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A data anomaly and detection method technology, applied in the field of big data processing, can solve the problems of slow speed and low accuracy, and achieve the effect of high speed, high accuracy and absolute safety.
Active Publication Date: 2019-07-09
SHANGHAI ADVANCED RES INST CHINESE ACADEMY OF SCI +1
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[0004] In view of the shortcomings of the prior art described above, the purpose of the present invention is to provide a data anomaly detection system and method for solving the problems of slow speed and low accuracy in the detection and analysis of data in the prior art
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Embodiment 1
[0042] see figure 1 , the present invention provides a data anomaly detection method, the data anomaly detection method comprises the following steps:
[0043] 1) Preprocessing the original data to remove the interference value in the original data, and filling the data after removing the interference value;
[0044] 2) Normalize the filled data;
[0045] 3) Shaping the normalized data to obtain supervised data;
[0046] 4) Using LSTM network to analyze the supervised data to obtain prediction data;
[0047] 5) Comparing the predicted data with the real data to determine whether the original data is abnormal.
[0048] In step 1), see figure 1 In the S1 step, the original data is preprocessed to remove the interference value in the original data, and the data after the removal of the interference value is filled.
[0049] As an example, the raw data includes low-dimensional flight data of the aircraft.
[0050] As an example, the raw data may include a data sequence of se...
Embodiment 2
[0073] see figure 2 , the present invention also provides a data anomaly detection system, the data anomaly detection system includes: a preprocessing module 1, the preprocessing module 1 is used to preprocess the original data, to remove the interference value in the original data , and fill the data after removing the interference value; a normalization processing module 2, the normalization processing module 2 is connected with the preprocessing module 1, and the normalization processing module 2 is used for The filled data is normalized; the shaping processing module 3 is connected to the normalizing processing module 2, and the shaping processing module 3 is used for normalizing the data after the normalizing processing Shaping to obtain supervised data; an analysis module 4, the analysis module 4 is connected to the shaping processing module 3, and the analysis module 4 is used to analyze the supervised data using an LSTM network to obtain Predicted data; comparison ju...
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Abstract
The invention provides a data exception detection system and method, and the method comprises the following steps: carrying out the preprocessing of original data, removing an interference value in the original data, and carrying out the filling of the data with the interference value removed; performing normalization processing on the filled data; shaping the normalized data to obtain superviseddata; analyzing the supervised data by using an LSTM network to obtain prediction data; and comparing the prediction data with the real data to judge whether the original data is abnormal or not. According to the data exception detection method disclosed by the invention, rapid and accurate exception detection can be carried out on the data, and exception can be immediately processed when an aircraft and the like are exceptional, so that the absolute safety of aircraft flight is ensured; the data exception detection system has the advantages of high speed, high accuracy and the like when usedfor carrying out exception detection on the data.
Description
technical field [0001] The invention belongs to the technical field of big data processing, and in particular relates to a data anomaly detection system and method. Background technique [0002] At this stage, for the anomaly detection of flight data, there is no algorithm at this stage that can effectively process flight data well. Previously, many statistical methods were used in data processing. However, it is not realistic to use statistical methods to process a large amount of time-series data generated during aircraft flight. First, statistical methods can only show the general laws and changes in the data as a whole, but cannot effectively correlate the data before and after time. Second, the data of the aircraft is generated by multiple sensors on the aircraft, the dimension of the data is relatively large, and it is difficult to link the data of different sensors by statistical methods. A lot of useful information is lost. Third, the performance of statistical m...
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Application Information
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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/044G06N3/045G06F18/22
Inventor 汪辉吴迪祝永新田犁黄尊恺
Owner SHANGHAI ADVANCED RES INST CHINESE ACADEMY OF SCI
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