CN117076886A - Petrochemical pipe gallery data analysis and decision system and operation method thereof - Google Patents
Petrochemical pipe gallery data analysis and decision system and operation method thereof Download PDFInfo
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Abstract
The application discloses a petrochemical pipe gallery data analysis and decision-making system and an operation method thereof, belonging to the technical field of petrochemical pipe galleries, and comprising the following steps: the method comprises the steps that a server receives monitoring data acquired by an acquisition terminal and serves as a first data set, and the first data set has a fixed length; performing feature extraction on the monitoring data in the first data set to form feature data with the same scale, and taking the feature data as a second data set; and carrying out decision analysis on the characteristic data in the second data set, and carrying out system early warning according to an analysis result. When the technical scheme of the application is implemented, the monitoring data acquired by the acquisition terminal is used as the first data set, the first data set has a fixed length, and in the processes of acquisition, transmission and analysis decision, the data transmission is performed based on the first data set with the fixed length, so that the analysis and decision efficiency is improved, the characteristic extraction is performed on the monitoring data in the first data set, the characteristic data with the same scale are formed, and the response efficiency of the server is improved.
Description
Technical Field
The application relates to the technical field of petrochemical pipe galleries, in particular to a petrochemical pipe gallery data analysis and decision-making system and an operation method thereof.
Background
Petrochemical pipe galleries are underground passage systems for installing and maintaining petrochemical pipelines, and are generally applied to the petrochemical field, and application scenes including petrochemical plants, refineries, chemical parks and the like, for neatly arranging petrochemical pipelines, and providing convenient access and maintenance conditions.
In order to ensure the operation stability of the petrochemical pipe gallery, a petrochemical pipe gallery operation monitoring system is generally adopted at present, the petrochemical pipe gallery is monitored in the operation process of the petrochemical pipe gallery, monitoring data are collected, the operation state of the petrochemical pipe gallery is analyzed and evaluated according to the monitoring data, early warning can be timely sent out when abnormal conditions occur, maintenance staff is informed of timely maintenance, and the petrochemical pipe gallery is prevented from being failed;
however, due to the complexity of the petrochemical piping lane operation process, the monitoring data may include various data, such as pipeline operation data, environment monitoring data, pipeline safety data, etc., which are generally collected in real time, so that a large amount of data is generated, and therefore, once transmission abnormality occurs in the process of transmitting the monitoring data, the analysis response of the server is slow, even the condition of response lag occurs, and the stability of the petrochemical piping lane in the operation process cannot be ensured.
It is desirable to provide a petrochemical piping lane data analysis and decision-making system that addresses the above-described issues.
It should be noted that the above information disclosed in this background section is only for understanding the background of the inventive concept and, therefore, it may contain information that does not constitute prior art.
Disclosure of Invention
Based on the above problems existing in the prior art, the present application aims to solve the problems: the petrochemical pipe gallery data analysis and decision-making system achieves the effect of improving the petrochemical pipe gallery data analysis and decision-making efficiency.
The technical scheme adopted for solving the technical problems is as follows: a method of operating a petrochemical piping lane data analysis and decision making system, comprising:
the method comprises the steps that a server receives monitoring data acquired by an acquisition terminal and serves as a first data set, and the first data set has a fixed length;
performing feature extraction on the monitoring data in the first data set to form feature data with the same scale, and taking the feature data as a second data set;
carrying out data analysis on the characteristic data in the second data set, and judging the relevance between the characteristic data according to the data analysis result;
and carrying out decision pre-warning according to the analysis result.
In the implementation process of the technical scheme, the monitoring data acquired by the acquisition terminal are used as the first data set, the first data set has a fixed length, and in the acquisition, transmission and analysis decision process, the data transmission is performed based on the first data set with the fixed length, so that the analysis and decision efficiency is improved, the characteristic extraction is performed on the monitoring data in the first data set, the characteristic data with the same scale are formed, and the response efficiency of the server is improved.
Furthermore, the acquisition mode of the acquisition terminal is real-time acquisition, and after the monitoring data in the first data set reach a fixed length, the monitoring data stored in the first data set can be automatically deleted after the transmission is completed.
Further, the first data set is configured to have a first-in first-out mode.
Further, the data analysis of the feature data in the second data set further includes:
preprocessing the characteristic data in the second data set, and taking the preprocessed characteristic data as a third data set;
selecting at least one characteristic data in the third data set as a reference, and performing relevance analysis on the rest characteristic data to generate an analysis result;
carrying out numerical representation on the characteristic data according to the generated analysis result, wherein the numerical value represents the relevance of the characteristic data;
and selecting a compression rate according to the relevance of the characteristic data, wherein the compression rate is in negative correlation with the relevance of the characteristic data.
