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CN-121980297-A - Comprehensive pipe rack health diagnosis system based on big data technology

CN121980297ACN 121980297 ACN121980297 ACN 121980297ACN-121980297-A

Abstract

The invention discloses a comprehensive pipe rack health diagnosis system based on a big data technology, which relates to the technical field of pipe rack health diagnosis and comprises a diagnosis center, wherein the diagnosis center is in communication connection with a data acquisition module, a data processing module, a data analysis module and an alarm module, operation data of a plurality of systems and devices in the comprehensive pipe rack are acquired through the data acquisition module, image data are acquired through image acquisition equipment, operation data corresponding to different systems and devices are subjected to unified conversion through the data processing module, a data set to be analyzed is further generated, the data set to be analyzed is further subjected to data cleaning, the data set to be analyzed is acquired through the data analysis module and is imported into a constructed big data analysis model for multidimensional data analysis, the data is further generated, the pipe rack health data is further transmitted to the diagnosis center, diagnosis results are generated through the diagnosis center, corresponding alarm data are generated through the alarm module, and corresponding maintenance personnel are arranged according to the alarm data, and maintenance operation is performed.

Inventors

  • YANG XUEJUN

Assignees

  • 安徽国智数据技术有限公司

Dates

Publication Date
20260505
Application Date
20240322

Claims (8)

