25J9/16Programme controls
    • B25J9/1602Programme controls characterised by the control system, structure, architecture
    • B25J9/161Hardware, e.g. neural networks, fuzzy logic, interfaces, processor
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00Programme-controlled manipulators
    • B25J9/16Programme controls
    • B25J9/1656Programme controls characterised by programming, planning systems for manipulators
    • B25J9/1661Programme controls characterised by programming, planning systems for manipulators characterised by task planning, object-oriented languages
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B25HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
    • B25JMANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
    • B25J9/00Programme-controlled manipulators
    • B25J9/16Programme controls
    • B25J9/1656Programme controls characterised by programming, planning systems for manipulators
    • B25J9/1664Programme controls characterised by programming, planning systems for manipulators characterised by motion, path, trajectory planning

Landscapes

  • Engineering & Computer Science (AREA)
  • Robotics (AREA)
  • Mechanical Engineering (AREA)
  • Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Electromagnetism (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Fuzzy Systems (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Investigating Or Analyzing Materials By The Use Of Magnetic Means (AREA)

Abstract

The invention discloses a transformer substation inspection robot system, which comprises an inspection trolley, a field intensity sensor for detecting the electric field or the magnetic field intensity in real time, an image collector for acquiring a real-time image, and a control center for analyzing the real-time pose of the inspection trolley and planning a path for the inspection trolley; the field intensity sensor and the image sensor are both carried on the inspection trolley and connected with the inspection trolley; the inspection trolley, the field intensity sensor and the image sensor are all interactive with the control center. Compared with the prior art, the inspection system and the inspection method provided by the invention are adapted to the specific conditions of more components in the transformer substation and electric field or magnetic field interference around power equipment by means of combining image processing and field intensity detection, provide safe, effective and multi-dimensional decision basis for obstacle avoidance of the inspection trolley, and ensure that the unmanned automatic inspection process of the inspection trolley is smoothly carried out.

