CN111814349A - Big data-based power system insulator monitoring and evaluating system - Google Patents
Big data-based power system insulator monitoring and evaluating system Download PDFInfo
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Abstract
The invention discloses a big data-based power system insulator monitoring and evaluating system, which comprises a defect detection module, a bearing capacity simulation analysis module, an environmental parameter acquisition module, an additional bearing detection module, an elastic additional analysis module, a model evolution module, a crack correction module and a management evaluation module, wherein the defect detection module is used for detecting the defect of a power system insulator; according to the method, the sudden change deformation coefficients corresponding to the temperature, the wind speed and the accumulated snow are analyzed through the temperature change, the wind speed and the pressure of the accumulated snow on the insulator in the environment, the remaining service life evaluation time of the insulator is estimated and analyzed through the bending moment, the temperature, the wind speed and the sudden change deformation coefficients corresponding to the accumulated snow of the insulator and the change quantity of the crack parameters of the insulator in two time interval periods, the remaining service life evaluation time of the insulator can be accurately counted, the service life of the insulator is fully utilized, the replacement frequency is reduced, the labor amount of workers for replacing the insulator is reduced, and the continuous stable and safe time of a power system is guaranteed.
Description
Technical Field
The invention belongs to the technical field of insulators of electric power systems, and relates to an insulator monitoring and evaluating system of an electric power system based on big data.
Background
The insulator is a main electric power accessory in an electric power system, is a special insulating control and plays an important role in the electric power system, is installed on conductors with different electric potentials or devices which can bear the voltage and mechanical stress between the conductors and a grounding component, is various in types and different in shape, and is large in difference along with the appearance of different types of insulators, but consists of two parts, namely an insulating part and a connecting hardware fitting.
The main function of the insulator is to realize electrical insulation and mechanical fixation, so that the insulator meets the requirements of different electrical and mechanical properties, such as no breakdown or flashover along the surface under the action of specified operating voltage, lightning overvoltage and internal overvoltage; under the action of specified long-term and short-term mechanical load, no damage and damage are generated; after long-term operation under the specified mechanical and electrical loads and various environmental conditions, no significant deterioration occurs.
The existing insulator detects each insulator through a manual handheld ultrasonic flaw detector to obtain the crack depth and length of the insulator, but because of the periodicity of manual detection, the crack condition of the insulator in two detection periods can not be accurately judged, once the crack of the insulator reaches the replacement requirement before the next detection, large-area power failure of a bus, a transformer substation or a power plant can be caused, the safety and the stability of the whole power system are directly influenced, meanwhile, the prior art can not judge the influence degree of parameters in the environment on the service life of the insulator according to the specific parameter condition in the environment where the insulator is located, and further can not judge the residual service life of the insulator, so that the insulator can not be replaced in time, and the problem of poor detection accuracy exists, in addition, when the insulator is not replaced, or the insulator reaches the replacement condition, the insulator can not be replaced in time, the replacement frequency of personnel is wasted, further, the insulator which can be continuously used is wasted, the replaced insulator cannot be damaged, and the insulator which does not reach the replacement condition is frequently replaced, so that the normal operation of a power system is influenced.
Disclosure of Invention
The invention aims to provide a power system insulator monitoring and evaluating system based on big data, which solves the problems in the prior art.
The purpose of the invention can be realized by the following technical scheme:
a big data-based power system insulator monitoring and evaluating system comprises a defect detection module, a bearing capacity simulation analysis module, an environmental parameter acquisition module, an additional bearing detection module, an elastic additional analysis module, a model evolution module, a crack correction module and a management evaluation module;
the defect detection module is an ultrasonic flaw detector, ultrasonic waves are sent to an insulator to be detected through an ultrasonic probe of the ultrasonic flaw detector, reflected wave pulse waveforms are obtained by the ultrasonic waves through reflection of an insulator, the reflected wave pulse waveforms are compared, crack positions, crack depths and crack lengths in the detected insulator are obtained, and the crack depths and the crack lengths in the detected insulator are sent to the crack correction module;
the bearing force simulation analysis module is used for acquiring the installation basic parameter information of the post insulator at the end part of the pipe trunk, inputting the installation basic parameter information into the bearing simulation formula according to the installation basic parameter information of the post insulator, simulating the bending moment of the end face of the post insulator under the condition of not being influenced by other external forces, and sending the simulated bending moment of the end face of the post insulator to the management evaluation module;
the environment parameter acquisition module comprises a wind speed detection unit and a temperature detection unit, the wind speed detection unit is used for acquiring the wind speed borne by the insulator in the region in real time and sending the acquired wind speed borne by the insulator to the elastic additional analysis module, and the temperature detection unit is used for acquiring the temperature in the environment where the insulator is located and sending the acquired temperature borne by the insulator to the additional bearing detection module and the elastic additional analysis module respectively;
the additional bearing detection module is used for acquiring the snow fall amount on the insulator in real time, receiving the temperature sent by the environment parameter acquisition module, simulating the additional gravity of the accumulated snow on the insulator along with the change of the environment temperature according to the snow fall amount on the insulator and the temperature change condition of the environment where the insulator is located, and sending the detected additional gravity of the accumulated snow on the insulator to the elastic additional analysis module;
