CN112083696A - System for intelligently managing and monitoring safety of chemical equipment through big data and application - Google Patents
System for intelligently managing and monitoring safety of chemical equipment through big data and application Download PDFInfo
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- CN112083696A CN112083696A CN202010902129.7A CN202010902129A CN112083696A CN 112083696 A CN112083696 A CN 112083696A CN 202010902129 A CN202010902129 A CN 202010902129A CN 112083696 A CN112083696 A CN 112083696A
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/4183—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by data acquisition, e.g. workpiece identification
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/31—From computer integrated manufacturing till monitoring
- G05B2219/31282—Data acquisition, BDE MDE
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The system comprises a monitoring system and a monitoring system, wherein the monitoring system is used for intelligently managing and monitoring the safety of chemical equipment through big data, and relates to a monitoring system for the safe operation of chemical factory equipment, in particular to a safety system for intelligently monitoring the chemical equipment through the big data. The big data input degree of main control center connects on big data storage comparison center, and a plurality of data acquisition contact nodes all connect on main control center, and every data acquisition contact node all is connected with data acquisition point, and the signal output part of temperature check point, pressure check point, air harmful gas content check point, equipment magnetic check point, water source check point, drainage check point is connected respectively on each data acquisition contact node. The invention can greatly improve the running safety of the equipment, and can know the position of the hidden danger in the initial stage of data change, thereby timely eliminating treatment, further improving the safety of chemical manufacturers, avoiding major accidents, and timely discovering and treating the hidden danger.
Description
Technical Field
The invention relates to a monitoring system for the safe operation of chemical plant equipment, in particular to a safety system for intelligently monitoring chemical equipment through big data.
Background
The equipment operation of the chemical plant often has states and processes of high pressure, high temperature, violent chemical reaction and the like, and the requirement on the equipment is very high. Chemical plants at home and abroad often have severe accidents including deflagration, explosion and the like, and the accidents often have serious consequences.
Pressure, temperature, hazardous gas content and the like of the chemical equipment in the operation process can be monitored and detected and displayed through corresponding display equipment, but the data are relatively independently displayed or partially displayed in a centralized manner, so that centralized monitoring is difficult, and data errors and errors of the detection equipment are easy to occur in the long-term operation of the monitoring detection equipment.
Disclosure of Invention
The invention aims to provide a system for intelligently managing and monitoring the safety of chemical equipment through big data and an application thereof aiming at the defects and defects of the prior art, which monitors all the running states of the current chemical equipment systematically and intelligently and compares and monitors running bodies through the big data so as to know the reliability and the safety of the chemical equipment; and transmits all the detected data back to the monitoring center through the network.
In order to achieve the purpose, the invention adopts the following technical scheme: the system comprises a main control center 1, a big data storage comparison center 2, a plurality of data acquisition contact nodes 3 and a plurality of data acquisition points 4; the big data input degree of main control center 1 is connected on big data storage comparison center 2, a plurality of data acquisition contact nodes 3 all connect on main control center 1, every data acquisition contact node 3 all is connected with data acquisition point 4, data acquisition point 4 includes temperature detection point 41, pressure detection point 42, harmful gas in air content detection point 43, equipment magnetic particle detection point 44, water source detection point 45, drainage detection point 46, the signal output part of temperature detection point 41, pressure detection point 42, harmful gas in air content detection point 43, equipment magnetic particle detection point 44, water source detection point 45, drainage detection point 46 connects respectively on each data acquisition contact node 3.
The temperature detection point 41 is arranged on the monitored chemical equipment, is arranged at the position needing to be detected and can be arranged on the shell, the feed inlet and the discharge outlet; the pressure detection points 42 are arranged on each pressure container and each reaction container; the air harmful gas content detection point 43 is arranged near the exhaust port of the equipment and at a position where the equipment is easy to leak.
The equipment magnetic powder detection point 44 is arranged at the position with the magnetic powder safety point of the chemical equipment; the water yard detection point 4 is arranged on a water source point of the water inlet of the equipment; the drainage detection point 46 is arranged on the sewage outlet of the chemical equipment.