Description

Transformer substation inspection robot system and obstacle avoidance method thereof
Technical Field
The invention belongs to the technical field of electric power detection, and particularly relates to a substation-oriented automatic inspection robot for electric power equipment.
Background
The transformer substation is internally provided with various power equipment, and a power department needs to routinely patrol the transformer substation according to the schedule and check the operation condition of each power equipment so as to ensure that each equipment works normally and find potential safety hazards in time.
Under the existing power system, the power department mainly depends on operation and maintenance personnel to complete routine inspection work of the transformer substation in a manual inspection mode. However, when the inspection, recording, maintenance and other operations of the electrical equipment in the substation are implemented in a manual inspection mode, due to the factors of large workload of field operation, low manual inspection efficiency, high requirement on human resources, large gap between professional personnel, easy influence of inspection results on the quality of work of an inspector and the like, it is difficult for the manual inspection to obtain an ideal routine inspection effect of the electrical equipment.
In the prior art, a technical scheme for polling electric power equipment in a transformer substation by using a robot exists, and by taking a Chinese patent application document with the application number of CN201110216728.4 as an example, an intelligent robot polling system and a polling method for the transformer substation are provided in the patent application document, wherein the polling system comprises a monitoring center, and the monitoring center is connected with the intelligent polling system for the station-level robot of at least one transformer substation through a network; each station level robot intelligence system of patrolling and examining includes at least one basic station, still is equipped with environmental information collection subsystem and installs the supplementary monitoring subsystem of the fixed point that each needs supervisory equipment department in the transformer substation simultaneously in the transformer substation, and the intelligence is patrolled and examined and is equipped with the intelligence and patrolled and examined the robot next computer on the robot, and the intelligence is patrolled and examined the robot next computer and still is connected with detecting element, and detecting element includes infrared detecting element and ultraviolet detecting element, and ultraviolet detecting element contains ultraviolet video server and ultraviolet detection device.
Since the power equipment arranged in the substation usually bears a large power, it will inevitably generate a corresponding electric field or magnetic field in its surrounding space during normal operation, and the larger the current flowing through the power equipment, the closer to the equipment, the stronger the electric field or magnetic field, therefore, for the intelligent robot provided in the patent application document, when the intelligent robot is applied to a specific transformer substation, if the robot is too close to the power equipment, not only the communication between the robot and the upper computer can not be normally connected under the interference of an electric field or a magnetic field, the internal electronics will also be difficult to operate properly under the influence of an electric or magnetic field, but according to the above-mentioned patent application, the detection unit only comprises an infrared detection unit and an ultraviolet detection unit, and does not have the capability of detecting an electric field or a magnetic field and further avoiding the electric field or the magnetic field from being interfered.
In the robot system for automatic inspection of the existing application and transformer substation, for technical personnel in the field, how to improve the robot so that when the robot is put into a specific transformer substation to execute an automatic inspection task of power equipment, physical obstacles can be avoided independently, collision can be avoided, meanwhile, the influence of an electric field or a magnetic field around each power equipment in the transformer substation on the communication of the robot and the work of the robot can be avoided, the relation among the robot, the power equipment in the transformer substation and the internal environment of the transformer substation is well processed, and the technical problem which needs to be solved urgently by the technical personnel in the field is solved.
Disclosure of Invention
In order to solve the problems, the invention aims to provide a transformer substation inspection robot system, a field intensity sensor and an image collector are parallel, the field intensity sensor is used for acquiring the distribution situation of an electric field or a magnetic field generated by power equipment in the environment of a transformer substation, the image collector is used for acquiring the distribution situation of tangible components in the environment of the transformer substation, two situations are fused to make an obstacle avoidance decision, the special situation that the distribution situation of the electric field or the magnetic field in the environment of the transformer substation is uncertain due to the fact that a plurality of power equipment are in a scene of the transformer substation and the load conditions of different power equipment are different is fully adapted, and a safer and more reliable system scheme is provided for effectively making obstacle avoidance measures, avoiding tangible component obstacles and intangible electromagnetic obstacles when a robot is applied to the environment of the transformer substation for inspection work.
The invention also aims to provide an obstacle avoidance method of the transformer substation inspection robot system, the method is based on the transformer substation inspection robot system, the information obtained by the field intensity sensor and the image sensor is processed, the distribution condition of an electric field or a magnetic field in the environment of the transformer substation is obtained, and after the distribution condition of a tangible component in the environment of the transformer substation is obtained by the image sensor, the distribution condition is used as an obstacle avoidance basis, and the two bases are combined to make a more comprehensive and more stable obstacle avoidance plan for the inspection trolley.
In order to achieve the purpose, the technical scheme of the invention is as follows:
the utility model provides a transformer substation patrols and examines robot system, this robot including:
the system comprises a carrying platform, an inspection trolley, a field intensity sensor, an image collector and a control center, wherein the inspection trolley is used for carrying other components and running along the ground to inspect the environment of a transformer substation;
the field intensity sensor and the image sensor are both carried on the inspection trolley and connected with the inspection trolley; the inspection trolley, the field intensity sensor and the image sensor are all interactive with the control center.
The invention also provides a method for inspecting the transformer substation inspection robot system, which is based on the transformer substation inspection robot system and specifically comprises the following steps:
s1: the field intensity sensor detects the electric field or the magnetic field intensity of the current position of the inspection trolley in real time;
s2: the image collector shoots and records an image in the current visual field of the inspection trolley;
s3: the control center fuses real-time electric field or magnetic field intensity information and real-time image information, barrier detection is carried out on the current environment, and the control center plans a routing inspection path for the routing inspection trolley according to the barrier detection result.
When the inspection trolley runs in a specific transformer substation environment, on one hand, tangible obstacles in the environment need to be avoided, and the tangible obstacles specifically comprise building components, electrical equipment components and other components which are in the transformer substation and can possibly collide with the inspection trolley, on the other hand, in consideration of the particularity of the transformer substation, electrical equipment which needs to bear large power is often arranged in the inspection trolley, and in the normal working process, an electric field or a magnetic field is inevitably generated in the surrounding space environment of the inspection trolley, and the electric field or the magnetic field is often radiated outwards by taking the corresponding electrical equipment as a field source center, if the inspection trolley mistakenly enters the electric field or the magnetic field range of the inspection trolley, not only is the communication between the inspection trolley and a control center or other equipment interfered, but also devices in the inspection trolley possibly are influenced by the electric field or the magnetic field, so that the inspection trolley cannot normally work; furthermore, for a transformer substation, a plurality of power transmission lines in multiple directions are often pulled in the environment, these transmission lines usually carry a large current or a high voltage, and also generate an electric field or a magnetic field in the surrounding space, but if an image collector is used singly to record images, due to the reasons of too high height of the transmission line, smaller volume of the transmission line compared with other electric equipment, influence on imaging definition by external specific weather and the like, which is easily mistaken for accidental error filtering in the image processing process, therefore, the technical proposal provided by the application, after the image collector and the field intensity sensor are used for parallel and the image processing result and the field intensity detection result are fused, the method for providing obstacle avoidance basis for the inspection trolley together enables the inspection trolley to be better adapted to the environment of the transformer substation, and facilitates unmanned and automatic inspection of the transformer substation.
Wherein, S1 specifically is:
s11: establishing a calculation model of the distance between the output electric signal and the external electric power equipment according to the type and specific parameters of the set field intensity sensor;
s12: and acquiring an electric signal output by the field intensity sensor, and transmitting the electric signal to a control center through amplification, filtering and A/D conversion. Wherein, further, S11 specifically is:
s111: establishing a coordinate system according to the position of the current inspection trolley, and specifying a field intensity zero point;
s112: according to the condition of actual power equipment arranged in a transformer substation, regarding each power equipment as a field source, and marking each field source in a coordinate system;
s113: establishing an equation set according to the interaction between each field source and a field intensity sensor carried on the inspection trolley, solving the equation set to obtain the actual charge condition of each field source, and carrying out precision check on the solution of the equation set;
s114: and calculating to obtain the information of the electric field or the magnetic field intensity of the current position where the routing inspection trolley is located according to the actual voltage or current condition of the actual power equipment arranged in the transformer substation and in combination with the actual charge condition of each field source.
When the sensor is applied to a specific automatic substation inspection environment, technicians can select a capacitive field intensity sensor or an inductive field intensity sensor to be applied according to specific requirements.
The capacitive field intensity sensor can be used for detecting the electric field intensity in the environment, technicians select the capacitive field intensity sensor with appropriate parameters, a rectangular coordinate system is established based on the real-time position of the inspection trolley, each electric power device in the environment is equivalent to a field source and is mapped into the rectangular coordinate system, an equation set is established according to the interaction of each field source and the capacitive field intensity sensor, the magnetic field intensity of the inspection trolley at the current position is obtained by solving the equation set and calculating, and the mapping relation of the distance between the inspection trolley and the electric power device is mastered; the inductive field intensity sensor is similar to the inductive field intensity sensor, the inductive field intensity sensor with suitable parameters can be used for detecting the magnetic field intensity in the environment, and after the magnetic field intensity signal output by the inductive field intensity sensor is conditioned by amplification, filtering and the like, the conditioned magnetic field intensity signal is provided for the control center through A/D conversion, so that the control center can conveniently analyze and process the conditioned magnetic field intensity signal.
Further, S3 specifically includes:
s31: processing the electric field or magnetic field intensity information input by the field intensity sensor, and mapping the information into the distance information between the current inspection trolley and the corresponding power equipment;