the elastic additional analysis module is used for receiving the real-time wind speed and the temperature of the environment where the insulator is located, which are sent by the environment parameter acquisition module, comparing the wind speed with a set wind speed lower limit threshold value, screening out the wind speed greater than the wind speed lower limit threshold value, counting the real-time bearing capacity of the insulator under the real-time wind speed according to the wind speed, analyzing the received temperature, screening out the highest temperature and the lowest temperature in the same day, counting the temperature change rate, receiving the additional gravity of the accumulated snow on the insulator, which is sent by the additional bearing detection module, screening out the maximum additional gravity and the accumulated time TPx of the additional gravity of the accumulated snow on the insulator under each additional force level, and applying the real-time bearing capacity, the highest temperature and the lowest temperature, the temperature change rate and the maximum additional gravity on the accumulated snow on the insulator under the wind speed, The accumulated time length of the additional gravity under each additional force level is sent to a model evolution module;
the model evolution module simulates wind power, temperature and snow accumulation parameter information in the environment where the insulator is located through experiments, and conducts massive analysis on environment parameters of the insulator in the process that the insulator is installed in a crack and reaches the use limit, so as to obtain sudden change deformation coefficients beta 1, beta 2 and beta 3 corresponding to the wind power, the temperature and the snow accumulation in the use process of the insulator to be detected through simulation, receive real-time applied bearing capacity, the daily highest temperature and lowest temperature and temperature change rate of the insulator under the wind speed sent by the elastic additional analysis module, the maximum additional gravity of the snow accumulation on the insulator and the accumulated time of the additional gravity under each additional force level, analyze the additional evolution comprehensive influence coefficient of the environment parameters through a simulation evolution model formula, and respectively send the additional evolution comprehensive influence coefficient to the management evaluation module and the crack correction module;
the crack correction module is used for receiving the crack depth and the crack length of the insulator detection sent by the defect detection module, extracting the crack depth and the crack length of the two detections, wherein the time interval corresponding to the two detections is r, receiving an additional evolution comprehensive influence coefficient corresponding to the environmental parameter in the environment where the insulator is located sent by the model evolution module, counting an additional influence coefficient psi corresponding to the insulator under the influence of the temperature, the wind power and the snow in the environment where the insulator is located by using a crack correction formula, and sending the detected additional influence coefficient, the crack depth and the crack length corresponding to the last detection of the screened crack to the management evaluation module,
the management evaluation module receives the bending moment on the end face of the insulator sent by the bearing capacity simulation analysis module, receives an additional influence coefficient sent by the crack correction module and screens out the crack depth and the crack length corresponding to the last detection of the crack, receives an additional evolution comprehensive influence coefficient of an environmental parameter sent by the model evolution module, extracts the upper limit depth and the upper limit length of the crack corresponding to the cut-off state of the crack life, predicts the remaining life evaluation duration K when the crack on the insulator reaches the upper limit parameter under the current environmental interference according to the additional influence coefficient influencing the insulator life, the additional evolution comprehensive influence coefficient of the environmental parameter, the crack depth and the crack length, and counts the duration of the insulator continuing use from the crack length Z2 and the depth Y2 of the detected insulator, and the management evaluation module compares the duration of the insulator continuing use with the life evaluation duration, And analyzing to judge whether the insulator with the crack is replaced or not, sending the serial number of the insulator to be replaced to the background computer management terminal, and screening the position corresponding to the serial number of the insulator by the rear computer management terminal through the serial number of the insulator.
Further, the bearing simulation formula
The mass of the pipe bus per unit length m1, the mass of the damping wire per unit length m2, the mass of the pipe bus metal tool m3, the mass of the down conductor m4, the mass of the insulator body m5, the distance from the insulator body to the root part of the insulator s1 and the height of the bus body s2, wherein g is 9.8m/s2。
Further, the additional load detection module analyzes the additional gravity of the snowfall quantity borne by the insulator, and the method comprises the following steps:
a1, extracting the snowfall amount covered on the insulator;
a2, screening the ambient temperature around the insulator at fixed points, and respectively extracting temperature values corresponding to 0 point, 4 points, 8 points, 12 points, 16 points and 20 points;
a3, respectively counting the highest temperature, the lowest temperature and the average temperature in adjacent time points to form a temperature array D [ a ] [ b ], wherein a is equal to 1,2,3,4,5 and 6 and is respectively represented by time intervals of 0 point to 4 points, 4 points to 8 points, 8 points to 12 points, 12 points to 16 points, 16 points to 20 points, 20 points to 0 points, and b is equal to 1,2 and 3 and is respectively the highest temperature, the lowest temperature and the average temperature;
a4, judging whether the highest temperature between each adjacent time point is greater than 0 ℃, if so, executing the step A5, if not, counting the additional gravity G applied to the insulator by the accumulated snow in the adjacent time pointsi＝Gi-1*(1+η)，Gi-1Expressed as the additional gravitational force, G, of the accumulated snow on the insulator in the i-1 th adjacent time pointiThe additional gravity of the accumulated snow on the insulator in the ith adjacent time point is expressed, and eta is expressed as the coefficient of the accumulated snow absorbing water vapor in the air;
a5, judging whether the lowest temperature in the adjacent time points is greater than 0 ℃, if so, extracting the average temperature in the adjacent time points, extracting the fusion coefficient corresponding to the average temperature, and counting the additional gravity G applied to the insulator by the accumulated snow in the adjacent time pointsi＝Gi-1And mu (1-mu), wherein mu is a coefficient of the accumulated snow absorbing water vapor in the air, if the accumulated snow is less than 0 ℃, respectively counting the time greater than 0 ℃ and the time less than 0 ℃ in the adjacent time points, and counting the additional gravity of the accumulated snow in the adjacent time points on the insulator
tηExpressed as the time, t, of less than 0 ℃ in the adjacent time pointμExpressed as the time greater than 0 ℃ in this adjacent time point.
