CN112113145A - Intelligent online detection method for chemical pipeline safety - Google Patents
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Abstract
The invention discloses an intelligent online detection method for chemical pipeline safety, which is arranged in a machine body and comprises a data storage unit, wherein the data storage unit is electrically connected with a data processing unit, the data storage unit is electrically connected with a data analysis unit, the output end of a data acquisition unit is electrically connected with the input end of the data processing unit, the output end of the data processing unit is electrically connected with the input end of the data analysis unit, and the output end of the data analysis unit is electrically connected with the input end of a control processing unit Poor detection effect, no effective preventive measures, high cost and the like.
Description
Technical Field
The invention relates to the technical field of intelligent detection, in particular to an intelligent online detection method for chemical pipeline safety.
Background
A lot of pipelines can be used to chemical enterprise's production facility, and these pipelines mainly used carry all kinds of production raw and other materials, semi-manufactured goods and finished product, and the safety of chemical pipeline directly relates to chemical enterprise's production safety, is chemical enterprise safety's important component, and the gas of just carrying, liquid kind are many because of chemical enterprise's the pipeline is in large quantity and kind is complicated, has brought very big pressure to the safety control of pipeline.
The on-line detection of chemical pipelines is an important means for safety management of chemical enterprises, and the following methods are mainly adopted at present:
1. based on the manual inspection method: an experienced technician carries a pipeline detection instrument or a trained animal segment to carry out pipeline detection and positioning; the method has the characteristics of accurate positioning and low false alarm rate, but leakage cannot be found in time, and pipeline detection can be only carried out discontinuously.
2. Based on the cable leak detection method: the method is very sensitive, has good effect on small leakage and slow leakage, but has high price and construction cost of the cable, and the cable needs to be replaced once being infected with the leakage, so that the method is mainly used for detecting the leakage of the liquid hydrocarbon fuel.
3. An external pipeline detection method based on operating parameters such as pipeline pressure, flow and temperature is as follows: the online monitoring can be realized, and the method is one of main attack directions of research on pipeline detection and positioning.
The current situation and problems of the three detection methods are as follows:
the timeliness is poor
The existing detection method adopts specific equipment or manual mode to collect data, and the data are basically non-real-time, discontinuous and have certain discreteness; the safety of the pipeline cannot be timely and accurately judged by the non-real-time discrete data.
Predictive difference
The data collected by the existing detection method is single, and scientific and comprehensive index system data is lacked; meanwhile, most data are discontinuous; therefore, the current detection method cannot predict the safety of the pipeline, and cannot prevent or eliminate the potential safety hazard of the pipeline in advance.
High cost
The existing detection method only can increase the probability of finding problems by increasing the input of manpower or equipment, and improves the detection of problems at the same time, so that a scientific and comprehensive high-cost performance scheme is lacked; the investment of enterprises is often repetitive, the utilization rate of equipment is very low, and the probability of finding problems is also low, so the overall cost is very high; this makes many business owners feel that the investment is like a bottomless hole, and do not want to increase the investment, or do local investment according to subjective basis.
Poor stability
Because the existing detection method lacks comprehensiveness, the relevance between index data cannot be utilized for automatic correction; therefore, the conclusion of the analysis using these relatively single and non-continuous inaccurate data is not stable, and can only be used as the basis for further determination, but not as the decision basis for directly taking emergency measures.
Aiming at the problems, the solution idea of the patent is to adopt a sensor and an image collector to replace the existing data collection mode, and simultaneously, the original various data are integrated and utilized in a unified way; and the artificial intelligence mode is used for replacing the prior inefficient actions of measurement, calculation, analysis, judgment, feedback and the like, so that the management convenience is provided for a manager of the safety of the chemical enterprises, the potential safety hazard of the chemical pipelines can be finally predicted accurately in time, measures are taken in advance, and the safety accidents are finally avoided.
Disclosure of Invention
The invention aims to provide an intelligent online detection method for chemical pipeline safety, which can solve the problems of poor timeliness, poor predictability, high cost and poor stability.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides an intelligent on-line measuring device of chemical pipeline safety, the device sets up inside the organism, including the data storage unit, the data storage unit includes real-time data, historical data, result data, model data and basic data, data storage unit and data processing unit electricity are connected, the data processing unit is by format conversion, filter screening and restoration merge and constitute, the data storage unit is connected with the data analysis unit electricity, the output of data acquisition unit and the input electricity of data processing unit are connected, the output of data processing unit and the input electricity of data analysis unit are connected, the output of data analysis unit and the input electricity of control processing unit are connected.
The data acquisition unit comprises a sensor, an intelligent camera, a chemical instrument and a management system.
