CN117288348B - Bus duct temperature measurement method and system - Google Patents
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Abstract
The invention relates to the technical field of temperature measurement, and provides a bus duct temperature measurement method and system, wherein the method comprises the following steps: obtaining local subsequences of the temperature of the bus duct and the ambient temperature, and further obtaining the continuous dependence degree and fluctuation turbulence characteristics of the ambient temperature; obtaining fluctuation turbulence feature vectors of the bus duct temperature, and further determining abnormal temperature data; obtaining an abnormal duty ratio and an abnormal temperature sequence according to the abnormal temperature data, obtaining the overall anomaly degree of the bus duct temperature sequence according to the abnormal duty ratio, the number of the abnormal temperature data and the abnormal temperature sequence of the bus duct temperature sequence, obtaining the self-adaptive parameter of the bus duct temperature sequence according to the overall anomaly degree, obtaining the actual temperature of the bus duct at the last acquisition time in the bus duct temperature sequence according to the self-adaptive parameter, and realizing real-time temperature measurement of the bus duct. The invention solves the problem of low efficiency of real-time monitoring of the temperature measurement of the bus duct.
Description
Technical Field
The invention relates to the technical field of temperature measurement, in particular to a bus duct temperature measurement method and system.
Background
Bus ducts are common conductive devices in power transmission and distribution systems. The bus duct is used for transmitting electric energy, and has the advantages of high current density, convenience in installation, high reliability and the like, so that the bus duct is usually used for transmitting high current. In the long-time operation of the bus duct, the heat accumulation and the temperature rise of the bus duct can be caused due to the influences of factors such as load change, environmental conditions and the like, so that the electric energy loss is increased. If the temperature is continuously increased even exceeds the allowable range, the insulation performance of the bus duct is further reduced, and the bus duct is burnt out due to breakdown of an insulation layer, so that the safety and the reliability of equipment are threatened. Therefore, in order to ensure safe operation of the power equipment, it is important to perform temperature monitoring on the bus duct.
At present, a commonly used bus duct temperature measurement method is contact type temperature measurement, namely a sensor such as a thermocouple or a thermistor is used, a temperature sensor is arranged on the surface of the bus duct, the sensor is connected with a detection instrument, and when the sensor and an object to be detected reach a thermal balance state, the temperature of the object can be accurately sensed. Therefore, the problem of measurement delay commonly exists in contact type temperature measurement, so that the real-time monitoring efficiency of the bus duct temperature is lower.
Disclosure of Invention
The invention provides a bus duct temperature measurement method and a bus duct temperature measurement system, which aim to solve the problem of low bus duct temperature measurement real-time monitoring efficiency, and the adopted technical scheme is as follows:
in a first aspect, an embodiment of the present invention provides a method for measuring a temperature of a bus duct, including:
collecting the temperature and the environment temperature of a bus duct, and obtaining a bus duct temperature sequence and an environment temperature sequence;
acquiring a local subsequence of the bus duct temperature in the bus duct temperature sequence and a local subsequence of the environmental temperature in the environmental temperature sequence, and acquiring the environmental temperature change continuous dependency of the bus duct temperature at the acquisition time according to the cross-correlation distance between the bus duct temperature at the same acquisition time and the local subsequence of the environmental temperature;
obtaining a variation coefficient of the bus duct temperature according to the local subsequence of the bus duct temperature, and obtaining fluctuation turbulence characteristics of the bus duct temperature according to the variation coefficient of adjacent elements of the bus duct temperature and the bus duct temperature in the bus duct temperature sequence;
obtaining fluctuation disorder feature vectors of the bus duct temperature according to the local subsequences of the bus duct temperature, obtaining fluctuation disorder feature vectors of the environment temperature according to the local subsequences of the environment temperature and the fluctuation disorder features, obtaining similarity and maximum disorder feature values among the fluctuation disorder feature vectors, obtaining local fluctuation sensitivity of the bus duct temperature according to the similarity among the fluctuation disorder feature vectors, the maximum disorder feature values and the environment temperature change continuous dependency, and determining abnormal temperature data according to the local fluctuation sensitivity;
obtaining an abnormal duty ratio and an abnormal temperature sequence of the bus duct temperature sequence according to the abnormal temperature data, obtaining the overall anomaly degree of the bus duct temperature sequence according to the abnormal duty ratio, the number of the abnormal temperature data and the abnormal temperature sequence of the bus duct temperature sequence, obtaining self-adaptive parameters of the bus duct temperature sequence according to the overall anomaly degree of the bus duct temperature sequence, and obtaining the actual temperature of the bus duct at the last acquisition time in the bus duct temperature sequence according to the self-adaptive parameters so as to realize real-time temperature measurement of the bus duct.