Further, the calculation formula of the real-time applied bearing capacity of the insulator under the real-time wind speed is as follows:
f is real-time applied bearing capacity under the wind speed v, and the unit kN/m2 is the wind speed v.
Further, the simulation evolution model formula is as follows:
r is the accumulated days of insulator monitoring, tau is the comprehensive influence coefficient of additional evolution of the environmental parameters on the insulator, beta 1, beta 2 and beta 3 are obtained by experimental simulation and are respectively the sudden change deformation coefficients corresponding to wind power, temperature and accumulated snow, F' is the average value of the additional bearing capacity corresponding to the wind speed with the wind speed larger than the wind speed lower limit threshold, FmaxAdditional bearing capacity, T, corresponding to the maximum wind speed bearable by the insulatorv > v lower thresholdIs the accumulated time duration of wind speed with wind speed greater than the lower wind speed threshold, TPx is the accumulated time duration at the xth additional level,
for the accumulated duration of the insulator monitoring process, x is 1,2,3,4, WHj and WLj is the highest temperature and the lowest temperature respectively applied to the insulator on the j day, WH is provided withAnd WL is provided withIs the maximum and minimum temperature, gamma, that the insulator can withstandWAs rate of change of temperature, Δ γThreshold(s)Maximum rate of temperature change, G, that the insulator can withstandmaxFor maximum additional application of gravity, G, to the insulator by accumulated snowThreshold valueAnd Gx is the average additional applied gravity corresponding to the xth additional level, qx is the weight coefficient corresponding to the average additional applied gravity at the xth additional level, and q1 < q2 < q3 < q4, and q1 is 0.
Further, the crack correction formula
Y1 and Y2 are respectively the crack depth detected in the previous r days and the corresponding crack depth after r seconds, tau is an additional evolution comprehensive influence coefficient of the environmental parameters on the insulator, phi is a proportionality coefficient of the crack depth on the insulator life, phi is less than 1, and Z2 and Z1 are respectively the crack depth length detected in the previous r days and the corresponding crack length after r days.
Further, an insulatorRemaining life evaluation duration when cracks on the insulator reach an upper limit parameter under the interference of the current environment
K represents the residual service life evaluation duration of the insulator influenced by the current environment, M represents the bending moment applied to the end face of the insulator, and M represents the residual service life evaluation durationThreshold(s)Is the ultimate bending moment, Y, borne by the end face of the insulatorThreshold(s)And ZThreshold(s)Respectively expressed as the upper limit depth and the upper limit length of the crack corresponding to the insulator, psi is expressed as an additional influence coefficient, tau is expressed as an additional evolution comprehensive influence coefficient of the environmental parameter on the insulator,
further, the management evaluation module analyzes the remaining service life evaluation duration of the insulator and judges whether the insulator needs to be replaced, and the method comprises the following steps:
b1, judging whether the accumulated continuous use time of the insulator is equal to the service life evaluation time K or not, and if so, sending a crack detection instruction to the defect detection module;
b2, acquiring the crack depth and the crack length fed back by the crack detection module;
b3, comparing the crack depth and the crack length with 0.9 time of crack upper limit depth and 0.9 time of crack upper limit length respectively, and if the crack depth is greater than 0.9 time of crack upper limit depth or the crack length is greater than 0.9 time of crack upper limit length, extracting the serial number of the insulator to be replaced to a background computer management terminal by a management evaluation module;
b4, if the crack depth is smaller than 0.9 times of the crack upper limit depth and the crack length is smaller than 0.9 times of the crack upper limit length, the remaining life evaluation duration calculation formula of the insulator recalculates the life evaluation duration corresponding to the insulator under the current environmental interference;
b5, continuously counting the accumulated continuous use time of the insulators again, repeating the steps B1-B4 until the crack depth is larger than 0.9 time of the crack upper limit depth or the crack length is larger than 0.9 time of the crack upper limit length, and extracting the serial number of the insulator to be replaced to the background computer management terminal.
The invention has the beneficial effects that:
the invention provides a power system insulator monitoring and evaluating system based on big data, which analyzes the influence of the temperature, the wind speed and the snow cover parameters in the external environment of an insulator through a bearing force simulation analysis module, an environment parameter acquisition module, an additional bearing detection module, an elastic additional analysis module, a management evaluation module and the like, sequentially counts the pressure of the wind power and the snow cover on the insulator, analyzes the sudden change deformation coefficients corresponding to the temperature, the wind speed and the snow cover through the temperature change and the wind speed in the environment and the pressure of the snow cover on the insulator, comprehensively predicts and analyzes the residual service life evaluation time when the crack on the insulator reaches the upper limit parameter under the current environmental interference through the big data through the sudden change deformation coefficients corresponding to the self bending moment, the temperature, the wind speed and the snow cover of the insulator and the change quantity of the crack parameters in two time intervals of the insulator, the method has the advantages that the length of the evaluation time of the residual life corresponding to the insulator under the condition of continuous interference of the current environment can be accurately counted, reliable data can be conveniently provided for insulator replacement, the service life of the insulator is fully utilized, the replacement frequency is reduced, the labor amount of workers for replacing the insulator is reduced, and the length of the continuous stability and safety time of the power system is ensured.