Further, the method for carrying out numerical representation on the characteristic data according to the generated analysis result adopts a data value linear mapping method, and a group of data ranges are generated after the linear mapping.
Further, the compression ratio is expressed in a fractional form.
Further, when the relevance of the feature data is zero, the feature data is directly rejected.
A petrochemical piping lane data analysis and decision-making system, characterized by: the system comprises:
the receiving module is used for receiving the monitoring data acquired by the acquisition terminal by the server and taking the monitoring data as a first data set, wherein the first data set has a fixed length;
the feature extraction module is used for carrying out feature extraction on the monitoring data in the first data set to form feature data with the same scale, and taking the feature data as a second data set;
the relevance analysis module is used for carrying out data analysis on the characteristic data in the second data set and judging relevance among the characteristic data according to a data analysis result;
and the early warning module is used for carrying out decision early warning according to the analysis result.
The beneficial effects of the application are as follows: according to the petrochemical pipe gallery data analysis and decision-making system, the monitoring data collected by the collection terminal is used as the first data set, the first data set has a fixed length, data transmission is carried out based on the first data set with the fixed length in the processes of collection, transmission and analysis decision-making, analysis and decision-making efficiency is improved, feature extraction is carried out on the monitoring data in the first data set, feature data with the same scale are formed, response efficiency of a server is improved, and meanwhile after the monitoring data in the first data set reach the fixed length, the monitoring data stored in the first data set can be automatically deleted after the transmission is finished, so that confidentiality and safety of the data are improved.
In addition to the objects, features and advantages described above, the present application has other objects, features and advantages. The present application will be described in further detail with reference to the drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application.
In the drawings:
FIG. 1 is a schematic flow chart of a method of operation of a petrochemical piping lane data analysis and decision-making system according to the present application;
FIG. 2 is a schematic diagram of a petrochemical piping lane data analysis and decision-making system module according to the present application.
Detailed Description
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other. The application will be described in detail below with reference to the drawings in connection with embodiments.
In order that those skilled in the art will better understand the present application, a technical solution in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings in which it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the present application without making any inventive effort, shall fall within the scope of the present application.
Embodiment one:
as shown in fig. 1, the present embodiment provides an operation method of a petrochemical piping lane data analysis and decision-making system, which is generally applied to a petrochemical piping lane data analysis and decision-making system, wherein the petrochemical piping lane is a pipeline transportation facility for petrochemical industry and generally includes underground or ground channels, pipelines, valves, power distribution equipment, monitoring equipment, etc., and the operation method may include the following steps:
step 101: the method comprises the steps that a server receives monitoring data collected by a collecting terminal and serves as a first data set, and the first data set has a fixed length;
in the operation process of the petrochemical pipe gallery data analysis and decision system, the acquisition terminal can perform uninterrupted monitoring data acquisition on the petrochemical pipe gallery so as to acquire a large amount of monitoring data, wherein the acquisition terminal can be various sensors arranged at various positions of a pipeline, data storage equipment for storing the data acquired by the sensors, monitoring equipment for monitoring, managing and controlling the operation state of the pipeline, wireless communication equipment for transmitting the monitoring data, remote monitoring equipment for providing remote operation permission and the like, and can adapt to various monitoring requirements without limitation in the embodiment;
the monitoring data includes:
pipeline operation data, such as: the pipeline flow, pipeline pressure, pipeline internal temperature and the like are used for knowing the running state and performance of the pipeline;
environmental monitoring data, such as monitoring data of parameters including temperature, humidity, gas concentration and the like of the surrounding environment of the pipeline, are used for evaluating the influence on the environment in the operation process of the pipeline;
structural monitoring data, such as monitoring data of parameters of vibration, displacement, stress and the like of the pipeline, are used for evaluating the safety and stability of the pipeline;
leak detection monitoring data, such as monitoring data of pipeline leakage and leakage conditions, are used for timely detecting and treating the pipeline leakage problem;
and safety monitoring data. Such as safety facilities around the pipeline and monitoring data of an alarm system, for ensuring the safety in the operation process of the pipeline;