s32: processing image information input by an image sensor, analyzing the surrounding environment of the current position of the inspection trolley, and acquiring depth information of a target object in the surrounding environment;
s33: and integrating the distance information between the current inspection trolley and the corresponding power equipment and the target object information of the surrounding environment, and judging whether the current inspection trolley needs to take obstacle avoidance measures. Further, S32 specifically includes:
s321: identifying whether a target object exists in front of the current inspection trolley or not according to image information input by the image sensor; if so, jumping to S322; otherwise, repeating S321;
s322: and calculating to obtain the pose information of the current inspection trolley, and calculating the depth information of the target object based on the image information input by the image sensor.
Further, S33 specifically includes:
s331: respectively setting a field intensity threshold value and an obstacle threshold value;
s332: comparing the depth information of the target object with an obstacle threshold, and skipping S333 if the depth of the target object is greater than the obstacle threshold; otherwise, skipping to S335;
s333: comparing the electric field or magnetic field intensity information of the current position of the inspection trolley input by the field intensity sensor with a field intensity threshold, and skipping S334 if the electric field or magnetic field intensity of the current position of the inspection trolley is smaller than the field intensity threshold; otherwise, skipping to S335;
s334: judging that no obstacle exists in front of the current inspection trolley, and controlling the inspection trolley by the control center to continuously inspect according to the original inspection route;
s335: and judging that an obstacle exists in front of the current inspection trolley, and controlling the inspection trolley by the control center to change the advancing route and avoid the obstacle.
The two data acquisition processes of image acquisition and field intensity detection are not interfered with each other; the method for shooting the environmental image by using the image collector and providing a decision basis for the obstacle avoidance decision after image processing is carried out on the basis of the collected image usually has higher precision, can sense the surrounding environment of the inspection trolley with high quality, timely and effectively provides information such as distribution position, shape outline, depth and the like of tangible components in the surrounding environment for the inspection trolley, and can provide a powerful basis for the obstacle avoidance decision. However, it cannot be ignored that when the image processing result is used as a basis for the obstacle avoidance decision, due to the uncertainty of the image processing technology and the possible error accumulation in the inspection process, the image processing result may have a certain drift, but the field strength detection means provided in addition to the image processing in the present application makes up for this defect, because for the power equipment in the substation, the position is fixed in the whole inspection process, the electric field or the magnetic field generated in the surrounding environment is also fixed relatively to the position, the field strength parameter detected by the field strength sensor can provide a strong reference for the control center, and the obstacle avoidance decision is continuously corrected while the decision basis on another dimension is provided for the obstacle avoidance decision of the control center, thereby avoiding the obstacle misjudgment caused by the system error accumulation in a single sensor.
The invention has the advantages that: compared with the prior art, the inspection system provided by the invention adapts to the specific conditions of more components in the transformer substation and electric field or magnetic field interference around the power equipment by means of combining image processing and field intensity detection, provides a safer, more stable, more effective and more dimensional decision basis for obstacle avoidance of the inspection trolley, and ensures that the unmanned automatic inspection process of the inspection trolley is smoothly carried out.
Drawings
Fig. 1 is a flowchart of an inspection method of a substation inspection robot system according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
In order to achieve the purpose, the technical scheme of the invention is as follows:
please refer to fig. 1.
In this embodiment, a transformer substation inspection robot system is provided, and the robot includes:
the system comprises a carrying platform, an inspection trolley, a field intensity sensor, an image collector and a control center, wherein the inspection trolley is used for carrying other components and running along the ground to inspect the environment of a transformer substation;
the field intensity sensor and the image sensor are both carried on the inspection trolley and connected with the inspection trolley; the inspection trolley, the field intensity sensor and the image sensor are all interactive with the control center.
In this embodiment, a method for inspecting a substation inspection robot system is further provided, where the method is based on the substation inspection robot system, and the method specifically includes:
s1: the field intensity sensor detects the electric field or the magnetic field intensity of the current position of the inspection trolley in real time;
s2: the image collector shoots and records an image in the current visual field of the inspection trolley;
s3: the control center fuses real-time electric field or magnetic field intensity information and real-time image information, barrier detection is carried out on the current environment, and the control center plans a routing inspection path for the routing inspection trolley according to the barrier detection result.
Specifically, in this embodiment, S1 specifically is:
s110: selecting capacitive field strength sensor, denoted as CMAccording to
Figure BDA0003450527680000071
Establishing the potential difference U output by the capacitive field intensity sensorM(t) advancing to the present capacitive field strength sensor CMElectric field intensity E at the location0(t) a mapping relationship between; a, B, C three power transmission lines for transmitting three-phase alternating current are taken as power equipment, and a capacitive field intensity sensor C carried on the inspection trolley for three power transmission line pairs is examinedMThe influence of (a);