Further, the method for acquiring the local subsequence of the bus duct temperature in the bus duct temperature sequence and the local subsequence of the environmental temperature in the environmental temperature sequence comprises the following steps:
taking each bus duct temperature in the bus duct temperature sequence as the bus duct temperature to be analyzed, and taking each environmental temperature in the environmental temperature sequence as the environmental temperature to be analyzed;
the method comprises the steps that before and after the acquisition time of the bus duct temperature to be analyzed, each first preset threshold value element and the bus duct temperature to be analyzed are recorded as neighborhood elements of the bus duct temperature to be analyzed;
arranging neighborhood elements of the bus duct temperature to be analyzed according to the acquisition time sequence, and acquiring a local subsequence of the bus duct temperature to be analyzed;
local subsequences of the ambient temperature to be analyzed are obtained.
Further, the obtaining method for obtaining the fluctuation turbulence characteristics of the bus duct temperature according to the local subsequence of the bus duct temperature and the variation coefficient of the adjacent element of the bus duct temperature and the bus duct temperature in the bus duct temperature sequence comprises the following steps:
the variation coefficient of the local subsequence of the bus duct temperature to be analyzed is recorded as the variation coefficient of the bus duct temperature to be analyzed;
the difference value between the bus duct temperature to be analyzed and the bus duct temperature at the moment before the bus duct temperature to be analyzed is recorded as a first difference value, and the difference value between the bus duct temperature at the moment after the bus duct temperature to be analyzed and the bus duct temperature to be analyzed is recorded as a second difference value;
and recording the product of the first difference value, the second difference value and the variation coefficient of the bus duct temperature to be analyzed as the fluctuation turbulence characteristic of the bus duct temperature to be analyzed.
Further, the method for obtaining the fluctuation disorder feature vector of the bus duct temperature according to the local subsequence of the bus duct temperature and the fluctuation disorder feature vector of the ambient temperature according to the local subsequence of the ambient temperature and the fluctuation disorder feature comprises the following steps:
arranging fluctuation disorder features of the bus duct temperature contained in the local subsequence of the bus duct temperature to be analyzed according to the acquisition time sequence of the bus duct temperature to obtain a fluctuation disorder feature vector of the bus duct temperature to be analyzed;
and obtaining a fluctuation disorder feature vector of the environmental temperature to be analyzed.
Further, the method for obtaining the similarity and the maximum disorder characteristic value between the fluctuation disorder characteristic vectors comprises the following steps:
obtaining similarity of a fluctuation turbulence feature vector of the temperature of the bus duct to be analyzed and a fluctuation turbulence feature vector of the temperature of the environment to be analyzed at the same acquisition time;
and (5) recording the maximum value of the similarity as a maximum disorder characteristic value.
Further, the method for determining abnormal temperature data according to the local fluctuation sensitivity comprises the following steps:
and marking the bus duct temperature with the local fluctuation sensitivity larger than a first preset threshold value as abnormal temperature data.
Further, the method for obtaining the abnormal duty ratio and the abnormal temperature sequence of the bus duct temperature sequence according to the abnormal temperature data comprises the following steps:
the ratio of the number of the abnormal temperature data to the total number of the collected bus duct temperatures is recorded as the abnormal duty ratio of the bus duct temperature sequence;
and arranging the abnormal temperature data according to the sequence of the acquisition time to obtain an abnormal temperature sequence.
Further, the method for obtaining the self-adaptive parameters of the bus duct temperature sequence according to the overall anomaly degree of the bus duct temperature sequence comprises the following steps:
and (3) recording the downward integral value of the product of the linear normalized value of the overall anomaly degree of the bus duct temperature sequence and the initial value of the autoregressive term number as the self-adaptive parameter of the bus duct temperature sequence.
Further, the method for obtaining the actual temperature of the bus duct at the last acquisition time in the bus duct temperature sequence according to the self-adaptive parameters and realizing real-time temperature measurement of the bus duct comprises the following steps:
taking the self-adaptive parameter as the autoregressive term number of the autoregressive differential moving average model, and predicting the bus duct temperature at a second preset threshold value after the last acquisition time in the bus duct temperature sequence according to the bus duct temperature sequence;
and taking the average value of the predicted second preset threshold values of the bus duct temperatures as the actual bus duct temperature at the last acquisition time in the bus duct temperature sequence, so as to realize real-time monitoring of the bus duct temperature.
In a second aspect, an embodiment of the present invention further provides a bus duct temperature measurement system, including a memory, a processor, and a computer program stored in the memory and running on the processor, where the processor implements the steps of any one of the methods described above when executing the computer program.