it should be noted that, in this embodiment, the server refers to a hardware module, such as a computer, an industrial personal computer, etc., that provides and manages data analysis or processing functions in the petrochemical gallery data analysis and decision system, and may be a physical server, that is, an actual hardware device, or may be a virtual server, such as a server cloud platform, in this embodiment, only needs to be guaranteed to have functions of data analysis, storage, etc., so that details are not repeated here and below;
in this embodiment, the acquisition mode of the acquisition terminal is real-time acquisition, the first data set is set to be of a fixed length, when the monitored data in the first data set reaches the set fixed length, the monitored data stored in the first data set can be automatically deleted after transmission is completed, so that continuity of the acquisition terminal in the acquisition process can be ensured, meanwhile, the monitored data can be deleted at the acquisition terminal after reaching the server, and the monitored data is only stored in hardware or a module with a storage function of the server, so that the safety of the monitored data is improved, and meanwhile, the follow-up data tracing is facilitated;
in another embodiment, if the traceability function is not required to be provided, only the safety of the monitored data is guaranteed, and the monitored data can also be deleted in all channels after the monitored data arrives at the server and is analyzed by the server, wherein the channels comprise an acquisition channel, a transmission channel and an analysis processing channel, and the acquisition end, the transmission end and the analysis processing end respectively correspond to the specific:
setting a first data set to be a fixed length, and setting the length to be 1 to n, wherein 1 is first monitoring data in the fixed length, and n is last monitoring data in the fixed length;
when the monitoring data in the first data set is fully loaded, namely the first data set contains 1 to n monitoring data, a transmission signal is sent to the acquisition end, the 1 to n monitoring data are transmitted, after the server receives the nth monitoring data, namely the last monitoring data in the first data set, a filling signal is sent to the acquisition end, and the first data set is filled in the next round, so that the first data set is always in a full-load state;
after the server analyzes the nth monitoring data, namely the last monitoring data in the first data set, a deleting signal is sent to the acquisition end, the transmission end and the analysis processing end, and deleting operation is carried out on the n monitoring data after the current analysis is finished, so that the n monitoring data are ensured to be deleted after all the n monitoring data are acquired, transmitted and analyzed, and confidentiality and safety of the monitoring data in each stage are ensured;
the first-in-first-out (FIFO) mode of the monitoring data in the first data set is required to ensure that the monitoring data entering the first data set first performs subsequent transmission and analysis processing steps, and the FIFO mode can maintain the acquisition sequence of the monitoring data in the first data set, so as to prevent disorder from occurring in the transmission process and influence the subsequent analysis result.
Step S102: performing feature extraction on the monitoring data in the first data set to form feature data with the same scale, and taking the feature data as a second data set;
because the monitoring data in the first data set has the characteristics of a large number, complicated types, non-uniform scale and the like, in order to reduce the calculation power and time consumed by the server in the analysis processing process, the monitoring data also need to be optimized, so that the scales of the monitoring data are uniform, specifically, a characteristic extraction method can be adopted to extract the characteristics of each monitoring data type in the first data set, and the original data is converted into a small amount of characteristic data with the same scale;
various methods are used for feature extraction, for example, statistical features (such as mean, variance, and maximum), frequency domain features (such as fourier transform), or time domain features (such as waveform transform and time sequence features), where the statistical feature method may refer to the chinese application patent with publication No. CN108108712B, the frequency domain feature method may refer to the chinese application patent with publication No. CN112101245A, the time domain feature method may refer to the chinese application patent with publication No. CN113189457a, and in this embodiment, the specific method for feature extraction is not limited, and only the monitored data in the first dataset need to form feature data with the same scale;
it should be noted that, no matter what method is adopted, linear relations including parameters such as numerical values, dimensions, the maximum values and the like need to exist among the feature data, so that optimization in the subsequent transmission process is facilitated.
Step S103: carrying out data analysis on the characteristic data in the second data set, and judging the relevance between the characteristic data according to the data analysis result;
in the process of data transmission, in order to improve transmission efficiency, compression, error correction and other processes are generally required to be performed on data to be transmitted, wherein a compression method is used for reducing the data amount of original data, and improving the transmission efficiency is the most common method.
