A man-machine collaborative inspection method and system based on a power grid resource service middle platform

Abstract

The application discloses a kind of man-machine cooperation inspection method and system based on power grid resource service middle station, belong to power grid inspection field.To distribute and mark the inspection object as machine inspection object or human inspection object for inspection task;The rationality of the distribution of inspection object is verified and analyzed, and the overall qualification of power inspection of power grid coverage area is determined when power inspection distribution is reasonable;When determining that the overall power inspection of the power grid coverage area is unqualified, find out the factors that cause the overall unqualified inspection;According to the search result, the protective equipment of the inspection personnel is strengthened or the skill training of the inspection personnel is strengthened.The application can reasonably distribute the inspection task to the inspection robot and the inspection personnel, preferentially match the inspection robot with the inspection object with high danger level, prevent the inspection personnel from involving high-risk areas, thereby reducing the probability of injury of the inspection personnel.

Description

Technical Field

[0001] The present invention belongs to the field of power grid inspection and relates to human-machine collaborative technology, specifically a human-machine collaborative inspection method and system based on a power grid resource business center. Background Art

[0002] Traditional distribution network systems only monitor and control the operation status of power lines and electrical equipment, discover equipment defects and hidden dangers, and issue alarm information to promptly eliminate defects and prevent accidents, or minimize the scope of faults as much as possible to ensure reliable power supply and power system stability, and achieve the operating goals of "safe, economical, high supply, and low loss" for the line system. The health status and operating environment of equipment in the distribution network system are mainly detected by manual regular inspections, which are cumbersome and inefficient.

[0003] In order to improve inspection efficiency and reduce human injuries, inspection personnel of distribution network systems are gradually replaced by inspection robots. On the one hand, it can improve inspection efficiency, and on the other hand, it can reduce the number of people working in some high-risk areas and reduce the probability of human injuries. However, due to the high R&D and production costs of inspection robots, the current power grid inspection work cannot rely entirely on inspection robots. Therefore, inspection robots and inspection personnel need to work together. In response to this situation, the existing power grid inspection system does not have the function of rationally allocating inspection robots and inspection personnel, and it is also unable to verify the rationality of the allocation of inspection objects. Summary of the Invention

[0004] The purpose of the present invention is to provide a human-machine collaborative inspection method and system based on a power grid resource business center, which is used to solve the problem that the existing power distribution inspection system does not have the function of reasonably allocating inspection robots and inspection personnel and verifying the rationality of the allocation.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] On the one hand, a human-machine collaborative inspection method based on the power grid resource business platform includes:

[0007] Assign inspection tasks and mark inspection objects as machine inspection objects or human inspection objects;

[0008] Verify and analyze the rationality of the allocation of inspection objects and determine the overall eligibility of power inspections in the grid coverage area when the power inspection allocation is reasonable;

[0009] When it is determined that the overall power inspection in the grid coverage area is unqualified, the factors that lead to the overall unqualified power inspection are identified;

[0010] According to the search result, the protection equipment of the inspection personnel is strengthened or the skill training of the inspection personnel is strengthened.

[0011] Further, the assigning of the inspection task and the marking of the inspection object as a machine inspection object or a human inspection object comprises:

[0012] Obtain pipeline data, line data and area data of the inspection object i of the power grid coverage area, i = 1, 2, …, n, n is a positive integer;

[0013] According to the pipeline data, line data and area data of the inspection object i, the machine pushing coefficient JTi of the inspection object i is calculated;

[0014] The machine pushing coefficient JTi of the inspection object i is compared with the machine pushing threshold JTmax, if the machine pushing coefficient JTi is greater than or equal to the machine pushing threshold JTmax, the corresponding inspection object is marked as a machine inspection object, and the inspection robot is matched with the machine inspection object; if the machine pushing coefficient JTi is less than the machine pushing threshold JTmax, the corresponding inspection object is marked as a human inspection object, and the inspection personnel is matched with the human inspection object.

[0015] Further, the verification analysis of the rationality of the assignment of the inspection object comprises:

[0016] Obtain the damage data SSi of the inspection object i of the power grid coverage area within L1 days, i = 1, 2, …, n, n is a positive integer;

[0017] The damage data of all inspection objects of the power grid coverage area is summed and averaged to obtain the damage value;

[0018] The obtained damage value is compared with the damage threshold, if the damage value is greater than or equal to the damage threshold, it is determined that the power inspection assignment of the power grid coverage area is unreasonable, and the inspection task is re-assigned; if the damage value is less than the damage threshold, it is determined that the power inspection assignment of the power grid coverage area is reasonable.

[0019] Further, the determination of the overall qualification of the power inspection of the power grid coverage area when the power inspection assignment is reasonable comprises:

[0020] When it is determined that the power inspection assignment of the power grid coverage area is reasonable, the damage data of the inspection object i is established as a damage set {SS1, SS2, …, SSn}, and the damage performance value is calculated by calculating the variance of the damage set;

[0021] The damage performance value is compared with the damage performance threshold, if the damage performance value is less than the damage performance threshold, it is determined that the overall power inspection of the power grid coverage area is qualified; if the damage performance value is greater than or equal to the damage performance threshold, it is determined that the overall power inspection of the power grid coverage area is unqualified.