The beneficial effects of the invention are as follows:
according to the invention, the influence degree of the environmental temperature change in the bus duct temperature measurement process is analyzed, and the environmental temperature change continuous dependence is obtained according to the bus duct temperature and the environmental temperature, wherein the environmental temperature change continuous dependence reflects the similarity degree of the local change of the bus duct temperature and the local change of the environmental temperature; further, analyzing the influence of the fluctuation degree of the ambient temperature of the environment where the bus duct is located on the change trend of the bus duct temperature measurement result, and acquiring local fluctuation sensitivity according to the fluctuation turbulence characteristics of the bus duct temperature and the ambient temperature, wherein the local fluctuation sensitivity reflects the sensitivity degree of the monitoring result of the bus duct temperature to the ambient temperature; then, aiming at the influence of the data abnormality degree on parameters in the prediction model, acquiring abnormal temperature data according to the local fluctuation sensitivity, and further acquiring the overall abnormality degree of the bus duct temperature sequence; finally, the actual bus duct temperature at the last acquisition time in the bus duct temperature sequence is obtained according to the self-adaptive parameters by adaptively adjusting the autoregressive term number of the autoregressive differential moving average model according to the overall abnormal degree, so that the real-time temperature measurement of the bus duct is realized, the problem of low real-time monitoring efficiency of the bus duct temperature measurement is solved, and the real-time monitoring efficiency and accuracy of the bus duct temperature are improved.
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In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings which are used in the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the description below are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive faculty for a person skilled in the art.
FIG. 1 is a schematic flow chart of a method for measuring temperature of a bus duct according to an embodiment of the present invention;
FIG. 2 is a schematic diagram showing a trend of bus duct temperature affected by ambient temperature;
fig. 3 is a flow chart of actual temperature acquisition of the bus duct.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a flowchart of a method for measuring temperature of a bus duct according to an embodiment of the invention is shown, and the method includes the following steps:
and S001, collecting the temperature of the bus duct and the ambient temperature, and obtaining a bus duct temperature sequence and an ambient temperature sequence.
Mounting temperature sensors to busway surfaces at intervals of timeAnd acquiring the temperature of the primary bus duct by using a temperature sensor. At the same time, another temperature sensor is placed in the external environment where the bus duct is located, every interval of time +.>The method comprises the steps of acquiring primary environment temperature, wherein the acquisition time of acquiring the environment temperature is identical to the acquisition time of the bus duct temperature. Co-acquisition->The individual busway temperature and the ambient temperature.
Wherein,the empirical value of (2) is 0.5s, < >>Is 600.
Respectively to collectThe temperature of each bus duct and the ambient temperature are arranged according to the sequence of the acquisition time, and the bus duct temperature sequence +.>And ambient temperature sequence->。
So far, a bus duct temperature sequence and an ambient temperature sequence are obtained.
Step S002, obtaining a local subsequence of the bus duct temperature in the bus duct temperature sequence and a local subsequence of the environmental temperature in the environmental temperature sequence, and obtaining the environmental temperature change continuous dependency of the bus duct temperature at the acquisition time according to the cross-correlation distance between the bus duct temperature at the same acquisition time and the local subsequence of the environmental temperature.
Because the bus duct is in the environment with the influence of heat sources such as a motor and a transformer, the environment temperature of the environment of the bus duct is increased, and when the environment of the bus duct is cooled by ventilation or heat dissipation equipment, the temperature of the environment of the bus duct can be greatly changed. Meanwhile, when the temperature of the bus duct is measured by adopting a contact temperature measuring method, the exposed temperature sensor is easily affected by the change condition of the ambient temperature, so that the change of the measuring result of the temperature of the bus duct is larger.
Based on the analysis, the influence degree of the environmental temperature change in the bus duct temperature measurement process can be obtained through the bus duct temperature sequence and the environmental temperature sequence.
And marking points corresponding to each numerical value in the bus duct temperature sequence and the environment temperature sequence respectively by taking the serial numbers of the data in the bus duct temperature sequence and the environment temperature sequence as the horizontal axis and taking the data value as the vertical axis, and sequentially connecting the same kind of data by fold lines to establish a change trend schematic diagram of the bus duct temperature affected by the environment temperature. The schematic diagram of the variation trend of the temperature of the bus duct affected by the ambient temperature is shown in fig. 2. As can be seen from the schematic diagram of the change trend of the bus duct temperature affected by the ambient temperature, certain similarity exists between the bus duct temperature sequence and the temperature change corresponding to the ambient temperature sequence, so that the dependence of the bus duct temperature on the ambient temperature can be obtained by analyzing the local similarity degree of the bus duct temperature sequence and the ambient temperature sequence.
Bus duct temperature sequenceMiddle element->Indicate->Bus duct temperatures at each acquisition instant. Acquisition elementSu->Front and back are respectively->Element->To element->Co (all ]>Element->Of the neighborhood elements of (1), wherein->Is 5.
When an element isIs insufficient in neighborhood elements>And obtaining element predicted values of the element-free positions by using a Lagrange interpolation method, and calculating by using the element predicted values so as to ensure that analysis is meaningful.
Will beThe neighborhood elements of (2) are arranged according to the acquisition time sequence to acquire +.>Is->。
Similarly, an ambient temperature sequence is obtainedMiddle element->Is->。
Since the temperature sensor has hysteresis in measuring the temperature, the cross-correlation distance measurement method SBD distance is used to measure the similarity between the local subsequence of the bus duct temperature and the local subsequence of the ambient temperature. The calculation of the SBD distance is a known technique, and will not be described in detail.