Step S301: preprocessing the characteristic data in the second data set, and taking the preprocessed characteristic data as a third data set;
the preprocessing process includes conventional operations such as data cleaning, missing value processing, outlier processing, and the like, which are conventional methods for preprocessing data in the field, and are not described herein and below;
step S302: selecting at least one characteristic data in the third data set as a reference, and performing relevance analysis on the rest characteristic data to generate an analysis result;
when the correlation analysis is performed on the feature data, one or more feature data are required to be selected as a reference, and correlation analysis is performed on other feature data by adopting methods common in the art, such as a correlation coefficient analysis method, a covariance analysis method, a thermodynamic diagram analysis method, a principal component analysis method and the like, which are not limited in the embodiment;
in this embodiment, optionally, one or more feature data is used as a reference, so that the randomness of the analysis result can be improved in the subsequent relevance analysis process, multiple selections can be made, relevance analysis under different references can be performed, and the average value is obtained according to the multiple relevance analysis results, so that the effectiveness of the relevance analysis results is improved;
step S303: carrying out numerical representation on the characteristic data according to the generated analysis result, wherein the numerical value represents the relevance of the characteristic data;
in order to facilitate the expression of the correlation result, after the correlation analysis is performed on the feature data, the value representation is performed according to the analysis result, so that the subsequent selection of the compression rate is facilitated, taking the correlation coefficient analysis method as an example, after the correlation analysis is performed on the feature data, each analyzed feature data can generate a correlation coefficient, such as a pearson correlation coefficient and a spearman correlation coefficient, and since the feature data contains a linear relationship, the pearson correlation coefficient can be selected in the embodiment, and is applicable to data with a linear relationship, and the value range of the coefficient is-1 to 1, while the feature data in the embodiment is the data with the linear feature;
in the case of numerical conversion, the pearson correlation coefficient can be mapped to other data ranges by a data value linear mapping method, for example, when the pearson correlation coefficient from-1 to 1 needs to be mapped to the interval from 0 to 100, the pearson correlation coefficient can be mapped to the interval from 0 to 100 by a (Pi Erman correlation coefficient+1) x 50 method;
step S304: selecting a compression rate according to the relevance of the characteristic data, wherein the compression rate is inversely related to the relevance of the characteristic data;
when data transmission is carried out, the data to be transmitted is required to be compressed, the data is inevitably lost in the compression process, after the relevance calculation, distributed compression can be carried out according to the relevance calculation result, for example, when the relevance of certain characteristic data is strong, the representative monitoring data occupy the analysis proportion is larger, therefore, the lower compression rate is required to be selected for the characteristic data to ensure the integrity of the characteristic data, when the relevance of certain characteristic data is weak, the representative monitoring data occupy the analysis proportion is smaller, therefore, the higher compression rate can be selected for the characteristic data to ensure the normal transmission of the characteristic data, even if certain data is lost in the compression process, the final analysis result can also have smaller influence, and the transmission efficiency can be improved on the premise of ensuring the integrity of the monitoring data by a distributed compression method;
the compression rate is usually expressed in a fraction, and in order to match with the relevance of the feature data, the method of taking the reciprocal of the numerical value in the mapped interval can be adopted, and particularly, when the relevance of the feature data is zero, the data can be directly removed, and because the data has no relevance with other data, the analysis result is not influenced.
Step S104: and carrying out decision early warning according to the analysis result, and carrying out integrity verification before outputting the early warning result.
Specifically, the decision pre-warning process according to the analysis result comprises the following steps:
step S401: making an early warning rule based on an analysis result of the server;
after the analysis of the server is finished, an early warning rule is established based on the analysis result, wherein the rule can be set based on a threshold value, the early warning is triggered when the analysis result of the monitoring data exceeds or is lower than the set threshold value, or the early warning is triggered when the analysis result of the monitoring data has a specific mode or trend based on a mode identification setting;
it should be noted that, in this embodiment, the early warning rule needs to be set or adjusted after the server analysis is completed, that is, the early warning rule is not invariable, and this way can be adjusted according to the difference of the monitored data, so that the early warning process is matched with the analysis result of the monitored data, and compared with the traditional fixed set early warning mechanism, the early warning behavior can reflect the information represented by the monitored data.
Step S402: carrying out early warning notification according to early warning rules;
after the steps are completed, comparing the analysis result of the server with an early warning mechanism to output the result, and simultaneously carrying out corresponding early warning notification, so that maintenance personnel can conveniently carry out maintenance;
step S403: and verifying the early warning result.
In order to improve the response speed of the early warning action and prevent the analysis result of the server from being transmitted delay or lost, integrity verification is needed before early warning notification, the information to be early warned is determined to be the information obtained by directly analyzing the server, and the effectiveness of decision early warning is improved;
the integrity verification can adopt a hash verification mode, firstly, hash calculation is carried out on the early warning result of the server to generate a first hash value, and the calculation method can adopt MD5, SHA-1, SHA-256 and the like, and is not limited herein;
then, the generated first hash value is stored in a storage medium such as a database, a file system and the like, so that the safety and the integrity of the hash value are ensured;
when the early warning is needed, early warning data output by a server are obtained, hash calculation is carried out on the data, a second hash value is generated, the second hash value represents a hash value generated by information needed to be subjected to early warning, then the first hash value is compared with the second hash value to judge whether the first hash value is consistent with the second hash value, if the first hash value is consistent with the second hash value, the early warning result is completely unchanged, the early warning data can be output, if the early warning result is inconsistent with the second hash value, the early warning data represented by the second hash value is abnormal, the early warning data can not be directly output, an inspection signal is sent to the server, the early warning is suspended, and after the overhaul of a worker is completed, the steps are repeated until the first hash value is consistent with the second hash value, and early warning output can be carried out.