[0022] Further, the method for obtaining the damage data SSi comprises:

[0023] If the inspection object i is a machine inspection object, the damage data SSi is the number of times that the inspection robot of the inspection object i is damaged within L1 days; if the inspection object i is a human inspection object, the damage data SSi is the number of times that the inspection personnel of the inspection object i is injured within L1 days.

[0024] Further, the method for searching for the factor causing the overall unqualified power inspection of the power grid coverage area when determining that the overall qualified power inspection of the power grid coverage area is unqualified comprises:

[0025] marking the inspection object with the value of the damage data SSi not less than the damage threshold value as a search object, marking one natural day as an inspection date, and obtaining the rainfall data, wind data and smoke data of the search object in the inspection date;

[0026] calculating the environmental coefficient of the search object according to the rainfall data, wind data and smoke data of the search object in the inspection date; comparing the environmental coefficient of the search object with the environmental threshold value, and marking the corresponding inspection date as an abnormal date if the environmental coefficient is greater than or equal to the environmental threshold value;

[0027] counting the number of abnormal dates of the search object within L1 days; marking the ratio of the number of abnormal dates to L1 as a ring anomaly ratio, comparing the ring anomaly ratio with the ring anomaly threshold value, and determining that the unqualified factor of the search object is environmental anomaly if the ring anomaly ratio is greater than or equal to the ring anomaly threshold value, or determining that the unqualified factor of the search object is the unqualified professional of the inspection personnel if the ring anomaly ratio is less than the ring anomaly threshold value.

[0028] On the other hand, a man-machine collaborative inspection system based on a power grid resource business middle platform comprises an inspection management platform, and a distribution management module, a verification analysis module, a factor searching module and an adjustment execution module in communication connection with the inspection management platform,

[0029] the distribution management module is configured to distribute the inspection tasks and mark the inspection objects as machine inspection objects or human inspection objects, and to redistribute the inspection tasks according to the received redistribution signal;

[0030] the verification analysis module is configured to verify and analyze the rationality of the distribution of the inspection objects, to send a redistribution signal to the inspection management platform when determining that the power inspection distribution is unreasonable, to determine the overall qualified property of the power inspection of the power grid coverage area when determining that the power inspection distribution is rational, and to send an overall unqualified signal to the inspection management platform when determining that the overall qualified power inspection of the power grid coverage area is unqualified;

[0031] The factor searching module is configured to search for a factor causing the overall unqualified power inspection when the overall unqualified signal is received, and send a protection signal or a training signal to the inspection management platform according to the unqualified factor searched.

[0032] The adjustment executing module is configured to strengthen the protection equipment of the inspection personnel or strengthen the skill training of the inspection personnel according to the received protection signal or training signal.

[0033] The inspection management platform is configured to send the received redistribution signal to the distribution management module, send the received overall unqualified signal to the factor searching module, and send the received protection signal or training signal to the adjustment executing module.

[0034] Further, the distribution management module comprises:

[0035] The first obtaining module is configured to obtain pipeline data, line data and area data of an inspection object i in a power grid coverage area, i = 1, 2, …, n, n being a positive integer.

[0036] The first calculating module is configured to calculate a machine pushing coefficient JTi of the inspection object i according to the pipeline data, line data and area data of the inspection object i.

[0037] The first comparison and judgment module is configured to compare the machine pushing coefficient JTi of the inspection object i with a machine pushing threshold JTmax, if the machine pushing coefficient JTi is greater than or equal to the machine pushing threshold JTmax, mark the corresponding inspection object as a machine inspection object, and match the inspection robot with the machine inspection object; if the machine pushing coefficient JTi is less than the machine pushing threshold JTmax, mark the corresponding inspection object as a human inspection object, and match the inspection personnel with the human inspection object.

[0038] Further, the verification analysis module comprises:

[0039] The second obtaining module is configured to obtain damage data SSi of the inspection object i in the power grid coverage area within L1 days, i = 1, 2, …, n, n being a positive integer.

[0040] The second calculating module is configured to sum and average the damage data of all the inspection objects in the power grid coverage area to obtain a damage value.

[0041] The second comparison and judgment module is configured to compare the obtained damage value with a damage threshold, if the damage value is greater than or equal to the damage threshold, determine that the power inspection distribution of the power grid coverage area is unreasonable; if the damage value is less than the damage threshold, determine that the power inspection distribution of the power grid coverage area is reasonable.

[0042] Further, the verification analysis module further comprises:

[0043] The third calculation module is configured to establish a damage set {SS1, SS2,..., SSn} of the damage data of the inspection object i when determining that the power inspection of the power grid coverage area is qualified, and to obtain a damage performance value by performing variance calculation on the damage set;

[0044] The third comparison and determination module is configured to compare the damage performance value with a damage performance threshold value, and if the damage performance value is less than the damage performance threshold value, it is determined that the power inspection of the power grid coverage area is qualified as a whole, and if the damage performance value is greater than or equal to the damage performance threshold value, it is determined that the power inspection of the power grid coverage area is unqualified as a whole.