  1. 1. The utility model provides a utility tunnel health diagnosis system based on big data technology, includes diagnosis center, its characterized in that, diagnosis center communication connection has data acquisition module, data processing module, data analysis module and alarm module; the data acquisition module is used for acquiring operation data of a plurality of systems and devices arranged in the comprehensive pipe rack, setting a plurality of shooting points in the comprehensive pipe rack, and arranging image acquisition devices at the shooting points to acquire image data; the data processing module is provided with a conversion module, and operation data corresponding to different systems and devices are uniformly converted through the conversion module, so that a data set to be analyzed is generated, and the data set to be analyzed is subjected to data cleaning; the data analysis module is used for acquiring a data set to be analyzed after data cleaning is completed, importing the data set to be analyzed into a constructed big data analysis model for multidimensional data analysis, further generating pipe gallery health data, transmitting the pipe gallery health data to a diagnosis center, and generating a diagnosis result by the diagnosis center; The alarm module is used for generating corresponding alarm data according to the diagnosis result and arranging corresponding maintenance personnel to execute maintenance operation according to the alarm data.
  2. 2. A utility tunnel health diagnostic system based on big data technology as claimed in claim 1, wherein the process of collecting operational data of several systems and devices disposed in the utility tunnel comprises: the system and the equipment are used for carrying out normal operation of electric power, communication, tap water and fuel gas in the comprehensive pipe rack, and a sensor module and a data checking program are arranged for each system and each equipment in an associated mode; The sensor module comprises a temperature sensor, a pressure sensor and a humidity sensor, and is used for respectively acquiring temperature data, pressure data and humidity data corresponding to each system and equipment, a data checking program is used for acquiring working parameters corresponding to each system or equipment, a normal reference value interval of the working parameters is recorded in the data checking program, and then the data checking program judges whether the working parameters are in the normal reference value interval or not; If the working parameters are in the normal reference value interval, no operation is performed, if not, an Error mark is input for a system and equipment corresponding to the working parameters, temperature data, pressure data and humidity data acquired by the sensor module are used as external operation data, the working parameters acquired by the data checking program are used as internal operation data, and the external operation data and the internal operation data are combined into operation data corresponding to each system and equipment.
  3. 3. The utility tunnel health diagnostic system based on big data technology according to claim 2, wherein a plurality of shooting points are set in the utility tunnel, and the process of arranging the image acquisition device at the shooting points to acquire the image data comprises the following steps: A plurality of shooting points are arranged in the comprehensive pipe rack and numbered, the numbers are i, i=1, 2,3, the number is n, wherein n is a natural number larger than 0, the image acquisition equipment is arranged at each shooting point, the acquisition and debugging work is started, the acquisition areas corresponding to the plurality of image acquisition equipment are generated through the acquisition and debugging work, acquiring a pipe gallery layout diagram corresponding to the comprehensive pipe gallery, locating a layout area through the pipe gallery layout diagram, mapping a plurality of acquisition areas to the layout area, locating an acquisition blind area, adding a photographing point location at the acquisition blind area, arranging image acquisition equipment, and acquiring image data of a plurality of photographing point locations corresponding to the comprehensive pipe gallery through the plurality of image acquisition equipment.
  4. 4. The utility tunnel health diagnosis system based on big data technology as set forth in claim 3, wherein the process of setting the conversion module to perform unified conversion on the operation data corresponding to different systems and devices, and further generating the data set to be analyzed includes: Setting a conversion module, inputting operation data corresponding to different systems and devices into the conversion module, further obtaining a data format and a data protocol associated with each operation data by the conversion module, obtaining a time stamp of each operation data, setting a data set format and a data set protocol, inputting the data set format and the data set protocol into the conversion module, sequentially uniformly converting the data format and the data protocol of each operation data into corresponding data set format and data set protocol according to the sequence of the data stamps from small to large by the conversion module, and further merging the operation data of all the systems and the devices to generate corresponding data sets to be analyzed.
  5. 5. The utility tunnel health diagnostic system based on big data technology of claim 4, wherein the process of data cleansing the data set to be analyzed comprises: Acquiring a data set to be analyzed, further acquiring the data quantity corresponding to the data set to be analyzed, marking as D, setting a plurality of data cleaning stacks, wherein each data cleaning stack is used for carrying out data cleaning of part of the data set to be analyzed, marking the cleaning capacity of the data cleaning stacks as D ', further acquiring the required number of data cleaning stacks according to D and D', marking the number as S, distributing the data set to be analyzed with the data quantity of D into the S data cleaning stacks, further screening the missing value, the repeated value and the error value of the data set to be analyzed, correspondingly carrying out missing value filling, repeated value screening and error value correction on the data set to be analyzed, completing data cleaning when the missing value filling, the repeated value screening and the error value correction are completed, and transmitting the data set to be analyzed to a data analysis module.
  6. 6. The utility tunnel health diagnostic system based on big data technology of claim 5, wherein the process of importing the data set to be analyzed into the big data analysis model, further performing multidimensional data analysis, and generating tunnel health data for transmission to the diagnostic center comprises: Judging whether the data set to be analyzed is qualified or not, dividing the data set to be analyzed into a plurality of data fields, presetting reference fields of the data fields, synchronously converting the data fields and the reference fields into 01 character strings in a binary form, sequentially comparing the 01 character strings from left to right according to the bits, if all the bits are corresponding to the same, the data fields and the reference fields are consistent, and if the data fields and the reference fields are corresponding to the same, the corresponding data set to be analyzed is normal, otherwise, the data set to be analyzed is not qualified, marking inconsistent character bits in the 01 character strings corresponding to the data fields and the reference fields as illegal character bits, and carrying out corresponding correction on 0 or 1 on the illegal character bits; Acquiring historical utility tunnel data and a corresponding initial format thereof, setting the initial format as a modeling data format, inputting the historical utility tunnel data in the modeling data format into a set model construction program through machine learning, further constructing a preliminary big data analysis model, and presetting modeling completion parameters of the big data analysis model, wherein the modeling completion parameters comprise accuracy, recall rate, F1 value and mean square error, and respectively corresponding numerical values are lambda 1 、λ 2 、λ 3 and lambda 4 ; Presetting qualified intervals of accuracy, recall, F1 value and mean square error, respectively recording the qualified intervals as omega 1 、Ω 2 、Ω 3 and omega 4 , and when lambda 1 ∈Ω 1 ,λ 2 ∈Ω 2 ,λ 3 ∈Ω 3 and lambda 4 ∈Ω 4 are all established, completing the construction of a final big data analysis model, otherwise, continuously increasing the sample size of historical comprehensive pipe gallery data, and re-constructing the big data analysis model; The method comprises the steps of importing a data set to be analyzed into a big data analysis model, further carrying out multidimensional data analysis by the big data analysis model, wherein the multidimensional data analysis comprises a first dimension and a second dimension, the first dimension is used for analyzing potential risks of the comprehensive pipe rack, the second dimension is used for analyzing existing risks of the comprehensive pipe rack, acquiring data contents corresponding to the potential risks and the existing risks, further merging and generating pipe rack health data, and transmitting the pipe rack health data into a database arranged in a diagnosis center.
  7. 7. The utility tunnel health diagnostic system based on big data technology of claim 6, wherein the process of generating diagnostic results by the diagnostic center comprises: Setting a data receiving period and a data analysis period of a diagnosis center, reading pipe gallery health data from a database by the diagnosis center in the data receiving period, synchronously receiving image data, starting diagnosis analysis on the pipe gallery health data and the image data in the data analysis period, setting an image library for storing a plurality of pipe gallery images, wherein each pipe gallery image is associated with a corresponding historical diagnosis scheme, importing the image data into the image library to match the pipe gallery image corresponding to the image data, further acquiring a corresponding historical diagnosis scheme, analyzing the pipe gallery health data into a corresponding real-time diagnosis scheme according to machine learning diagnosis, judging whether the historical diagnosis scheme is consistent with the real-time diagnosis scheme, if so, taking the historical diagnosis scheme as a diagnosis result, and if not, taking the real-time diagnosis scheme as the diagnosis result.
  8. 8. The utility tunnel health diagnostic system based on big data technique of claim 7, wherein the process of generating corresponding alarm data based on the diagnostic result and scheduling corresponding maintenance personnel to perform maintenance operations based on the alarm data comprises: The diagnosis result is provided with different danger levels, alarm data of corresponding alarm levels are generated according to the different danger levels, the danger levels comprise a general level, a danger level and a high-risk level, and the alarm levels comprise yellow early warning, orange early warning and red early warning; The corresponding relation between the diagnosis results of different dangerous grades and the alarm data of different alarm grades is as follows, namely, general grade-yellow early warning, dangerous grade-orange early warning, high-dangerous grade-red early warning, and corresponding maintainers are arranged to go to the comprehensive pipe gallery to execute maintenance operation according to the sequence of the red early warning, the orange early warning and the yellow early warning, so that the problems of the comprehensive pipe gallery are eliminated.