Through the verification process, the integrity and the authenticity of the early warning result can be verified, the early warning result is ensured not to be changed, and the early warning accuracy of the system is improved.
Embodiment two:
as shown in fig. 2, the present embodiment provides a petrochemical piping lane data analysis and decision-making system that operates the method of the first embodiment, the system comprising:
the receiving module is used for receiving the monitoring data acquired by the acquisition terminal by the server and taking the monitoring data as a first data set, wherein the first data set has a fixed length;
the feature extraction module is used for carrying out feature extraction on the monitoring data in the first data set to form feature data with the same scale, and taking the feature data as a second data set;
the relevance analysis module is used for carrying out data analysis on the characteristic data in the second data set and judging relevance among the characteristic data according to a data analysis result;
and the early warning module is used for carrying out decision early warning according to the analysis result and carrying out integrity verification before outputting the early warning result.
The above description is only of the preferred embodiments of the present application and is not intended to limit the present application, but various modifications and variations can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.
Claims (9)
1. The operation method of the petrochemical pipe gallery data analysis and decision system is characterized by comprising the following steps of: comprising the following steps:
the method comprises the steps that a server receives monitoring data acquired by an acquisition terminal and serves as a first data set, and the first data set has a fixed length;
performing feature extraction on the monitoring data in the first data set to form feature data with the same scale, and taking the feature data as a second data set;
carrying out data analysis on the characteristic data in the second data set, and judging the relevance between the characteristic data according to the data analysis result;
and carrying out decision early warning according to the analysis result, and carrying out integrity verification before outputting the early warning result.
2. A method of operating a petrochemical piping lane data analysis and decision-making system according to claim 1, wherein: the acquisition mode of the acquisition terminal is real-time acquisition, and after the monitoring data in the first data set reach a fixed length, the monitoring data stored in the first data set can be automatically deleted after the transmission is completed.
3. A method of operating a petrochemical piping lane data analysis and decision-making system according to claim 1, wherein: the first data set is a first-in first-out monitoring data set.
4. A method of operating a petrochemical piping lane data analysis and decision-making system according to claim 1, wherein: the data analysis of the feature data in the second data set further comprises:
preprocessing the characteristic data in the second data set, and taking the preprocessed characteristic data as a third data set;
selecting at least one characteristic data in the third data set as a reference, and performing relevance analysis on the rest characteristic data to generate an analysis result;
carrying out numerical representation on the characteristic data according to the generated analysis result, wherein the numerical value represents the relevance of the characteristic data;
and selecting a compression rate according to the relevance of the characteristic data, wherein the compression rate is in negative correlation with the relevance of the characteristic data.
5. The method of operation of a petrochemical piping lane data analysis and decision-making system according to claim 4, wherein: and carrying out numerical representation on the characteristic data according to the generated analysis result by adopting a data value linear mapping method, and generating a group of data ranges after linear mapping.
6. The method of operation of a petrochemical piping lane data analysis and decision-making system according to claim 4, wherein: the compression ratio is expressed in fractional form.
7. The method of operation of a petrochemical piping lane data analysis and decision-making system according to claim 4, wherein: and when the relevance of the characteristic data is zero, the characteristic data is directly rejected.
8. A petrochemical piping lane data analysis and decision-making system, characterized by: the system comprises:
the receiving module is used for receiving the monitoring data acquired by the acquisition terminal by the server and taking the monitoring data as a first data set, wherein the first data set has a fixed length;
the feature extraction module is used for carrying out feature extraction on the monitoring data in the first data set to form feature data with the same scale, and taking the feature data as a second data set;
the relevance analysis module is used for carrying out decision analysis on the characteristic data in the second data set and judging relevance among the characteristic data according to decision analysis results;
and the early warning module is used for carrying out decision early warning according to the analysis result and carrying out integrity verification before outputting the early warning result.
9. The petrochemical piping lane data analysis and decision-making system of claim 8, wherein: the system operates the operating method of any one of claims 1 to 7.
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| CN202311057099.4A CN117076886A (en) | 2023-08-22 | 2023-08-22 | Petrochemical pipe gallery data analysis and decision system and operation method thereof |
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| CN202311057099.4A CN117076886A (en) | 2023-08-22 | 2023-08-22 | Petrochemical pipe gallery data analysis and decision system and operation method thereof |
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