CN118138491A - Information communication system operation situation sensing method based on multisource data aggregation - Google Patents
Information communication system operation situation sensing method based on multisource data aggregation Download PDFInfo
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Abstract
The invention discloses an information communication system operation situation sensing method based on multi-source data aggregation, which comprises the following steps: s1: acquiring related original data of the operation of an information communication system; s2: preprocessing the acquired operation related data of the information communication system; s3: constructing a multi-source data fusion model based on Hermi te orthogonal basis forward neural network; s4: sending the preprocessed data into the data fusion model, and training the model; s5: and obtaining operation situation composition data of the information communication system by utilizing the multi-source data fusion model according to the related original data in the time period selected by the user. The information communication system operation situation sensing method based on multi-source data aggregation not only provides a new thought and method for information communication system operation situation assessment, but also ensures higher test precision.
Description
Technical Field
The invention relates to the technical field of power, in particular to an information communication system operation situation sensing method based on multisource data aggregation.
Background
With the comprehensive deployment of smart grids, grid companies may involve a large amount of work data in the actual operation and maintenance work. Through reasonable analysis of the data, reliable support can be provided for the state of the power grid equipment, the energy consumption characteristics of users and the maintenance and management of the power grid equipment; along with the continuous development and perfection of Internet big data, the intelligent power grid is analyzed by reasonably utilizing operation and maintenance data, so that a reasonable guiding scheme can be provided for operation and maintenance personnel, the operation and maintenance efficiency can be improved, the operation and maintenance quality can be guaranteed, and the intelligent power grid has important practical significance for operation, maintenance and detection of an information communication system.
Disclosure of Invention
The invention aims to provide an information communication system operation situation sensing method based on multi-source data aggregation, which is used for accurately analyzing the operation state of a power grid information communication system.
In order to achieve the above object, the present invention provides the following technical solutions:
an information communication system operation situation awareness method based on multisource data aggregation comprises the following steps:
S1: acquiring related original data of the operation of an information communication system;
S2: preprocessing the acquired operation related data of the information communication system;
S3: constructing a multisource data fusion model based on Hermite orthogonal basis forward neural network;
s4: sending the preprocessed data into the data fusion model, and training the model;
S5: and obtaining operation situation composition data of the information communication system by utilizing the multi-source data fusion model according to the related original data in the time period selected by the user.
Further, in the step S1, the relevant raw data of the operation of the information communication system is monitored operation data of the information communication system, and the data sources of the relevant raw data are at least two devices.
Further, in the step S1, the data sources of the related raw data include at least two of SCADA, smart meter and sensor.
Further, in the step S2, the data preprocessing includes extracting data items required for analysis from the relevant original data set, and then performing structural preprocessing on the data of the data items to enable the original data to meet the data requirements of the multi-source data fusion model.
Further, in the step S2, the data preprocessing includes abnormal data processing or missing data processing.
Further, in the step S3, the multi-source data fusion model is constructed as follows:
wherein the input layer and the output layer are provided with f (x) =x, and the input x is a multi-dimensional array;
The function f (x) is a gradient propagation process performed by inputting the original data into the neural network;
setting weights and thresholds of an input layer and an output layer to be 1 and 0 respectively, wherein the number of hidden neurons is n, and the Hermite orthogonal basis function is expressed as follows:
The input excited matrix X is expressed as:
the target output vector Y is expressed as:
Wherein, W is a weight coefficient.
Further, the model process error function is expressed as:
Wherein ω= (X TX)-1XT Y (5).
Further, in the step S4, the input layer is an aggregated multi-dimensional array of multi-source data, including multi-source information communication system operation data;
the output layer is used for judging whether the operation situation of the information communication system is normal or abnormal according to the multi-source data.
In the technical scheme, the information communication system operation situation awareness method based on multi-source data aggregation has the following beneficial effects:
The information communication system operation situation awareness technology based on multi-source data aggregation plays an important role in the field of information communication system operation and maintenance, provides a new thought and method for the information communication system operation and maintenance, and ensures higher test precision. The invention provides a multisource data fusion model based on a Hermite orthogonal basis forward neural network, which fuses multisource data of an information communication system in a power grid by adopting the Hermite orthogonal polynomial excited forward neural network model so as to accurately analyze the running state of the power grid information communication system and reasonably guide the running and maintenance behaviors. The test result shows that the model has higher precision in the evaluation result.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments described in the present application, and other drawings may be obtained according to these drawings for a person having ordinary skill in the art.
FIG. 1 is a flow chart of an information communication system operation situation awareness method based on multi-source data aggregation;
fig. 2 is a schematic structural diagram of a multisource data fusion model based on a Hermite orthogonal base forward neural network.
Detailed Description
In order to make the technical scheme of the present invention better understood by those skilled in the art, the present invention will be further described in detail with reference to the accompanying drawings.
An information communication system operation situation awareness method based on multisource data aggregation comprises the following steps:
S1: acquiring related original data of the operation of an information communication system;
S2: preprocessing acquired operation related data of an information communication system at least comprising related original data;
S3: constructing a multisource data fusion model based on Hermite orthogonal basis forward neural network;
S4: sending the preprocessed data into the data fusion model, and training the multi-source data fusion model;
S5: and obtaining operation situation composition data of the information communication system by utilizing the multi-source data fusion model according to the related original data in the time period selected by the user. Because the data-driven algorithm is built according to the existing historical information system operation data in the S4, the current operation situation can be judged by the S5 through inputting the information communication system operation data of the current time or the specific time and the specific state by a user and utilizing the generated algorithm.
In step S1, the relevant raw data of the operation of the information communication system is monitored operation data of the information communication system, and the data sources of the relevant raw data are at least two devices.