According to elementsLocal subsequence and element->SBD distance between partial subsequences of (2) to obtain +.>Bus duct temperature at individual acquisition times +.>Is dependent on the environmental temperature change continuously->。
Wherein,is->Bus duct temperature at individual acquisition times +.>Is a continuous dependence of ambient temperature change;is the first part of the bus duct temperature sequence>Individual element->Is->And (4) in the ambient temperature sequence>Individual element->Is->SBD distance between;is the first part of the bus duct temperature sequence>Individual element->Is->And (4) in the ambient temperature sequence>Individual element->Is->SBD distance between; />Is->Neighborhood element number of (2); />Is an exponential function based on natural constants; />For the first preset threshold, the empirical value is 5.
When the bus duct temperature is the element in the sequenceThe smaller the difference in SBD distance between the local subsequence of the adjacent element in the neighborhood element and the local subsequence of the corresponding element in the ambient temperature sequence, the more similar the local change of the bus duct temperature and the local change of the ambient temperature, the bus duct temperature +.>The greater the ambient temperature change continuity dependence of +.>The greater the extent to which the busway temperature at each acquisition instant is affected by ambient temperature changes.
So far, the environmental temperature change continuous dependency of the bus duct temperature at each acquisition time is obtained.
Step S003, obtaining a variation coefficient of the bus duct temperature according to the local subsequence of the bus duct temperature, and obtaining fluctuation turbulence characteristics of the bus duct temperature according to the variation coefficients of adjacent elements of the bus duct temperature and the bus duct temperature in the bus duct temperature sequence.
The complexity of the environment where the bus duct is located determines the variation turbulence degree of the ambient temperature, and the ambient temperature shows the variation trend of irregular fluctuation due to the heating of the power equipment and the cooling of the heat dissipation equipment. If the change characteristics of the collected bus duct temperature are similar to the change characteristics of the ambient temperature, namely the greater the ambient temperature change continuity dependence of the bus duct temperature, the more severely the collected bus duct temperature is affected by the ambient temperature fluctuation trend, namely the more sensitive to the ambient temperature change, and the further the collected bus duct temperature deviates from the true value. Therefore, it is necessary to analyze the degree of synchronous change between the ambient temperature change characteristic and the change characteristic of the bus duct temperature.
First, an element is acquiredThe coefficient of variation of the local subsequence of (2) will be element +.>The mutation coefficient of the partial subsequence of (2) is marked as element +.>Coefficient of variation->. The calculation process of the coefficient of variation of the sequence is a known technique and will not be described in detail.
According to the bus duct temperature sequenceMiddle element->Adjacent elements and elements->Obtain the coefficient of variation of->Bus duct temperature at individual acquisition times +.>Is characterized by fluctuation disorder of->。
Wherein,is->Bus duct temperature at individual acquisition times +.>Is characterized by a wave disorder of (a); />Is->Bus duct temperatures at the respective acquisition times; />Is->Bus duct temperatures at the respective acquisition times; />Is->Bus duct temperatures at the respective acquisition times; />Is->Is a coefficient of variation of (a).
When the fluctuation turbulence characteristics are smaller than 0, the fluctuation turbulence characteristics indicate that the temperature change trend of the bus duct at the collection time is not monotonous, namely the fluctuation change trend of the bus duct at the collection time is relatively turbulent; when the bus duct temperature at the collection time is larger than the bus duct temperature at the front and rear adjacent collection times and the variation coefficient is larger, the bus duct temperature at the collection time is more intense in change and the fluctuation disorder degree is stronger, the absolute value of fluctuation disorder characteristics is larger, and the bus duct temperature fluctuation is more disorder.
So far, the fluctuation turbulence characteristics of the bus duct temperature at each acquisition time are obtained.
Step S004, obtaining fluctuation disorder feature vectors of the bus duct temperature according to the local subsequences of the bus duct temperature, obtaining fluctuation disorder feature vectors of the environment temperature according to the local subsequences of the environment temperature and the fluctuation disorder features, obtaining similarity and maximum disorder feature values among the fluctuation disorder feature vectors, obtaining local fluctuation sensitivity of the bus duct temperature according to the similarity and the maximum disorder feature values among the fluctuation disorder feature vectors and the environment temperature change continuous dependency, and determining abnormal temperature data according to the local fluctuation sensitivity.
And obtaining fluctuation turbulence characteristics of all elements in the bus duct temperature sequence according to the fluctuation turbulence characteristics of the bus duct temperature at each collection time.