s111: according to the position of the current routing inspection trolley, a rectangular coordinate system is established by taking a junction point right below the intermediate phase power transmission line and the horizontal ground as an origin of coordinates, the horizontal ground as a horizontal coordinate and the vertical upward direction as a vertical coordinate, and the potential value of the ground is specified to be 0; arranging a cylindrical power transmission lineFor simulating the charge, the central point of the cylindrical power transmission line is set as the point Q of the simulated charge1,Q2,Q3Finding the only corresponding matching point on each analog charge point, and marking the analog charge points Q corresponding to A, B, C three power transmission lines in a rectangular coordinate system according to the mirror image principle1,Q2,Q3sub-Earth mirror point Q4,Q5,Q6Establishing an equation set:
Figure BDA0003450527680000081
p in the above equation setijIs a potential coefficient, and satisfies the following conditions:
Figure BDA0003450527680000082
Pijdielectric constant taking in expression
Figure BDA0003450527680000083
DijDistance of the ith matching point to the image of the jth analog charge; dijThe distance from the ith matching point to the j analog charges.
S112: according to the condition of actual power equipment arranged in a transformer substation, regarding each power equipment as a field source, and marking each field source in a coordinate system;
taking A, B, C three power lines for carrying three-phase alternating current as an example, analysis shows that the alternating current carried on each power line satisfies the following conditions:
Figure BDA0003450527680000084
s113: according to analog charge Q1,Q2,Q3And establishing an equation set through interaction between the capacitance type field intensity sensor CM carried on the patrol trolley, and calculating the potential value of A, B, C three-phase power transmission line as follows:
Figure BDA0003450527680000085
in the above equation set
Figure BDA0003450527680000086
And
Figure BDA0003450527680000087
the real part potential value and the imaginary part potential value of the A-phase power transmission line are respectively, the other parameters are similar, the equation set is solved, and the value of the analog charge is obtained as follows: [ Q ]]=[P]-1[φ](ii) a Carrying out precision check on the solution of the equation set;
s114: according to the actual voltage conditions of the three power lines, the voltage of the alternating current transmitted by the A, B, C three-phase power line meets the following conditions:
Figure BDA0003450527680000091
the electric field strength generated by the phase conductors at point P (x, y) in the field domain can be calculated according to the superposition principle and gaussian theorem:
Figure BDA0003450527680000092
and obtaining the magnetic field intensity information of the current position where the routing inspection trolley is located.
Further, in this embodiment, S3 is specifically:
s31: processing the magnetic field intensity information input by the field intensity sensor, and mapping the information into the distance information between the current inspection trolley and the corresponding power equipment;
s32: processing image information input by an image sensor, analyzing the surrounding environment of the current position of the inspection trolley, and acquiring depth information of a target object in the surrounding environment;
s33: and integrating the distance information between the current inspection trolley and the corresponding power equipment and the target object information of the surrounding environment, and judging whether the current inspection trolley needs to take obstacle avoidance measures.
Further, in this embodiment, S32 is specifically:
s320: modeling a camera: in the embodiment, a binocular camera is adopted, and selected binocular camera internal parameters are combined to construct a relation model about a world coordinate system (XW, YW, ZW) of the binocular camera, a camera coordinate system (XC, YC, ZC) and an image coordinate system (x, y) and a pixel image coordinate system (u, v));
s321: image feature extraction and matching: ORB feature extraction is carried out on the image, firstly FAST angular points are extracted, then BRIEF descriptors of the image are obtained according to the FAST angular points, after feature matching is further carried out on the images at the front moment and the back moment, registration between point sets is realized through iterative closest point ICP, and pose estimation of the inspection trolley is realized through spatial point set registration;
s322: image edge detection and contour extraction: performing edge detection analysis by using a Canny operator, performing convolution noise reduction and noise elimination by using a Gaussian smoothing filter, then calculating the gradient amplitude and direction in the image, and then eliminating non-edge pixels and performing non-maximum suppression on the image; setting a high threshold and a low threshold, comparing the amplitude of each pixel position in the image, and if the amplitude of a certain pixel position exceeds the high threshold, reserving the pixel as an edge pixel; if the amplitude of a certain pixel position is less than the low threshold value, the pixel is excluded; if the magnitude of a pixel location is between two thresholds, the pixel is retained only when connected to a pixel above the high threshold;
s323: binocular ranging: and sending the image edge detection and contour extraction results into a binocular camera model, and calculating to obtain the pose information of the current inspection trolley and the distance information between the current inspection trolley and the target object.
Further, in this embodiment, S33 is specifically:
s331: respectively setting a field intensity threshold value and an obstacle threshold value;
s332: comparing the depth information of the target object with an obstacle threshold, and skipping S333 if the depth of the target object is greater than the obstacle threshold; otherwise, skipping to S335;
s333: comparing the magnetic field intensity information of the field at the position of the current routing inspection trolley, which is input by the field intensity sensor, with a field intensity threshold value, and skipping S334 if the magnetic field intensity of the field at the position of the current routing inspection trolley is smaller than the field intensity threshold value; otherwise, skipping to S335;
s334: judging that no obstacle exists in front of the current inspection trolley, and controlling the inspection trolley to return to S1 by the control center; continuously inspecting according to the original inspection route;
s335: and judging that an obstacle exists in front of the current inspection trolley, and controlling the inspection trolley by the control center to change the advancing route and avoid the obstacle.
The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (7)