According to the invention, the additional influence coefficients of the insulator, which are influenced by other factors besides the influence of the temperature, the wind power and the accumulated snow in the current environment, can be counted by the crack correction module, the corresponding additional influence coefficients of the insulator, which are influenced by other factors, can be accurately analyzed by big data, the comprehensive influence of environmental parameters on the insulator is improved, the correction of the remaining service life evaluation duration when the crack on the insulator reaches the upper limit parameter under the influence of the current environment on the insulator is counted at the later stage is facilitated, and the precision of the statistics of the remaining service life evaluation duration of the insulator is further improved.
According to the invention, the remaining service life evaluation time when the cracks on the insulator reach the upper limit parameter under the interference of the current environment in the management evaluation module is counted in sequence, the duration of the continuous use of the insulator after detection is counted in sequence, the counted duration of the continuous use of the insulator is compared with the service life evaluation time, so that the current crack depth and the length of the insulator are obtained, and the current crack depth and the length of the insulator are respectively compared with the 0.9-time upper limit depth and the length of the crack to judge whether the insulator meets the replacement requirement or whether the insulator can be used continuously, so that the service life of the insulator can be effectively utilized, the phenomenon that the insulator cannot be fully utilized due to untimely or early replacement of the insulator is avoided, the replacement frequency of the insulator and the workload of a replacement worker are increased, and the replacement cost of the insulator is wasted.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic diagram of a power system insulator monitoring and evaluation system based on big data according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, a power system insulator monitoring and evaluation system based on big data includes a defect detection module, a bearing capacity simulation analysis module, an environmental parameter acquisition module, an additional bearing detection module, an elastic additional analysis module, a model evolution module, a crack correction module, and a management evaluation module.
The defect detection module is an ultrasonic flaw detector, ultrasonic waves are sent to the insulator to be detected through an ultrasonic probe of the ultrasonic flaw detector, reflected wave pulse waveforms are obtained through reflection of the ultrasonic waves by insulators, the reflected wave pulse waveforms are compared, crack positions, crack depths and crack lengths in the detected insulator are obtained, the crack depths and the crack lengths in the detected insulator are sent to the crack correction module, and the insulator detected by the defect detection module is an insulator which meets factory requirements and is normal and nondestructive in the installation process.
The insulators in the transformer substation are numbered and are respectively 1,2 and 3.
The bearing force simulation analysis module is used for acquiring the installation basic parameter information of the post insulator at the end part of the pipe main body, inputting the installation basic parameter information into the bearing simulation formula according to the installation basic parameter information of the post insulator, simulating the bending moment of the end face of the post insulator under the condition of not being influenced by other external forces, and sending the simulated bending moment of the end face of the post insulator to the management evaluation module.
The basic installation parameter information comprises a unit length pipe bus mass m1, a unit length damping wire mass m2, a pipe bus metal mass m3, a down lead mass m4, an insulator body mass m5, a distance s1 from an insulator body to an insulator root easy-fracture surface and a bus body height s2, wherein g is 9.8m/s2。
Bearing simulation formula
The environment parameter acquisition module comprises a wind speed detection unit and a temperature detection unit, the wind speed detection unit is used for acquiring the wind speed borne by the insulator in the region in real time and sending the acquired wind speed borne by the insulator to the elastic additional analysis module, and the temperature detection unit is used for acquiring the temperature in the environment where the insulator is located and sending the acquired temperature borne by the insulator to the additional bearing detection module and the elastic additional analysis module respectively.
The additional bearing detection module is used for collecting the snow fall amount on the insulator in real time, receiving the temperature sent by the environmental parameter collection module, simulating the additional gravity of the accumulated snow on the insulator along with the change of the environmental temperature according to the snow fall amount on the insulator and the temperature change condition of the environment where the insulator is located, and sending the additional gravity of the accumulated snow on the insulator to the elastic additional analysis module.
Wherein, the additional gravity that detects module was born the snowfall volume to the insulator carries out the analysis in addition, includes following step:
a1, extracting the snowfall amount covered on the insulator;
a2, screening the ambient temperature around the insulator at fixed points, and respectively extracting temperature values corresponding to 0 point, 4 points, 8 points, 12 points, 16 points and 20 points;
a3, respectively counting the highest temperature, the lowest temperature and the average temperature in adjacent time points to form a temperature array D [ a ] [ b ], wherein a is equal to 1,2,3,4,5 and 6 and is respectively represented by time intervals of 0 point to 4 points, 4 points to 8 points, 8 points to 12 points, 12 points to 16 points, 16 points to 20 points, 20 points to 0 points, and b is equal to 1,2 and 3 and is respectively the highest temperature, the lowest temperature and the average temperature;
a4, judging whether the highest temperature between each adjacent time point is greater than 0 ℃, if so, executing the step A5, if not, counting the additional gravity G applied to the insulator by the accumulated snow in the adjacent time pointsi＝Gi-1*(1+η)，Gi-1Expressed as the additional gravitational force, G, of the accumulated snow on the insulator in the i-1 th adjacent time pointiThe additional gravity of the accumulated snow on the insulator in the ith adjacent time point is expressed, and eta is expressed as the coefficient of the accumulated snow absorbing water vapor in the air;
a5, judging whether the lowest temperature in the adjacent time points is greater than 0 ℃, if so, extracting the average temperature in the adjacent time points, extracting the fusion coefficient corresponding to the average temperature, and counting the additional gravity G applied to the insulator by the accumulated snow in the adjacent time pointsi＝Gi-1And mu (1-mu), wherein mu is a coefficient of the accumulated snow absorbing water vapor in the air, if the accumulated snow is less than 0 ℃, respectively counting the time greater than 0 ℃ and the time less than 0 ℃ in the adjacent time points, and counting the additional gravity of the accumulated snow in the adjacent time points on the insulator
tηExpressed as the time, t, of less than 0 ℃ in the adjacent time pointμExpressed as the time greater than 0 ℃ in this adjacent time point.