Description

Comprehensive pipe rack health diagnosis system based on big data technology Technical Field The invention relates to the technical field of pipe gallery health diagnosis, in particular to a comprehensive pipe gallery health diagnosis system based on a big data technology. Background Utility tunnel is a concept of infrastructure construction, which is a comprehensive piping corridor system built for centralized management and arrangement of various utility lines (e.g., electricity, communications, tap water, gas, heat, etc.) in urban underground or on relatively small ground spaces. In recent years, with the development of urban process, the construction of underground pipe galleries is increased, however, the operation maintenance problem of pipe galleries is followed, and once faults occur, the normal use is influenced, and safety accidents are possibly caused, so that the operation data of each system and equipment in the underground pipe galleries are accurately and comprehensively collected, the compatibility problem existing between different systems and equipment is solved, a solid data base is achieved, data support is provided for the fault diagnosis of the follow-up comprehensive pipe galleries, the accuracy of the fault diagnosis is improved, and the fault problem is solved timely. Disclosure of Invention In order to solve the problems, the invention aims to provide a comprehensive pipe rack health diagnosis system based on big data technology. The utility model discloses a comprehensive pipe rack health diagnosis system based on big data technology, which comprises a diagnosis center, wherein the diagnosis center is in communication connection with a data acquisition module, a data processing module, a data analysis module and an alarm module; the data acquisition module is used for acquiring operation data of a plurality of systems and devices arranged in the comprehensive pipe rack, setting a plurality of shooting points in the comprehensive pipe rack, and arranging image acquisition devices at the shooting points to acquire image data; the data processing module is provided with a conversion module, and operation data corresponding to different systems and devices are uniformly converted through the conversion module, so that a data set to be analyzed is generated, and the data set to be analyzed is subjected to data cleaning; the data analysis module is used for acquiring a data set to be analyzed after data cleaning is completed, importing the data set to be analyzed into a constructed big data analysis model for multidimensional data analysis, further generating pipe gallery health data, transmitting the pipe gallery health data to a diagnosis center, and generating a diagnosis result by the diagnosis center; The alarm module is used for generating corresponding alarm data according to the diagnosis result and arranging corresponding maintenance personnel to execute maintenance operation according to the alarm data. Further, the process of collecting operational data of a number of systems and devices disposed in the utility tunnel includes: the system and the equipment are used for carrying out normal operation of electric power, communication, tap water and fuel gas in the comprehensive pipe rack, and a sensor module and a data checking program are arranged for each system and each equipment in an associated mode; The sensor module comprises a temperature sensor, a pressure sensor and a humidity sensor, and is used for respectively acquiring temperature data, pressure data and humidity data corresponding to each system and equipment, a data checking program is used for acquiring working parameters corresponding to each system or equipment, a normal reference value interval of the working parameters is recorded in the data checking program, and then the data checking program judges whether the working parameters are in the normal reference value interval or not; If the working parameters are in the normal reference value interval, no operation is performed, if not, an Error mark is input for a system and equipment corresponding to the working parameters, temperature data, pressure data and humidity data acquired by the sensor module are used as external operation data, the working parameters acquired by the data checking program are used as internal operation data, and the external operation data and the internal operation data are combined into operation data corresponding to each system and equipment. Further, a plurality of shooting points are set in the utility tunnel, and the process of arranging the image acquisition equipment at the shooting points to acquire image data comprises the following steps: A plurality of shooting points are arranged in the comprehensive pipe rack and numbered, the numbers are i, i=1, 2,3, the number is n, wherein n is a natural number larger than 0, the image acquisition equipment is arranged at each shooting point, the acquisition and debugging work is