1. The utility model provides a transformer substation patrols and examines robot system which characterized in that, this robot including:
the inspection trolley is provided with a carrying platform and is used for carrying other components and running along the ground to inspect the environment of the transformer substation;
a field intensity sensor for detecting the electric field or magnetic field intensity in real time;
the image collector is used for obtaining a real-time image;
the control center is used for analyzing the real-time pose of the inspection trolley and planning a path for the inspection trolley;
the field intensity sensor and the image sensor are both carried on the inspection trolley and are connected with the inspection trolley; the inspection trolley, the field intensity sensor and the image sensor are all interactive with the control center.
2. An obstacle avoidance method of a transformer substation inspection robot system is based on the transformer substation inspection robot system according to claim 1, and is characterized in that the method specifically comprises the following steps:
s1: the field intensity sensor detects the electric field or the magnetic field intensity of the current position of the inspection trolley in real time;
s2: the image collector shoots and records an image in the current visual field of the inspection trolley;
s3: the control center fuses real-time electric field or magnetic field intensity information and real-time image information to detect obstacles in the current environment, and plans an inspection path for the inspection trolley according to the obstacle detection result.
3. The obstacle avoidance method for the substation inspection robot system according to claim 2, wherein the S1 specifically is:
s11: establishing a calculation model of the distance between the output electric signal and the external electric power equipment according to the type and specific parameters of the set field intensity sensor;
s12: and acquiring the electric signal output by the field intensity sensor, and transmitting the electric signal to the control center through amplification, filtering and A/D conversion.
4. The obstacle avoidance method of the substation inspection robot system according to claim 3, wherein the S11 specifically is:
s111: establishing a coordinate system according to the current position of the inspection trolley, and specifying a field intensity zero point;
s112: according to the condition of actual power equipment arranged in a transformer substation, regarding each power equipment as a field source, and marking each field source in a coordinate system;
s113: establishing an equation set according to the interaction between each field source and a field intensity sensor carried on the inspection trolley, solving the equation set to obtain the actual charge condition of each field source, and carrying out precision check on the solution of the equation set;
s114: and calculating to obtain the information of the electric field or the magnetic field intensity of the current position of the routing inspection trolley according to the actual voltage or current condition of the actual power equipment arranged in the transformer substation and the actual charge condition of each field source.
5. The obstacle avoidance method for the substation inspection robot system according to claim 1, wherein the S3 specifically is:
s31: processing the electric field or magnetic field intensity information input by the field intensity sensor, and mapping the information into the distance information between the current inspection trolley and the corresponding power equipment;
s32: processing image information input by the image sensor, analyzing the surrounding environment of the position of the current inspection trolley, and acquiring depth information of a target object in the surrounding environment;
s33: and integrating the current distance information between the inspection trolley and the corresponding power equipment and the target object information of the surrounding environment, and judging whether the inspection trolley needs to take obstacle avoidance measures or not.
6. The obstacle avoidance method for the substation inspection robot system according to claim 5, wherein the step S32 specifically comprises:
s321: identifying whether a target object exists in front of the inspection trolley or not according to image information input by the image sensor; if so, jumping to S322; otherwise, repeating S321;
s322: and calculating to obtain the pose information of the current inspection trolley, and calculating the depth information of the target object based on the image information input by the image sensor.
7. The obstacle avoidance method for the substation inspection robot system according to claim 6, wherein the S33 specifically is:
s331: respectively setting a field intensity threshold value and an obstacle threshold value;
s332: comparing the depth information of the target object with an obstacle threshold, and skipping S333 if the depth of the target object is greater than the obstacle threshold; otherwise, skipping to S335;
s333: comparing the electric field or magnetic field intensity information of the field at the position where the inspection trolley is currently located, which is input by the field intensity sensor, with a field intensity threshold, and skipping to S334 if the electric field or magnetic field intensity of the field at the position where the inspection trolley is currently located is smaller than the field intensity threshold; otherwise, skipping to S335;
s334: judging that no obstacle exists in front of the inspection trolley at present, and continuing to inspect according to an original inspection route;
s335: and judging that an obstacle exists in front of the inspection trolley at present, and controlling the inspection trolley by the control center to change an advancing route and avoid the obstacle.
CN202111664013.5A 2021-12-31 2021-12-31 Substation inspection robot system and obstacle avoidance method thereof Active CN114179093B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111664013.5A CN114179093B (en) 2021-12-31 2021-12-31 Substation inspection robot system and obstacle avoidance method thereof