The snow falling amount on the insulator is detected by the additional bearing detection module, and the snow on the insulator is judged to be melted or frozen according to the temperature change in the environment, the gravity applied to the insulator by the snow in the change state can be accurately judged, the gravity applied to the insulator by the snow under the influence of the environment can be detected for all insulators in the area, a gravity detector is prevented from being installed on each insulator, the resource waste is reduced, the installation labor amount is reduced, and the gravity applied to the insulator by the snow can be accurately calculated.
The elastic additional analysis module is used for receiving the real-time wind speed and the temperature of the environment where the insulator is located, which are sent by the environment parameter acquisition module, comparing the wind speed with a set wind speed lower limit threshold value, screening out the wind speed larger than the wind speed lower limit threshold value, counting the real-time bearing capacity of the insulator under the real-time wind speed according to the wind speed, analyzing the received temperature, screening out the highest temperature and the lowest temperature in the day, and counting the temperature change rate
WHAnd WLMaximum and minimum temperatures, T, respectivelyHAnd TLThe time points corresponding to the maximum temperature and the minimum temperature are respectively set as min, and the additional gravity applied to the insulator by the snow cover sent by the additional bearing detection module is received, the maximum additional gravity applied and the accumulated time length TPx of the additional gravity applied to the insulator by the snow cover under each additional force level are screened out, x is 1,2,3,4, TPx is represented as the accumulated time length under the x additional level, the additional gravity applying ranges 0-F1, F1-F2, F2-F3 and F3-F4 corresponding to TP1, TP2, TP3 and TP4 additional force levels are set as F4 > F3 > F2 > 1 > 0, and the real-time applied bearing force, the daily maximum temperature and the minimum temperature, the temperature change rate, the maximum additional gravity applied to the snow cover and the accumulated time length of the additional gravity applied and the additional gravity applied under each additional force level under the wind speed of the insulator are sent to the model evolution module, the larger the additional force level is, the larger the additional gravity of the accumulated snow on the insulator is.
The calculation formula of the real-time applied bearing capacity of the insulator under the real-time wind speed is as follows:
f is real-time applied bearing capacity under wind speed v and is in unit kN/m2And v is wind speed, and the real-time wind speed greater than the lower limit wind speed threshold is analyzed to convert the wind speed into the bearing force applied to the insulator by the wind speed, wherein the larger the wind speed is, the larger the bearing force applied to the insulator by the wind speed is, and the larger the moment of the insulator is.
The model evolution module simulates wind power, temperature and snow cover parameter information in the environment where the insulator is located through experiments, a large amount of analysis is conducted on environment parameters of the insulator in the process that the insulator is installed in a crack and reaches the use limit, sudden change deformation coefficients beta 1, beta 2 and beta 3 corresponding to the wind power, the temperature and the snow cover in the use process of the insulator to be detected are obtained through simulation, real-time bearing force, the highest temperature and the lowest temperature of each day, temperature change rate, the maximum additional gravity of the snow cover on the insulator and the accumulated time of the additional gravity at each additional force level are received by the insulator sent by the elastic additional analysis module, the additional evolution comprehensive influence coefficients of the environment parameters are analyzed through a simulation evolution model formula, and the additional evolution comprehensive influence coefficients are sent to the management evaluation module and the crack correction module respectively.
The numerical values of the wind power sudden change deformation coefficient beta 1 affected by wind power, the temperature sudden change deformation coefficient beta 2 affected by temperature and the snow cover sudden change deformation coefficient beta 3 affected by snow cover are obtained through a large amount of experimental data and simulation experiments, and only the influence of a single factor is considered in the experimental process of the wind power sudden change deformation coefficient beta 1, the temperature sudden change deformation coefficient beta 2 and the snow cover sudden change deformation coefficient beta 3.
The simulation evolution model formula is as follows:
q1＜q2＜q3＜q4，q1＝0。
The crack correction module is used for receiving the crack depth and the crack length of the insulator detection sent by the defect detection module, extracting the crack depth and the crack length of the two detections, the time interval corresponding to the two detections is r, receiving the additional evolution comprehensive influence coefficient corresponding to the environmental parameter in the environment where the insulator is located sent by the model evolution module, counting the corresponding additional influence coefficient psi of the insulator under the influence of the temperature, the wind power and the snow in the environment where the insulator is located by the crack correction formula, and sending the detected additional influence coefficient, the crack depth and the crack length corresponding to the last detection of the selected crack to the management evaluation module, wherein the crack correction formula is used for receiving the crack depth and the crack length of the insulator detected by the defect detection module, and the crack
Y1 and Y2 are respectively the crack depth detected in the previous r days and the corresponding crack depth after r seconds, tau is an additional evolution comprehensive influence coefficient of the environmental parameters on the insulator, phi is a proportionality coefficient of the crack depth on the insulator life, phi is less than 1, and Z2 and Z1 are respectively the crack depth length detected in the previous r days and the corresponding crack length after r days.
Environmental parameters except for environmental parameters such as temperature, wind power and snow can be corrected through the crack correction module to obtain the influence degree that the insulator corresponds extra influence coefficient masters other environmental factors except that the insulator is influenced by temperature, wind power and snow, the comprehensive influence of the environmental parameters on the insulator is improved, and reliable data are provided for the crack evolution of the insulator in the later stage.
