CN114872086B - Inspection robot state detection method and system - Google Patents
Inspection robot state detection method and system Download PDFInfo
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- CN114872086B CN114872086B CN202210580838.7A CN202210580838A CN114872086B CN 114872086 B CN114872086 B CN 114872086B CN 202210580838 A CN202210580838 A CN 202210580838A CN 114872086 B CN114872086 B CN 114872086B
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- 238000007689 inspection Methods 0.000 title claims abstract description 129
- 238000001514 detection method Methods 0.000 title claims abstract description 106
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- 230000007613 environmental effect Effects 0.000 description 23
- 238000004458 analytical method Methods 0.000 description 22
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B25—HAND TOOLS; PORTABLE POWER-DRIVEN TOOLS; MANIPULATORS
- B25J—MANIPULATORS; CHAMBERS PROVIDED WITH MANIPULATION DEVICES
- B25J19/00—Accessories fitted to manipulators, e.g. for monitoring, for viewing; Safety devices combined with or specially adapted for use in connection with manipulators
- B25J19/06—Safety devices
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/18—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form
- G05B19/406—Numerical control [NC], i.e. automatically operating machines, in particular machine tools, e.g. in a manufacturing environment, so as to execute positioning, movement or co-ordinated operations by means of programme data in numerical form characterised by monitoring or safety
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02B—BOARDS, SUBSTATIONS OR SWITCHING ARRANGEMENTS FOR THE SUPPLY OR DISTRIBUTION OF ELECTRIC POWER
- H02B3/00—Apparatus specially adapted for the manufacture, assembly, or maintenance of boards or switchgear
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S40/00—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them
- Y04S40/12—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment
- Y04S40/128—Systems for electrical power generation, transmission, distribution or end-user application management characterised by the use of communication or information technologies, or communication or information technology specific aspects supporting them characterised by data transport means between the monitoring, controlling or managing units and monitored, controlled or operated electrical equipment involving the use of Internet protocol
Abstract
The invention discloses a method for detecting the state of a patrol robot, which comprises the following steps: judging the running state of the inspection robot through detecting the signal receiving state of the node; if the inspection robot runs abnormally, the path from the current detection node to the next detection node is sent to the management terminal; if the inspection robot runs normally, the operation level, the power grid environment and the detection node environment of the inspection robot are judged, and the operation state of the inspection robot can be monitored reversely.
Description
Technical Field
The invention belongs to the technical field of substation inspection, and particularly relates to a state detection method and system of an inspection robot.
Background
With the rapid development of internet technology, in the current application of network technology, the data of different products are accessed to analyze various data so as to realize the operation of various indexes and data, which is already an important content of internet application; in order to analyze big data, relevant basic data is accessed from each product to become one important content, and the efficiency and quality of accessing the basic data directly influence the efficiency and quality of subsequent analysis and processing and other processes.
In the existing power grid monitoring field, data acquisition is carried out by relying on a patrol robot, and the patrol robot is used for storing acquired data in an intranet through the intervention of an electric power data security access technology; however, the navigation technology of the existing inspection robot is not mature enough, and the data receiving module cannot reversely monitor the running state of the inspection robot through the data access condition, so that the running state of the inspection robot cannot be guaranteed, and the normal access of the power data is affected.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a method and a system for detecting the state of a patrol robot, which can be used for reversely monitoring the running state of the patrol robot.
The technical problems to be solved by the invention are realized by the following technical scheme:
in a first aspect, a method for detecting a state of a patrol robot is provided, including:
judging the running state of the inspection robot through detecting the signal receiving state of the node;
if the inspection robot runs abnormally, the path from the current detection node to the next detection node is sent to the management terminal;
if the inspection robot runs normally, judging the running grade, the power grid environment and the detection node environment of the inspection robot.
With reference to the first aspect, further, the determining, by detecting the signal receiving state of the node, the running state of the inspection robot includes:
when the system time advances to the detection time when the inspection robot is expected to finish a certain detection node, judging whether detection information from the detection node is received, if so, judging that the inspection robot operates normally, and otherwise, judging that the inspection robot operates abnormally.