[0045] Further, the factor searching module comprises:

[0046] The fourth acquisition module is configured to mark the inspection object with damage data SSi whose value is not less than a damage threshold value as a searching object, mark one natural day as an inspection date, and acquire rainfall data, wind data and smoke data of the searching object in the inspection date.

[0047] The fourth calculation module is configured to calculate an environmental coefficient of the searching object according to the rainfall data, the wind data and the smoke data of the searching object in the inspection date, compare the environmental coefficient of the searching object with an environmental threshold value, and if the environmental coefficient is greater than or equal to the environmental threshold value, mark the corresponding inspection date as an abnormal date.

[0048] The fourth comparison and determination module is configured to count the number of abnormal dates of the searching object in L1 days, mark the ratio of the number of abnormal dates to L1 as a ring abnormality ratio, compare the ring abnormality ratio with a ring abnormality threshold value, and if the ring abnormality ratio is greater than or equal to the ring abnormality threshold value, determine that the unqualified factor of the searching object is environmental abnormality, and if the ring abnormality ratio is less than the ring abnormality threshold value, determine that the unqualified factor of the searching object is unqualified professional quality of the inspection personnel.

[0049] Compared with the prior art, the present application has the following beneficial effects:

[0050] 1. The present application reasonably allocates the inspection task to the inspection robot and the inspection personnel, and the calculated machine-pushing coefficient can reflect the danger degree of the inspection object during power inspection, so that the inspection robot is preferentially matched with the inspection object with high danger degree, the inspection personnel is prevented from involving in the high-risk area, the probability of injury of the inspection personnel is reduced, and the inspection task is reasonably allocated.

[0051] 2、The application can verify and analyze the distribution rationality after a period of time, determine the distribution rationality through the damage data of the inspection objects in a certain period of time, re-distribute when the distribution is unreasonable, analyze the damage difference of each inspection object when the distribution is reasonable, determine that the whole is unqualified when the difference is too large, and investigate the reasons;

[0052] 3、The application can determine the factors that cause the whole power inspection to be unqualified in the power grid coverage area, determine whether the factors are environmental abnormalities through the environmental coefficient obtained by analyzing the environmental data of the inspection date and the numerical value of the environmental coefficient, determine whether the factors are environmental abnormalities, execute corresponding adjustment operations according to different factors, adjust the subsequent inspection process, and further reduce the damage rate. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 A man-machine cooperative inspection method flow chart based on a power grid resource business middle station according to an embodiment of the application;

[0054] Figure 2 A system structure block diagram of man-machine cooperative inspection based on a power grid resource business middle station according to an embodiment of the application. DETAILED DESCRIPTION

[0055] The application will be further described below in combination with specific embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the application, and cannot be used to limit the protection scope of the application.

[0056] As shown in Figure 1 A man-machine cooperative inspection method based on a power grid resource business middle station, comprising:

[0057] Step S1, distributing the inspection tasks and marking the inspection objects as machine inspection objects or human inspection objects;

[0058] The step specifically comprises:

[0059] Step S101, marking the inspection points of the power grid coverage area as inspection objects i, i=1, 2, …, n, n is a positive integer, obtaining the pipeline data, line data and area data of the inspection object i;

[0060] The pipeline data of the inspection object i can be the number value of the high-temperature pipeline in the inspection object i, the line data of the inspection object i can be the number value of the high-voltage line in the inspection object i, and the area data of the inspection object i can be the land area value of the inspection object i.

[0061] Step S102, calculating the machine pushing coefficient JTi of the inspection object i according to the pipeline data, line data and area data of the inspection object i;

[0062] The machine pushing coefficient JTi is calculated according to the following formula:

[0063] JTi = a1 x GLi + a2 x XLi + a3 x MJi

[0064] where GLi is the pipeline data of the inspection object i, XLi is the line data of the inspection object i, MJi is the area data of the inspection object i, a1, a2 and a3 are proportional coefficients, and a1 > a2 > a3 > 1.

[0065] The machine pushing coefficient is a value reflecting the inspection risk level of the inspection object. The larger the value of the machine pushing coefficient, the higher the inspection risk of the corresponding inspection object, and the more suitable it is for the inspection robot to perform inspection.

[0066] Step S103, comparing the machine pushing coefficient JTi of the inspection object i with the machine pushing threshold JTmax, and marking the inspection object as a machine inspection object or a human inspection object according to the comparison result.

[0067] Comparing the machine pushing coefficient JTi of the inspection object i with the machine pushing threshold JTmax, if the machine pushing coefficient JTi is greater than or equal to the machine pushing threshold JTmax, marking the corresponding inspection object as a machine inspection object, and matching the inspection robot with the machine inspection object;

[0068] If the machine pushing coefficient JTi is less than the machine pushing threshold JTmax, marking the corresponding inspection object as a human inspection object, and matching the inspection personnel with the human inspection object.

[0069] The machine pushing coefficient calculated can reflect the risk degree of the inspection object during power inspection, so as to preferentially match the inspection robot with the inspection object with high risk degree, prevent the inspection personnel from involving in high-risk areas, thereby reducing the injury probability of the inspection personnel, and reasonably allocate the inspection task.

