CN116468422A - Method and device for predicting wire clamp temperature rise and residual life of power transmission line - Google Patents
Method and device for predicting wire clamp temperature rise and residual life of power transmission line Download PDFInfo
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Abstract
The invention relates to the technical field of operation and maintenance of a transmission line, in particular to a method and a device for monitoring the temperature rise of a wire clamp of a transmission line and predicting the residual life of the wire clamp of the transmission line. The prediction method comprises the following steps: acquiring state quantity of a wire clamp at each moment; combining the state quantities of the wire clamps at all times to construct a multi-time line clamp tensor; constructing a wire clamp temperature rise and residual life prediction model, and training the model; inputting a multi-moment wire clamp tensor to predict the wire clamp temperature, the residual life and the aging rate in the model; and carrying out early warning based on the wire clamp temperature, the residual service life and the aging rate. The power transmission line clamp temperature rise and residual life prediction method adopts a data driving prediction method to obtain the clamp health state, performs fusion analysis on the acquired multi-source data, gives a risk assessment effect, and can provide references for subsequent state maintenance and line amplification.
Description
Technical Field
The invention relates to the technical field of operation and maintenance of a transmission line, in particular to a method and a device for monitoring the temperature rise of a wire clamp of a transmission line and predicting the residual life of the wire clamp of the transmission line.
Background
In an overhead line, a strain clamp is used as an important component fitting to play a role of fixing a wire, so that the tension of the wire is borne, the load current of the line is borne, the mechanical performance and the electrical performance of the overhead line are subjected to the test of an external environment and a high-intensity electromagnetic field at any time, and the running state of the overhead line is related to the safe and reliable running of the overhead line.
The method has the advantages that the method has wide amplitude and various climates, natural conditions are bad in certain places, the ageing degree of the wire clamps is different due to the different investment years and models, even the situation that the wire clamps with the same type have different failure conditions and different service lives is caused, the risks of the power transmission line are increased due to the situations, and the stable, safe and stable development of the power transmission line in China is hindered. Therefore, the operation state of the wire clamp can be intuitively obtained aiming at the wire clamp temperature rise and the service life prediction, and a foundation is provided for subsequent state maintenance.
The main defects of the wire clamp are displacement, falling off, loosening of parts, missing, corrosion, arc burning, damage, abnormal temperature rise and the like. The existing strain clamp research is scattered, the main research is concentrated in the material field, such as the research on mechanical property and corrosion resistance, and the related life prediction is only obtained based on corrosion rate and temperature simulation; most of researches in the electrical field are based on heating mechanism and failure mechanism, such as building a thermal circuit model to calculate the temperature, and data-driven temperature rise prediction and residual life prediction are less.
Disclosure of Invention
Aiming at the defects of the existing method, the invention provides a method and a device for predicting the temperature rise and the residual life of a power transmission line wire clamp, which adopt a data driving prediction method to obtain the health state of the wire clamp, perform fusion analysis on collected multi-source data, give a risk assessment effect and provide references for subsequent state maintenance and line amplification.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method for predicting temperature rise and residual life of a power transmission line clamp comprises the following steps:
acquiring state quantity of a wire clamp at each moment;
combining the state quantities of the wire clamps at all times to construct a multi-time line clamp tensor;
constructing a wire clamp temperature rise and residual life prediction model, and training the model;
inputting a multi-moment wire clamp tensor to predict the wire clamp temperature, the residual life and the aging rate in the model;
and carrying out early warning based on the wire clamp temperature, the residual service life and the aging rate.
Preferably, the construction of the wire clamp temperature rise and residual life prediction model comprises the construction of a wire clamp temperature rise prediction model, wherein the wire clamp temperature rise prediction model is constructed by an RNN (RNN recurrent neural network), and comprises the following steps:
the time window length is set to be M;
setting the time step to n;
inputting a multi-time line clamping tensor formed by combining M/n single-moment line clamping state quantities;
the output is the last moment t of the time window f Wire clamp temperature θ at the moment of +time step n.