With reference to the first aspect, further, when the detection time of the inspection robot completing a certain detection node is expected to be received, the detection time is obtained by the following formula:
JS＝KS+α1×LC/YS (1)
wherein KS is the starting time, alpha 1 is the proportionality coefficient, LC is the path length from the current node to the next node, YS is the current running speed of the inspection robot, JS is the detection time for the inspection robot to finish a certain detection node.
With reference to the first aspect, further, determining an operation level of the inspection robot includes:
comparing the running coefficient of the inspection robot with the maximum running threshold and the minimum running threshold according to the given maximum running threshold and minimum running threshold, and judging that the running level of the inspection robot is three-level if the running coefficient is smaller than or equal to the minimum running threshold; if the operation coefficient is between the maximum operation threshold value and the minimum operation threshold value, judging that the operation level of the inspection robot is two-level; and if the operation coefficient is greater than or equal to the maximum operation threshold value, judging that the operation level of the inspection robot is one level.
With reference to the first aspect, further, the operation coefficient is obtained by the following formula
YX＝PC/(JS-KS)
Wherein YX is an operation coefficient, PC is a difference between a time when information of a certain detection node is actually received and a time when the inspection robot is expected to complete the detection of the certain detection node, JS is a time when the inspection robot is expected to complete the detection of the certain detection node, and KS is a current time of the system.
With reference to the first aspect, further, determining the running power grid environment and the detection node environment of the inspection robot includes:
if the anomaly ratio is greater than or equal to the anomaly threshold value and the environment representation value is greater than or equal to the environment representation threshold value, judging that the power grid environment and the detection node environment are both required to be regulated;
if the anomaly ratio is greater than or equal to the anomaly threshold value and the environment representation value is smaller than the environment representation threshold value, judging that the power grid environment needs to be regulated;
if the anomaly ratio is smaller than the anomaly threshold value and the environment representation value is larger than or equal to the environment representation threshold value, judging that the detection node needs environment adjustment;
if the anomaly ratio is smaller than the anomaly threshold value and the environment representation value is smaller than the environment representation threshold value, judging that the power grid environment and the detection node environment meet the requirements.
In a second aspect, a system for detecting a state of a patrol robot is provided, which is characterized in that the system includes:
the robot running state judging module is used for judging the running state of the inspection robot through detecting the signal receiving state of the node;
the abnormal processing module is used for sending the path from the current detection node to the next detection node to the management terminal if the inspection robot runs abnormally;
and the environment judging module is used for judging the operation grade of the inspection robot, the power grid environment and the detection node environment if the inspection robot operates normally.
The invention has the following beneficial effects:
1. the time and the state of each time the inspection robot reaches the detection node can be monitored through the set access analysis module, so that operation faults caused by immature navigation technology of the inspection robot are avoided, the phenomenon that power data cannot be normally accessed due to abnormal operation of the inspection robot is prevented, in addition, operation grade analysis is conducted on the inspection robot which is normal in operation, and the operation grade of the inspection robot is judged through the timeliness of the inspection robot reaching the next detection node;
2. judging whether the detection node is an abnormal node or not according to the numerical value of the environment coefficient, and further obtaining the duty ratio of the abnormal node in the detection node and the environment coefficient deviation degree of each detection node, so that the environment of the power grid and each detection node is monitored.
Drawings
FIG. 1 is a system block diagram of the present invention;
FIG. 2 is a block diagram of a system module involved in determining an operational level in accordance with the present invention;
FIG. 3 is a flow chart of the present invention when determining the operation level;
FIG. 4 is a block diagram of a system module involved in determining an environment in accordance with the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to better understand the present invention, the following describes related technologies in the technical solution of the present invention.
Example 1
As shown in fig. 1-4, the invention provides a method for detecting the state of a patrol robot, which comprises the following steps:
step one, judging the running state of the inspection robot
In order to judge the running state of the inspection robot, the inspection robot needs to acquire the acquired data, a camera for image shooting is arranged on the inspection robot, the position of the inspection robot for data acquisition is marked as a detection node i, i=1, 2, …, n and n are positive integers, and the inspection robot responds to a signal sent by an intelligent access platform to send the acquired data to an access analysis module after running to the detection node.