The management evaluation module receives the bending moment applied to the end face of the insulator sent by the bearing force simulation analysis module, receives an additional influence coefficient sent by the crack correction module and screens out the crack depth and the crack length corresponding to the last detection of the crack, receives an additional evolution comprehensive influence coefficient of an environmental parameter sent by the model evolution module, extracts the crack upper limit depth and the crack upper limit length corresponding to the crack service life at a cut-off state, and estimates the remaining service life evaluation duration when the crack on the insulator reaches the upper limit parameter under the current environmental interference according to the additional influence coefficient affecting the insulator service life, the additional evolution comprehensive influence coefficient of the environmental parameter, the crack depth and the crack length
K represents the residual service life evaluation duration of the insulator influenced by the current environment, M represents the bending moment applied to the end face of the insulator, and M represents the residual service life evaluation durationThreshold(s)Is the ultimate bending moment, Y, borne by the end face of the insulatorThreshold(s)And ZThreshold(s)Respectively representing the crack upper limit depth and the crack upper limit length corresponding to the insulator, psi representing an additional influence coefficient, tau representing an additional evolution comprehensive influence coefficient of the environmental parameters on the insulator, and counting the accumulated influence coefficient of the insulator from the crack length Z2 and the crack depth Y2 of the detected insulatorWhen the insulator is measured to continue to be used, the management evaluation module compares and analyzes the length of the insulator which is measured to continue to be used and the length of the service life evaluation module to judge whether the insulator with cracks is replaced or not, the serial number of the insulator which needs to be replaced is sent to the background computer management terminal, and the position corresponding to the serial number of the insulator is screened out through the serial number of the insulator by the rear computer management terminal, so that the insulator which needs to be replaced is replaced conveniently.
The management evaluation module analyzes the remaining service life evaluation duration of the insulator and judges whether the insulator needs to be replaced or not, and the method comprises the following steps:
b1, judging whether the accumulated continuous use time of the insulator is equal to the service life evaluation time K or not, and if so, sending a crack detection instruction to the defect detection module;
b2, acquiring the crack depth and the crack length fed back by the crack detection module;
b3, comparing the crack depth and the crack length with 0.9 time of crack upper limit depth and 0.9 time of crack upper limit length respectively, and if the crack depth is greater than 0.9 time of crack upper limit depth or the crack length is greater than 0.9 time of crack upper limit length, extracting the serial number of the insulator to be replaced to a background computer management terminal by a management evaluation module;
b4, if the crack depth is smaller than 0.9 times of the crack upper limit depth and the crack length is smaller than 0.9 times of the crack upper limit length, the remaining life evaluation duration calculation formula of the insulator recalculates the life evaluation duration corresponding to the insulator under the current environmental interference;
b5, continuously counting the accumulated continuous use time of the insulators again, repeating the steps B1-B4 until the crack depth is larger than 0.9 time of the crack upper limit depth or the crack length is larger than 0.9 time of the crack upper limit length, and extracting the serial number of the insulator to be replaced to the background computer management terminal.
The method has the advantages that the length of the accumulated insulator continuing to be used is compared with the length of the service life evaluation time, and the analysis is carried out, so that whether the insulator reaches the state of replacing the service life or not is judged, the service life of the insulator can be effectively utilized, the insulator is prevented from being replaced untimely or too early, the insulator cannot be fully utilized, the replacement frequency of the insulator and the workload of replacement personnel are increased, and the replacement cost of the insulator is wasted.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (8)
1. The utility model provides an electric power system insulator monitoring evaluation system based on big data, includes the defect detection module, the defect detection module is ultrasonic flaw detector, and the ultrasonic probe through ultrasonic flaw detector sends the ultrasonic wave to the insulator that needs to detect, and the ultrasonic wave obtains the reflection wave pulse waveform through the insulator reflection to contrast reflection wave pulse waveform, obtain the inside crack position of insulator that detects, crack depth and crack length, and send the inside crack depth and the crack length of insulator that detect to crack correction module, its characterized in that: the device also comprises a bearing capacity simulation analysis module, an environmental parameter acquisition module, an additional bearing detection module, an elastic additional analysis module, a model evolution module, a crack correction module and a management evaluation module;
the bearing force simulation analysis module is used for acquiring the installation basic parameter information of the post insulator at the end part of the pipe trunk, inputting the installation basic parameter information into the bearing simulation formula according to the installation basic parameter information of the post insulator, simulating the bending moment of the end face of the post insulator under the condition of not being influenced by other external forces, and sending the simulated bending moment of the end face of the post insulator to the management evaluation module;
the environment parameter acquisition module comprises a wind speed detection unit and a temperature detection unit, the wind speed detection unit is used for acquiring the wind speed borne by the insulator in the region in real time and sending the acquired wind speed borne by the insulator to the elastic additional analysis module, and the temperature detection unit is used for acquiring the temperature in the environment where the insulator is located and sending the acquired temperature borne by the insulator to the additional bearing detection module and the elastic additional analysis module respectively;
the additional bearing detection module is used for acquiring the snow fall amount on the insulator in real time, receiving the temperature sent by the environment parameter acquisition module, simulating the additional gravity of the accumulated snow on the insulator along with the change of the environment temperature according to the snow fall amount on the insulator and the temperature change condition of the environment where the insulator is located, and sending the detected additional gravity of the accumulated snow on the insulator to the elastic additional analysis module;