Preferably, the construction of the wire clamp temperature rise and residual life prediction model comprises the construction of the wire clamp residual life prediction model, and the construction of the wire clamp life prediction model comprises the following steps:
recording the wire clamp temperature theta exceeding a constant reference temperature theta H The device run time T at time is converted into theta H The equivalent run time is T eq ；
The real-time aging rate of the wire clamp is l, and l=T eq /T；
When the wire clamp temperature theta exceeds the constant reference temperature theta H When the aging acceleration probability IDP of the equipment in the time window is calculated, wherein the IDP is the aging acceleration frequency S in the time window IDP Total number of state samples M;
loss of wire clamp life E i The expected life loss due to aging acceleration is expressed by the formula:
thereby calculating the expected value E of the residual life of the wire clamp r ，E r Alarm when the residual life threshold value Y is lower:
E r ＝E-E i
e is the preset life of the wire clamp.
Preferably, the wire clipThe output layer of the temperature rise and clamp life prediction model is connected with a risk assessment layer, and the risk assessment layer is connected with the risk assessment layer according to the clamp temperature theta and the reference temperature theta H Maximum operating temperature theta MAX Expected value of remaining life E r A life remaining critical value Y, a wire clamp real-time aging rate l and an aging rate critical value l MAX Early warning is carried out:
when theta is as<θ H When the temperature theta of the wire clamp is output, the alarm is not given;
when theta is as H ≤θ<θ MAX At the time, calculate E r And l, when l is greater than or equal to l MAX Or E is r When the temperature is less than or equal to Y, outputting the wire clamp temperature theta and carrying out risk early warning;
when theta is greater than or equal to theta H And outputting the wire clamp temperature theta and alarming.
A power transmission line clamp temperature rise and residual life prediction device comprises:
the data acquisition module acquires the state quantity of the wire clamps at all moments;
and the front-end processing unit is used for combining the state quantities of the wire clamps at all times to construct a multi-time line clamp tensor, calculating edges, predicting the temperature rise of the wire clamps and the residual life and early warning.
Preferably, the data acquisition module comprises a meteorological sensor, a wire current sensor, a wire temperature sensor, a wire clamp temperature sensor and an image sensor, and is distributed on a transmission tower, a wire clamp or a wire.
Preferably, the front-end processing unit is arranged on a transmission tower and is powered by adopting a photovoltaic panel and a storage battery; or the front-end processing unit is arranged on the lead and adopts an induction electricity taking and storage battery mode for energy supply.
Preferably, the front-end processing unit is in communication with the data acquisition module in a wired or wireless mode.
Preferably, the remote master station system is composed of a server and a monitoring system and is used for storing multi-source data obtained by the front-end processing unit, fusing the multi-source data and predicting and early warning wire clamp temperature rise, residual life and aging rate in a longer time scale.
Preferably, the front-end processing unit and the remote main station system communicate through a 3G/4G network or an optical fiber composite overhead ground wire.
The invention has the positive beneficial effects that:
1. the power transmission line clamp temperature rise and residual life prediction method adopts a data driving prediction method to obtain the clamp health state, performs fusion analysis on the acquired multi-source data, gives a risk assessment effect, and can provide references for subsequent state maintenance and line amplification.
2. According to the invention, the distributed sensor is arranged at the transmission tower, the wire clamp or the wire, and the front-end processing unit is arranged at the transmission tower or the wire, so that the temperature rise early warning of the important transmission line wire clamp can be realized, and the problem that the wire clamp is not obvious in heating and is not easy to sense in severe weather conditions is solved.
3. According to the invention, the remote master station system stores the multi-source data obtained by the front-end processing unit, and fuses the multi-source data, so that the wire clamp temperature rise, the residual life and the aging rate of a longer time scale are predicted and early-warned, a powerful reference is provided for state maintenance, model optimization can be performed according to a manual check result, and the model prediction accuracy is improved.