[0070] Step S2, verifying and analyzing the rationality of the distribution of the inspection objects, and determining the overall qualification of the power inspection of the power grid coverage area when the distribution of the power inspection is rational;

[0071] The verification and analysis of the rationality of the distribution of the inspection objects specifically includes:

[0072] Step S201, obtaining the damage data SSi of the inspection object i of the power grid coverage area within L1 days, i = 1, 2, …, n, n is a positive integer;

[0073] Wherein, the process of obtaining the damage data SSi includes:

[0074] If the inspection object i is a machine inspection object, the damage data SSi is the number of times that the inspection robot of the inspection object i is damaged within L1 days; if the inspection object i is a human inspection object, the damage data SSi is the number of times that the inspection personnel of the inspection object i is injured within L1 days.

[0075] Step S202, summing up the damage data of all the inspection objects in the power grid coverage area to obtain a damage value;

[0076] Step S203, comparing the damage value with a damage threshold value, if the damage value is greater than or equal to the damage threshold value, determining that the power inspection distribution of the power grid coverage area is unreasonable, and re-distributing the inspection tasks; if the damage value is less than the damage threshold value, determining that the power inspection distribution of the power grid coverage area is reasonable.

[0077] When it is determined that the power inspection distribution of the power grid coverage area is reasonable, the overall qualification of the power inspection of the power grid coverage area is determined, specifically:

[0078] Step S204, establishing a damage set {SS1, SS2, …, SSn} for the damage data of the inspection object i, and calculating the variance of the damage set to obtain a damage performance value;

[0079] The damage performance value is a value reflecting the damage difference between the inspection objects, the greater the damage performance value, the greater the damage difference between the inspection objects, and it is indicated that the damage data of some inspection objects is too large, and the damage condition needs to be further analyzed.

[0080] Step S205, comparing the damage performance value with a damage performance threshold value:

[0081] If the damage performance value is less than the damage performance threshold value, determining that the overall power inspection of the power grid coverage area is qualified; if the damage performance value is greater than or equal to the damage performance value, determining that the overall power inspection of the power grid coverage area is unqualified.

[0082] Step S3, when it is determined that the overall power inspection of the power grid coverage area is unqualified, searching for the factors causing the overall unqualified inspection;

[0083] This step specifically includes:

[0084] Step S301, marking the inspection object whose damage data SSi value is not less than the damage threshold value as a search object, marking a natural day as an inspection date, and obtaining the rainfall data, wind data and smoke data of the search object in the inspection date;

[0085] The rainfall data of the search object can be the total rainfall in the search object within the inspection date. The rainfall can be directly obtained by a tipping bucket rain sensor. The sensor receives the rainfall into a small bucket and automatically pours it out when a certain amount is reached, and a corresponding rainfall record is formed.

[0086] The wind data of the search object can be the maximum wind level of the search object within the inspection date. Wind refers to the size of the force exerted by the wind on an object. Generally, the size of the wind is divided into 18 levels according to various phenomena caused by the wind blowing on the ground or water surface. The smallest is level 0, and the largest is level 17.

[0087] The smoke data of the search object can be the maximum smoke concentration value of the search object within the inspection date. The smoke concentration value is directly obtained by a smoke sensor. The smoke sensor, also known as a smoke alarm or smoke alarm, can detect smoke concentration.

[0088] Step S302, according to the rainfall data, wind data and smoke data of the search object within the inspection date, the environmental coefficient of the search object is calculated; the environmental coefficient of the search object is compared with the environmental threshold value, and the inspection date is determined according to the comparison result whether it is normal;

[0089] The environmental coefficient HJ of the search object is calculated according to the following formula:

[0090] HJ = β1 × JY + β2 × FL + β3 × YW

[0091] Where JY is the rainfall data, FL is the wind data, YW is the smoke data, β1, β2 and β3 are proportional coefficients, and β3 > β2 > β1 > 1.

[0092] The environmental coefficient is a value reflecting the degree of environmental abnormality. The larger the value of the environmental coefficient, the higher the degree of environmental abnormality within the inspection date, and the higher the possibility of inspection damage caused by environmental abnormality.

[0093] Wherein, the environmental coefficient of the search object is compared with the environmental threshold value, according to the comparison result, whether the inspection date is normal, including:

[0094] If the environmental coefficient HJ is less than the environmental threshold value Jmax, the corresponding inspection date is marked as a normal date; if the environmental coefficient HJ is greater than or equal to the environmental threshold value Jmax, the corresponding inspection date is marked as an abnormal date.

[0095] Step S303, the number of abnormal dates of the search object within L1 days is counted and marked as Y1; the ratio of Y1 to L1 is marked as ring anomaly ratio, the ring anomaly ratio is compared with the ring anomaly threshold value, and the factors leading to the overall unqualified inspection are determined according to the comparison result.

[0096] If the ring difference ratio is greater than or equal to the ring difference threshold, it is determined that the unqualified factor of the search object is an environmental anomaly; if the ring difference ratio is less than the ring difference threshold, it is determined that the unqualified factor of the search object is that the professional quality of the inspection personnel is unqualified.