The data analysis unit comprises an intelligent algorithm, intelligent analysis and intelligent prediction.
The control processing unit comprises early warning control, instruction sending and instruction adaptation.
A method of using the apparatus as described above, comprising the steps of:
the method comprises the following steps that firstly, a data acquisition unit acquires original data such as pressure, temperature, appearance, vibration, pipeline thickness, unit flow and the like of each part of a chemical pipeline through equipment such as a sensor, an intelligent camera, a chemical instrument and the like, extracts relevant data such as production raw materials, intermediate product types and the like from a production management system in real time, converts non-digitized data into digitized data, and then transmits the data to a data processing unit through a network; the design of the process ensures the synchronism and integrity of real-time data, provides continuous data for subsequent analysis and processing, and has strong real-time acquisition and higher safety; the untimely and accurate manual data recording is avoided;
after the data processing unit receives the data, according to a preset data filtering and cleaning rule and a data structuring logic principle, carrying out preprocessing operations such as format conversion, invalid removal, duplicate removal, restoration, merging, structuring and the like on the original data, storing the valid structured data, and providing basic data for data operation and analysis for the data analysis unit; in addition, invalid data is discarded, so that analysis interference and storage resource waste are avoided;
thirdly, the data analysis unit recombines the real-time data sent by the data processing unit and the historical data read from the data storage unit at regular time into data flow meeting the requirement of the analysis algorithm through a structured preprocessing algorithm, and carries out analysis operation according to multiple dimensions such as time, space, process relation, role relation and the like to generate analysis results required by various services; the system also corrects algorithm data through deep learning, further enhances the operational analysis and assistance processing capacity, and achieves the self-improvement function;
step four, the result data of the index analysis operation is used as the input of an intelligent processing algorithm and is used for monitoring and judging whether major potential safety hazards exist in the current chemical pipeline or not, whether timely alarming is needed or not and the like; meanwhile, the trend analysis of the potential safety hazard is carried out by combining historical mass data, early warning judgment and comprehensive assessment of early warning grades are implemented, and pushing warning messages are triggered; if the alarm needs to be automatically controlled, an instruction is sent to the control processing unit; various index analysis operation results of the data processing unit can be displayed by a terminal, such as index result data, alarm information, an automatic control trigger log and the like; compared with manual analysis and control, the design has the advantages that the analysis is more comprehensive and visual, the reflection is more timely, the result is more practical, and the monitoring alarm and the automatic control are intelligentized particularly;
the control processing unit is an operation integration unit and is responsible for receiving the control instruction of the data analysis unit, adapting the instruction and converting the instruction into an instruction which can be recognized by a front-end system, and executing remote calling of each interface to trigger each device for automatically controlling the site of the remote chemical pipeline to perform early warning and real-time monitoring, so that an intelligent control effect of generating the site safety problem of the chemical pipeline is realized;
step six, the data storage unit stores the real-time effective data and result data to form real-time data and result data; meanwhile, arranging outdated real-time data and result data according to different sequences such as time and the like, and performing dump according to different dimensions to form historical data; storing the preprocessed model data, the model data of the analysis algorithm and the like to form model data, and performing autonomous updating on the model data through deep learning; and storing various rules required in the data processing process to form basic data.
Compared with the prior art, the invention has the beneficial effects that: the system can basically replace all working activities of manual patrol monitoring, comprises the items of on-site patrol, instrument monitoring, data acquisition and recording, chemical pipeline state analysis and report, feedback of abnormal conditions of chemical pipelines, related emergency operation and the like, and solves the problems of high risk, poor detection effect, no effective preventive measures, high cost and the like of manual patrol; meanwhile, the problems of stability and accuracy of an automatic control system and a safety instrument system of the original chemical production system can be solved; the method has the characteristics of non-contact detection, high efficiency, low cost, high equipment and data relevance, high intelligent degree and the like, can bring multiple benefits of reducing cost, improving efficiency, enhancing safety and the like for safety prediction of chemical pipelines, and accords with the intelligent development direction advocated by the state.
Compared with the traditional chemical pipeline safety prediction method, the method has the following characteristics and advantages:
(1) low risk
The labor amount of manpower is reduced, and the personal risk probability is reduced; the sensor replaces the detection work of the risk area, and the intelligent camera replaces the image acquisition work of the risk area, so that personal risk factors are eliminated; the accident is intelligently prevented or the occurrence of a major accident is prevented, and the loss probability is reduced.