4. The front-end processing unit and the data acquisition module are communicated in a wired or wireless mode, and the front-end processing unit and the remote master station system are communicated through a 3G/4G network or an optical fiber composite overhead ground wire, so that the wireless communication between the front-end processing unit and the data acquisition module and between the front-end processing unit and the remote master station system can be realized. The edge calculation in the front-end processing unit can preprocess mass acquisition data, the front-end processing unit greatly reduces data transmission quantity, reduces communication pressure, saves communication cost, and avoids the problem of communication blocking caused by scattered transmission of data.
Drawings
FIG. 1 is a schematic diagram of an RNN;
FIG. 2 is a flow chart of a method for predicting the temperature rise and the residual life of a power transmission line clamp;
FIG. 3 is a working diagram of a wire clamp temperature rise and residual life prediction model structure;
FIG. 4 is a block diagram of a power transmission line clamp temperature rise and remaining life prediction device;
FIG. 5 is a diagram of a data acquisition module installation location;
fig. 6 is a diagram of the installation position of the power transmission line clamp temperature rise and residual life prediction device.
Detailed Description
The invention will be further illustrated with reference to a few specific examples.
Example 1
A method for predicting temperature rise and residual life of a power transmission line clamp comprises the following steps:
acquiring state quantity of a wire clamp at each moment;
combining the state quantities of the wire clamps at all times to construct a multi-time line clamp tensor;
constructing a wire clamp temperature rise and residual life prediction model, and training the model;
inputting a multi-moment wire clamp tensor to predict the wire clamp temperature, the residual life and the aging rate in the model;
and carrying out early warning based on the wire clamp temperature, the residual service life and the aging rate.
Further, a wire clamp temperature rise and residual life prediction model is constructed, including construction of the wire clamp temperature rise prediction model, which is constructed by an RNN (RNN recurrent neural network), and the method comprises the following steps:
referring to fig. 1, x is an input layer vector, o is an output layer vector, U is a weight matrix from an input layer to a hidden layer, V is a weight matrix from a hidden layer to an output layer, a value s of a hidden layer of the recurrent neural network depends not only on a current input x but also on a value s of a last hidden layer, and a weight matrix W is a last value of a hidden layer as an input weight of the current time.
The input of the cyclic neural network is sequence data, each training sample is a time sequence and comprises a plurality of vectors with the same dimension, the input values of the same training sample at the front and rear moments are associated, the sequence length of each sample is possibly different, the input value of each moment in the sequence is firstly transmitted forward during training, then the gradient value of the parameter is calculated through backward transmission, and the parameter is updated.
Training and testing the model by using the multi-time line clamping tensor, respectively carrying out iterative training on the training and testing samples which are 70% and 30% respectively until the training converges, and obtaining an RNN line clamp temperature rise and residual life prediction model;
the details are as follows:
the time window length is set to M, preferably 30min;
the time step is set to n, preferably 1min, i.e. the time difference between the moments in the present model;
inputting a multi-time line clamping tensor formed by combining M/n single-moment line clamping state quantities;
the output is the last moment t of the time window f Wire clamp temperature θ at the moment of +time step n.
Further, the wire clamp temperature rise and residual life prediction model is constructed, the wire clamp residual life prediction model is constructed, and the wire clamp life prediction model is constructed by the following steps:
recording the wire clamp temperature theta exceeding a constant reference temperature theta H The device run time T at time is converted into theta H The equivalent run time is T eq ；
The real-time aging rate of the wire clamp is l, and l=T eq /T；
When the wire clamp temperature theta exceeds the constant reference temperature theta H When the aging acceleration probability IDP of the equipment in the time window is calculated, wherein the IDP is the aging acceleration frequency S in the time window IDP Total number of state samples M;
loss of wire clamp life E i The expected life loss due to aging acceleration is expressed by the formula:
thereby calculating the expected value E of the residual life of the wire clamp r ，E r Alarm when the residual life threshold value Y is lower:
E r ＝E-E i
e is a predetermined life of the wire clamp, which is set to 50 years in this example.