[0097] Step S4, according to the search result, the protective equipment of the inspection personnel is strengthened or the skill training of the inspection personnel is strengthened.

[0098] When it is determined that the unqualified factor of the search object is an environmental anomaly, the protective equipment of the inspection personnel is strengthened;

[0099] When it is determined that the unqualified factor of the search object is that the professional quality of the inspection personnel is unqualified, the skill training of the inspection personnel is strengthened.

[0100] As shown in Figure 2 A man-machine cooperative inspection system based on a power grid resource business middle platform, comprising: an inspection management and control platform, and a distribution management module, a verification analysis module, a factor searching module, an adjustment execution module and a storage module in communication connection with the inspection management and control platform.

[0101] The distribution management module is used for distributing the inspection tasks and marking the inspection objects as machine inspection objects or human inspection objects; and re-distributing the inspection tasks according to the received re-distribution signal.

[0102] The verification analysis module is used for verifying and analyzing the rationality of the distribution of the inspection objects, sending a re-distribution signal to the inspection management and control platform when it is determined that the power inspection distribution is unreasonable, determining the overall qualification of the power inspection of the power grid coverage area when it is determined that the power inspection distribution is reasonable, sending an overall qualified signal to the inspection management and control platform if it is determined that the overall qualification of the power inspection of the power grid coverage area, and sending an overall unqualified signal to the inspection management and control platform if it is determined that the overall qualification of the power inspection of the power grid coverage area.

[0103] The factor searching module is used for searching for the factors causing the overall unqualification of the inspection when the overall unqualified signal is received, and sending a protection signal or a training signal to the inspection management and control platform according to the unqualified factors searched.

[0104] The adjustment execution module is used for strengthening the protective equipment of the inspection personnel or strengthening the skill training of the inspection personnel according to the received protection signal or training signal.

[0105] The inspection management and control platform is used for sending the re-distribution signal to the distribution management module after receiving it, sending the overall unqualified signal to the factor searching module after receiving it, and sending the protection signal or the training signal to the adjustment execution module after receiving it.

[0106] The distribution management module comprises:

[0107] a first obtaining module, configured to obtain pipeline data, line data and area data of an inspection object i in a power grid coverage area, i=1, 2, …, n, n being a positive integer;

[0108] a first calculating module, configured to calculate a machine pushing coefficient JTi of the inspection object i according to the pipeline data, the line data and the area data of the inspection object i;

[0109] a first comparison and judgment module, configured to compare the machine pushing coefficient JTi of the inspection object i with a machine pushing threshold JTmax, if the machine pushing coefficient JTi is greater than or equal to the machine pushing threshold JTmax, mark the corresponding inspection object as a machine inspection object, and match the inspection robot with the machine inspection object; if the machine pushing coefficient JTi is less than the machine pushing threshold JTmax, mark the corresponding inspection object as a human inspection object, and match the inspection personnel with the human inspection object.

[0110] The verification and analysis module comprises:

[0111] a second obtaining module, configured to obtain damage data SSi of the inspection object i in the power grid coverage area within L1 days, i=1, 2, …, n, n being a positive integer;

[0112] a second calculating module, configured to sum and average the damage data of all the inspection objects in the power grid coverage area to obtain a damage value;

[0113] a second comparison and judgment module, configured to compare the obtained damage value with a damage threshold, if the damage value is greater than or equal to the damage threshold, determine that the power inspection distribution of the power grid coverage area is unreasonable; if the damage value is less than the damage threshold, determine that the power inspection distribution of the power grid coverage area is reasonable.

[0114] The verification and analysis module further comprises:

[0115] a third calculating module, configured to, when it is determined that the power inspection distribution of the power grid coverage area is reasonable, establish a damage set {SS1, SS2, …, SSn} of the damage data of the inspection object i, and calculate a damage performance value by performing variance calculation on the damage set;

[0116] a third comparison and judgment module, configured to compare the damage performance value with a damage performance threshold, if the damage performance value is less than the damage performance threshold, determine that the power inspection of the power grid coverage area is overall qualified; if the damage performance value is greater than or equal to the damage performance threshold, determine that the power inspection of the power grid coverage area is overall unqualified.

[0117] The factor searching module comprises:

[0118] The fourth acquisition module is configured to mark the inspection object with a value of the damage data SSi not less than a damage threshold as a search object, mark one natural day as one inspection date, and acquire rainfall data, wind data and smoke data of the search object in the inspection date.

[0119] The fourth calculation module is configured to calculate an environmental coefficient of the search object according to the rainfall data, the wind data and the smoke data of the search object in the inspection date, compare the environmental coefficient of the search object with an environmental threshold, and mark the corresponding inspection date as an abnormal date if the environmental coefficient is greater than or equal to the environmental threshold.

[0120] The fourth comparison and judgment module is configured to count a number of abnormal dates of the search object in L1 days, mark a ratio of the number of the abnormal dates to L1 as a ring abnormality ratio, compare the ring abnormality ratio with a ring abnormality threshold, and determine that an unqualified factor of the search object is environmental abnormality if the ring abnormality ratio is greater than or equal to the ring abnormality threshold, or determine that the unqualified factor of the search object is unqualified professional of the inspection personnel if the ring abnormality ratio is less than the ring abnormality threshold.