(2) High efficiency
The computer replaces manpower, and the time consumption for completing a plurality of working items is almost zero; the platform has the advantages that the equipment data can be acquired and recorded more quickly and more frequently, the equipment data correlation is high, the mass database can be used for uninterruptedly analyzing and calculating, the instant state of the chemical pipeline can be output in real time, and the safety of the chemical pipeline can be measured quickly by sensing the state of the chemical pipeline in time through big data analysis.
(3) Low cost
The labor amount of manpower is reduced, and the labor cost is reduced; the management is simpler, the risk is lower, and the management cost, the risk cost and other indirect costs are reduced.
(4) Is more stable
The operation of the platform is not affected by the weak points of physiology, emotion and character of people, and cannot be greatly affected by personnel flow, the platform can ensure the normal operation of detection and monitoring, guarantee is provided for accurate and effective prediction, and management is facilitated.
(5) Intelligent control
The platform provides wider and deeper data analysis, makes things convenient for monitoring personnel to know more comprehensively and establishes meteorological condition, can predict the state trend of chemical pipeline, and the loss that chemical pipeline safety problem brought is prevented to automatic early warning, makes the potential safety hazard of chemical pipeline fall to minimumly.
Drawings
FIG. 1 is a schematic diagram of the components and the relationship between the components of the intelligent online detection method for the safety of chemical pipelines;
FIG. 2 is a schematic diagram of the implementation design and principle logic of the intelligent online detection method for chemical pipeline safety of the present invention;
FIG. 3 is a logic diagram of an intelligent processing algorithm of the intelligent online detection method for chemical pipeline safety of the present invention;
fig. 4 is a schematic diagram of a specific embodiment of the intelligent online detection method for chemical pipeline safety of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The intelligent online detection device for the safety of the chemical pipeline is arranged in a machine body and comprises a data storage unit, wherein the data storage unit comprises real-time data, historical data, result data, model data and basic data, the data storage unit is electrically connected with a data processing unit, the data processing unit is formed by format conversion, filtering, screening, repairing and merging, the data storage unit is electrically connected with a data analysis unit, the output end of a data acquisition unit is electrically connected with the input end of the data processing unit, the output end of the data processing unit is electrically connected with the input end of the data analysis unit, and the output end of the data analysis unit is electrically connected with the input end of a control processing unit; the data acquisition unit comprises a sensor, an intelligent camera, a chemical instrument and a management system; the data analysis unit comprises an intelligent algorithm, intelligent analysis and intelligent prediction; the control processing unit comprises early warning control, instruction sending and instruction adaptation.
As shown in fig. 4, a specific embodiment of the intelligent online detection method for chemical pipeline safety of the present invention is described as follows;
1. the data of sensors arranged at different positions on a chemical pipeline, such as real-time data information of sensors for temperature, vibration, gas detection and the like, and image information of the pipeline appearance and the surrounding environment shot by an intelligent camera in real time on site are transmitted to a monitoring center server through an optical fiber network.
2. Real-time data, image information and related historical data are processed, analyzed and intelligently calculated by each functional server, a big data model is built, the development trend of the data information and the possible abnormal conditions are predicted, all the data and the image information are displayed through a monitoring center terminal, an industrial personal computer sets initial parameters, and the state and the early warning condition of a field pipeline are displayed in real time.
3. When data is abnormal, if chemical pipelines are abnormally changed and continue, the server judges according to the abnormal conditions of related data, the data analysis system carries out intelligent analysis and prediction, early warning is carried out when the possibility of chemical safety hidden danger is generated due to abnormal prediction, an operator on duty is reminded to carry out related operation and carry out early warning processing, and according to the processing level, corresponding level departments are notified, so that processing measures are made and are reported to the related departments in a grading mode. When a decision-making department makes a decision according to a prediction result and needs to issue early warning information, the control processing unit sends a command to the related instruction adapter through the local area network, the related instruction adapter receives the instruction information, issues the early warning information to a road site and a subordinate control center, simultaneously monitors the state and the change trend of the chemical pipeline in real time, manages and controls the change condition and the trend, assists the site to conduct command and other related measures to guarantee the safety of the chemical pipeline, and finally reduces the adverse effect of potential safety hazards on enterprise production.