It should be noted that, the inspection robot is divided into a magnetic navigation robot and a laser navigation robot according to different navigation modes, the magnetic navigation needs to arrange magnetic tracks in advance (i.e. the permanent magnets are buried on the inspection route of the robot), the robot moves forward or backward along the magnetic tracks, an electronic tag RFID needs to be additionally buried beside each electromagnetic track needing to stop to detect points or perform actions such as turning speed regulation, and information injected during debugging is available in the electronic tag, such as detection, speed regulation, turning and the like, and the robot performs corresponding actions after sweeping the tags. Six magnetic sensors are arranged below the robot, so that whether the robot moves along a preset magnetic track or not can be ensured, if the robot deviates slightly, adjustment can be performed, and when the next label is detected, the robot can know the position of the robot to continue to execute the current task; the navigation of the laser navigation robot is laser, compared with the magnetic navigation, the laser navigation is more advanced, the magnetic track and the electronic tag are not required to be arranged in advance, and the hardware is saved and mainly analyzed by software. Although the magnetic guide rail is not required to be arranged, a two-dimensional plan of the laser map is required to be established in the first step, because the two-dimensional plan contains XY coordinates, the XY coordinates are corresponding to each corresponding point in the power station, and an action (detection, turning and speed regulation) is set for the robot when the robot reaches each point, so that an electronic tag is not required, and the robot movement is also performed by setting the coordinate points, so that the magnetic rail is not required. One problem with laser navigation robots is the problem of laser matching rate, namely that the robot actually scans the scene and previously sets an electronic map to match, and if the matching rate is too low, the robot cannot judge the position of the robot and stops. The establishment of the electronic map can push the robot to patrol the power station once or sweep the power station once by using a special laser scanner, and the height setting of the laser scanner is consistent with the height of the laser navigator of the robot.
It can be understood that the detection node of the present application is disposed at the position where the inspection robot performs the operations of "detection, turning, speed regulation", whether it is a magnetic navigation robot or a laser navigation robot.
After receiving the data acquired by the inspection robot, the access analysis module acquires the current position of the inspection robot, sends the current position of the inspection robot and the acquired data to the anomaly analysis module, marks the current system time as a start time KS, acquires the path length from the current node to the next node and marks the path length as a path length LC; obtaining the current running speed of the inspection robot and marking the current running speed as YS, and obtaining the ending time JS through a formula JS=KS+alpha 1 xLC/YS, namely, when the detection time of the inspection robot for completing the next detection node is expected to be received, wherein alpha 1 is a proportionality coefficient (set according to an empirical value), and 1 is more than or equal to 1 and less than or equal to 1.15; when the system time reaches the end time, judging whether the access analysis module receives the collected data of the inspection robot again or not: if the data is received, judging that the inspection robot runs normally, and sending the received data to an anomaly analysis module; if the inspection robot is not received, the inspection robot is judged to be abnormal in operation.
Step two, exception handling
When the running state of the inspection robot is abnormal, the paths of the current node and the next node are sent to the intelligent access platform, the intelligent access platform sends the received paths to the mobile phone terminal of the manager, and whether to intervene can be determined by manual judgment.
Step three, normal treatment
When the inspection robot operates normally, marking the time when the access analysis module receives the acquired data of the inspection robot again as marking time (when a certain detection node information is actually received), marking the time difference value between the ending time and the marking time as a deviation value PC, and obtaining an operation coefficient YX of the inspection robot through a formula YX=PC/(JS-KS), wherein the operation coefficient is a numerical value reflecting the operation state of the inspection robot, and the larger the numerical value of the operation coefficient is, the better the operation state of the inspection robot is indicated; setting a minimum operation threshold value YXmin and a maximum operation threshold value YXmax according to experience, storing the minimum operation threshold value YXmin and the maximum operation threshold value YXmax in a storage module, and comparing the operation coefficient YX of the inspection robot with the operation threshold values YXmin and YXmax: if YX is less than or equal to YXmin, judging that the running grade of the inspection robot is three grades; if YXmin is less than YX and less than YXmax, judging that the operation level of the inspection robot is two levels; if YX is more than or equal to YXmax, judging that the running grade of the inspection robot is one grade; the access analysis module sends the operation grade of the inspection robot to the intelligent access platform; according to the invention, the time and the state of each arrival of the inspection robot at the detection node can be monitored through the set access analysis module, so that the operation fault of the inspection robot caused by the immature navigation technology is avoided, the phenomenon that the power data cannot be normally accessed due to abnormal operation of the inspection robot is prevented, in addition, the operation grade analysis is carried out on the inspection robot which operates normally, and the operation grade of the inspection robot is judged through the timeliness of the inspection robot arriving at the next detection node.