The system for intelligently managing and monitoring the safety of the chemical equipment by using the big data is applied as follows: the method comprises the steps that a plurality of temperature detection points 41 are arranged on monitored chemical equipment, the temperature of each temperature detection point 41 is slightly different, data obtained by each temperature detection point 41 are t1, t2 and t 3-tn, and data of t1, t2 and t 3-tn are divided into arrays for data transmission according to detection of different equipment; the master control center 1 records all data, records the temperature data of the same group of data into the big data storage comparison center 2, calculates the temperature difference of each temperature data acquisition point of the same equipment and records the temperature difference; when the temperature data of the same group are abnormal, the big data storage and comparison center 2 sends the data back to the main control center 1, and the main control center 1 displays the abnormal temperature difference information and sends out a warning signal; meanwhile, the big data storage and comparison center 2 performs key monitoring on key temperature data of the temperature detection points 41, wherein the key temperature data comprises internal and external temperature data of the pressure container, internal and external temperature data of the reaction furnace, temperature data of a dangerous goods yard, humidity data and the like.
The method comprises the steps that a plurality of pressure detection points 42 are arranged on monitored chemical equipment, data obtained from different pressure detection points 42 on the same equipment are set into one group, pressure data of different equipment are recorded in a grouping mode, and the first group is Y1-1, Y1-2, Y1-3 and Y1-4 …; the second group is Y2-1, T2-2 and Y2-3 …, and the number of each group can be detected according to requirements; the data detected by the pressure detection points 42 are transmitted back to the main control center 1 through the data acquisition contact node 3, the main control center 1 compares the obtained pressure data with each data of the big data storage comparison center 2, when each pressure data is abnormal and exceeds an early warning value, the main control center 1 displays the abnormal pressure data on a display screen, displays the current data in real time, and sends out an alarm signal.
A plurality of air harmful gas content detection points 43 are arranged in a monitored equipment workshop, data detected by the air harmful gas content detection points 43 are transmitted back to the main control center 1 through the data acquisition contact node 3, the main control center 1 compares the air data of each harmful gas detection point with big data of the big data storage comparison center 2, and whether the current air harmful gas is within a normal value or not is analyzed through the big data center; when the data comparison is in an abnormal value, the current data is highlighted and an alarm prompt is sent out through the main control center 1 to remind people to intervene and process.
The equipment magnetic particle detection point 44 is arranged on equipment capable of carrying out magnetic particle inspection detection, data detected by the magnetic particle detection point 44 are transmitted back to the main control center 1 through the data acquisition contact node 3, the magnetic particle detection point 44 is mainly used for surface defects of ferromagnetic materials in chemical equipment, and when the detected data are abnormal with the big data storage comparison center 2, the current defects are displayed and alarm information is sent out through the main control center 1.
The method comprises the steps that a plurality of water source detection points 45 are arranged at a water source of monitored chemical equipment, the water source detection points 45 detect the pH value and the mineral content equivalence of the water source, data detected by the water source detection points 45 are transmitted back to a main control center 1 through a data acquisition contact node 3, the data are compared with data of the main control center 1 through a big data storage comparison center 2, an alarm signal is sent out when the detected data exceed an expected value, and manual intervention is required. The water source at the water source is generally used as cooling water, so various values of the water source directly influence the later cooling effect and the influence on the safety and the service life of the equipment.
The method comprises the steps that a plurality of drainage detection points 46 are arranged at the drainage position of monitored chemical equipment, the drainage detection points 46 detect multiple items of data of each drainage point respectively, the obtained data are transmitted back to a main control center 1 through a data acquisition contact node 3, the main control center 1 compares the transmitted data with the data of a big data storage comparison center 2, and when the data are abnormal, the main control center 1 sends out prompt and alarm information. The drainage is that all kinds of chemical industry equipment need cooling water, purified water etc., this part of water is easily polluted, and the pollution process has direct relation with whether equipment operation is safe, therefore monitor the drainage point be one of necessary and effectual safe means.