As shown in fig. 2, which describes the implementation design and principle logic of the present invention, first, when the data acquisition unit acquires the original data of pressure, temperature, appearance, vibration, pipe thickness, unit flow and the like of each part of the chemical pipeline through the devices such as the sensor, the smart camera, the chemical instrument and the like, and extracts the relevant data of production raw materials, intermediate types and the like from the production management system in real time, meanwhile, the non-digitized data is converted into the digitized data, and then the data is transmitted to the data processing unit through the network; the design of the process ensures the synchronism and integrity of real-time data, provides continuous data for subsequent analysis and processing, and has strong real-time acquisition and higher safety; the untimely and accurate manual data recording is avoided;
after the data processing unit receives the data, according to a preset data filtering and cleaning rule and a data structuring logic principle, carrying out preprocessing operations such as format conversion, invalid removal, duplicate removal, restoration, merging, structuring and the like on the original data, storing the effective structured data, and providing basic data for data operation and analysis for the data analysis unit; in addition, invalid data is discarded, so that analysis interference and storage resource waste are avoided; the data analysis unit is used for recombining the real-time data sent by the data processing unit and the historical data read from the data storage unit at regular time into a data stream meeting the requirements of an analysis algorithm through a structured preprocessing algorithm, and performing analysis operation according to multiple dimensions such as time, space, process relation, role relation and the like to generate analysis results required by various services; the system also corrects algorithm data through deep learning, further enhances the operational analysis and assistance processing capacity, and achieves the self-improvement function;
then, the result data of the index analysis operation is used as the input of an intelligent processing algorithm and is used for monitoring and judging whether major potential safety hazards exist in the current chemical pipeline or not, whether timely alarming is needed or not and the like; meanwhile, the trend analysis of the potential safety hazard is carried out by combining historical mass data, early warning judgment and comprehensive assessment of early warning grades are implemented, and pushing warning messages are triggered; if the alarm needs to be automatically controlled, an instruction is sent to the control processing unit; various index analysis operation results of the data processing unit can be displayed by a terminal, such as index result data, alarm information, an automatic control trigger log and the like; compared with manual analysis and control, the design has the advantages that the analysis is more comprehensive and visual, the reflection is more timely, the result is more practical, and the monitoring alarm and the automatic control are intelligentized particularly;
then the control processing unit is an operation integration unit and is responsible for receiving the control instruction of the data analysis unit, adapting the instruction and converting the instruction into an instruction which can be recognized by a front-end system, and executing remote calling of each interface to trigger each device for automatically controlling the site of the remote chemical pipeline to perform early warning and real-time monitoring, so that an intelligent control effect of generating the site safety problem of the chemical pipeline is realized;
finally, the data storage unit stores the real-time effective data and result data to form real-time data and result data; meanwhile, arranging outdated real-time data and result data according to different sequences such as time and the like, and performing dump according to different dimensions to form historical data; storing the preprocessed model data, the model data of the analysis algorithm and the like to form model data, and performing autonomous updating on the model data through deep learning; storing various rules required in the data processing process to form basic data;
in addition, as shown in fig. 3, the intelligent processing algorithm logic is described in detail in the embodiment of the present invention, which is specifically as follows:
(1) the algorithm receives the result data of index operation and analysis of the data analysis unit, namely the result data of multidimensional statistical operation and analysis of various indexes, circularly obtains each index data value, checks whether the threshold value is exceeded or checks the index data value trend in the latest N unit periods, calculates the possible index values in the next X unit periods, and summarizes whether the index is abnormal or not currently;
(2) if the index data is judged to be abnormal, calculating and setting the type, influence coefficient, grade value and the like of the current abnormality of the index according to the definition of the abnormality detection rule, and then immediately entering the next index processing cycle; on the contrary, if no abnormity exists, the next index processing cycle is directly entered;
(3) after the abnormal analysis and monitoring processing of all indexes is finished, carrying out comprehensive score calculation through the influence coefficient of each index and the current abnormal grade value, determining the final abnormal grade and judging whether to initiate an alarm or not by combining with an alarm rule;
(4) if the alarm condition is met, initiating an alarm; in order to avoid repeated alarm and high-frequency alarm interference, convergence judgment needs to be carried out on the alarm, namely association, combination, duplication removal and other processing judgment are carried out on the abnormal alarm by combining the alarm history of the near period of time and the alarm rule; on the contrary, if the alarm condition is not met, the process is ended after the relevant information is stored;
(5) if the alarm is not converged, the alarm processing is started according to the abnormal alarm rule, and different levels of personnel notification and processing are carried out aiming at the alarms of different levels, such as a primary (P1) alarm notification operator, a secondary (P2) alarm notification department manager and a general responsible person notified by more than three levels (P3); if the alarm is converged (judged to be repeated or combined), the process is ended after the relevant information is stored;
(6) after executing the alarm processing, if the alarm level reaches the formation condition of the potential safety hazard and meets the control condition, generating and sending the required control data to the control processing unit, and then storing the relevant information and ending the process.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (5)
1. The utility model provides an intelligent on-line measuring device of chemical pipeline safety, the device sets up inside the organism, including data storage unit, its characterized in that: the data storage unit comprises real-time data, historical data, result data, model data and basic data, the data storage unit is electrically connected with the data processing unit, the data processing unit is formed by format conversion, filtering, screening and repairing combination, the data storage unit is electrically connected with the data analysis unit, the output end of the data acquisition unit is electrically connected with the input end of the data processing unit, the output end of the data processing unit is electrically connected with the input end of the data analysis unit, and the output end of the data analysis unit is electrically connected with the input end of the control processing unit.