the elastic additional analysis module is used for receiving the real-time wind speed and the temperature of the environment where the insulator is located, which are sent by the environment parameter acquisition module, comparing the wind speed with a set wind speed lower limit threshold value, screening out the wind speed greater than the wind speed lower limit threshold value, counting the real-time bearing capacity of the insulator under the real-time wind speed according to the wind speed, analyzing the received temperature, screening out the highest temperature and the lowest temperature in the same day, counting the temperature change rate, receiving the additional gravity of the accumulated snow on the insulator, which is sent by the additional bearing detection module, screening out the maximum additional gravity and the accumulated time TPx of the additional gravity of the accumulated snow on the insulator under each additional force level, and applying the real-time bearing capacity, the highest temperature and the lowest temperature, the temperature change rate and the maximum additional gravity on the accumulated snow on the insulator under the wind speed, The accumulated time length of the additional gravity under each additional force level is sent to a model evolution module;
the model evolution module simulates wind power, temperature and snow accumulation parameter information in the environment where the insulator is located through experiments, and conducts massive analysis on environment parameters of the insulator in the process that the insulator is installed in a crack and reaches the use limit, so as to obtain sudden change deformation coefficients beta 1, beta 2 and beta 3 corresponding to the wind power, the temperature and the snow accumulation in the use process of the insulator to be detected through simulation, receive real-time applied bearing capacity, the daily highest temperature and lowest temperature and temperature change rate of the insulator under the wind speed sent by the elastic additional analysis module, the maximum additional gravity of the snow accumulation on the insulator and the accumulated time of the additional gravity under each additional force level, analyze the additional evolution comprehensive influence coefficient of the environment parameters through a simulation evolution model formula, and respectively send the additional evolution comprehensive influence coefficient to the management evaluation module and the crack correction module;
the crack correction module is used for receiving the crack depth and the crack length of the insulator detection sent by the defect detection module, extracting the crack depth and the crack length of the two detections, wherein the time interval corresponding to the two detections is r, receiving an additional evolution comprehensive influence coefficient corresponding to the environmental parameter in the environment where the insulator is located sent by the model evolution module, counting an additional influence coefficient psi corresponding to the insulator under the influence of the temperature, the wind power and the snow in the environment where the insulator is located by using a crack correction formula, and sending the detected additional influence coefficient, the crack depth and the crack length corresponding to the last detection of the screened crack to the management evaluation module,
the management evaluation module receives the bending moment on the end face of the insulator sent by the bearing capacity simulation analysis module, receives an additional influence coefficient sent by the crack correction module and screens out the crack depth and the crack length corresponding to the last detection of the crack, receives an additional evolution comprehensive influence coefficient of an environmental parameter sent by the model evolution module, extracts the upper limit depth and the upper limit length of the crack corresponding to the cut-off state of the crack life, predicts the remaining life evaluation duration K when the crack on the insulator reaches the upper limit parameter under the current environmental interference according to the additional influence coefficient influencing the insulator life, the additional evolution comprehensive influence coefficient of the environmental parameter, the crack depth and the crack length, and counts the duration of the insulator continuing use from the crack length Z2 and the depth Y2 of the detected insulator, and the management evaluation module compares the duration of the insulator continuing use with the life evaluation duration, And analyzing to judge whether the insulator with the crack is replaced or not, sending the serial number of the insulator to be replaced to the background computer management terminal, and screening the position corresponding to the serial number of the insulator by the rear computer management terminal through the serial number of the insulator.
2. The big data based power system insulator monitoring and evaluation system according to claim 1, wherein: the bearingAnalog formula
The mass of the pipe bus per unit length m1, the mass of the damping wire per unit length m2, the mass of the pipe bus metal tool m3, the mass of the down conductor m4, the mass of the insulator body m5, the distance from the insulator body to the root part of the insulator s1 and the height of the bus body s2, wherein g is 9.8m/s2。
3. The big data based power system insulator monitoring and evaluation system according to claim 1, wherein: the additional load detection module analyzes the additional gravity of the snowfall quantity borne by the insulator, and comprises the following steps:
a1, extracting the snowfall amount covered on the insulator;
a2, screening the ambient temperature around the insulator at fixed points, and respectively extracting temperature values corresponding to 0 point, 4 points, 8 points, 12 points, 16 points and 20 points;
a3, respectively counting the highest temperature, the lowest temperature and the average temperature in adjacent time points to form a temperature array D [ a ] [ b ], wherein a is equal to 1,2,3,4,5 and 6 and is respectively represented by time intervals of 0 point to 4 points, 4 points to 8 points, 8 points to 12 points, 12 points to 16 points, 16 points to 20 points, 20 points to 0 points, and b is equal to 1,2 and 3 and is respectively the highest temperature, the lowest temperature and the average temperature;
a4, judging whether the highest temperature between each adjacent time point is greater than 0 ℃, if so, executing the step A5, if not, counting the additional gravity G applied to the insulator by the accumulated snow in the adjacent time pointsi＝Gi-1*(1+η)，Gi-1Expressed as the additional gravitational force, G, of the accumulated snow on the insulator in the i-1 th adjacent time pointiThe additional gravity of the accumulated snow on the insulator in the ith adjacent time point is expressed, and eta is expressed as the coefficient of the accumulated snow absorbing water vapor in the air;
a5, judging whether the lowest temperature in the adjacent time points is greater than 0 ℃, if so, extracting the average temperature in the adjacent time points, extracting the fusion coefficient corresponding to the average temperature, and counting the additional application of the accumulated snow in the adjacent time points to the insulatorGravity Gi＝Gi-1And mu (1-mu), wherein mu is a coefficient of the accumulated snow absorbing water vapor in the air, if the accumulated snow is less than 0 ℃, respectively counting the time greater than 0 ℃ and the time less than 0 ℃ in the adjacent time points, and counting the additional gravity of the accumulated snow in the adjacent time points on the insulator
tηExpressed as the time, t, of less than 0 ℃ in the adjacent time pointμExpressed as the time greater than 0 ℃ in this adjacent time point.