The big data storage comparison center 2 carries out longitudinal time period sectional recording on all acquired detection data of the temperature detection point 41, the pressure detection point 42, the air harmful gas content detection point 43, the equipment magnetic powder detection point 44, the water source detection point 45 and the drainage detection point 46, records the data according to the requirement every day, every six hours, every three hours, every hour and every half hour, counts the data and calculates the safety fluctuation range; and calculating and storing the data difference among a plurality of detection points of the same equipment, and carrying out statistical calculation on the data to calculate the safety range of the difference value.
The daily data of the chemical equipment through the big data system comprises the following steps: comprehensively detecting data such as temperature, pressure, air harmful gas content, equipment surface corrosion damage, water source, drainage and the like, and recording the data transversely and longitudinally to form a big data system according to data difference and a data fluctuation safety range; whether the chemical equipment is safe or not is obtained, so that the safety of the whole chemical equipment is obtained, the position of the potential safety hazard can be known at the initial stage of data fluctuation, and the potential safety hazard is timely eliminated to ensure the safe operation of the equipment.
After the technical scheme is adopted, the safety of equipment operation can be greatly improved, and the location where the hidden danger occurs can be known at the initial stage of data change, so that the treatment can be timely eliminated, the safety of chemical manufacturers can be further improved, major accidents can be avoided, and the potential safety hazard can be timely discovered and treated.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a block diagram of the present invention;
FIG. 2 is a diagram showing a detailed detection information distribution of temperature detection points 41 in the present invention;
fig. 3 shows the distribution of the packet detection information of the pressure detection points 42 in the present invention.
Description of reference numerals: the system comprises a main control center 1, a big data storage comparison center 2, a data acquisition contact node 3, a data acquisition point 4, a temperature detection point 41, a pressure detection point 42, an air harmful gas content detection point 43, an equipment magnetic powder detection point 44, a water source detection point 45 and a drainage detection point 46.
Detailed Description
Referring to fig. 1 to fig. 3, the technical solution adopted by the present embodiment is: the system comprises a main control center 1, a big data storage comparison center 2, a plurality of data acquisition contact nodes 3 and a plurality of data acquisition points 4; the big data input degree of main control center 1 is connected on big data storage comparison center 2, a plurality of data acquisition contact nodes 3 all connect on main control center 1, every data acquisition contact node 3 all is connected with data acquisition point 4, data acquisition point 4 includes temperature detection point 41, pressure detection point 42, harmful gas in air content detection point 43, equipment magnetic particle detection point 44, water source detection point 45, drainage detection point 46, the signal output part of temperature detection point 41, pressure detection point 42, harmful gas in air content detection point 43, equipment magnetic particle detection point 44, water source detection point 45, drainage detection point 46 connects respectively on each data acquisition contact node 3.
The temperature detection points 41 are arranged on the tank body of the monitored chemical production equipment, are arranged at positions needing to be detected and can be arranged on a feed port and a discharge port of the tank body; the pressure detection points 42 are arranged on each pressure container, reaction container or reaction kettle; the air harmful gas content detection point 43 is arranged near the exhaust port of the equipment and at the position where the equipment is easy to leak; the equipment magnetic powder detection point 44 is arranged at the position with the magnetic powder safety point of the chemical equipment; the water yard detection point 4 is arranged on a water source point of the water inlet of the equipment; the drainage detection point 46 is arranged on the sewage outlet of the chemical equipment.
The system for intelligently managing and monitoring the safety of the chemical equipment by using the big data is applied as follows: the method comprises the steps that a plurality of temperature detection points 41 are arranged on monitored chemical equipment, the temperature of each temperature detection point 41 is slightly different, data obtained by each temperature detection point 41 are t1, t2 and t 3-tn, and data of t1, t2 and t 3-tn are divided into arrays for data transmission according to detection of different equipment; the master control center 1 records all data, records the temperature data of the same group of data into the big data storage comparison center 2, calculates the temperature difference of each temperature data acquisition point of the same equipment and records the temperature difference; when the temperature data of the same group are abnormal, the big data storage and comparison center 2 sends the data back to the main control center 1, and the main control center 1 displays the abnormal temperature difference information and sends out a warning signal; meanwhile, the big data storage and comparison center 2 performs key monitoring on key temperature data of the temperature detection points 41, wherein the key temperature data comprises internal and external temperature data of the pressure container, internal and external temperature data of the reaction furnace, temperature data of a dangerous goods yard, humidity data and the like.