Will be the firstBus duct temperature at individual acquisition times +.>The fluctuation disorder characteristics of the bus duct temperature contained in the local subsequence of (a) are arranged according to the sequence of the bus duct temperature in the local subsequence, so as to obtain the bus duct temperature +.>Is>，/>。
Similarly, according to the acquisition method of the fluctuation disorder characteristic sequence, the corresponding first phase in the environmental temperature sequence is acquiredAmbient temperature at the individual acquisition instants +.>Is>。
Acquiring vectorsVector->Cosine similarity between them. The calculation of cosine similarity of two vectors with the same dimension is a well-known technique, and is not described in detail. The maximum value of cosine similarity between the fluctuation disorder characteristic vector of the bus duct temperature and the fluctuation disorder characteristic vector of the ambient temperature at all acquisition moments is recorded as a maximum disorder characteristic value +.>。
According to the firstBus duct temperature at individual acquisition times +.>And ambient temperature->Cosine similarity of fluctuation disorder feature vector, maximum disorder feature value and environment temperature change continuous dependency to obtain +.>Bus duct temperature at individual acquisition times +.>Is>。
Wherein,is->Bus duct temperature at individual acquisition times +.>Is a local fluctuation sensitivity of (1); />Is->Bus duct temperature at individual acquisition times +.>Is>And->Ambient temperature at the individual acquisition instants +.>Is>Cosine similarity between them; />Is->Bus duct temperature at individual acquisition times +.>Is a continuous dependence of ambient temperature change; />Is the maximum disturbance characteristic value; />Is an exponential function based on natural constants; />The empirical value is 1 for the first tuning coefficient.
When the similarity between the fluctuation disorder feature vector of the bus duct temperature at the collection time and the fluctuation disorder feature vector of the ambient temperature is larger than the maximum disorder feature value and the continuous dependence of the ambient temperature is larger, the local fluctuation sensitivity is larger as compared with the similarity between the disorder feature of the bus duct temperature at the collection time and the disorder feature of the ambient temperature is larger at other collection times and the influence degree of the ambient temperature is larger, the monitoring result of the bus duct temperature at the collection time is more sensitive to the ambient temperature, and the bus duct temperature measurement is more inaccurate.
The local fluctuation sensitivity is larger than a first preset threshold valueIs marked as abnormal temperature data. Wherein,is 0.6.
So far, abnormal temperature data is acquired.
Step S005, obtaining an abnormal duty ratio and an abnormal temperature sequence of the bus duct temperature sequence according to the abnormal temperature data, obtaining the overall anomaly degree of the bus duct temperature sequence according to the abnormal duty ratio, the quantity of the abnormal temperature data and the abnormal temperature sequence of the bus duct temperature sequence, obtaining self-adaptive parameters of the bus duct temperature sequence according to the overall anomaly degree of the bus duct temperature sequence, and obtaining the actual temperature of the bus duct at the last acquisition time in the bus duct temperature sequence according to the self-adaptive parameters so as to realize real-time temperature measurement of the bus duct.
In order to solve the problem of measurement delay commonly existing when a temperature sensor is used for measuring the temperature of the bus duct, an ARIMA autoregressive differential moving average model is adopted, and the bus duct temperature for a period of time in the future is predicted according to a bus duct temperature sequence, so that the purpose of monitoring the bus duct temperature in real time is achieved. When using the ARIMA model for prediction, the efficiency and accuracy of the prediction result is affected by the autoregressive terms of the ARIMA model. The number of autoregressive terms is the number of historical observations involved in the prediction, i.e., the number of busway temperatures involved in the prediction. The larger the autoregressive term number is, the more accurate the prediction result is; the smaller the number of autoregressive terms, the higher the prediction efficiency.
Based on the analysis, the autoregressive term number of the ARIMA model is adaptively adjusted according to the abnormal condition of the bus duct temperature in the bus duct temperature sequence, so that a good prediction effect is obtained.
First, the number of abnormal temperature data is calculatedQuantity of bus duct temperature collected +.>The ratio of (2) is recorded as the abnormal ratio of the bus duct temperature sequence +.>. Then the abnormal temperature data are arranged according to the sequence of the acquisition time corresponding to the abnormal temperature data, and an abnormal temperature sequence +.>。
Acquiring the overall anomaly degree of the bus duct temperature sequence according to the anomaly duty ratio of the bus duct temperature sequence, the quantity of the anomaly temperature data and the anomaly temperature sequence。
Wherein,the overall anomaly of the bus duct temperature sequence; />The abnormal duty ratio of the bus duct temperature sequence; />Is the number of abnormal temperature data; />Is an abnormal temperature sequence->Middle->The corresponding acquisition time of the abnormal temperature data, wherein,；/>is an abnormal temperature sequence->Middle->And the acquisition time corresponding to the abnormal temperature data.
When the abnormal occupation ratio is larger and the acquisition time corresponding to adjacent abnormal temperature data is closer, the more and denser the abnormal temperature data are, the larger the overall abnormal degree of the bus duct temperature sequence is, the larger the autoregressive item number is selected to improve the prediction accuracy; when the abnormal proportion is smaller and the acquisition time corresponding to the adjacent abnormal temperature data is farther away, the abnormal temperature data is smaller and more discrete, the whole abnormal degree of the bus duct temperature sequence is smaller, and the smaller autoregressive item number is selected to improve the prediction efficiency.
Obtaining self-adaptive parameters of the bus duct temperature sequence according to the overall anomaly degree of the bus duct temperature sequence。
Wherein,the self-adaptive parameter is the self-adaptive parameter of the bus duct temperature sequence; />The overall anomaly of the bus duct temperature sequence;a downward rounding function that functions as a downward rounding of the values in brackets; />As a linear normalization function, acts as a linear normalization value for the values in brackets; />For the initial value of the autoregressive term, the empirical value is +.>，/>Is the number of busway temperatures contained in the busway temperature sequence.
Will adapt parametersAnd predicting the bus duct temperature at a second preset threshold value after the last acquisition time in the bus duct temperature sequence according to the bus duct temperature sequence as the autoregressive term number of the ARIMA model. Wherein, the empirical value of the differential order is 2; the empirical value of the moving average order is 3; the empirical value of the second preset threshold is 6.
Taking the average value of the predicted bus duct temperatures at the second preset threshold value collecting time as the actual bus duct temperature at the last collecting time in the bus duct temperature sequence. The actual temperature obtaining flow chart of the bus duct is shown in fig. 3.
Thus, the real-time monitoring of the bus duct temperature is completed.
Based on the same inventive concept as the above method, the embodiment of the invention further provides a bus duct temperature measurement system, which comprises a memory, a processor and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to realize the steps of any one of the bus duct temperature measurement methods.
The foregoing description of the preferred embodiments of the present invention is not intended to be limiting, but rather, any modifications, equivalents, improvements, etc. that fall within the principles of the present invention are intended to be included within the scope of the present invention.
Claims (6)
1. The bus duct temperature measurement method is characterized by comprising the following steps of:
collecting the temperature and the environment temperature of a bus duct, and obtaining a bus duct temperature sequence and an environment temperature sequence;
acquiring a local subsequence of the bus duct temperature in the bus duct temperature sequence and a local subsequence of the environmental temperature in the environmental temperature sequence, and acquiring the environmental temperature change continuous dependency of the bus duct temperature at the acquisition time according to the cross-correlation distance between the bus duct temperature at the same acquisition time and the local subsequence of the environmental temperature;
obtaining a variation coefficient of the bus duct temperature according to the local subsequence of the bus duct temperature, and obtaining fluctuation turbulence characteristics of the bus duct temperature according to the variation coefficient of adjacent elements of the bus duct temperature and the bus duct temperature in the bus duct temperature sequence;
obtaining fluctuation disorder feature vectors of the bus duct temperature according to the local subsequences of the bus duct temperature, obtaining fluctuation disorder feature vectors of the environment temperature according to the local subsequences of the environment temperature and the fluctuation disorder features, obtaining similarity and maximum disorder feature values among the fluctuation disorder feature vectors, obtaining local fluctuation sensitivity of the bus duct temperature according to the similarity among the fluctuation disorder feature vectors, the maximum disorder feature values and the environment temperature change continuous dependency, and determining abnormal temperature data according to the local fluctuation sensitivity;
obtaining an abnormal duty ratio and an abnormal temperature sequence of the bus duct temperature sequence according to the abnormal temperature data, obtaining the overall anomaly degree of the bus duct temperature sequence according to the abnormal duty ratio, the quantity of the abnormal temperature data and the abnormal temperature sequence of the bus duct temperature sequence, obtaining self-adaptive parameters of the bus duct temperature sequence according to the overall anomaly degree of the bus duct temperature sequence, and obtaining the actual temperature of the bus duct at the last acquisition time in the bus duct temperature sequence according to the self-adaptive parameters so as to realize real-time temperature measurement of the bus duct;
the method for acquiring the local subsequence of the bus duct temperature in the bus duct temperature sequence and the local subsequence of the environmental temperature in the environmental temperature sequence comprises the following steps:
taking each bus duct temperature in the bus duct temperature sequence as the bus duct temperature to be analyzed, and taking each environmental temperature in the environmental temperature sequence as the environmental temperature to be analyzed;
the method comprises the steps that before and after the acquisition time of the bus duct temperature to be analyzed, each first preset threshold value element and the bus duct temperature to be analyzed are recorded as neighborhood elements of the bus duct temperature to be analyzed;
arranging neighborhood elements of the bus duct temperature to be analyzed according to the acquisition time sequence, and acquiring a local subsequence of the bus duct temperature to be analyzed;
obtaining a local subsequence of the environmental temperature to be analyzed;
the method for acquiring the fluctuation disorder characteristics of the bus duct temperature according to the variation coefficient of the bus duct temperature and the adjacent elements of the bus duct temperature in the bus duct temperature sequence comprises the following steps:
the variation coefficient of the local subsequence of the bus duct temperature to be analyzed is recorded as the variation coefficient of the bus duct temperature to be analyzed;
the difference value between the bus duct temperature to be analyzed and the bus duct temperature at the moment before the bus duct temperature to be analyzed is recorded as a first difference value, and the difference value between the bus duct temperature at the moment after the bus duct temperature to be analyzed and the bus duct temperature to be analyzed is recorded as a second difference value;
the product of the first difference value, the second difference value and the variation coefficient of the temperature of the bus duct to be analyzed is recorded as fluctuation turbulence characteristics of the temperature of the bus duct to be analyzed;
the method for obtaining the fluctuation turbulence feature vector of the bus duct temperature according to the local subsequence of the bus duct temperature and the fluctuation turbulence feature vector of the ambient temperature according to the local subsequence of the ambient temperature and the fluctuation turbulence feature comprises the following steps:
arranging fluctuation disorder features of the bus duct temperature contained in the local subsequence of the bus duct temperature to be analyzed according to the acquisition time sequence of the bus duct temperature to obtain a fluctuation disorder feature vector of the bus duct temperature to be analyzed;
obtaining a fluctuation disorder feature vector of the environmental temperature to be analyzed;
the method for obtaining the similarity and the maximum disturbance characteristic value between the fluctuation disturbance characteristic vectors comprises the following steps:
obtaining similarity of a fluctuation turbulence feature vector of the temperature of the bus duct to be analyzed and a fluctuation turbulence feature vector of the temperature of the environment to be analyzed at the same acquisition time;
the maximum value of the similarity is recorded as a maximum disorder characteristic value;
the environment temperature change continuous dependency degree is obtained by the following steps:
wherein,is->Bus duct temperature at individual acquisition times +.>Is a continuous dependence of ambient temperature change;is the first part of the bus duct temperature sequence>Individual element->Is->And (4) in the ambient temperature sequence>Individual element->Is->SBD distance between;is the first part of the bus duct temperature sequence>Individual element->Is->And (4) in the ambient temperature sequence>Individual element->Is->Between which are locatedSBD distance of (c); />Is->Neighborhood element number of (2); />Is an exponential function based on natural constants; />A first preset threshold value.
2. The bus duct temperature measurement method according to claim 1, wherein the method for determining abnormal temperature data according to local fluctuation sensitivity is as follows:
and marking the bus duct temperature with the local fluctuation sensitivity larger than a first preset threshold value as abnormal temperature data.
3. The bus duct temperature measurement method according to claim 1, wherein the method for obtaining the abnormal duty ratio and the abnormal temperature sequence of the bus duct temperature sequence according to the abnormal temperature data comprises the following steps:
the ratio of the number of the abnormal temperature data to the total number of the collected bus duct temperatures is recorded as the abnormal duty ratio of the bus duct temperature sequence;
and arranging the abnormal temperature data according to the sequence of the acquisition time to obtain an abnormal temperature sequence.
4. The bus duct temperature measurement method according to claim 1, wherein the method for obtaining the adaptive parameters of the bus duct temperature sequence according to the overall anomaly degree of the bus duct temperature sequence comprises the following steps:
and (3) recording the downward integral value of the product of the linear normalized value of the overall anomaly degree of the bus duct temperature sequence and the initial value of the autoregressive term number as the self-adaptive parameter of the bus duct temperature sequence.
5. The bus duct temperature measurement method according to claim 1, wherein the method for obtaining the actual bus duct temperature at the last acquisition time in the bus duct temperature sequence according to the adaptive parameters, and realizing the real-time temperature measurement of the bus duct comprises the following steps:
taking the self-adaptive parameter as the autoregressive term number of the autoregressive differential moving average model, and predicting the bus duct temperature at a second preset threshold value after the last acquisition time in the bus duct temperature sequence according to the bus duct temperature sequence;
and taking the average value of the predicted second preset threshold values of the bus duct temperatures as the actual bus duct temperature at the last acquisition time in the bus duct temperature sequence, so as to realize real-time monitoring of the bus duct temperature.
6. A bus duct temperature measurement system comprising a memory, a processor and a computer program stored in the memory and running on the processor, characterized in that the processor implements the steps of the method according to any one of claims 1-5 when the computer program is executed.
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Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201724748U (en) * | 2010-04-30 | 2011-01-26 | 北京科力通电气股份有限公司 | Bus temperature monitoring system |
| KR20150099036A (en) * | 2014-02-21 | 2015-08-31 | 엘에스전선 주식회사 | multi point temperature monitering system of busduct and temperature monitering method thereof |
| CN205607561U (en) * | 2016-03-19 | 2016-09-28 | 江苏美联集团有限公司 | Detecting system of dc bus |
| CN108321932A (en) * | 2018-03-13 | 2018-07-24 | 镇江西杰电气有限公司 | Bus duct temperature rise monitoring system based on wireless sensor network |
| DE102018126006A1 (en) * | 2017-10-20 | 2019-04-25 | Industrial Connections & Solutions LLC | RAIL ASSEMBLY CONNECTOR MONITORING SYSTEM AND METHOD OF MOUNTING THE SAME |
| CN112985644A (en) * | 2021-05-18 | 2021-06-18 | 深圳市共济科技股份有限公司 | Bus duct abnormal temperature rise early warning method and system |
| CN114061770A (en) * | 2021-11-25 | 2022-02-18 | 江苏攸米智能科技有限公司 | Distributed prefabricated optical fiber bus temperature measurement system |
| JP2022038659A (en) * | 2020-08-27 | 2022-03-10 | 横河電機株式会社 | Abnormal temperature detection device, abnormal temperature detection method, and abnormal temperature detection program |
| CN114674452A (en) * | 2022-05-19 | 2022-06-28 | 江苏中顺电气有限公司 | Temperature rise monitoring system of bus duct |
| CN114756915A (en) * | 2022-06-15 | 2022-07-15 | 青岛东山集团母线智造有限公司 | Parameterization design method and parameterization design platform of bus duct |
| CN114897061A (en) * | 2022-04-26 | 2022-08-12 | 中国电信股份有限公司 | Prediction model training method, bus temperature early warning method and related equipment |
| CN116046187A (en) * | 2023-04-03 | 2023-05-02 | 探长信息技术(苏州)有限公司 | A unusual remote monitoring system of temperature for communication cabinet |
| CN116183058A (en) * | 2023-04-21 | 2023-05-30 | 实德电气集团有限公司 | Monitoring method of intelligent capacitor |
| CN116453305A (en) * | 2023-03-15 | 2023-07-18 | 镇江加勒智慧电力科技股份有限公司 | Bus duct abnormal temperature rise early warning method and system |
| CN116794385A (en) * | 2023-08-21 | 2023-09-22 | 山东德源电力科技股份有限公司 | High-voltage current monitoring method based on multidimensional data analysis |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8576082B2 (en) * | 2010-07-15 | 2013-11-05 | Jones Group Forensic Engineers | Busway joint parameter detection system |
| US11909193B2 (en) * | 2021-01-29 | 2024-02-20 | Schneider Electric USA, Inc. | Busway joint integral temperature sensor |
-
2023
- 2023-11-24 CN CN202311577234.8A patent/CN117288348B/en active Active
Patent Citations (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201724748U (en) * | 2010-04-30 | 2011-01-26 | 北京科力通电气股份有限公司 | Bus temperature monitoring system |
| KR20150099036A (en) * | 2014-02-21 | 2015-08-31 | 엘에스전선 주식회사 | multi point temperature monitering system of busduct and temperature monitering method thereof |
| CN205607561U (en) * | 2016-03-19 | 2016-09-28 | 江苏美联集团有限公司 | Detecting system of dc bus |
| DE102018126006A1 (en) * | 2017-10-20 | 2019-04-25 | Industrial Connections & Solutions LLC | RAIL ASSEMBLY CONNECTOR MONITORING SYSTEM AND METHOD OF MOUNTING THE SAME |
| CN108321932A (en) * | 2018-03-13 | 2018-07-24 | 镇江西杰电气有限公司 | Bus duct temperature rise monitoring system based on wireless sensor network |
| JP2022038659A (en) * | 2020-08-27 | 2022-03-10 | 横河電機株式会社 | Abnormal temperature detection device, abnormal temperature detection method, and abnormal temperature detection program |
| CN112985644A (en) * | 2021-05-18 | 2021-06-18 | 深圳市共济科技股份有限公司 | Bus duct abnormal temperature rise early warning method and system |
| CN114061770A (en) * | 2021-11-25 | 2022-02-18 | 江苏攸米智能科技有限公司 | Distributed prefabricated optical fiber bus temperature measurement system |
| CN114897061A (en) * | 2022-04-26 | 2022-08-12 | 中国电信股份有限公司 | Prediction model training method, bus temperature early warning method and related equipment |
| CN114674452A (en) * | 2022-05-19 | 2022-06-28 | 江苏中顺电气有限公司 | Temperature rise monitoring system of bus duct |
| CN114756915A (en) * | 2022-06-15 | 2022-07-15 | 青岛东山集团母线智造有限公司 | Parameterization design method and parameterization design platform of bus duct |
| CN116453305A (en) * | 2023-03-15 | 2023-07-18 | 镇江加勒智慧电力科技股份有限公司 | Bus duct abnormal temperature rise early warning method and system |
| CN116046187A (en) * | 2023-04-03 | 2023-05-02 | 探长信息技术(苏州)有限公司 | A unusual remote monitoring system of temperature for communication cabinet |
| CN116183058A (en) * | 2023-04-21 | 2023-05-30 | 实德电气集团有限公司 | Monitoring method of intelligent capacitor |
| CN116794385A (en) * | 2023-08-21 | 2023-09-22 | 山东德源电力科技股份有限公司 | High-voltage current monitoring method based on multidimensional data analysis |
Non-Patent Citations (3)
| Title |
|---|
| Design of Fiber Distributed busway temperature monitoring system;Yun, Qin;Advanced Materials Research;20130904;全文 * |
| 基于时间序列异常检测的铝电解槽阴极压降判异方法研究;曹丹阳;段立娜;李晋宏;;轻金属;20180320(03);全文 * |
| 密集型母线槽温度监测参数异常点定位方法;文典;谢维成;胡锐;杨加国;蒋文波;;传感器与微系统;20180926(10);全文 * |
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