And when the inspection robot runs normally, the power grid environment and the detection node environment are required to be judged.
The data collected by the inspection robot includes temperature data WDi, humidity data SDi and dust data HCi of the detection node i, and the process of obtaining the temperature data WDi includes: the temperature value and the proper temperature range acquired by the inspection robot are acquired, the temperature value is directly acquired by a temperature sensor, and the temperature sensor is a sensor capable of sensing the temperature and converting the temperature into a usable output signal. The temperature sensor is a core part of the temperature measuring instrument, has various varieties, can be divided into two main types of contact type and non-contact type according to the measuring mode, and is divided into two types of thermal resistors and thermocouples according to the characteristics of sensor materials and electronic elements; marking the average value of the maximum value and the minimum value of the proper temperature range as a temperature standard value, and marking the absolute value of the difference value between the temperature value and the temperature standard value as temperature data WDi; the acquisition process of the humidity data SDi includes: the humidity value and the proper humidity range acquired by the inspection robot are acquired, the humidity value is directly acquired by a humidity sensor, the humidity sensor is a device capable of sensing external humidity change and converting the humidity into useful signals through physical or chemical property change of device materials, and humidity detection is more difficult than detection of other physical quantities, firstly, because the water vapor content in the air is much less than that in the air; in addition, the liquid water can dissolve some high polymer materials and electrolyte materials, and after ionization, a part of water molecules are combined with impurities in the air dissolved in the water to form acid or alkali, so that the humidity-sensitive material is corroded and aged to different degrees, and the original property of the humidity-sensitive material is lost; furthermore, the transfer of the wet information must be accomplished by direct contact of the water with the moisture sensitive device, so that the moisture sensitive device is only directly exposed to the environment to be tested and cannot be sealed. In general, the following requirements are placed on the humidity sensitive device: the stability is good, the response time is short, the service life is long, the interchangeability is realized, the pollution resistance and the temperature influence are small, and the like under various gas environments; marking the average value of the maximum value and the minimum value of the proper humidity range as a humidity standard value; marking the absolute value of the difference between the humidity value and the humidity standard value as humidity data SDi; the acquisition process of dust data HCi includes: the method comprises the steps of acquiring an air dust concentration value acquired by a patrol robot and marking the air dust concentration value as dust data HCi, wherein the dust concentration value is directly acquired by a dust detector, and the dust detector is an instrument for detecting dust content in air; the environmental coefficient HJi is obtained by the formula HJi =β1× WDi +β2×sdi+β3×hci, and it is to be noted that the environmental coefficient is a value reflecting the environmental quality of the detection node, and the greater the value of the environmental coefficient, the worse the environment of the detection node; wherein β1, β2 and β3 are all scaling factors, obtained according to the following method: collecting a plurality of groups of sample data and setting corresponding environment coefficients for each group of sample data; substituting the set environmental coefficient and the acquired sample data into a formula, forming a ternary once equation set by any three formulas, screening the calculated coefficient and taking an average value to obtain values of beta 1, beta 2 and beta 3, wherein the values of beta 1, beta 2 and beta 3 are 5.27, 2.54 and 1.25 respectively, and beta 1 is more than beta 2 and more than beta 3 is more than 1; the environmental threshold HJmax is obtained through the data storage module, and the environmental coefficient HJi of the detection node i is compared with the environmental threshold HJmax (HJmax is used for measuring whether the environment is abnormal or not and is