The method comprises the steps that a plurality of pressure detection points 42 are arranged on monitored chemical equipment, data obtained from different pressure detection points 42 on the same equipment are set into one group, pressure data of different equipment are recorded in a grouping mode, and the first group is Y1-1, Y1-2, Y1-3 and Y1-4 …; the second group is Y2-1, T2-2 and Y2-3 …, and the number of each group can be detected according to requirements; the data detected by the pressure detection points 42 are transmitted back to the main control center 1 through the data acquisition contact node 3, the main control center 1 compares the obtained pressure data with each data of the big data storage comparison center 2, when each pressure data is abnormal and exceeds an early warning value, the main control center 1 displays the abnormal pressure data on a display screen, displays the current data in real time, and sends out an alarm signal.
A plurality of air harmful gas content detection points 43 are arranged in a monitored equipment workshop, data detected by the air harmful gas content detection points 43 are transmitted back to the main control center 1 through the data acquisition contact node 3, the main control center 1 compares the air data of each harmful gas detection point with big data of the big data storage comparison center 2, and whether the current air harmful gas is within a normal value or not is analyzed through the big data center; when the data comparison is in an abnormal value, the current data is highlighted and an alarm prompt is sent out through the main control center 1 to remind people to intervene and process.
The equipment magnetic particle detection point 44 is arranged on equipment capable of carrying out magnetic particle inspection detection, data detected by the magnetic particle detection point 44 are transmitted back to the main control center 1 through the data acquisition contact node 3, the magnetic particle detection point 44 is mainly used for surface defects of ferromagnetic materials in chemical equipment, and when the detected data are abnormal with the big data storage comparison center 2, the current defects are displayed and alarm information is sent out through the main control center 1.
The method comprises the steps that a plurality of water source detection points 45 are arranged at a water source of monitored chemical equipment, the water source detection points 45 detect the pH value and the mineral content equivalence of the water source, data detected by the water source detection points 45 are transmitted back to a main control center 1 through a data acquisition contact node 3, the data are compared with data of the main control center 1 through a big data storage comparison center 2, an alarm signal is sent out when the detected data exceed an expected value, and manual intervention is required. The water source at the water source is generally used as cooling water, so various values of the water source directly influence the later cooling effect and the influence on the safety and the service life of the equipment.
The method comprises the steps that a plurality of drainage detection points 46 are arranged at the drainage position of monitored chemical equipment, the drainage detection points 46 detect multiple items of data of each drainage point respectively, the obtained data are transmitted back to a main control center 1 through a data acquisition contact node 3, the main control center 1 compares the transmitted data with the data of a big data storage comparison center 2, and when the data are abnormal, the main control center 1 sends out prompt and alarm information. The drainage is that all kinds of chemical industry equipment need cooling water, purified water etc., this part of water is easily polluted, and the pollution process has direct relation with whether equipment operation is safe, therefore monitor the drainage point be one of necessary and effectual safe means.
The big data storage comparison center 2 carries out longitudinal time period sectional recording on all acquired detection data of the temperature detection point 41, the pressure detection point 42, the air harmful gas content detection point 43, the equipment magnetic powder detection point 44, the water source detection point 45 and the drainage detection point 46, records the data according to the requirement every day, every six hours, every three hours, every hour and every half hour, counts the data and calculates the safety fluctuation range; and calculating and storing the data difference among a plurality of detection points of the same equipment, and carrying out statistical calculation on the data to calculate the safety range of the difference value.
The daily data of the chemical equipment through the big data system comprises the following steps: comprehensively detecting data such as temperature, pressure, air harmful gas content, equipment surface corrosion damage, water source, drainage and the like, and recording the data transversely and longitudinally to form a big data system according to data difference and a data fluctuation safety range; whether the chemical equipment is safe or not is obtained, so that the safety of the whole chemical equipment is obtained, the position of the potential safety hazard can be known at the initial stage of data fluctuation, and the potential safety hazard is timely eliminated to ensure the safe operation of the equipment.