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111664013.5A CN114179093B (en) 2021-12-31 2021-12-31 Substation inspection robot system and obstacle avoidance method thereof

Publications (2)

Publication Number Publication Date
CN114179093A true CN114179093A (en) 2022-03-15
CN114179093B CN114179093B (en) 2024-06-11

Family

ID=80545413

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111664013.5A Active CN114179093B (en) 2021-12-31 2021-12-31 Substation inspection robot system and obstacle avoidance method thereof

Country Status (1)

Country Link
CN (1) CN114179093B (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023203367A1 (en) * 2022-04-20 2023-10-26 博歌科技有限公司 Automatic inspection system

Citations (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5668452A (en) * 1996-05-09 1997-09-16 Vlsi Technology, Inc. Magnetic sensing robotics for automated semiconductor wafer processing systems
US20080033282A1 (en) * 2006-08-07 2008-02-07 Bar-Tal Meir Distortion-immune position tracking using redundant measurements
JP2011034518A (en) * 2009-08-05 2011-02-17 Ihi Corp Autonomous control method of underwater vehicle and autonomously controlled underwater vehicle
JP2011033609A (en) * 2009-07-31 2011-02-17 Aichi Micro Intelligent Corp Indoor position detector
CN104953709A (en) * 2015-06-15 2015-09-30 湖南机电职业技术学院 Intelligent patrol robot of transformer substation
CN206185911U (en) * 2016-11-22 2017-05-24 云南电网有限责任公司电力科学研究院 Arm safe distance monitoring device
CN206878544U (en) * 2017-07-03 2018-01-12 詹皇源 A kind of super-pressure power station crusing robot
KR20190088135A (en) * 2018-01-06 2019-07-26 정택윤 Autonomous freight vehicle control system and method
US20200122330A1 (en) * 2018-10-22 2020-04-23 New Era Ai Robotic Inc. Anti-collision method for robot
CN210819634U (en) * 2019-08-15 2020-06-23 北京致行慕远科技有限公司 Line patrol device for distribution robot and distribution robot
CN111390903A (en) * 2020-03-13 2020-07-10 北京理工大学 Device and method for monitoring interaction distance of magnetic control robot
CN111633660A (en) * 2020-06-15 2020-09-08 吴洪婷 Intelligent inspection robot
CN111754083A (en) * 2020-06-01 2020-10-09 三峡大学 Routing inspection path planning method for intelligent inspection robot in direct current field of converter station
CN111969488A (en) * 2020-08-21 2020-11-20 福州大学 Coordinate transformation-based unmanned aerial vehicle inspection obstacle avoidance method for high-voltage line overhead area
CN112605987A (en) * 2020-11-25 2021-04-06 深圳拓邦股份有限公司 Robot navigation working method and device and robot
CN113240249A (en) * 2021-04-26 2021-08-10 泰瑞数创科技(北京)有限公司 Urban engineering quality intelligent evaluation method and system based on unmanned aerial vehicle augmented reality