[0121] The system of the present application has the following specific working process:

[0122] The inspection task is distributed by the distribution management module, and the inspection object is marked as a machine inspection object or a human inspection object, and the specific process includes: acquiring pipeline data, line data and area data of an inspection object i in a power grid coverage area; calculating a machine pushing coefficient JTi of the inspection object i according to the pipeline data, the line data and the area data of the inspection object i; comparing the machine pushing coefficient JTi of the inspection object i with a machine pushing threshold JTmax, marking the corresponding inspection object as a machine inspection object if the machine pushing coefficient JTi is greater than or equal to the machine pushing threshold JTmax, and matching the inspection robot with the machine inspection object; and marking the corresponding inspection object as a human inspection object if the machine pushing coefficient JTi is less than the machine pushing threshold JTmax, and matching the inspection personnel with the human inspection object.

[0123] After the distribution of the inspection points of the inspection personnel and the inspection robot is completed, the verification analysis module verifies and analyzes the rationality of the distribution of the inspection objects: obtaining damage data SSi of the inspection object i in L1 days; summing and averaging the damage data of all inspection objects in the power grid coverage area to obtain a damage value; obtaining a damage threshold value through a storage module, and comparing the damage value with the damage threshold value: if the damage value is greater than or equal to the damage threshold value, it is determined that the power inspection distribution of the power grid coverage area is unreasonable, the verification analysis module sends a redistribution signal to the inspection management and control platform, the inspection management and control platform receives the redistribution signal and sends the redistribution signal to the distribution management module, and the distribution management module receives the redistribution signal and redistributes the inspection tasks again; if the damage value is less than the damage threshold value, it is determined that the power inspection distribution of the power grid coverage area is reasonable, the damage data of the inspection object i is established into a damage set {SS1, SS2, …, SSn}, and a damage performance value is obtained by calculating the variance of the damage set; obtaining a damage performance threshold value through a storage module, and comparing the damage performance value with the damage performance threshold value: if the damage performance value is less than the damage performance threshold value, it is determined that the overall power inspection of the power grid coverage area is qualified, and the verification analysis module sends an overall qualified signal to the inspection management and control platform; if the damage performance value is greater than or equal to the damage performance threshold value, it is determined that the overall power inspection of the power grid coverage area is unqualified, and the verification analysis module sends an overall unqualified signal to the inspection management and control platform, and the inspection management and control platform receives the overall unqualified signal and sends the overall unqualified signal to the factor finding module.

[0124] When determining that the power inspection of the power grid coverage area as a whole is unqualified, the factor searching module determines the factor causing the overall unqualified inspection: mark the inspection object whose damage data SSi is not less than the damage threshold as a search object, and obtain the rainfall data JY, wind data FL and smoke data YW of the search object in the inspection date; according to HJ=β1*JY+β2*FL+β3*YW, the environmental coefficient HJ of the search object is calculated; the environmental threshold HJmax is obtained through the storage module, and the environmental coefficient HJ of the search object is compared with the environmental threshold: if the environmental coefficient HJ is less than the environmental threshold HJmax, the corresponding inspection date is marked as a normal date, and if the environmental coefficient HJ is greater than or equal to the environmental threshold HJmax, the corresponding inspection date is marked as an abnormal date; the number of abnormal dates of the search object in L1 days is counted and marked as Y1, and the ratio of Y1 to L1 is marked as the ring difference ratio, and the ring difference ratio is compared with the ring difference threshold through the storage module: if the ring difference ratio is greater than or equal to the ring difference threshold, it is determined that the unqualified factor of the search object is environmental abnormality, the factor searching module sends a protection signal to the inspection control platform, and the inspection control platform sends the protection signal to the adjustment execution module after receiving the protection signal, and the adjustment execution module strengthens and upgrades the protection equipment of the inspection personnel after receiving the protection signal; if the ring difference ratio is less than the ring difference threshold, it is determined that the unqualified factor of the search object is the unqualified professional of the inspection personnel, the factor searching module sends a training signal to the inspection control platform, and the inspection control platform sends the training signal to the adjustment execution module after receiving the training signal, and the adjustment execution module strengthens the skill training of the inspection personnel after receiving the training signal.

[0125] The distribution management module is arranged to reasonably distribute the inspection tasks to the inspection robots and the inspection personnel, the machine-push coefficient calculated can reflect the danger degree of the inspection object during power inspection, so that the inspection robot is preferentially matched with the inspection object with high danger degree, the inspection personnel is prevented from involving in the high-risk area, the injury probability of the inspection personnel is reduced, and the inspection tasks are reasonably distributed; the verification analysis module can verify and analyze the distribution rationality after a period of time, the distribution rationality is determined according to the damage data of the inspection object in a certain period of time, the distribution is re-distributed when the distribution is unreasonable, the damage difference of each inspection object is analyzed when the distribution is reasonable, and the overall unqualified is determined and the reason is investigated when the difference is too large; the factor searching module can determine the factor causing the overall unqualified inspection of the power grid coverage area when the power inspection of the power grid coverage area as a whole is unqualified, the environmental coefficient is obtained through the environmental data analysis of the inspection date, whether the inspection date is normal is determined according to the value of the environmental coefficient, so that whether the factor is environmental abnormality is determined, different factors are output by the factor searching module, the adjustment execution module performs corresponding adjustment operation, and the subsequent inspection process is adjusted, and the damage rate is further reduced.