The data sources of the relevant raw data may be at least two of SCADA, smart meter and sensor.
In the step S2, the data preprocessing includes extracting data items required for analysis from the relevant original data set, that is, extracting the data items as required, and then performing structural preprocessing on the data of the data items, so that the original data meets the data requirement of the multi-source data fusion model.
The data preprocessing includes abnormal data processing or missing data processing.
In the step S3, the multi-source data fusion model is constructed as follows:
Wherein the input layer and the output layer are provided with f (x) =x, and the input x is a multi-dimensional array; the function f (x) is a gradient propagation process performed by inputting the original data into the neural network; f (x) =x is an identity function, i.e. input x, and at the input layer is x, which needs to be passed through.
Setting weights and thresholds of an input layer and an output layer to be 1 and 0 respectively, wherein the number of hidden neurons is n, and the Hermite orthogonal basis function is expressed as follows:
The input excited matrix X is expressed as:
the target output vector Y is expressed as:
Wherein, The vector W consisting of W j is a weight coefficient, i.e., W j is a weight coefficient; by inputting x, y i is finally obtained to determine the system condition represented by data x. The weight coefficient W is the weight that gradually approximates the correct result by the error between the calculated result and y, and finally converges.
The model process error function is expressed as:
Where ω= (X TX)-1XTY(5),ωj is a vector of n×1, representing n neuron weights, i.e., ω j is a weight coefficient).
The input layer is an aggregate multi-dimensional array of multi-source data and comprises information communication system operation data of various sources;
The output layer is used for judging whether the operation situation of the information communication system is normal or abnormal according to the multi-source data. The value output by the output layer is set to 0 or 1, if the output is 1, the output layer is in accordance with the expectation, namely normal; otherwise, it is abnormal.
The multisource operation data of the information communication system in recent years is input, and specific operation situation loss data of the information communication system can be obtained through a model.
Table 1 loss comparison
In order to verify the effectiveness of the invention, the invention compares the Hermite-based orthogonal basis forward neural network, the DBN-based time sequence prediction method and the RNN model, and the results are shown in table 1. The result shows that the Hermite-based orthogonal basis forward neural network provided by the invention has higher and better advantages under the loss evaluation index. The invention can effectively improve the evaluation accuracy.
The invention has the beneficial effects that: the information communication system operation situation awareness technology based on multi-source data aggregation plays an important role in the field of information communication system operation and maintenance, provides a new thought and method for the information communication system operation and maintenance, and ensures higher test precision. The invention provides a multisource data fusion model based on a Hermite orthogonal basis forward neural network, which fuses multisource data of an information communication system in a power grid by adopting the Hermite orthogonal polynomial excited forward neural network model so as to accurately analyze the running state of the power grid information communication system and reasonably guide the running and maintenance behaviors. The test result shows that the model has higher precision in the evaluation result.
While certain exemplary embodiments of the present invention have been described above by way of illustration only, it will be apparent to those of ordinary skill in the art that modifications may be made to the described embodiments in various different ways without departing from the spirit and scope of the invention. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive of the scope of the invention, which is defined by the appended claims.
Claims (8)
1. An information communication system operation situation awareness method based on multi-source data aggregation is characterized by comprising the following steps:
S1: acquiring related original data of the operation of an information communication system;
S2: preprocessing the acquired operation related data of the information communication system;
S3: constructing a multisource data fusion model based on Hermite orthogonal basis forward neural network;
s4: sending the preprocessed data into the multi-source data fusion model, and training the model;
S5: and obtaining operation situation composition data of the information communication system by utilizing the multi-source data fusion model according to the related original data in the time period selected by the user.
2. The method for sensing the operation situation of the information communication system based on the multi-source data aggregation according to claim 1, wherein in the step S1, the relevant raw data of the operation of the information communication system is monitored operation data of the information communication system, and the data sources of the relevant raw data are at least two monitoring devices.
3. The method for sensing the operational situation of the information communication system based on the multi-source data aggregation according to claim 2, wherein in the step S1, the data sources of the related raw data include at least two of SCADA, smart meter and sensor.
4. The method for sensing the operation situation of an information communication system based on multi-source data aggregation according to claim 2, wherein in the step S2, the data preprocessing includes extracting data items required for analysis from the relevant original data set, and then performing structural preprocessing on the data of the data items to enable the original data to meet the data requirements of the multi-source data fusion model.
5. The method for sensing the operation situation of the information communication system based on the multi-source data aggregation according to claim 2, wherein in the step S2, the data preprocessing includes abnormal data processing or lost data processing.
6. The method for sensing the running situation of the information communication system based on the multi-source data aggregation according to claim 1, wherein in the step S3, a multi-source data fusion model is constructed as follows:
wherein the input layer and the output layer are provided with f (x) =x, and the input x is a multi-dimensional array;
The function f (x) is a gradient propagation process performed by inputting the original data into the neural network;
setting weights and thresholds of an input layer and an output layer to be 1 and 0 respectively, wherein the number of hidden neurons is n, and the Hermite orthogonal basis function is expressed as follows:
The input excited matrix X is expressed as:
the target output vector Y is expressed as:
Wherein,
7. The method for sensing the operational situation of an information communication system based on multi-source data aggregation according to claim 6, wherein the model processing error function is expressed as follows:
Wherein the weight coefficient
8. The method for sensing the operation situation of the information communication system based on the multi-source data aggregation according to claim 6, wherein in the step S4, the input layer is an aggregated multi-dimensional array of multi-source data, including multi-source information communication system operation data;
the output layer is used for judging whether the operation situation of the information communication system is normal or abnormal according to the multi-source data.
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