Patent Citations (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5668452A (en) * 1996-05-09 1997-09-16 Vlsi Technology, Inc. Magnetic sensing robotics for automated semiconductor wafer processing systems
US20080033282A1 (en) * 2006-08-07 2008-02-07 Bar-Tal Meir Distortion-immune position tracking using redundant measurements
JP2011033609A (en) * 2009-07-31 2011-02-17 Aichi Micro Intelligent Corp Indoor position detector
JP2011034518A (en) * 2009-08-05 2011-02-17 Ihi Corp Autonomous control method of underwater vehicle and autonomously controlled underwater vehicle
CN104953709A (en) * 2015-06-15 2015-09-30 湖南机电职业技术学院 Intelligent patrol robot of transformer substation
CN206185911U (en) * 2016-11-22 2017-05-24 云南电网有限责任公司电力科学研究院 Arm safe distance monitoring device
CN206878544U (en) * 2017-07-03 2018-01-12 詹皇源 A kind of super-pressure power station crusing robot
KR20190088135A (en) * 2018-01-06 2019-07-26 정택윤 Autonomous freight vehicle control system and method
US20200122330A1 (en) * 2018-10-22 2020-04-23 New Era Ai Robotic Inc. Anti-collision method for robot
CN210819634U (en) * 2019-08-15 2020-06-23 北京致行慕远科技有限公司 Line patrol device for distribution robot and distribution robot
CN111390903A (en) * 2020-03-13 2020-07-10 北京理工大学 Device and method for monitoring interaction distance of magnetic control robot
CN111754083A (en) * 2020-06-01 2020-10-09 三峡大学 Routing inspection path planning method for intelligent inspection robot in direct current field of converter station
CN111633660A (en) * 2020-06-15 2020-09-08 吴洪婷 Intelligent inspection robot
CN111969488A (en) * 2020-08-21 2020-11-20 福州大学 Coordinate transformation-based unmanned aerial vehicle inspection obstacle avoidance method for high-voltage line overhead area
CN112605987A (en) * 2020-11-25 2021-04-06 深圳拓邦股份有限公司 Robot navigation working method and device and robot
CN113240249A (en) * 2021-04-26 2021-08-10 泰瑞数创科技(北京)有限公司 Urban engineering quality intelligent evaluation method and system based on unmanned aerial vehicle augmented reality

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
郑天茹;孙立民;娄婷婷;郭翔;刘巧红;: "基于电磁场计算的输电线路无人机巡检安全飞行区域确定方法", 山东电力技术, no. 02, 25 February 2018 (2018-02-25) *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2023203367A1 (en) * 2022-04-20 2023-10-26 博歌科技有限公司 Automatic inspection system

Also Published As

Publication number Publication date
CN114179093B (en) 2024-06-11

Similar Documents

Publication Publication Date Title
CN112910094B (en) Remote automatic transformer substation inspection system and method based on ubiquitous power Internet of things
WO2018028103A1 (en) Unmanned aerial vehicle power line inspection method based on characteristics of human vision
CN113313005B (en) Power transmission conductor on-line monitoring method and system based on target identification and reconstruction
CN103413139B (en) Electric equipment abnormal heating detection method based on infrared inspection video data of power line inspection
CN107885224A (en) Unmanned plane barrier-avoiding method based on tri-item stereo vision
CN114782626B (en) Transformer substation scene map building and positioning optimization method based on laser and vision fusion
CN112528979B (en) Transformer substation inspection robot obstacle distinguishing method and system
CN114114314A (en) Power transmission line inspection detection system and detection method based on laser point cloud
CN114179093B (en) Substation inspection robot system and obstacle avoidance method thereof
CN111476762A (en) Obstacle detection method and device of inspection equipment and inspection equipment
CN111967323B (en) Electric power live working safety detection method based on deep learning algorithm
CN115049322A (en) Container management method and system for container yard
CN116976721A (en) Power distribution operation behavior normalization evaluation method, system and computing equipment
CN116862712A (en) Electric power construction potential safety risk detection method and system based on thunder fusion
Sheng et al. Mobile robot localization and map building based on laser ranging and PTAM
CN113223155A (en) Distance prediction method, device, equipment and medium
CN113160202A (en) Crack detection method and system
CN117313969A (en) Substation robot inspection path optimization method and device
CN117351025A (en) Inspection and investigation method and system based on target segmentation and extraction
CN113949142B (en) Inspection robot autonomous charging method and system based on visual recognition
CN103198326B (en) A kind of image classification method of transmission line of electricity helicopter routing inspection
CN116739963A (en) Power grid equipment defect detection method based on multi-level multi-scale feature fusion
Fu et al. Research on monitoring device for indicating external damage risk of overhead line based on image recognition technology with binocular vision cameras
Suzuki et al. Spatial model for capturing size and shape of object from point cloud data for robot vision system with LIDAR sensors
CN118351672B (en) Intelligent detection early warning method and system for electrified region of transformer substation

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant