CN116879683B - Method and device for identifying local defects of high-voltage power cable - Google Patents
Method and device for identifying local defects of high-voltage power cable Download PDFInfo
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Abstract
The application discloses a method and a device for identifying local defects of a high-voltage power cable, and relates to the technical field of cable defect identification. According to the high-voltage power cable local defect identification method, automatic inspection is performed along the extending direction of the high-voltage power cable, the cable temperature is detected and acquired, the cable temperature is processed, if abnormal temperature is detected, early warning is sent out, the local defect position of the high-voltage power cable can be accurately positioned through various technical means such as temperature detection, time domain reflection, current response analysis and the like, and specific defect types can be identified according to comparison of current response data and a pre-stored defect model, so that defect diagnosis and maintenance become more accurate and reliable, accurate defect positioning and type identification can be provided, reliability and practicability of an early warning system are improved, current response data acquisition is realized, and the current response data can be analyzed in combination with parameters of the pre-stored defect model, so that the specific defect types of the defect positions can be determined.
Description
Technical Field
The application relates to the technical field of cable defect identification, in particular to a method and a device for identifying local defects of a high-voltage power cable.
Background
With the increase of the operational life, the local defect of the high-voltage power cable can further develop into a cable hard fault to cause an electrical accident. Therefore, the detection research of the local defects of the high-voltage power cable is developed, the originating local defects of the cable are detected and positioned in time, the type of the local defects of the cable is accurately identified on the basis, the analysis of the reasons for the generation of the local defects of the cable is facilitated, guidance is provided for an operation and maintenance engineer to repair the cable, the electric power operation cost can be effectively reduced, the safety and stability of the electric power system operation are improved, and the continuous healthy development of an electric power industry is promoted.
The existing cable local defect diagnosis method only stays on the positioning of the cable local defect, but the type of the high-voltage power cable local defect is difficult to determine according to current response data, so that the identification method capable of effectively identifying the high-voltage power cable local defect is provided, and the technical problem to be solved by the person skilled in the art is urgent.
Disclosure of Invention
Aiming at the defects of the prior art, the application provides a method and a device for identifying the local defects of a high-voltage power cable, which solve the problem that the existing method for diagnosing the local defects of the cable only stays on the positioning of the local defects of the cable, but the type of the local defects of the high-voltage power cable is difficult to determine according to current response data.
In order to achieve the above purpose, the application is realized by the following technical scheme: a method for identifying local defects of a high-voltage power cable comprises the following steps: the automatic inspection robot automatically inspects along the extending direction of the high-voltage power cable, detects and acquires the temperature of the cable, processes the temperature of the cable, and sends out early warning if detecting abnormal temperature; after the processing center receives the early warning, a time domain reflection detection method is used for determining the distance between the abnormal temperature region and the detection starting point, the abnormal temperature region is marked as a defect position, and if the defect position is not marked, the early warning is canceled; applying a low-frequency electric field signal at the defect position to obtain current response data; comparing the obtained current response data with parameters of a pre-stored defect model to determine the defect type of the defect position; the automatic inspection is carried out along the extending direction of the high-voltage power cable, the cable temperature is detected and obtained, and the cable temperature is processed as follows: periodically detecting the cable temperature within a set distance from the inspection starting point, recording the detected cable temperature, and preprocessing the detected cable temperature, wherein the preprocessing comprises deleting abnormal temperature data; calculating a normal temperature contrast value of the high-voltage power cable according to the pretreated cable temperature; periodically sampling the cable verification temperature after leaving the tail end point of the set distance, and comparing the cable verification temperature with the normal temperature contrast value of the cable to obtain an abnormal temperature coefficient, wherein the cable verification temperature comprises temperature data periodically obtained in the process of continuously keeping the original direction from the tail end point of the set distance for automatic inspection and temperature data periodically obtained in the process of returning to the inspection starting point after leaving the tail end point of the set distance; if the abnormal temperature coefficient is larger than the set temperature threshold coefficient, judging that the abnormal temperature is detected, and sending out early warning; the method for determining the distance between the region where the abnormal temperature is located and the detection starting point by using the time domain reflection detection method comprises the following steps of: the detection starting point sends a pulse signal through a high-voltage power cable, and the sending time is recorded; recording the receiving moment when the detection starting point receives the reflected signal; calculating the distance from the region where the abnormal temperature is located to the detection starting point according to the time difference between the sending time and the receiving time, and marking the distance as a defect position; the formula for calculating the distance of the region where the abnormal temperature is located from the detection start point is as follows:
，/>is the distance from the detection start point of the region where the abnormal temperature is located, wherein +.>For the moment of reception +.>For the moment of transmission->Is the reference temperature->The propagation speed of the pulse signal at the bottom,is a temperature coefficient>Is the dielectric constant of the cable insulation material +.>For the magnetic permeability of the cable->To be within a set distance->Subsampled cable temperature, +.>For the number of samplings within a set distance, +.>Is the normal temperature contrast value of the high-voltage power cable, < ->Is a normal temperature calibration factor of the high-voltage power cable.
Further, the calculation formula of the abnormal temperature coefficient is as follows:
wherein->Is abnormal temperature coefficient>Is->Subsampled cable validation temperature, +.>To be within a set distance->Subsampled cable temperature，/>For the number of samplings within a set distance, +.>Verifying the value of the temperature to the normal temperature contrast of the high-voltage power cable for the cable +.>Allowable error of +.>For the normal temperature calibration factor of the high voltage power cable, < >>Is a temperature coefficient modulation factor.
Further, a low-frequency electric field signal is applied to the defect position, and the current response data is obtained as follows: applying a low frequency electric field signal around the defect location causing it to induce a current response in the high voltage power cable; measuring current response in real time, recording data of current change along with time, and writing into a current response curve; current response data including amplitude, phase and waveform are obtained from the current response curve.
Further, a calculation formula for comparing the acquired current response data with the response data of the pre-stored defect model is as follows:
wherein (1)>For the fitness value, +.>，/>，/>Amplitude +.>Phase->And waveform->Weight factor of->，/>，/>The amplitude, phase and waveform of the defect model are respectively; and if the adaptation value approaches to the adaptation value of the defect model, determining the defect type of the defect position.
Further, after the pre-warning is canceled at the position of the unlabeled defect, the processing center still marks that the high-voltage power cable has temperature abnormality, and receives environment information sent by the automatic inspection equipment, wherein the environment information comprises environment image information and heat source information around the cable and is used for determining the reason of the temperature abnormality of the high-voltage power cable.
The utility model provides a high voltage power cable local defect identification device, includes cable temperature processing module, defect position determination module, electric current response data acquisition module and defect type determination module, wherein:
the cable temperature processing module is used for automatically inspecting along the extending direction of the high-voltage power cable through the automatic inspection robot, detecting and acquiring the cable temperature, processing the cable temperature, and sending out early warning if the abnormal temperature is detected, wherein the automatic inspection robot comprises a travelling mechanism for enabling the automatic inspection robot to move on the high-voltage power cable, a temperature detection mechanism for realizing periodic temperature detection and a communication module capable of realizing wireless communication;
the defect position determining module is used for determining the distance between the area where the abnormal temperature is located and the detection starting point by using a time domain reflection detection method after the processing center receives the early warning, marking the area as a defect position, and canceling the early warning if the defect position is not marked;
the current response data acquisition module is used for applying a low-frequency electric field signal to a defect position to acquire current response data;
the defect type determining module is used for comparing the acquired current response data with parameters of a pre-stored defect model to determine the defect type of the defect position;
the automatic inspection is carried out along the extending direction of the high-voltage power cable, the cable temperature is detected and obtained, and the cable temperature is processed as follows:
periodically detecting the cable temperature within a set distance from the inspection starting point, recording the detected cable temperature, and preprocessing the detected cable temperature, wherein the preprocessing comprises deleting abnormal temperature data;
calculating a normal temperature contrast value of the high-voltage power cable according to the pretreated cable temperature;
periodically sampling the cable verification temperature after leaving the tail end point of the set distance, and comparing the cable verification temperature with the normal temperature contrast value of the cable to obtain an abnormal temperature coefficient, wherein the cable verification temperature comprises temperature data periodically obtained in the process of continuously keeping the original direction from the tail end point of the set distance for automatic inspection and temperature data periodically obtained in the process of returning to the inspection starting point after leaving the tail end point of the set distance;
if the abnormal temperature coefficient is larger than the set temperature threshold coefficient, judging that the abnormal temperature is detected, and sending out early warning;
the method for determining the distance between the region where the abnormal temperature is located and the detection starting point by using the time domain reflection detection method comprises the following steps of:
the detection starting point sends a pulse signal through a high-voltage power cable, and the sending time is recorded;
recording the receiving moment when the detection starting point receives the reflected signal;
calculating the distance from the region where the abnormal temperature is located to the detection starting point according to the time difference between the sending time and the receiving time, and marking the distance as a defect position;
the formula for calculating the distance of the region where the abnormal temperature is located from the detection start point is as follows:
，/>is the distance from the detection start point of the region where the abnormal temperature is located, wherein +.>For the moment of reception +.>For the moment of transmission->Is the reference temperature->The propagation speed of the pulse signal at the bottom,is a temperature coefficient>Is the dielectric constant of the cable insulation material +.>For the magnetic permeability of the cable->To be within a set distance->Subsampled cable temperature, +.>For the number of samplings within a set distance, +.>Is the normal temperature contrast value of the high-voltage power cable, < ->Is a normal temperature calibration factor of the high-voltage power cable.
The application has the following beneficial effects:
(1) According to the method for identifying the local defects of the high-voltage power cable, the local defect positions of the high-voltage power cable can be accurately positioned through various technical means such as temperature detection, time domain reflection, current response analysis and the like, and specific defect types can be identified according to comparison of current response data and a pre-stored defect model, so that diagnosis and maintenance of defects become more accurate and reliable, accurate defect positioning and type identification can be provided, the false alarm rate is reduced, the reliability and the practicability of an early warning system are improved, current response data are obtained, and the current response data can be analyzed by combining parameters of the pre-stored defect model, so that the specific defect types of the defect positions can be determined;
(2) According to the method for identifying the local defects of the high-voltage power cable, not only are the current response data of the cable focused, but also a plurality of factors such as temperature abnormality, environment image information, heat source information around the cable and the like are comprehensively considered, and the reason of the temperature abnormality can be accurately judged by comprehensively analyzing the multi-source information, so that false alarms are eliminated, and the reliability and the effectiveness of an early warning system are improved;
of course, it is not necessary for any one product to practice the application to achieve all of the advantages set forth above at the same time.
Drawings
FIG. 1 is a flowchart showing a method for identifying a local defect of a high-voltage power cable according to the present application.
FIG. 2 is a flow chart of the processing steps of the high voltage power cable partial defect identification method of the present application for processing the cable temperature.
FIG. 3 is a flowchart showing the steps of determining the position of an abnormal defect by using the time domain reflection detection method according to the high voltage power cable local defect identification method of the present application.
Fig. 4 is a flowchart of a process of acquiring current response data by the high voltage power cable partial defect identification method of the present application.
Detailed Description
According to the embodiment of the application, through the method and the device for identifying the local defects of the high-voltage power cable, the current response data are obtained, and the current response data can be analyzed by combining the parameters of the pre-stored defect model, so that the specific defect type of the defect position is determined.
The problems in the embodiment of the application have the following general ideas:
and automatically inspecting the high-voltage power cable along the extending direction, simultaneously monitoring and acquiring cable temperature data, processing and analyzing the cable temperature data, detecting whether an abnormal temperature condition exists, and sending an early warning signal to inform a processing center if the abnormal temperature is detected. After the processing center receives the early warning signal, a time domain reflection detection method is used, and the distance from the abnormal temperature area to the detection starting point is determined by analyzing the reflection condition of the signal, so that the defect position is accurately positioned.
And applying a low-frequency electric field signal to the defect position, exciting the current response in the cable, and acquiring current response data through a sensor and other devices. Comparing the obtained current response data with a model by using parameters of a pre-stored defect model, analyzing the difference or similarity of the current response data based on the comparison with the defect model, and determining the specific defect type of the defect position, such as the problems of bubbles, corrosion and the like in the cable according to the difference.
And according to the defect type and the positioning result, a maintenance plan and a repair strategy are formulated, and the defect type, the position and related maintenance measures are recorded for subsequent tracking and management.
Referring to fig. 1, the embodiment of the application provides a technical scheme: a method for identifying local defects of a high-voltage power cable comprises the following steps: the automatic inspection robot automatically inspects along the extending direction of the high-voltage power cable, detects and acquires the temperature of the cable, processes the temperature of the cable, and sends out early warning if detecting abnormal temperature; the automatic inspection robot can use some existing inspection robots capable of automatically walking on high-altitude high-voltage cables, for example, china patent publication No. CN216565423U discloses an automatic inspection device for high-voltage cable layer cables, which comprises a walking track, a mobile observation mechanism and a driving mechanism, wherein the driving mechanism comprises a driving motor and the walking mechanism, can enable the driving mechanism to stably walk on the cables, provides a basis for detection on the cables, and also comprises a detection mechanism, wherein the detection mechanism comprises a high-definition camera and an infrared thermal imaging camera, can realize shooting and temperature monitoring, and can be additionally provided with a temperature sensor, a contact type temperature sensor and a non-contact type temperature sensor, and can realize periodical temperature detection while automatically walking on the cables through an internal control module; after the processing center receives the early warning, a time domain reflection detection method is used for determining the distance between the abnormal temperature region and the detection starting point, the abnormal temperature region is marked as a defect position, and if the defect position is not marked, the early warning is canceled; applying a low-frequency electric field signal to the defect position, wherein the application of the low-frequency electric field signal can be realized through an application low-frequency electric field signal generating device additionally arranged on the automatic inspection robot, or the application low-frequency electric field signal generating device can be manually placed to the defect position after the defect position is obtained, so that current response data can be obtained; comparing the obtained current response data with parameters of a pre-stored defect model, and determining the defect type of the defect position.
Specifically, as shown in fig. 2, automatic inspection is performed along the extending direction of the high-voltage power cable, the cable temperature is detected and obtained, and the cable temperature is processed as follows: periodically detecting the cable temperature within a set distance from the start of inspection, recording the detected cable temperature, preprocessing the detected cable temperature, including deleting abnormal temperature data, so as to obtain accurate calculation data, prevent the abnormal temperature data from affecting the subsequent calculation of a normal temperature contrast value, and judge the abnormal temperature data by using a contrast method, for example, comparing the acquired data one by one, and considering that the temperature data is an abnormal value when a certain data is found to be obviously larger or smaller than other data, and deleting the abnormal temperature data; calculating a normal temperature contrast value of the high-voltage power cable according to the pretreated cable temperature; periodically sampling the cable verification temperature after leaving the tail end point of the set distance, and comparing the cable verification temperature with the normal temperature contrast value of the cable to obtain an abnormal temperature coefficient, wherein the cable verification temperature comprises temperature data periodically obtained in the process of continuously keeping the original direction from the tail end point of the set distance for automatic inspection and temperature data periodically obtained in the process of returning to the inspection starting point after leaving the tail end point of the set distance, judging whether the cable in the set distance needs to be returned to the starting point for abnormal temperature verification after the automatic inspection robot moves to the tail end point of the set distance, and judging whether the abnormal temperature data is deleted or not in the process of periodically detecting the cable in the set distance, if the abnormal temperature data is not deleted, the cable is not required to return to the inspection starting point, keeps the original direction, and continues to move until the cable is moved to the end point; if the abnormal temperature coefficient is larger than the set temperature threshold coefficient, judging that the abnormal temperature is detected, and giving out early warning.
In this embodiment, a distance range is set from a cable start point, periodic cable temperature detection is performed within the range, detected cable temperature data is recorded, a normal temperature contrast value of the cable is calculated based on the recorded cable temperature data, when the distance exceeds the set range, a verification stage is entered, the cable temperature is periodically sampled at an end point, the cable temperature is compared with the calculated normal temperature contrast value of the cable, an abnormal temperature coefficient is calculated, if the abnormal temperature coefficient is greater than the set temperature threshold coefficient, the system determines that the abnormal temperature is detected, and early warning information is sent.
Through setting the temperature threshold coefficient, when the abnormal temperature coefficient is detected to be larger than the threshold value, early warning information can be sent out to remind operators of possible abnormal conditions, so that the operators can take timely action, the response speed of maintenance personnel can be accelerated through automatic inspection and abnormal temperature early warning, and potential problems can be more accurately positioned and processed by the operators, and therefore maintenance efficiency is improved.
Setting a distance range from the inspection starting point, periodically detecting the temperature of the cable in the range, if the abnormal temperature is detected, directly deleting the abnormal temperature, not counting the calculation of the normal temperature contrast value of the high-voltage power cable, returning the automatic inspection robot to the inspection starting point to carry out temperature detection again after reaching the end point of the set distance, periodically sampling the temperature of the cable in the inspection process after returning, and comparing the sampling temperatures with the abnormal temperature recorded before so as to verify whether the abnormal temperature detected before exists or not and ensure that the abnormal temperature is not caused by temporary factors.
And returning to the inspection starting point to carry out temperature detection again, verifying whether the detected abnormal temperature exists truly, reducing false alarm, ensuring the reliability of the system, and judging whether the local defect exists more accurately by verifying and comparing the abnormal temperature, so that the accuracy of the whole system is improved.
Based on the scheme, the normal temperature contrast value of the high-voltage power cable can be calculated according to the detected temperature in the set distance, instead of the preset contrast value or the contrast value obtained by using an empirical method, the normal temperature of the whole cable is more accurate represented by the temperature in the set distance, because the cable in the set distance and the whole cable are in the same environment, various parameters are close, and the calculation is more accurate.
Specifically, abnormal temperature coefficientThe calculation formula of (2) is as follows:
wherein->Is->Subsampled cable validation temperature, +.>To be within a set distance->Subsampled cable temperature, +.>For the number of samplings within a set distance, +.>Verifying the value of the temperature to the normal temperature contrast of the high-voltage power cable for the cable +.>Allowable error of +.>For the normal temperature calibration factor of the high voltage power cable, < >>Is a temperature coefficient modulation factor.
In the embodiment, the temperature of multiple samples within a set distance is synthesized through a summation term in a formula, the diversity of the samples is fully considered, the stability and the accuracy of the result are improved, the normal temperature calibration factor and the allowable error of the high-voltage power cable are introduced, the temperature calibration and the error tolerance are allowed, the method is more flexible, and different conditions and changes can be adapted.
The temperature coefficient modulation factors are introduced, and the conditions of different temperature ranges can be adjusted in the calculation, so that the calculation is more suitable for the actual conditions under different temperature conditions, and the statistical terms and physical parameters in the formula are combined, so that the abnormal temperature coefficient calculation has more practical significance and accuracy, and meanwhile, the change and characteristics of temperature data are fully considered.
Specifically, as shown in fig. 3, the step of determining the distance of the abnormal temperature region from the detection start point, labeled as the defect position, using the time domain reflection detection method is as follows: the detection starting point sends a pulse signal through a high-voltage power cable, and the sending time is recorded; recording the receiving moment when the detection starting point receives the reflected signal; and calculating the distance from the abnormal temperature area to the detection starting point according to the time difference between the sending time and the receiving time, and marking the distance as the defect position.
In this embodiment, at the detection start point, a pulse signal is sent through the high-voltage power cable, the time of sending the signal is recorded, after the detection start point receives the reflected signal of the pulse signal, the time of receiving the signal is recorded, the distance between the abnormal temperature area and the detection start point is calculated according to the time difference between the time of sending the signal and the time of receiving the signal and the propagation speed of the signal in the cable, and the calculated distance between the abnormal temperature area and the detection start point is used as a defect position, so that accurate reference is provided for subsequent analysis and processing.
The time domain reflection detection method is a nondestructive detection mode, and the cable is not damaged by sending and receiving signals for analysis, so that the integrity of the cable is maintained, the instantaneity is higher, reflected signals can be obtained and analyzed in a short time, and the positioning of the abnormal temperature region can be responded quickly.
Specifically, the equation for calculating the distance of the abnormal temperature region from the detection start point is as follows:
wherein->For the distance of the region of the abnormal temperature from the detection start point, < >>For the moment of reception +.>For the moment of transmission->Is the reference temperature->The propagation speed of the pulse signal at the bottom,is a temperature coefficient>Is the dielectric constant of the cable insulation material +.>Is the magnetic permeability of the cable.
In this embodiment, a plurality of parameters such as a reception time, a transmission time, a pulse signal propagation speed at a reference temperature, a temperature coefficient, a dielectric constant of a cable insulating material, and magnetic permeability of a cable are comprehensively considered. The method can calculate more comprehensively, the distance of an abnormal temperature region can be estimated more accurately, the temperature coefficient is introduced to take the influence of temperature on the propagation speed into consideration, the method can still provide more accurate distance estimation under different temperature conditions, the related parameters such as dielectric constant and magnetic permeability are basic parameters of the physical properties of the cable, and the parameters are combined, so that the calculation has more practical significance.
In addition, a plurality of calibration factors and parameters are introduced into the formula, so that errors caused by factors such as temperature, material properties and the like are reduced, and the accuracy of distance calculation is improved.
The accurate measurement of the propagation speed is the basis for accurately calculating the distance of the abnormal temperature region, so that the temperature correction can improve the measurement accuracy, and the temperature correction can be performed by using the cable temperature obtained before, so that the propagation speed of the pulse signal can be calculated more accurately, the measurement accuracy can be improved, the error can be reduced, and meanwhile, various factors are comprehensively considered, so that the result of calculating the distance of the abnormal temperature region is more accurate and reliable.
Specifically, as shown in fig. 4, a low-frequency electric field signal is applied to the defect position, and the current response data is acquired as follows: applying a low frequency electric field signal around the defect location causing it to induce a current response in the high voltage power cable; measuring current response in real time, recording data of current change along with time, and writing into a current response curve; current response data including amplitude, phase and waveform are obtained from the current response curve.
In this embodiment, a low frequency electric field signal is applied around the defect site, which excites the current response in the cable, and these low frequency signals can be used to detect the current behavior of the defect site, and as the low frequency signal is applied, the current response is induced in the cable, and by recording the time-varying data of the current, a current response curve can be generated, which can reflect the current variation in the vicinity of the defect site.
By applying a low frequency electric field signal, current response is induced at the defect position, so that the detection and positioning of the local defect can be facilitated, the characteristic of the current response can provide information about the type and position of the defect, the detection of the current response induced by the low frequency electric field signal is a non-destructive method, damage to a cable is avoided, the integrity of the cable is facilitated to be maintained, the current response is measured in real time, the data of the current change along with time is recorded, and immediate results can be provided, so that the defect condition can be rapidly analyzed and judged.
Specifically, a calculation formula for comparing the acquired current response data with the response data of the pre-stored defect model is as follows:
wherein->For the fitness value, +.>，/>，/>Amplitude +.>Phase->And waveform->Weight factor of->，/>，/>The amplitude, phase and waveform of the defect model are respectively; and if the adaptation value approaches to the adaptation value of the defect model, determining the defect type of the defect position.
In this embodiment, the matching degree is obtained by calculating the relationship between the feature weight factor and the feature value, so that the matching condition of the current response data and the defect model can be reflected, and compared with the preset matching value, if the matching degree value approaches to the matching value of the defect model, the defect type of the defect position can be determined to be consistent with the model.
The calculation formula integrates a plurality of characteristics such as amplitude, phase and waveform, which is helpful for more comprehensively analyzing the matching degree between the current response data and the defect model, providing more accurate defect type judgment, and introducing weight factors which allow weighting according to the importance of the amplitude, the phase and the waveform, and are helpful for balancing balance among different characteristics so as to obtain more accurate matching results.
Specifically, after the pre-warning is canceled at the position of the unlabeled defect, the processing center still marks that the high-voltage power cable has temperature abnormality, receives environment information sent by the automatic inspection equipment, wherein the environment information comprises environment image information and heat source information around the cable and is used for determining the reason of the temperature abnormality of the high-voltage power cable.
In this embodiment, if the early warning is canceled when the defect position is not marked, which means that the processing center considers that there is no actual defect, but still there is an abnormal situation, the processing center receives the environmental information sent by the automatic inspection device, including the environmental image information and the heat source information around the cable, and further analyzes the temperature abnormality of the high-voltage power cable based on the received environmental information. And comparing the abnormal condition of the cable temperature with the environment image and the heat source information, and comprehensively judging whether other abnormal reasons exist.
