CN117109754A - Electrical connector fault prediction method - Google Patents
Electrical connector fault prediction method Download PDFInfo
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- CN117109754A CN117109754A CN202310857497.8A CN202310857497A CN117109754A CN 117109754 A CN117109754 A CN 117109754A CN 202310857497 A CN202310857497 A CN 202310857497A CN 117109754 A CN117109754 A CN 117109754A
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- G—PHYSICS
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Abstract
The application discloses a method for predicting faults of an electrical connector, which comprises the following steps: s1: acquiring position data of an electrical connector, and establishing a position space model; s2: establishing a temperature radiation function, and establishing a temperature radiation model according to the temperature radiation function and the position space model; s3: acquiring historical electrical joint temperature data, environment data and fault data, calculating historical electrical joint internal temperature data according to a temperature radiation model, and constructing a fault prediction model; s4: and acquiring real-time data and environmental data of the electrical connector, and predicting the failure of the electrical connector according to the failure prediction model. The application has the beneficial effects that: according to the different influences of the internal temperature of the electric connector and the external temperature of the electric connector, the fault prediction of the electric connector is carried out, so that the prediction of the fault of the electric connector is ensured to be suitable for different types of electric connectors, and the prediction accuracy is improved.
Description
Technical Field
The application relates to the technical field of electrical equipment fault prediction, in particular to an electrical joint fault prediction method.
Background
The main loops of the electrical equipment are all connected with each other through electrical connectors, and the main loops comprise incoming cables, outgoing cables, busbar connectors and the like. The electrical connector can be gradually aged in the long-term operation process, and the contact resistance is increased increasingly, so that the electrical connector is overheated, and the fire hazard is extremely high. Meanwhile, because the electrical equipment is often installed in a centralized way, once a fire disaster occurs, the impact range is often wide, the loss is serious, and the repair time is long.
In the related art, the temperature of the electric connector is monitored in real time, and an alarm is given out in time when the temperature of the electric connector is abnormal, so that hidden danger caused by the fault of the electric connector is avoided. However, the temperature of the electrical connector comes from two aspects, namely, the heat generated by the internal current passing through the electrical connector and the temperature of the external environment, and the influence of the heat generated by the internal current and the temperature of the external environment are different for different types of electrical connectors, so that the surface temperature of the electrical connector is monitored singly, the state of the electrical connector cannot be accurately reflected, and the fault prediction result by the surface temperature of the electrical connector is inaccurate.
China patent on-line monitoring system and method of temperature of electric power equipment, publication number: CN 110855513A, publication date: the 28 th year of 2020, 02 month, disclose the wireless temperature sensor specifically, is used for measuring the temperature of the electrical equipment, and send the measured temperature data to the temperature measurement communication terminal; the temperature measurement communication terminal is used for periodically collecting temperature data sent by the wireless temperature sensor and sending the temperature data to the data management center; the data management center is used for centrally managing the measured temperature data and simultaneously displaying and storing the data of each power equipment monitoring point in real time; a management workstation for monitoring the power devices in the form of graphics, lists, historical curves, real-time curves and/or alarms. According to the scheme, the temperatures of power equipment such as a high-voltage switch cabinet, a transformer, a reactor and the like and cable joints are monitored on line in real time through the wireless temperature sensor, the current temperature is displayed in real time, the temperature change rule of monitoring points is analyzed through software, the fault trend is predicted, the fault trend is timely alarmed when the temperature exceeds the limit, the fault part is accurately provided, the bearing capacity of different types of electric joints to different temperature conditions is not considered, and the prediction result is inaccurate.
Chinese patent, "electrical power equipment temperature supervision and regulation system based on big data", publication No.: CN114964528A, publication date: 2021, 10 and 25, specifically discloses deep, comprehensive and accurate judgment of overheat of electric power and electric equipment through symbolized calibration, data acquisition, mean value processing, formulated processing and substitution comparison. According to the scheme, only the processing of temperature data is considered, the bearing capacity of different types of electrical connectors to different temperature conditions is not considered, and the accuracy of a prediction result is low.
Disclosure of Invention
Aiming at the problem that the accuracy of a prediction result is low due to the fact that the bearing capacity of different types of electric connectors to different temperature conditions is not considered, the surface temperature of the electric connectors is simply adopted for performing fault prediction in the prior art, the application provides the electric connector fault prediction method, the external temperature influence among the electric connectors is obtained by establishing a temperature radiation model and displaying the temperature radiation relation among the electric connectors, the internal temperature of the electric connectors is obtained by calculation according to the radiation temperature and the environment temperature, the fault prediction model is constructed according to the internal temperature of the electric connectors and the correlation between the external temperature of the electric connectors and fault data of the electric connectors, and the fault prediction of the electric connectors is performed according to the different influence of the internal temperature of the electric connectors and the external temperature of the electric connectors, so that the prediction of the faults of the electric connectors is ensured to be suitable for the electric connectors of different types, and the prediction accuracy is improved.
In order to achieve the technical purpose, the technical scheme provided by the application is that the electrical joint fault prediction method comprises the following steps: s1: acquiring position data of an electrical connector, and establishing a position space model; s2: establishing a temperature radiation function, and establishing a temperature radiation model according to the temperature radiation function and the position space model; s3: acquiring historical electrical joint temperature data, environment data and fault data, calculating historical electrical joint internal temperature data according to a temperature radiation model, and constructing a fault prediction model; s4: and acquiring real-time data and environmental data of the electrical connector, and predicting the failure of the electrical connector according to the failure prediction model.
Further, the electrical connector position data at least comprises an electrical connector type, an electrical connector number and an electrical connector position, a spatial position relation among different electrical connectors is built, and a position spatial model is built.
Further, a temperature radiation function is established according to the principle of heat radiation: q=εδ (T 1 4 -T 2 4 ) S lambda; wherein Q is heat, ε is emissivity, 0 < ε < 1, δ is Stifen Bohr constant, δ=5.67×10 -8 w/(m 2 *k 4 )，T 1 For radiating the temperature of the surface 1, T 2 Lambda is the radiation proportion for the temperature of the radiation surface 2.
Further, constructing the fault prediction model includes: and calculating historical electric joint internal temperature data and historical electric joint external temperature data by using the temperature radiation model, and constructing a fault prediction model according to the historical electric joint internal temperature data, the historical electric joint external temperature data and the fault data.
Further, the temperature radiation model is utilized to calculate the internal temperature data of the historical electric joint as follows: q (Q) i ＝Q o -Q e -Q r The method comprises the steps of carrying out a first treatment on the surface of the Wherein Q is i For the internal temperature of the electrical joint, Q o For electrical junction temperature, Q e At ambient temperature, Q r The radiation temperature is calculated according to a temperature radiation model.
Further, the historical electrical connector external temperature data calculated by using the temperature radiation model is as follows: q (Q) out ＝Q e +Q r The method comprises the steps of carrying out a first treatment on the surface of the Wherein Q is out Is the temperature outside the electrical connector.
Further, constructing the fault prediction model further includes: acquiring fault data, selecting internal temperature data and external temperature data of the electrical connector during faults, respectively taking median values of the internal temperature data and the external temperature data of the electrical connector during normal operation, calculating the difference value between the internal temperature of the electrical connector during faults and the median value of the internal temperature of the electrical connector during normal operation, constructing a fault internal temperature interval, calculating the difference value between the external temperature of the electrical connector during faults and the median value of the external temperature of the electrical connector during normal operation, constructing a fault external temperature interval, and constructing a fault prediction model by using the fault internal temperature interval and the fault external temperature interval.
Further, constructing the fault prediction model includes: and calculating an internal temperature influence coefficient of the electric joint, an external temperature influence coefficient of the electric joint and an electric joint fault threshold according to the historical internal temperature data of the electric joint, the historical external temperature data of the electric joint and the fault data, and constructing a fault prediction model.
Further, the fault prediction model is: q (Q) i *λ 1 +Q out *λ 2 Not less than delta? Failure: normal; wherein lambda is 1 Lambda is the internal temperature influence coefficient of the electric joint 2 Delta is the electrical connector fault threshold and is the electrical connector external temperature influence coefficient.
Further, S4 includes: s41: acquiring historical electric joint operation data, and constructing an electric joint operation temperature change curve according to the historical electric joint operation data and the historical electric joint temperature data; s42: acquiring real-time data and environmental data of the electric joint, outputting predicted temperature data of the electric joint according to the real-time data and the running temperature change curve of the electric joint, and outputting a failure prediction result of the electric joint through a failure prediction model.
The application has the beneficial effects that: the temperature radiation model is established, the temperature radiation relation between the electric connectors is displayed, so that the external temperature influence between the electric connectors is obtained, the internal temperature of the electric connectors is calculated according to the radiation temperature and the environment temperature, a fault prediction model is constructed according to the correlation between the internal temperature of the electric connectors and the fault data of the electric connectors, and the fault prediction of the electric connectors is carried out according to the difference of the influence of the internal temperature of the electric connectors and the influence of the external temperature of the electric connectors, so that the prediction of the faults of the electric connectors is ensured to be suitable for different types of electric connectors, and the prediction accuracy is improved.
Drawings
FIG. 1 is a flow chart of an embodiment of a method for predicting electrical connector failure according to the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the present application will be described in further detail with reference to the accompanying drawings and examples, it being understood that the detailed description herein is merely a preferred embodiment of the present application, which is intended to illustrate the present application, and not to limit the scope of the application, as all other embodiments obtained by those skilled in the art without making any inventive effort fall within the scope of the present application.
As shown in fig. 1, as an embodiment of the present application, an electrical joint failure prediction method includes the steps of:
s1: acquiring position data of an electrical connector, and establishing a position space model;
s2: establishing a temperature radiation function, and establishing a temperature radiation model according to the temperature radiation function and the position space model;
s3: acquiring historical electrical joint temperature data, environment data and fault data, calculating historical electrical joint internal temperature data according to a temperature radiation model, and constructing a fault prediction model;
s4: and acquiring real-time data and environmental data of the electrical connector, and predicting the failure of the electrical connector according to the failure prediction model.
When the temperature of any object is higher than 0K, heat radiation is continuously emitted to the surrounding space, the main circuits of the electric equipment are connected through the electric joints, the residual gaps between the electric equipment are small, the electric joints are affected by the heat radiation from the environment temperature and the rest joints, namely, the temperature of the electric joints is from three parts: the electrical current within the electrical connector generates heat, ambient temperature, and heat radiation from the remaining electrical connector. In a different electrical connector, the temperature from the inside and the temperature from the outside are not the same as the life of the electrical connector, e.g. the wire clamps and the knife switch are more susceptible to the influence from the outside temperature, whereas the high voltage electrical equipment connector is more susceptible to the influence of the inside temperature generated by the high voltage current. In this embodiment, position data of the electrical connector is obtained, a position space model is established, so that a position relation between different connectors is displayed through the position space model, a heat radiation relation between different connector positions is calculated according to a temperature radiation function, a temperature radiation model is established, historical internal temperature data of the electrical connector is calculated according to the temperature radiation model, a fault prediction model is established according to the historical internal temperature data of the electrical connector and fault data, and therefore fault possible conditions of the electrical connector under different temperature conditions are calculated, and prediction of faults of the electrical connector is guaranteed to be adapted to different types of electrical connectors.
In this embodiment, the electrical connector position data at least includes an electrical connector type, an electrical connector number, and an electrical connector position, and a spatial position relationship between different electrical connectors is constructed, and a position spatial model is established. The fault data includes at least a fault type, a fault location, and a fault temperature. Establishing a temperature radiation function according to a heat radiation principle:
Q＝εδ(T 1 4 -T 2 4 )*S*λ；
wherein Q is heat, ε is emissivity, 0 < ε < 1, δ is Stifen Bohr constant, δ=5.67×10 -8 w/(m 2 *k 4 )，T 1 For radiating the temperature of the surface 1, T 2 Lambda is the radiation proportion for the temperature of the radiation surface 2. Emissivity is a function of material and surface morphology and can be calculated from the type of electrical connector and the temperature of the electrical connector surface. The radiation proportion is the proportion of the transmission value in the heat transmission process to all the transmission heat, namely the radiation proportion is influenced by the relative position relation of the ambient temperature and the electric joints in the heat transmission process, so that the temperature radiation function is brought into the position space model, the emissivity and the radiation proportion can be obtained according to the position space model, namely the emissivity and the radiation proportion can be obtained according to the type of the electric joints, and the heat transmitted between the electric joints can be calculated.
Bringing a temperature radiation function into a position space model, establishing a temperature radiation model, acquiring historical electric joint temperature data and environment data, and obtaining internal temperature data of the electric joint according to the relative radiation influence and the environment temperature influence between the electric joints:
Q i ＝Q o -Q e -Q r ；
wherein Q is i For the internal temperature of the electrical joint, Q o For electrical junction temperature, Q e Is the ambient temperature，Q r The radiation temperature is calculated according to a temperature radiation model.
The external temperature of the electrical connector is thus:
Q out ＝Q e +Q r ；
wherein Q is out Is the temperature outside the electrical connector.
According to the internal temperature of the electric joint, the external temperature of the electric joint and the electric joint fault data, the condition of the internal temperature and the external temperature of a certain electric joint when the electric joint is in fault can be obtained, and a fault prediction model related to the temperature is established. And acquiring real-time data and environment data of the electrical connector, outputting real-time internal temperature and real-time external temperature of the electrical connector according to the temperature radiation model, outputting fault prediction data according to the fault prediction model by using the real-time internal temperature and the real-time external temperature, and performing fault prediction of the electrical connector. According to the correlation between the internal and external temperatures of the electrical connectors and the failure of the electrical connectors, the failure probability of the electrical connectors under the condition of the temperature is output, and the temperature failure prediction of different electrical connectors is adapted.
In this embodiment, the historical electrical joint internal temperature data and the historical electrical joint external temperature data are obtained through the temperature radiation model calculation, after the fault data are obtained, the electrical joint internal temperature data and the electrical joint external temperature data during the fault are selected, the electrical joint internal temperature data and the electrical joint external temperature data during the normal operation of the electrical joint are respectively median values, the difference value between the electrical joint internal temperature during the fault and the electrical joint internal temperature median value during the normal operation is calculated, a fault internal temperature interval is constructed, the difference value between the electrical joint external temperature during the fault and the electrical joint external temperature median value during the normal operation is calculated, a fault external temperature interval is constructed, and a fault prediction model is constructed by the fault internal temperature interval and the fault external temperature interval. And when the difference value between the real-time internal temperature of the electric joint and the median value of the internal temperature of the electric joint in normal operation falls in a fault internal temperature interval, and simultaneously, the difference value between the real-time external temperature of the electric joint and the median value of the external temperature of the electric joint in normal operation falls in a fault external temperature interval, and fault early warning is carried out.
As a second embodiment of the present application, considering that an electrical joint may fail when an internal temperature of the electrical joint is too high and an external temperature does not reach a failed external temperature section due to environmental influence, constructing a failure prediction model includes: and calculating an internal temperature influence coefficient of the electric joint, an external temperature influence coefficient of the electric joint and an electric joint fault threshold according to the historical internal temperature data of the electric joint, the historical external temperature data of the electric joint and the fault data, and constructing a fault prediction model.
In this embodiment, the failure prediction model is:
Q i *λ 1 +Q out *λ 2 not less than delta? Failure: normal;
wherein lambda is 1 Lambda is the internal temperature influence coefficient of the electric joint 2 And when the product of the internal temperature of the electric joint and the influence coefficient of the internal temperature of the electric joint plus the influence coefficient of the external temperature of the electric joint is smaller than the electric joint fault threshold, the electric joint is in a normal working temperature state, and no intervention is needed. Lambda (lambda) 1 、λ 2 And calculating the correlation between the historical electric joint internal temperature data and the historical electric joint external temperature data and fault data, and calculating the electric joint fault threshold according to the lowest electric joint internal temperature data and the lowest electric joint external temperature data under the historical fault condition. Therefore, when the internal temperature of the electric connector is too high or the external temperature is too high, the fault early warning can be triggered, and the unstable influence of the ambient temperature is eliminated.
As a third embodiment of the present application, step S4 includes:
s41: acquiring historical electric joint operation data, and constructing an electric joint operation temperature change curve according to the historical electric joint operation data and the historical electric joint temperature data;
s42: acquiring real-time data and environmental data of the electric joint, outputting predicted temperature data of the electric joint according to the real-time data and the running temperature change curve of the electric joint, and outputting a failure prediction result of the electric joint through a failure prediction model.
The historical electric joint operation data at least comprise electric joint operation time, and a change relation curve of the electric joint operation time and the electric joint temperature, namely an electric joint operation temperature change curve, can be obtained according to the electric joint operation time and the historical electric joint temperature data. The real-time data of the electric joint at least comprises the real-time temperature of the electric joint and the running time of the electric joint, so that the temperature of the electric joint is predicted according to a change curve of the running temperature of the electric joint, and the predicted temperature data of the electric joint is output. The environment data at least comprises real-time environment data and predicted environment data, and the electrical connector fault prediction result is output through the fault prediction model according to the predicted environment data and the electrical connector predicted temperature data. The predicted environmental temperature can directly obtain the temperature change condition in a future period through networking, an environmental temperature change curve can be constructed through historical environmental temperature, the predicted environmental temperature can be output according to the environmental temperature change curve and real-time environmental data, in other embodiments, the initial predicted environmental temperature can be output according to the environmental temperature change curve and the real-time environmental data, and average calculation is carried out according to the temperature change condition in the future period and the initial predicted environmental temperature, so that the predicted environmental temperature is obtained, the environmental temperature prediction accuracy is improved, and the difference between the temperature change condition in the future period obtained through networking caused by indoor environment and the actual indoor temperature is reduced.
In other embodiments, the historical electrical joint operating data further includes electrical joint current data, such that the electrical joint temperature is predicted based on the electrical joint current data and the electrical joint operating time.
In the embodiment, the prediction of the future fault possibility of the electric connector is realized by predicting the temperature of the electric connector in the future time period, so that the electric connector fault is predicted in advance, the electric connector is convenient to maintain and repair in time, and the safety problem caused by the fault is avoided.
The above embodiments are preferred embodiments of the electrical connector fault prediction method according to the present application, and the scope of the present application is not limited to the preferred embodiments, but all equivalent changes according to the shape and structure of the present application are within the scope of the present application.
Claims (10)
1. The electric joint fault prediction method is characterized in that: the method comprises the following steps:
s1: acquiring position data of an electrical connector, and establishing a position space model;
s2: establishing a temperature radiation function, and establishing a temperature radiation model according to the temperature radiation function and the position space model;
s3: acquiring historical electrical joint temperature data, environment data and fault data, calculating historical electrical joint internal temperature data according to a temperature radiation model, and constructing a fault prediction model;
s4: and acquiring real-time data and environmental data of the electrical connector, and predicting the failure of the electrical connector according to the failure prediction model.
2. The electrical connector fault prediction method of claim 1, wherein:
the electric joint position data at least comprises electric joint types, electric joint numbers and electric joint positions, and space position relations among different electric joints are built, so that a position space model is built.
3. The electrical connector fault prediction method of claim 1, wherein:
establishing a temperature radiation function according to a heat radiation principle:
Q＝εδ(T 1 4 -T 2 4 )*S*λ；
wherein Q is heat, εFor emissivity, 0 < ε < 1, δ is the Stifen Bohr constant, δ=5.67×10 -8 w/(m 2 *k 4 )，T 1 For radiating the temperature of the surface 1, T 2 Lambda is the radiation proportion for the temperature of the radiation surface 2.
4. The electrical connector fault prediction method of claim 1, wherein:
the construction of the fault prediction model comprises the following steps:
and calculating historical electric joint internal temperature data and historical electric joint external temperature data by using the temperature radiation model, and constructing a fault prediction model according to the historical electric joint internal temperature data, the historical electric joint external temperature data and the fault data.
5. The electrical connector fault prediction method as claimed in claim 4, wherein:
the method for calculating the internal temperature data of the historical electric joint by using the temperature radiation model comprises the following steps:
Q i ＝Q o -Q e -Q r ；
wherein Q is i For the internal temperature of the electrical joint, Q o For electrical junction temperature, Q e At ambient temperature, Q r The radiation temperature is calculated according to a temperature radiation model.
6. The electrical connector fault prediction method as claimed in claim 5, wherein:
the method for calculating the historical electrical connector external temperature data by using the temperature radiation model comprises the following steps of:
Q out ＝Q e +Q r ；
wherein Q is out Is the temperature outside the electrical connector.
7. The electrical connector fault prediction method as claimed in claim 4, wherein:
the constructing of the fault prediction model further comprises:
acquiring fault data, selecting internal temperature data and external temperature data of the electrical connector during faults, respectively taking median values of the internal temperature data and the external temperature data of the electrical connector during normal operation, calculating the difference value between the internal temperature of the electrical connector during faults and the median value of the internal temperature of the electrical connector during normal operation, constructing a fault internal temperature interval, calculating the difference value between the external temperature of the electrical connector during faults and the median value of the external temperature of the electrical connector during normal operation, constructing a fault external temperature interval, and constructing a fault prediction model by using the fault internal temperature interval and the fault external temperature interval.
8. The electrical connector fault prediction method of claim 1, wherein:
the construction of the fault prediction model comprises the following steps: and calculating an internal temperature influence coefficient of the electric joint, an external temperature influence coefficient of the electric joint and an electric joint fault threshold according to the historical internal temperature data of the electric joint, the historical external temperature data of the electric joint and the fault data, and constructing a fault prediction model.
9. The electrical connector fault prediction method as claimed in claim 8, wherein:
the fault prediction model is as follows:
Q i *λ 1 +Q out *λ 2 not less than delta? Failure: normal;
wherein lambda is 1 Lambda is the internal temperature influence coefficient of the electric joint 2 Delta is the electrical connector fault threshold and is the electrical connector external temperature influence coefficient.
10. The electrical connector fault prediction method of claim 1, wherein:
the step S4 comprises the following steps:
s41: acquiring historical electric joint operation data, and constructing an electric joint operation temperature change curve according to the historical electric joint operation data and the historical electric joint temperature data;
s42: acquiring real-time data and environmental data of the electric joint, outputting predicted temperature data of the electric joint according to the real-time data and the running temperature change curve of the electric joint, and outputting a failure prediction result of the electric joint through a failure prediction model.
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