Further, an output layer of the wire clamp temperature rise and wire clamp life prediction model is connected with a risk assessment layer, and the risk assessment layer is connected with the risk assessment layer according to the wire clamp temperature theta and the reference temperature theta H Maximum operating temperature theta MAX Expected value of remaining life E r A life remaining critical value Y, a wire clamp real-time aging rate l and an aging rate critical value l MAX Early warning is carried out:
when theta is as<θ H When the temperature theta of the wire clamp is output, the alarm is not given;
when theta is as H ≤θ<θ MAX At the time, calculate E r And l, when l is greater than or equal to l MAX Or E is r When the temperature is less than or equal to Y, outputting the wire clamp temperature theta and carrying out risk early warning;
when theta is greater than or equal to theta H And outputting the wire clamp temperature theta and alarming.
As shown in fig. 2 and 3, the method for predicting the temperature rise and the residual life of the power transmission line clamp comprises the following steps:
(1) And (3) inputting wire clamp basic information: inputting the basic model information of the wire clamp, wherein the basic model information comprises size information, crimping length, crimping error and operation life, and determining a model constant value;
(2) And (3) operating state information input: the front-end processing unit inputs real-time running state information from the data acquisition module, wherein the real-time running state information comprises current, wind speed, wind direction, wire clamp temperature, environment temperature and environment humidity information, and real-time state measuring values are determined;
(3) Image information input: the input image information comprises appearance information of the wire clamp, and the corrosion rate of the wire clamp is obtained after image processing;
(4) Wire clamp temperature, residual life, aging rate prediction: because the wire clamp sampling data are time sequence data, a data driving prediction method is adopted, the wire clamp temperature is predicted based on the wire clamp temperature rise prediction model in the wire clamp temperature rise and residual life prediction model, the multi-moment wire clamp tensor is input to predict the wire clamp temperature, the wire clamp residual life and the aging rate are calculated based on the wire clamp temperature rise and the residual life prediction model in the residual life prediction model;
(5) Early warning: and carrying out early warning in the risk assessment layer based on the temperature, the residual life and the aging rate.
Further, the wire clamp corrosion rate Δx is calculated as follows:
acquiring an image of a corresponding perfect wire clamp, writing a corresponding number, and establishing a perfect wire clamp image library;
acquiring an image of a wire clamp at the current moment, and dividing the area of the wire clamp in the image into S;
at a frequency f x Comparing the image of the current wire clamp with the image of the perfect wire clamp, and identifying the rust area s of the surface of the wire clamp x ；
Calculating the corrosion rate of the wire clamp delta x, delta x=s x /S，f x Setting for 10min.
Example 2
The utility model provides a transmission line fastener temperature rise and remaining life prediction device, as shown in fig. 4, includes:
the lower layer is a data acquisition module and acquires the state quantity of the wire clamps at all moments;
the middle layer is a front-end processing unit, the state quantity of the wire clamps at all times is combined to construct a multi-time line clamp tensor, edge calculation is carried out, and the temperature rise of the wire clamps and the residual life are predicted and early warned.
Further, as shown in fig. 5, the data acquisition module comprises a microclimate sensor, a wire current sensor, a wire temperature sensor, a wire clamp temperature sensor and an image sensor, which are distributed on a tower, a wire clamp or a wire, wherein the microclimate sensor is positioned as 1; wire clamp temperature sensor locations such as 2; an image sensor is installed at a first position, such as 3, and an image sensor is installed at a second position, such as 3'; the wire current sensor, wire temperature sensor are integrated at locations 4, 5.
Further, as shown in fig. 6, the front-end processing unit is installed on the transmission tower and adopts a photovoltaic panel and storage battery mode; or the front-end processing unit is arranged on the lead and adopts an induction electricity taking and storage battery mode for energy supply.
Further, the intelligent remote master station system further comprises an upper remote master station system, wherein the remote master station system is composed of a server and a monitoring system and is used for storing multi-source data obtained by a front-end processing unit, and the multi-source data are fused to realize prediction and early warning of wire clamp temperature rise, residual service life and aging rate in a longer time scale.
Further, the front-end processing unit comprises an integrated terminal, various sensors are transmitted to the integrated terminal in a wired or wireless mode, and the integrated terminal firstly preprocesses data, deletes repeated data and complements missing data. Common missing data supplementing methods comprise mean value interpolation, modeling prediction, high-dimensional mapping, multiple interpolation and manual difference value, different missing supplementing schemes can be adopted according to sampling frequency and data characteristics, such as wire clamp temperature data with high sampling frequency and low time sensitivity, and the data can be supplemented by adopting the mean value interpolation method; for real-time data acquired by multiple sources, the front-end processing unit can compress the data, and typical time discrete monitoring data are stored for subsequent temperature rise and life prediction.
In the embodiment, the wireless communication between various sensors and the front-end processing unit is realized by adopting the LoRa wireless communication technology, the communication distance is greatly prolonged by adopting the frequency hopping spread spectrum technology, and meanwhile, the power consumption is greatly reduced by adopting the frequency shift keying modulation, so that the transmission cost is saved.
After the front-end processing unit preprocesses data, the remote master station system needs to carry out secondary judgment on abnormal data transmission, and the embodiment adopts a remote data transmission means to realize communication between the front-end processing unit and the remote master station system, and specifically comprises two communication modes:
1. the signal can be transmitted to the master station through a 3G/4G network in a region with good signals, with the continuous development of communication technology, the communication coverage rate of China rises year by year, and the 3G/4G network can be adopted for transmission under the condition of energy supply condition permission.
2. The optical fiber composite overhead ground wire (OPGW optical cable) is used for transmission, namely, the optical fiber is placed in the ground wire, so that an optical fiber communication network on the transmission line is formed, and the optical fiber communication network has the advantages of high reliability, good mechanical strength, low cost and the like, and is widely applied to newly-built transmission lines above 110 kV.
Finally, it is noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention, and that other modifications and equivalents thereof by those skilled in the art should be included in the scope of the claims of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (10)
1. The method for predicting the temperature rise and the residual life of the wire clamp of the power transmission line is characterized by comprising the following steps:
acquiring state quantity of a wire clamp at each moment;
combining the state quantities of the wire clamps at all times to construct a multi-time line clamp tensor;
constructing a wire clamp temperature rise and residual life prediction model, and training the model;
inputting a multi-moment wire clamp tensor to predict the wire clamp temperature, the residual life and the aging rate in the model;
and carrying out early warning based on the wire clamp temperature, the residual service life and the aging rate.
2. The power transmission line clamp temperature rise and remaining life prediction method according to claim 1, wherein the constructing of the clamp temperature rise and remaining life prediction model comprises constructing of a clamp temperature rise prediction model, the clamp temperature rise prediction model is constructed by an RNN cyclic neural network, and the method comprises the following steps:
the time window length is set to be M;
setting the time step to n;
inputting a multi-time line clamping tensor formed by combining M/n single-moment line clamping state quantities;
the output is the last moment t of the time window f Wire clamp temperature θ at the moment of +time step n.