set according to an empirical value): if the environment coefficient HJi is smaller than the environment threshold value HJMax, judging that the environment of the detection node i is normal, and marking the corresponding detection node as a normal node; if the environmental coefficient HJi is greater than or equal to the environmental threshold value HJMax, judging that the environment of the detection node i is abnormal, and marking the corresponding detection node as an abnormal node; marking the number of abnormal nodes as m, marking the ratio of m to n (n represents the number of detection points) as an abnormal ratio, establishing an environment set { HJ1, HJ2, …, HJn } by the environment coefficient of the detection node, performing variance calculation on the environment set to obtain an environment representation value, acquiring an abnormal threshold value and an environment representation threshold value through a data storage module, and comparing the abnormal ratio and the environment representation value with the abnormal threshold value and the environment representation threshold value respectively: if the anomaly ratio is greater than or equal to the anomaly threshold value and the environmental representation value is greater than or equal to the environmental representation threshold value, determining that the power grid and the detection node both need environmental regulation, and sending a network node regulation signal to the intelligent access platform by the anomaly analysis module, wherein the intelligent access platform sends the network node regulation signal to a mobile phone terminal of a manager after receiving the network node regulation signal; if the anomaly ratio is greater than or equal to the anomaly threshold value and the environmental representation value is smaller than the environmental representation threshold value, determining that the power grid needs environmental regulation, and sending a power grid regulation signal to the intelligent access platform by the anomaly analysis module, wherein the intelligent access platform sends the power grid regulation signal to a mobile phone terminal of a manager after receiving the power grid regulation signal; if the anomaly ratio is smaller than the anomaly threshold value and the environmental representation value is larger than or equal to the environmental representation threshold value, judging that the detection node needs environmental adjustment, and sending a node adjustment signal to the intelligent access platform by the anomaly analysis module, wherein the intelligent access platform sends the node adjustment signal to a mobile phone terminal of a manager after receiving the node adjustment signal; if the anomaly ratio is smaller than the anomaly threshold value and the environment representation value is smaller than the environment representation threshold value, judging that the environments of the power grid and the detection nodes meet the requirements, and sending an environment normal signal to the intelligent access platform by the anomaly analysis module; the anomaly analysis module sends the data acquired by the inspection robot and the environmental coefficient to the data storage module, the temperature data, the humidity data and the dust data of the detection nodes are processed through the set anomaly analysis module to obtain the environmental coefficient, whether the detection nodes are the anomaly nodes or not is judged through the numerical value of the environmental coefficient, and then the duty ratio of the anomaly nodes in the detection nodes and the environmental coefficient deviation degree of each detection node are obtained, so that the environment monitoring is carried out on the power grid and each detection node.
The intelligent access system for the machine inspection data based on the electric power data safety access technology is characterized in that when the intelligent access system is operated, the inspection robot receives a switching signal sent by an intelligent access platform after operating to a detection node and sends acquired data to an access analysis module, the access analysis module analyzes the received data acquired by the inspection robot to obtain an end time JS, when the system time reaches the end time JS, the access analysis module judges whether the acquired data of the inspection robot are received again, and the abnormal analysis module processes and analyzes the data after receiving the data acquired by the inspection robot and judges whether the environment of a power grid and the detection node is qualified.
Example 2
The invention also provides a system for detecting the state of the inspection robot, which comprises the following steps:
the robot running state judging module is used for judging the running state of the inspection robot through detecting the signal receiving state of the node;
the abnormal processing module is used for sending the path from the current detection node to the next detection node to the management terminal if the inspection robot runs abnormally;
and the environment judging module is used for judging the operation grade of the inspection robot, the power grid environment and the detection node environment if the inspection robot operates normally.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Claims (5)
1. The inspection robot state detection method is characterized by comprising the following steps:
judging the running state of the inspection robot through detecting the signal receiving state of the node;
if the inspection robot runs abnormally, the path from the current detection node to the next detection node is sent to the management terminal;
if the inspection robot runs normally, judging the running grade, the power grid environment and the detection node environment of the inspection robot;
determining the operation level of the inspection robot includes:
comparing the running coefficient of the inspection robot with the maximum running threshold and the minimum running threshold according to the given maximum running threshold and minimum running threshold, and judging that the running level of the inspection robot is three-level if the running coefficient is smaller than or equal to the minimum running threshold; if the operation coefficient is between the maximum operation threshold value and the minimum operation threshold value, judging that the operation level of the inspection robot is two-level; if the operation coefficient is greater than or equal to the maximum operation threshold value, judging that the operation level of the inspection robot is one level;
the operation coefficient is obtained by
YX=PC/（JS-KS）
Wherein YX is an operation coefficient, PC is a difference between a time when information of a certain detection node is actually received and a time when the inspection robot is expected to complete the detection of the certain detection node, JS is a time when the inspection robot is expected to complete the detection of the certain detection node, and KS is a current time of the system.
2. The inspection robot state detection method according to claim 1, wherein the determining the operation state of the inspection robot by detecting the signal receiving state of the node includes:
when the system time advances to the detection time when the inspection robot is expected to finish a certain detection node, judging whether detection information from the detection node is received, if so, judging that the inspection robot operates normally, and otherwise, judging that the inspection robot operates abnormally.
3. The inspection robot condition detection method of claim 2, further comprising: the estimated time for the inspection robot to complete the inspection of a certain inspection node is obtained by the following equation:
JS=KS+α1×LC/YS（1）
wherein KS is the current time of the system, alpha 1 is a proportionality coefficient, LC is the path length from the current node to the next node, YS is the current running speed of the inspection robot, JS is the detection time of the inspection robot for completing a certain detection node.
4. The inspection robot condition detection method according to claim 1, wherein determining the inspection robot operating grid environment and the inspection node environment comprises:
if the anomaly ratio is greater than or equal to the anomaly threshold value and the environment representation value is greater than or equal to the environment representation threshold value, judging that the power grid environment and the detection node environment are both required to be regulated;
if the anomaly ratio is greater than or equal to the anomaly threshold value and the environment representation value is smaller than the environment representation threshold value, judging that the power grid environment needs to be regulated;
if the anomaly ratio is smaller than the anomaly threshold value and the environment representation value is larger than or equal to the environment representation threshold value, judging that the detection node needs environment adjustment;
if the anomaly ratio is smaller than the anomaly threshold value and the environment representation value is smaller than the environment representation threshold value, judging that the power grid environment and the detection node environment meet the requirements;
wherein the anomaly ratio is the ratio of the number of the anomaly nodes to the number of the detection nodes;
and establishing an environment set { HJ1, HJ2, …, HJn } by using the environment coefficients of the detection nodes, wherein the environment representation value is obtained by performing variance calculation on the environment set, and HJn is the environment coefficient of the nth detection point.
5. The inspection robot state detection system is characterized by comprising:
the robot running state judging module is used for judging the running state of the inspection robot through detecting the signal receiving state of the node;
the abnormal processing module is used for sending the path from the current detection node to the next detection node to the management terminal if the inspection robot runs abnormally;
the environment judging module is used for judging the operation grade of the inspection robot, the power grid environment and the detection node environment if the inspection robot operates normally;
determining the operation level of the inspection robot includes:
comparing the running coefficient of the inspection robot with the maximum running threshold and the minimum running threshold according to the given maximum running threshold and minimum running threshold, and judging that the running level of the inspection robot is three-level if the running coefficient is smaller than or equal to the minimum running threshold; if the operation coefficient is between the maximum operation threshold value and the minimum operation threshold value, judging that the operation level of the inspection robot is two-level; if the operation coefficient is greater than or equal to the maximum operation threshold value, judging that the operation level of the inspection robot is one level;
the operation coefficient is obtained by
YX=PC/（JS-KS）
Wherein YX is an operation coefficient, PC is a difference between a time when information of a certain detection node is actually received and a time when the inspection robot is expected to complete the detection of the certain detection node, JS is a time when the inspection robot is expected to complete the detection of the certain detection node, and KS is a current time of the system.
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