The utility model provides a high voltage power cable local defect identification device, includes cable temperature processing module, defect position determination module, electric current response data acquisition module and defect type determination module, wherein:
the cable temperature processing module is used for automatically inspecting along the extending direction of the high-voltage power cable through the automatic inspection robot, detecting and acquiring the cable temperature, processing the cable temperature, and sending out early warning if the abnormal temperature is detected, wherein the automatic inspection robot comprises a travelling mechanism for enabling the automatic inspection robot to move on the high-voltage power cable, a temperature detection mechanism for realizing periodic temperature detection and a communication module capable of realizing wireless communication;
the defect position determining module is used for determining the distance between the area where the abnormal temperature is located and the detection starting point by using a time domain reflection detection method after the processing center receives the early warning, marking the area as a defect position, and canceling the early warning if the defect position is not marked;
the current response data acquisition module is used for applying a low-frequency electric field signal to the defect position to acquire current response data;
the defect type determining module is used for comparing the acquired current response data with parameters of a pre-stored defect model to determine the defect type of the defect position;
automatic inspection is carried out along the extending direction of the high-voltage power cable, the temperature of the cable is detected and obtained, and the cable temperature is processed as follows:
periodically detecting the cable temperature within a set distance from the inspection starting point, recording the detected cable temperature, and preprocessing the detected cable temperature, wherein the preprocessing comprises deleting abnormal temperature data;
calculating a normal temperature contrast value of the high-voltage power cable according to the pretreated cable temperature;
periodically sampling the cable verification temperature after leaving the tail end point of the set distance, and comparing the cable verification temperature with the normal temperature contrast value of the cable to obtain an abnormal temperature coefficient, wherein the cable verification temperature comprises temperature data periodically obtained in the process of continuously keeping the original direction for automatic inspection after leaving the tail end point of the set distance and temperature data periodically obtained in the process of returning to the inspection starting point after leaving the tail end point of the set distance;
if the abnormal temperature coefficient is larger than the set temperature threshold coefficient, judging that the abnormal temperature is detected, and sending out early warning;
the method for determining the distance between the region where the abnormal temperature is located and the detection starting point by using the time domain reflection detection method comprises the following steps of:
the detection starting point sends a pulse signal through a high-voltage power cable, and the sending time is recorded;
recording the receiving moment when the detection starting point receives the reflected signal;
calculating the distance from the region where the abnormal temperature is located to the detection starting point according to the time difference between the sending time and the receiving time, and marking the distance as a defect position;
the formula for calculating the distance of the region where the abnormal temperature is located from the detection start point is as follows:
，/>is the distance from the detection start point of the region where the abnormal temperature is located, wherein +.>For the moment of reception +.>For the moment of transmission->Is the reference temperature->The propagation speed of the pulse signal at the bottom,is a temperature coefficient>Is the dielectric constant of the cable insulation material +.>For the magnetic permeability of the cable->To be within a set distance->Subsampled cable temperature, +.>For the number of samplings within a set distance, +.>Is the normal temperature contrast value of the high-voltage power cable, < ->Is a normal temperature calibration factor of the high-voltage power cable.
In summary, the present application has at least the following effects:
through various technical means, such as temperature detection, time domain reflection, current response analysis and the like, the local defect position of the high-voltage power cable can be accurately positioned, and specific defect types can be identified according to comparison of current response data and a pre-stored defect model, so that diagnosis and maintenance of defects become more accurate and reliable.
Not only the current response data of the cable is concerned, but also a plurality of factors such as temperature abnormality, environment image information, heat source information around the cable and the like are comprehensively considered, and the reason of the temperature abnormality can be accurately judged by comprehensively analyzing the multi-source information, so that false alarms are eliminated, and the credibility and the effectiveness of the early warning system are improved.
The method adopts a nondestructive detection mode, judges the defect condition through signal response in the cable, does not cause extra damage to the cable, is excellent in real-time performance, can rapidly acquire, analyze and process data, provides powerful support for timely maintenance and repair, can provide accurate defect positioning and type identification, reduces false alarm rate, and improves reliability and practicability of an early warning system.
It will be appreciated by those skilled in the art that embodiments of the present application 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 systems, apparatuses (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.
While preferred embodiments of the present application have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. It is therefore intended that the following claims be interpreted as including the preferred embodiments and all such alterations and modifications as fall within the scope of the application.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present application without departing from the spirit or scope of the application. Thus, it is intended that the present application also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (6)
1. The method for identifying the local defect of the high-voltage power cable is characterized by comprising the following steps of:
the automatic inspection robot is used for automatically inspecting along the extending direction of the high-voltage power cable, detecting and acquiring the cable temperature, processing the cable temperature, and sending out early warning if the abnormal temperature is detected, wherein the automatic inspection robot comprises a travelling mechanism for enabling the automatic inspection robot to move on the high-voltage power cable, a temperature detection mechanism for realizing periodic temperature detection and a communication module capable of realizing wireless communication;
after the processing center receives the early warning, determining the distance between the area where the abnormal temperature is located and the detection starting point by using a time domain reflection detection method, marking the area as a defect position, and if the defect position is not marked, canceling the early warning;
applying a low-frequency electric field signal at the defect position to obtain current response data;
comparing the obtained current response data with parameters of a pre-stored defect model to determine the defect type of the defect position;
the automatic inspection is carried out along the extending direction of the high-voltage power cable, the cable temperature is detected and obtained, and the cable temperature is processed as follows:
periodically detecting the cable temperature within a set distance from the inspection starting point, recording the detected cable temperature, and preprocessing the detected cable temperature, wherein the preprocessing comprises deleting abnormal temperature data;
calculating a normal temperature contrast value of the high-voltage power cable according to the pretreated cable temperature;
periodically sampling the cable verification temperature after leaving the tail end point of the set distance, and comparing the cable verification temperature with the normal temperature contrast value of the cable to obtain an abnormal temperature coefficient, wherein the cable verification temperature comprises temperature data periodically obtained in the process of continuously keeping the original direction from the tail end point of the set distance for automatic inspection and temperature data periodically obtained in the process of returning to the inspection starting point after leaving the tail end point of the set distance;
if the abnormal temperature coefficient is larger than the set temperature threshold coefficient, judging that the abnormal temperature is detected, and sending out early warning;
the method for determining the distance between the region where the abnormal temperature is located and the detection starting point by using the time domain reflection detection method comprises the following steps of:
the detection starting point sends a pulse signal through a high-voltage power cable, and the sending time is recorded;
recording the receiving moment when the detection starting point receives the reflected signal;
calculating the distance from the region where the abnormal temperature is located to the detection starting point according to the time difference between the sending time and the receiving time, and marking the distance as a defect position;
the formula for calculating the distance of the region where the abnormal temperature is located from the detection start point is as follows:
wherein->For the distance of the region of the abnormal temperature from the detection start point, < >>For the moment of reception +.>For the moment of transmission->Is the reference temperature->Pulse signal propagation speed, < >>Is a temperature coefficient>Is the dielectric constant of the cable insulation material +.>For the magnetic permeability of the cable->To be within a set distance->Subsampled cable temperature, +.>For the number of samplings within a set distance, +.>Is the normal temperature contrast value of the high-voltage power cable, < + >>Is a normal temperature calibration factor of the high-voltage power cable.
2. The method for identifying local defects of high-voltage power cable according to claim 1, wherein the abnormal temperature coefficient is recorded asThe calculation formula is as follows: />Wherein->Is->Subsampled cable validation temperature, +.>Verifying the comparison value of the temperature and the normal temperature of the high-voltage power cable for the cableAllowable error of +.>For the normal temperature calibration factor of the high voltage power cable, < >>Is a temperature coefficient modulation factor.
3. The method for identifying local defects of high-voltage power cable according to claim 1, wherein the step of applying a low-frequency electric field signal to the defect position and obtaining current response data comprises the steps of:
applying a low frequency electric field signal around the defect location causing it to induce a current response in the high voltage power cable;
measuring current response in real time, recording data of current change along with time, and forming a current response curve;
current response data including amplitude, phase and waveform are obtained from the current response curve.
4. A method for identifying a local defect in a high voltage power cable according to claim 3, wherein the calculation formula for comparing the obtained current response data with the response data of a pre-stored defect model is as follows:
wherein->For the fitness value, +.>，/>，/>Amplitude +.>Phase->And waveform->Weight factor of->，/>，/>The amplitude, phase and waveform of the defect model are respectively;
and if the adaptation value approaches to the adaptation value of the defect model, determining the defect type of the defect position.
5. The method for identifying the local defect of the high-voltage power cable according to claim 1, wherein after the position of the unlabeled defect is canceled and pre-warned, the processing center still marks the temperature abnormality of the high-voltage power cable, receives environment information sent by automatic inspection equipment, wherein the environment information comprises environment image information and heat source information around the cable and is used for determining the reason of the temperature abnormality of the high-voltage power cable.
6. The device for identifying the local defect of the high-voltage power cable is characterized by comprising a cable temperature processing module, a defect position determining module, a current response data acquisition module and a defect type determining module, wherein:
the cable temperature processing module is used for automatically inspecting along the extending direction of the high-voltage power cable through the automatic inspection robot, detecting and acquiring the cable temperature, processing the cable temperature, and sending out early warning if the abnormal temperature is detected, wherein the automatic inspection robot comprises a travelling mechanism for enabling the automatic inspection robot to move on the high-voltage power cable, a temperature detection mechanism for realizing periodic temperature detection and a communication module capable of realizing wireless communication;
the defect position determining module is used for determining the distance between the area where the abnormal temperature is located and the detection starting point by using a time domain reflection detection method after the processing center receives the early warning, marking the area as a defect position, and canceling the early warning if the defect position is not marked;
the current response data acquisition module is used for applying a low-frequency electric field signal to a defect position to acquire current response data;
the defect type determining module is used for comparing the acquired current response data with parameters of a pre-stored defect model to determine the defect type of the defect position;
the automatic inspection is carried out along the extending direction of the high-voltage power cable, the cable temperature is detected and obtained, and the cable temperature is processed as follows:
periodically detecting the cable temperature within a set distance from the inspection starting point, recording the detected cable temperature, and preprocessing the detected cable temperature, wherein the preprocessing comprises deleting abnormal temperature data;
calculating a normal temperature contrast value of the high-voltage power cable according to the pretreated cable temperature;
periodically sampling the cable verification temperature after leaving the tail end point of the set distance, and comparing the cable verification temperature with the normal temperature contrast value of the cable to obtain an abnormal temperature coefficient, wherein the cable verification temperature comprises temperature data periodically obtained in the process of continuously keeping the original direction from the tail end point of the set distance for automatic inspection and temperature data periodically obtained in the process of returning to the inspection starting point after leaving the tail end point of the set distance;
if the abnormal temperature coefficient is larger than the set temperature threshold coefficient, judging that the abnormal temperature is detected, and sending out early warning;
the method for determining the distance between the region where the abnormal temperature is located and the detection starting point by using the time domain reflection detection method comprises the following steps of:
the detection starting point sends a pulse signal through a high-voltage power cable, and the sending time is recorded;
recording the receiving moment when the detection starting point receives the reflected signal;
calculating the distance from the region where the abnormal temperature is located to the detection starting point according to the time difference between the sending time and the receiving time, and marking the distance as a defect position;
the formula for calculating the distance of the region where the abnormal temperature is located from the detection start point is as follows:
wherein->For the distance of the region of the abnormal temperature from the detection start point, < >>For the moment of reception +.>For the moment of transmission->Is the reference temperature->Pulse signal propagation speed, < >>Is a temperature coefficient>Is the dielectric constant of the cable insulation material +.>For the magnetic permeability of the cable->To be within a set distance->Subsampled cable temperature, +.>For the number of samplings within a set distance, +.>Is the normal temperature contrast value of the high-voltage power cable, < + >>Is a normal temperature calibration factor of the high-voltage power cable.
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| CN117890740B (en) * | 2024-03-14 | 2024-06-21 | 云南电投绿能科技有限公司 | Partial discharge positioning method, device and equipment for power station cable and storage medium |
| CN118243240B (en) * | 2024-05-30 | 2024-08-16 | 湖南华菱线缆股份有限公司 | Hot defect detection system and method for electrified cable |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4411536A (en) * | 1981-05-29 | 1983-10-25 | Raychem Corporation | Bi-directional temperature excursion sensing and locating apparatus |
| AU5790194A (en) * | 1993-03-18 | 1994-09-22 | Telstra Corporation Limited | A method and apparatus for inducing a temporary localised transmission loss in a telecommunications cable |
| US5717337A (en) * | 1996-01-16 | 1998-02-10 | Kelly; John M. | Time-domain reflectometer based measurement system |
| GB0112113D0 (en) * | 2001-05-17 | 2001-07-11 | Paddison Jason | Method for detecting faults in electrical cables |
| CN103499768A (en) * | 2013-07-03 | 2014-01-08 | 甘肃省电力公司兰州供电公司 | Power cable real-time state monitoring and operation management system and measuring method of temperature of cable |
| CN106323499A (en) * | 2015-07-08 | 2017-01-11 | 中国电力科学研究院 | Distributed Raman temperature sensor temperature compensation method |
| CN108061843A (en) * | 2017-12-27 | 2018-05-22 | 温岭市创嘉信息科技有限公司 | A kind of equipment for Cable Fault Location |
| CN109904932A (en) * | 2019-04-11 | 2019-06-18 | 中国铁路设计集团有限公司 | A kind of tractive power supply system 27.5kV high-tension cable on-line condition monitoring method and monitoring device |
| CN209590197U (en) * | 2018-02-09 | 2019-11-05 | 中国人民解放军海军航空大学 | A kind of cable fault positioning device based on time-domain pulse reflection method |
| CN115372747A (en) * | 2022-09-14 | 2022-11-22 | 国网江苏省电力有限公司电力科学研究院 | Cable aging degradation state detection method and aging monitoring device |
| CN116184117A (en) * | 2023-02-23 | 2023-05-30 | 国网陕西省电力有限公司西安供电公司 | Cable local defect positioning method, system, equipment and medium |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10360485B4 (en) * | 2003-12-22 | 2005-11-24 | Airbus Deutschland Gmbh | Method and device for temperature monitoring along a measuring line |
| US7057401B2 (en) * | 2004-03-23 | 2006-06-06 | Pass & Seymour, Inc. | Electrical wiring inspection system |
| DE102017213931A1 (en) * | 2017-08-10 | 2019-02-14 | Leoni Kabel Gmbh | Device and method for determining a temperature-dependent impedance curve along an electrical conductor |
| GB201913194D0 (en) * | 2019-09-12 | 2019-10-30 | Welldata Subsurface Surveillance Systems Ltd | Measurement method and apparatus |
-
2023
- 2023-09-04 CN CN202311130112.4A patent/CN116879683B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4411536A (en) * | 1981-05-29 | 1983-10-25 | Raychem Corporation | Bi-directional temperature excursion sensing and locating apparatus |
| AU5790194A (en) * | 1993-03-18 | 1994-09-22 | Telstra Corporation Limited | A method and apparatus for inducing a temporary localised transmission loss in a telecommunications cable |
| US5717337A (en) * | 1996-01-16 | 1998-02-10 | Kelly; John M. | Time-domain reflectometer based measurement system |
| GB0112113D0 (en) * | 2001-05-17 | 2001-07-11 | Paddison Jason | Method for detecting faults in electrical cables |
| CN103499768A (en) * | 2013-07-03 | 2014-01-08 | 甘肃省电力公司兰州供电公司 | Power cable real-time state monitoring and operation management system and measuring method of temperature of cable |
| CN106323499A (en) * | 2015-07-08 | 2017-01-11 | 中国电力科学研究院 | Distributed Raman temperature sensor temperature compensation method |
| CN108061843A (en) * | 2017-12-27 | 2018-05-22 | 温岭市创嘉信息科技有限公司 | A kind of equipment for Cable Fault Location |
| CN209590197U (en) * | 2018-02-09 | 2019-11-05 | 中国人民解放军海军航空大学 | A kind of cable fault positioning device based on time-domain pulse reflection method |
| CN109904932A (en) * | 2019-04-11 | 2019-06-18 | 中国铁路设计集团有限公司 | A kind of tractive power supply system 27.5kV high-tension cable on-line condition monitoring method and monitoring device |
| CN115372747A (en) * | 2022-09-14 | 2022-11-22 | 国网江苏省电力有限公司电力科学研究院 | Cable aging degradation state detection method and aging monitoring device |
| CN116184117A (en) * | 2023-02-23 | 2023-05-30 | 国网陕西省电力有限公司西安供电公司 | Cable local defect positioning method, system, equipment and medium |
Non-Patent Citations (2)
| Title |
|---|
| Development of cable fault location method using fiber optic distributed temperature sensor;Naoki Takinami 等;《Electrical Engineering in Japan》;第1-12页 * |
| 基于改进时频域反射法的电力电缆局部缺陷定位;王昱皓 等;《中国电机工程学报》;第2584-2593页 * |
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