4. The big data based power system insulator monitoring and evaluation system according to claim 1, wherein: the calculation formula of the real-time applied bearing capacity of the insulator under the real-time wind speed is as follows:
f is real-time applied bearing capacity under wind speed v and is in unit kN/m2And v is wind speed.
5. The big data based power system insulator monitoring and evaluation system according to claim 1, wherein: the simulation evolution model formula is as follows:
r is the accumulated days of insulator monitoring, tau is the comprehensive influence coefficient of additional evolution of the environmental parameters on the insulator, beta 1, beta 2 and beta 3 are obtained by experimental simulation and are respectively the sudden change deformation coefficients corresponding to wind power, temperature and accumulated snow, F' is the average value of the additional bearing capacity corresponding to the wind speed with the wind speed larger than the wind speed lower limit threshold, FmaxAdditional bearing capacity, T, corresponding to the maximum wind speed bearable by the insulatorv > v lower thresholdFor wind speed accumulation periods where the wind speed is greater than the lower wind speed threshold, TPx is the accumulation at the xth additional levelThe length of the time is counted,
for the accumulated duration of the insulator monitoring process, x is 1,2,3,4, WHj and WLj is the highest temperature and the lowest temperature respectively applied to the insulator on the j day, WH is provided withAnd WL is provided withIs the maximum and minimum temperature, gamma, that the insulator can withstandWAs rate of change of temperature, Δ γThreshold(s)Maximum rate of temperature change, G, that the insulator can withstandmaxFor maximum additional application of gravity, G, to the insulator by accumulated snowThreshold valueAnd Gx is the average additional applied gravity corresponding to the xth additional level, qx is the weight coefficient corresponding to the average additional applied gravity at the xth additional level, and q1 < q2 < q3 < q4, and q1 is 0.
6. The big data based power system insulator monitoring and evaluation system according to claim 5, wherein: the formula for correcting cracks
Y1 and Y2 are respectively the crack depth detected in the previous r days and the corresponding crack depth after r seconds, tau is an additional evolution comprehensive influence coefficient of the environmental parameters on the insulator, phi is a proportionality coefficient of the crack depth on the insulator life, phi is less than 1, and Z2 and Z1 are respectively the crack depth length detected in the previous r days and the corresponding crack length after r days.
7. The big data based power system insulator monitoring and evaluation system according to claim 6, wherein: remaining service life evaluation duration when cracks on the insulator reach an upper limit parameter under the interference of the current environment
K represents the residual service life evaluation duration of the insulator influenced by the current environment, M represents the bending moment applied to the end face of the insulator, and M represents the residual service life evaluation durationThreshold(s)To be insulatedUltimate bending moment, Y, to which the end faces of the sub-members are subjectedThreshold(s)And ZThreshold(s)The crack upper limit depth and the crack upper limit length corresponding to the insulator are respectively expressed, psi is expressed as an additional influence coefficient, and tau is expressed as an additional evolution comprehensive influence coefficient of the environmental parameters on the insulator.
8. The big data based power system insulator monitoring and evaluation system according to claim 7, wherein: the management evaluation module analyzes the remaining service life evaluation duration of the insulator and judges whether the insulator needs to be replaced or not, and the method comprises the following steps:
b1, judging whether the accumulated continuous use time of the insulator is equal to the service life evaluation time K or not, and if so, sending a crack detection instruction to the defect detection module;
b2, acquiring the crack depth and the crack length fed back by the crack detection module;
b3, comparing the crack depth and the crack length with 0.9 time of crack upper limit depth and 0.9 time of crack upper limit length respectively, and if the crack depth is greater than 0.9 time of crack upper limit depth or the crack length is greater than 0.9 time of crack upper limit length, extracting the serial number of the insulator to be replaced to a background computer management terminal by a management evaluation module;
b4, if the crack depth is smaller than 0.9 times of the crack upper limit depth and the crack length is smaller than 0.9 times of the crack upper limit length, the remaining life evaluation duration calculation formula of the insulator recalculates the life evaluation duration corresponding to the insulator under the current environmental interference;
b5, continuously counting the accumulated continuous use time of the insulators again, repeating the steps B1-B4 until the crack depth is larger than 0.9 time of the crack upper limit depth or the crack length is larger than 0.9 time of the crack upper limit length, and extracting the serial number of the insulator to be replaced to the background computer management terminal.
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| CN112883576A (en) * | 2021-02-26 | 2021-06-01 | 深圳市磐锋精密技术有限公司 | Internet-based battery cover rapid rubberizing pressure maintaining monitoring method |
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| CN114091305A (en) * | 2021-11-18 | 2022-02-25 | 广东电网有限责任公司 | Random seismic response analysis method and system for supporting tubular busbar structure |
| CN114091305B (en) * | 2021-11-18 | 2022-07-12 | 广东电网有限责任公司 | Random seismic response analysis method and system for supporting tubular busbar structure |
| CN115840895A (en) * | 2021-12-31 | 2023-03-24 | 江苏常胜电器(淮安)有限公司 | Electronic device temperature protection system |
| CN115840895B (en) * | 2021-12-31 | 2024-05-03 | 江苏常胜电器(淮安)有限公司 | Electronic device temperature protection system |
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