3. The power transmission line wire clamp temperature rise and residual life prediction method according to claim 2, wherein the construction of the wire clamp temperature rise and residual life prediction model comprises the construction of the wire clamp residual life prediction model, and the wire clamp life prediction model construction steps are as follows:
recording the wire clamp temperature theta exceeding a constant reference temperature theta H The device run time T at time is converted into theta H The equivalent run time is T eq ；
The real-time aging rate of the wire clamp is l, and l=T eq /T；
When the wire clamp temperature theta exceeds the constant reference temperature theta H When the aging acceleration probability IDP of the equipment in the time window is calculated, wherein the IDP is the aging acceleration frequency S in the time window IDP Total number of state samples M;
loss of wire clamp life E i The expected life loss due to aging acceleration is expressed by the formula:
thereby calculating the expected value E of the residual life of the wire clamp r ，E r Alarm when the residual life threshold value Y is lower:
E r ＝E-E i
e is the preset life of the wire clamp.
4. The power transmission line clamp temperature rise and residual life prediction method according to claim 3, wherein an output layer of the clamp temperature rise and clamp life prediction model is connected with a risk assessment layer, and the risk assessment layer is used for predicting the power transmission line clamp temperature rise and residual life according to the clamp temperature theta and the reference temperature theta H Maximum operating temperature theta MAX Expected value of remaining life E r A life remaining critical value Y, a wire clamp real-time aging rate l and an aging rate critical value l MAX Early warning is carried out:
when theta is as<θ H When the temperature theta of the wire clamp is output, the alarm is not given;
when theta is as H ≤θ<θ MAX At the time, calculate E r And l, when l is greater than or equal to l MAX Or E is r When the temperature is less than or equal to Y, outputting the wire clamp temperature theta and carrying out risk early warning;
when theta is greater than or equal to theta H Output line whenAnd clamping the temperature theta and alarming.
5. The utility model provides a transmission line fastener temperature rise and surplus life prediction unit which characterized in that includes:
the data acquisition module acquires the state quantity of the wire clamps at all moments;
and the front-end processing unit is used for combining the state quantities of the wire clamps at all times to construct a multi-time line clamp tensor, calculating edges, predicting the temperature rise of the wire clamps and the residual life and early warning.
6. The power transmission line clamp temperature rise and remaining life prediction device according to claim 5, wherein the data acquisition module comprises a weather sensor, a wire current sensor, a wire temperature sensor, a clamp temperature sensor and an image sensor, and is distributed on a power transmission tower, a wire clamp or a wire.
7. The power transmission line clamp temperature rise and residual life prediction device according to claim 5, wherein the front-end processing unit is arranged on a power transmission tower and is powered by adopting a photovoltaic panel and a storage battery; or the front-end processing unit is arranged on the lead and adopts an induction electricity taking and storage battery mode for energy supply.
8. The power line clamp temperature rise and remaining life prediction device according to claim 5, wherein the front-end processing unit and the data acquisition module are in communication in a wired or wireless mode.
9. The power transmission line clamp temperature rise and residual life prediction device according to claim 5, further comprising a remote master station system, wherein the remote master station system is composed of a server and a monitoring system and is used for storing multi-source data obtained by a front-end processing unit, and fusing the multi-source data to predict and early warn the clamp temperature rise, residual life and aging rate in a longer time scale.
10. The power line clamp temperature rise and remaining life prediction device of claim 9, wherein the front-end processing unit communicates with a remote master station system through a 3G/4G network or an optical fiber composite overhead ground wire.
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| CN202310327892.5A CN116468422A (en) | 2023-03-29 | 2023-03-29 | Method and device for predicting wire clamp temperature rise and residual life of power transmission line |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117199844A (en) * | 2023-11-03 | 2023-12-08 | 江苏嘉盟电力设备有限公司 | Wire clamp system with intelligent temperature measurement function |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117199844A (en) * | 2023-11-03 | 2023-12-08 | 江苏嘉盟电力设备有限公司 | Wire clamp system with intelligent temperature measurement function |
| CN117199844B (en) * | 2023-11-03 | 2024-02-13 | 江苏嘉盟电力设备有限公司 | Wire clamp system with intelligent temperature measurement function |
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