After the technical scheme is adopted, the safety of equipment operation can be greatly improved, and the location where the hidden danger occurs can be known at the initial stage of data change, so that the treatment can be timely eliminated, the safety of chemical manufacturers can be further improved, major accidents can be avoided, and the potential safety hazard can be timely discovered and treated.
The above description is only for the purpose of illustrating the technical solutions of the present invention and not for the purpose of limiting the same, and other modifications or equivalent substitutions made by those skilled in the art to the technical solutions of the present invention should be covered within the scope of the claims of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims (10)
1. System and application through big data intelligent management monitoring chemical industry equipment safety, its characterized in that: the system comprises a main control center (1), a big data storage comparison center (2), a plurality of data acquisition contact nodes (3) and a plurality of data acquisition points (4); the big data input degree of main control center (1) is connected on big data storage comparison center (2), a plurality of data acquisition contact nodes (3) are all connected on main control center (1), every data acquisition contact node (3) all is connected with data acquisition point (4), data acquisition point (4) are including temperature detection point (41), pressure detection point (42), harmful gas content in air check point (43), equipment magnetic powder check point (44), water source check point (45), drainage check point (46), temperature detection point (41), pressure detection point (42), harmful gas content in air check point (43), equipment magnetic powder check point (44), water source check point (45), the signal output part of drainage check point (46) is connected respectively on each data acquisition contact node (3).
2. The system and the application for monitoring the safety of the chemical equipment through big data intelligent management according to claim 1 are characterized in that: the temperature detection point (41) is arranged on the monitored chemical equipment, is arranged at a position needing to be detected and can be arranged on the shell, the feed inlet and the discharge outlet; the pressure detection points (42) are arranged on the pressure containers and the reaction container; the air harmful gas content detection point (43) is arranged near the exhaust port of the equipment and at the position where the equipment is easy to leak.
3. The system and the application for monitoring the safety of the chemical equipment through big data intelligent management according to claim 1 are characterized in that: the equipment magnetic powder detection point (44) is arranged at the position with the magnetic powder safety point of the chemical equipment; the water yard detection point (4) is arranged on a water source point of the water inlet of the equipment; the drainage detection point (46) is arranged on the sewage outlet of the chemical equipment.
4. The system and the application for monitoring the safety of the chemical equipment through big data intelligent management according to claim 1 are characterized in that: the system for intelligently managing and monitoring the safety of the chemical equipment by using the big data is applied as follows: the method comprises the steps that a plurality of temperature detection points (41) are arranged on monitored chemical equipment, the temperature of each temperature detection point (41) is slightly different, data obtained by each temperature detection point (41) are t1, t2, t 3-tn, and data of t1, t2 and t 3-tn are divided into arrays according to detection of different equipment to be transmitted; the master control center (1) records all data, records the temperature data of the data in the same group into the big data storage comparison center (2), calculates the temperature difference of each temperature data acquisition point of the same equipment and records the temperature difference; when the temperature data of the same group are abnormal, the big data storage comparison center (2) sends the data back to the main control center (1), and the main control center (1) displays the abnormal temperature difference information and sends out a warning signal; meanwhile, the big data storage comparison center (2) performs key monitoring on key temperature data of the temperature detection points (41), wherein the key temperature data comprise temperature data inside and outside the pressure container, temperature data inside and outside the reaction furnace, temperature data of a dangerous goods yard, humidity data and the like.
5. The system and the application for monitoring the safety of the chemical equipment through big data intelligent management according to claim 1 are characterized in that: the method comprises the steps that a plurality of pressure detection points (42) are arranged on monitored chemical equipment, data obtained from different pressure detection points (42) on the same equipment are set into one group, pressure data of different equipment are recorded in a grouping mode, and the first group is Y1-1, Y1-2, Y1-3 and Y1-4 …; the second group is Y2-1, T2-2 and Y2-3 …, and the number of each group can be detected according to requirements; the data detected by the pressure detection points (42) are transmitted back to the main control center (1) through the data acquisition contact node (3), the main control center (1) compares the obtained pressure data with each data of the big data storage comparison center (2), and when each pressure data is abnormal and exceeds an early warning value, the main control center (1) displays the abnormal pressure data on the display screen, displays the current data in real time and sends out an alarm signal.