2. The intelligent online detection device for the safety of the chemical pipeline according to claim 1, characterized in that: the data acquisition unit comprises a sensor, an intelligent camera, a chemical instrument and a management system.
3. The intelligent online detection device for the safety of the chemical pipeline according to claim 1, characterized in that: the data analysis unit comprises an intelligent algorithm, intelligent analysis and intelligent prediction.
4. The intelligent online detection device for the safety of the chemical pipeline according to claim 1, characterized in that: the control processing unit comprises early warning control, instruction sending and instruction adaptation.
5. A method of using the apparatus of claims 1-4, comprising the steps of:
the method comprises the following steps that firstly, a data acquisition unit acquires original data such as pressure, temperature, appearance, vibration, pipeline thickness, unit flow and the like of each part of a chemical pipeline through equipment such as a sensor, an intelligent camera, a chemical instrument and the like, extracts relevant data such as production raw materials, intermediate product types and the like from a production management system in real time, converts non-digitized data into digitized data, and then transmits the data to a data processing unit through a network; the design of the process ensures the synchronism and integrity of real-time data, provides continuous data for subsequent analysis and processing, and has strong real-time acquisition and higher safety; the untimely and accurate manual data recording is avoided;
after the data processing unit receives the data, according to a preset data filtering and cleaning rule and a data structuring logic principle, carrying out preprocessing operations such as format conversion, invalid removal, duplicate removal, restoration, merging, structuring and the like on the original data, storing the valid structured data, and providing basic data for data operation and analysis for the data analysis unit; in addition, invalid data is discarded, so that analysis interference and storage resource waste are avoided;
thirdly, the data analysis unit recombines the real-time data sent by the data processing unit and the historical data read from the data storage unit at regular time into data flow meeting the requirement of the analysis algorithm through a structured preprocessing algorithm, and carries out analysis operation according to multiple dimensions such as time, space, process relation, role relation and the like to generate analysis results required by various services; the system also corrects algorithm data through deep learning, further enhances the operational analysis and assistance processing capacity, and achieves the self-improvement function;
step four, the result data of the index analysis operation is used as the input of an intelligent processing algorithm and is used for monitoring and judging whether major potential safety hazards exist in the current chemical pipeline or not, whether timely alarming is needed or not and the like; meanwhile, the trend analysis of the potential safety hazard is carried out by combining historical mass data, early warning judgment and comprehensive assessment of early warning grades are implemented, and pushing warning messages are triggered; if the alarm needs to be automatically controlled, an instruction is sent to the control processing unit; various index analysis operation results of the data processing unit can be displayed by a terminal, such as index result data, alarm information, an automatic control trigger log and the like; compared with manual analysis and control, the design has the advantages that the analysis is more comprehensive and visual, the reflection is more timely, the result is more practical, and the monitoring alarm and the automatic control are intelligentized particularly;
the control processing unit is an operation integration unit and is responsible for receiving the control instruction of the data analysis unit, adapting the instruction and converting the instruction into an instruction which can be recognized by a front-end system, and executing remote calling of each interface to trigger each device for automatically controlling the site of the remote chemical pipeline to perform early warning and real-time monitoring, so that an intelligent control effect of generating the site safety problem of the chemical pipeline is realized;
step six, the data storage unit stores the real-time effective data and result data to form real-time data and result data; meanwhile, arranging outdated real-time data and result data according to different sequences such as time and the like, and performing dump according to different dimensions to form historical data; storing the preprocessed model data, the model data of the analysis algorithm and the like to form model data, and performing autonomous updating on the model data through deep learning; and storing various rules required in the data processing process to form basic data.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113884247A (en) * | 2021-12-09 | 2022-01-04 | 南京派光智慧感知信息技术有限公司 | Comprehensive monitoring system and method for oil and gas pipeline |
| CN113988552A (en) * | 2021-10-18 | 2022-01-28 | 北理新源(佛山)信息科技有限公司 | Hydrogen industry chain risk monitoring system based on big data |
| CN116617616A (en) * | 2023-04-24 | 2023-08-22 | 深圳市筑乐科技有限公司 | Fire-fighting pipeline monitoring method, fire-fighting pipeline monitoring system, terminal equipment and storage medium |
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