[0126] It should be noted that the formula in the present application is to calculate the value without dimension, the formula is obtained by collecting a large amount of data to simulate the recent real situation, and the preset parameters in the formula are set by the person skilled in the art according to the actual situation;

[0127] For example: JTi = α1 x GLi + α2 x XLi + α3 x MJi,

[0128] A plurality of sample data are collected by the person skilled in the art, and a corresponding machine pushing coefficient is set for each sample data; the set machine pushing coefficient and the collected sample data are substituted into the formula, any three formulas constitute a ternary linear equation group, the calculated coefficients are screened and the mean value is taken, and the values of α1, α2 and α3 are 3.87, 3.25 and 2.16 respectively;

[0129] The size of the coefficient is to obtain a specific numerical value by quantifying each parameter, which is convenient for subsequent comparison. As for the size of the coefficient, as long as it does not affect the proportional relationship between the parameter and the quantized numerical value.

[0130] The above has disclosed the present application with the preferred embodiments, but it is not intended to limit the present application. Any technical solution obtained by equivalent replacement or equivalent transformation falls within the protection scope of the present application.

Claims

1. A human-machine collaborative inspection method based on a power grid resource business platform, characterized in that: include: Assign inspection tasks and mark inspection objects as machine inspection objects or human inspection objects; Verify and analyze the rationality of the allocation of inspection objects and determine the overall eligibility of power inspections in the grid coverage area when the power inspection allocation is reasonable; When it is determined that the overall power inspection in the grid coverage area is unqualified, the factors that lead to the overall unqualified power inspection are identified; Strengthen the protective equipment of patrol personnel or enhance their skills training based on the search results; The verification and analysis of the rationality of the allocation of inspection objects includes: Obtain the damage data SSi of the inspection object i in the power grid coverage area within L1 days, where i=1, 2, ..., n, and n is a positive integer; The damage data of all inspection objects in the grid coverage area are summed and averaged to obtain the damage value; The obtained damage value is compared with the damage threshold. If the damage value is greater than or equal to the damage threshold, it is determined that the power inspection distribution in the grid coverage area is unreasonable and the inspection tasks are reallocated. If the damage value is less than the damage threshold, it is determined that the power inspection distribution in the grid coverage area is reasonable. The determination of the overall eligibility of the power inspection in the area covered by the power grid when the power inspection distribution is reasonable includes: When it is determined that the power inspection distribution in the grid coverage area is reasonable, the damage data of the inspection object i is used to establish a damage set {SS1, SS2, ..., SSn}, and the variance of the damage set is calculated to obtain the damage performance value; The damage performance value is compared with the damage performance threshold. If the damage performance value is less than the damage performance threshold, the power inspection in the grid coverage area is judged to be qualified as a whole; if the damage performance value is greater than or equal to the damage performance threshold, the power inspection in the grid coverage area is judged to be unqualified as a whole.

2. A human-machine collaborative inspection method based on a power grid resource business platform according to claim 1, characterized in that: The allocating inspection tasks and marking the inspection objects as machine inspection objects or human inspection objects includes: Obtain pipeline data, line data, and area data of inspection object i in the grid coverage area, where i=1, 2, ..., n, and n is a positive integer; According to the pipeline data, line data and area data of the inspection object i, the thrust coefficient JTi of the inspection object i is calculated; The machine-pushing coefficient JTi of the inspection object i is compared with the machine-pushing threshold JTmax. If the machine-pushing coefficient JTi is greater than or equal to the machine-pushing threshold JTmax, the corresponding inspection object will be marked as a machine-inspected object, and the inspection robot will be matched with the machine-inspected object; if the machine-pushing coefficient JYi is less than the machine-pushing threshold JTmax, the corresponding inspection object will be marked as a human-inspected object, and the inspection personnel will be matched with the human-inspected object.

3. A human-machine collaborative inspection method based on a power grid resource business platform according to claim 1, characterized in that: The method for obtaining the damage data SSi includes: If the inspection object i is a machine inspection object, the damage data SSi is the number of times the inspection robot is damaged within L1 days for the inspection object i; if the inspection object i is a human inspection object, the damage data SSi is the number of times the inspection personnel are injured within L1 days for the inspection object i.