6. The system and the application for monitoring the safety of the chemical equipment through big data intelligent management according to claim 1 are characterized in that: a plurality of air harmful gas content detection points (43) are arranged in a monitored equipment workshop, data detected by the air harmful gas content detection points (43) are transmitted back to the main control center (1) through the data acquisition contact node (3), the main control center (1) compares the air data of each harmful gas detection point with big data of the big data storage comparison center (2), and whether the current air harmful gas is within a normal value or not is analyzed through the big data center; when the data comparison is in an abnormal value, the current data is highlighted and an alarm prompt is sent out through the main control center (1) to remind people to intervene and process.
7. The system and the application for monitoring the safety of the chemical equipment through big data intelligent management according to claim 1 are characterized in that: set up equipment magnetic particle detection point (44) on the equipment that can carry out magnetic particle inspection and detect, say that the data that magnetic particle detection point (44) detected pass through data acquisition contact node (3) and return master control center (1), magnetic particle detection point (44) mainly used ferromagnetic material's in the chemical industry equipment surface defect, then show current defect and send alarm information through master control center (1) when data that detect and big data storage compare center (2) are unusual.
8. The system and the application for monitoring the safety of the chemical equipment through big data intelligent management according to claim 1 are characterized in that: set up several water source check point (45) in the water source department of monitoring chemical industry equipment, water source check point (45) detect the pH value of water source, mineral content equivalence, the data that water source check point (45) detected pass through data acquisition contact node (3) and pass back data to master control center (1), compare through the data of big data storage compare center (2) with master control center (1), send alarm signal when the data that detect surpass the expected value to require the manual work to intervene.
9. The system and the application for monitoring the safety of the chemical equipment through big data intelligent management according to claim 1 are characterized in that: the method comprises the steps that a plurality of drainage detection points (46) are arranged at the drainage position of monitored chemical equipment, the drainage detection points (46) detect a plurality of data of each drainage point respectively, the obtained data are transmitted back to a main control center (1) through a data acquisition contact node (3), the main control center (1) compares the transmitted data with the data of a big data storage comparison center (2), and when the data are abnormal, the main control center (1) sends out prompt and alarm information.
10. The system and the application for monitoring the safety of the chemical equipment through big data intelligent management according to claim 1 are characterized in that: the big data storage comparison center (2) carries out longitudinal time period segmented recording on all acquired detection data of a temperature detection point (41), a pressure detection point (42), an air harmful gas content detection point (43), an equipment magnetic powder detection point (44), a water source detection point (45) and a drainage detection point (46), records the data according to the requirements every day, every six hours, every three hours, every hour and every half hour, counts the data and calculates the safety fluctuation range; and calculating and storing the data difference among a plurality of detection points of the same equipment, and carrying out statistical calculation on the data to calculate the safety range of the difference value.
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| CN104019935A (en) * | 2014-06-17 | 2014-09-03 | 天津市天泽化工有限公司 | Automatic wireless pressure measurement warning system for chemical equipment |
| CN209085657U (en) * | 2017-08-02 | 2019-07-09 | 强力物联网投资组合2016有限公司 | For data gathering system related or industrial environment with chemical production technology |
| CN107908160A (en) * | 2017-11-14 | 2018-04-13 | 合肥奇骏自动化控制有限公司 | A kind of chemical plant laboratory safety wireless supervisory control system |
| CN108628273A (en) * | 2018-06-29 | 2018-10-09 | 中安高新（北京）智能化科技有限公司 | A kind of acquisition system of chemical industry equipment isomeric data |
| CN108664008A (en) * | 2018-07-18 | 2018-10-16 | 武汉理工大学 | A kind of Fibre Optical Sensor Internet of things system for petrochemical iy produced novel intelligent |
| CN210007722U (en) * | 2019-07-03 | 2020-01-31 | 皖西学院 | Chemical plant visual safety monitoring system based on Internet of things |
| CN110726494A (en) * | 2019-11-27 | 2020-01-24 | 成都比善科技开发有限公司 | High-voltage switch cabinet temperature monitoring system and monitoring method |
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