4. A human-machine collaborative inspection method based on a power grid resource business platform according to claim 1, characterized in that: When determining that the power inspection in the power grid coverage area is unqualified as a whole, searching for factors that lead to the unqualified power inspection as a whole includes: Mark the inspection objects whose damage data SSi values ​​are not less than the damage threshold as search objects, mark a natural day as an inspection date, and obtain the rainfall data, wind data, and smoke data of the search objects within the inspection date; Calculate the environmental coefficient of the search object based on the rainfall data, wind data, and smoke data of the search object during the inspection date; compare the environmental coefficient of the search object with the environmental threshold; if the environmental coefficient is greater than or equal to the environmental threshold, mark the corresponding inspection date as an abnormal date; Count the number of abnormal dates for the search object within L1 days; mark the ratio of the number of abnormal dates to L1 as the ring-shaped ratio, and compare the ring-shaped ratio with the ring-shaped threshold. If the ring-shaped ratio is greater than or equal to the ring-shaped threshold, it is determined that the unqualified factor of the search object is environmental abnormality; if the ring-shaped ratio is less than the ring-shaped threshold, it is determined that the unqualified factor of the search object is the unqualified professionalism of the inspection personnel.

5. A human-machine collaborative inspection system based on a power grid resource business platform, characterized in that: include: Inspection and control platform, as well as the distribution management module, verification analysis module, factor search module and adjustment execution module connected to the inspection and control platform, The allocation management module is used to allocate inspection tasks and mark inspection objects as machine inspection objects or human inspection objects; and reallocate inspection tasks according to received reallocation signals; The verification and analysis module is used to verify and analyze the rationality of the allocation of inspection objects, and send a reallocation signal to the inspection control platform when it is determined that the power inspection allocation is unreasonable. When it is determined that the power inspection allocation is reasonable, it determines the overall eligibility of the power inspection in the power grid coverage area, and sends an overall unqualified signal to the inspection control platform when it is determined that the power inspection in the power grid coverage area is unqualified. The factor search module is used to search for factors that lead to overall failure of the power inspection upon receiving the overall failure signal, and send a protection signal or a training signal to the inspection control platform based on the found failure factors; The adjustment execution module is used to strengthen the protective equipment of the inspection personnel or strengthen the skills training of the inspection personnel according to the received protection signal or training signal; The inspection and control platform is used to send the received reallocation signal to the allocation management module; send the received overall unqualified signal to the factor search module; and sending the received protection signal or training signal to the regulation execution module; The verification and analysis module includes: The second acquisition module is used to obtain the damage data SSi of the inspection object i in the power grid coverage area within L1 days, where i=1, 2, ..., n, and n is a positive integer; The second calculation module is used to sum and average the damage data of all inspection objects in the power grid coverage area to obtain a damage value; The second comparison and judgment module is used to compare the obtained damage value with the damage threshold. If the damage value is greater than or equal to the damage threshold, it is determined that the power inspection distribution in the area covered by the power grid is unreasonable; if the damage value is less than the damage threshold, it is determined that the power inspection distribution in the area covered by the power grid is reasonable; The third calculation module is used to create a damage set {SS1, SS2, ..., SSn} based on the damage data of the inspection object i when it is determined that the power inspection distribution in the grid coverage area is reasonable, and perform variance calculation on the damage set to obtain a damage performance value; The third comparison and judgment module is used to compare the damage performance value with the damage performance threshold. If the damage performance value is less than the damage performance threshold, it is determined that the power inspection in the grid coverage area is qualified as a whole; if the damage performance value is greater than or equal to the damage performance threshold, it is determined that the power inspection in the grid coverage area is unqualified as a whole.

6. A human-machine collaborative inspection system based on a power grid resource business platform according to claim 5, characterized in that: The allocation management module includes: The first acquisition module is used to acquire pipeline data, line data, and area data of an inspection object i in the power grid coverage area, where i=1, 2, ..., n, and n is a positive integer; The first calculation module is used to calculate the thrust coefficient JTi of the inspection object i based on the pipeline data, line data and area data of the inspection object i; The first comparison and judgment module is used to compare the machine push coefficient JTi of the inspection object i with the machine push threshold JTmax. If the machine push coefficient JTi is greater than or equal to the machine push threshold JTmax, the corresponding inspection object will be marked as a machine inspection object, and the inspection robot will be matched with the machine inspection object; if the machine push coefficient JYi is less than the machine push threshold JTmax, the corresponding inspection object will be marked as a human inspection object, and the inspection personnel will be matched with the human inspection object.

7. A human-machine collaborative inspection system based on a power grid resource business platform according to claim 5, characterized in that: The factor search module includes: The fourth acquisition module is used to mark the inspection objects whose damage data SSi values ​​are not less than the damage threshold as search objects, mark a natural day as an inspection date, and obtain the rainfall data, wind data, and smoke data of the search objects within the inspection date; a fourth calculation module, configured to calculate an environmental coefficient of the search object based on the rainfall data, wind data, and smoke data of the search object during the inspection date; compare the environmental coefficient of the search object with an environmental threshold; and if the environmental coefficient is greater than or equal to the environmental threshold, mark the corresponding inspection date as an abnormal date; The fourth comparison and judgment module is used to count the number of abnormal dates for the search object within L1 days; mark the ratio of the number of abnormal dates to L1 as the ring-shaped ratio, and compare the ring-shaped ratio with the ring-shaped threshold. If the ring-shaped ratio is greater than or equal to the ring-shaped threshold, it is determined that the unqualified factor of the search object is environmental abnormality; if the ring-shaped ratio is less than the ring-shaped threshold, it is determined that the unqualified factor of the search object is the unqualified professionalism of the inspection personnel.

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