CN114090681A - VOCs processing apparatus on-line monitoring system and method - Google Patents
VOCs processing apparatus on-line monitoring system and method Download PDFInfo
- Publication number
- CN114090681A CN114090681A CN202111419132.4A CN202111419132A CN114090681A CN 114090681 A CN114090681 A CN 114090681A CN 202111419132 A CN202111419132 A CN 202111419132A CN 114090681 A CN114090681 A CN 114090681A
- Authority
- CN
- China
- Prior art keywords
- data
- analysis
- database
- model
- vocs
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012545 processing Methods 0.000 title claims abstract description 203
- 239000012855 volatile organic compound Substances 0.000 title claims abstract description 167
- 238000012544 monitoring process Methods 0.000 title claims abstract description 104
- 238000000034 method Methods 0.000 title claims abstract description 34
- 238000004458 analytical method Methods 0.000 claims abstract description 132
- 238000007405 data analysis Methods 0.000 claims abstract description 75
- 238000013500 data storage Methods 0.000 claims abstract description 63
- 238000007781 pre-processing Methods 0.000 claims abstract description 23
- 239000003344 environmental pollutant Substances 0.000 claims abstract description 14
- 231100000719 pollutant Toxicity 0.000 claims abstract description 14
- 238000010801 machine learning Methods 0.000 claims abstract description 12
- 238000007726 management method Methods 0.000 claims abstract description 10
- 230000000007 visual effect Effects 0.000 claims abstract description 6
- 238000013499 data model Methods 0.000 claims description 88
- 238000012360 testing method Methods 0.000 claims description 52
- 230000003068 static effect Effects 0.000 claims description 46
- 230000000694 effects Effects 0.000 claims description 24
- 238000004140 cleaning Methods 0.000 claims description 13
- 230000008859 change Effects 0.000 claims description 12
- 238000003860 storage Methods 0.000 claims description 12
- 230000002159 abnormal effect Effects 0.000 claims description 10
- 238000009825 accumulation Methods 0.000 claims description 10
- 238000010223 real-time analysis Methods 0.000 claims description 10
- 238000004519 manufacturing process Methods 0.000 claims description 9
- 238000004891 communication Methods 0.000 claims description 8
- 230000008569 process Effects 0.000 claims description 7
- 238000012549 training Methods 0.000 claims description 5
- 238000012423 maintenance Methods 0.000 abstract description 6
- 230000006870 function Effects 0.000 abstract description 5
- 239000002912 waste gas Substances 0.000 abstract description 3
- 239000007789 gas Substances 0.000 description 14
- 238000012805 post-processing Methods 0.000 description 5
- 230000008054 signal transmission Effects 0.000 description 3
- 230000005540 biological transmission Effects 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000007246 mechanism Effects 0.000 description 2
- 238000012800 visualization Methods 0.000 description 2
- 238000001816 cooling Methods 0.000 description 1
- 238000003795 desorption Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 239000013618 particulate matter Substances 0.000 description 1
- 230000000737 periodic effect Effects 0.000 description 1
- 231100000572 poisoning Toxicity 0.000 description 1
- 230000000607 poisoning effect Effects 0.000 description 1
- 230000008707 rearrangement Effects 0.000 description 1
- 238000001179 sorption measurement Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001960 triggered effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/26—Visual data mining; Browsing structured data
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D53/00—Separation of gases or vapours; Recovering vapours of volatile solvents from gases; Chemical or biological purification of waste gases, e.g. engine exhaust gases, smoke, fumes, flue gases, aerosols
- B01D53/30—Controlling by gas-analysis apparatus
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/0004—Gaseous mixtures, e.g. polluted air
- G01N33/0009—General constructional details of gas analysers, e.g. portable test equipment
- G01N33/0062—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method or the display, e.g. intermittent measurement or digital display
- G01N33/0068—General constructional details of gas analysers, e.g. portable test equipment concerning the measuring method or the display, e.g. intermittent measurement or digital display using a computer specifically programmed
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N20/00—Machine learning
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01D—SEPARATION
- B01D2257/00—Components to be removed
- B01D2257/70—Organic compounds not provided for in groups B01D2257/00 - B01D2257/602
- B01D2257/708—Volatile organic compounds V.O.C.'s
Landscapes
- Engineering & Computer Science (AREA)
- Chemical & Material Sciences (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Data Mining & Analysis (AREA)
- General Physics & Mathematics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Analytical Chemistry (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Software Systems (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Databases & Information Systems (AREA)
- Evolutionary Computation (AREA)
- General Chemical & Material Sciences (AREA)
- Evolutionary Biology (AREA)
- Mathematical Physics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Medical Informatics (AREA)
- Oil, Petroleum & Natural Gas (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Combustion & Propulsion (AREA)
- Computing Systems (AREA)
- Food Science & Technology (AREA)
- Medicinal Chemistry (AREA)
- Biochemistry (AREA)
- General Health & Medical Sciences (AREA)
- Immunology (AREA)
- Pathology (AREA)
- Debugging And Monitoring (AREA)
Abstract
The invention discloses an online monitoring system and a method of a VOCs processing device, wherein the online monitoring system comprises a signal acquisition and processing unit, a data storage and analysis unit and a monitoring application unit, the signal acquisition and processing unit can simultaneously acquire real-time operation working condition data of various VOCs processing devices in an operation working state, carry out primary preprocessing on the operation working condition data to generate a data packet to be stored and analyzed, and transmit the data packet to the data storage and analysis unit, wherein the state monitoring data of processing device equipment is processed, classified and analyzed by using a machine learning algorithm, and an analysis result is uploaded to the monitoring application unit; the functions of dynamic alarm, visual monitoring board, equipment management, waste gas treatment state analysis and the like are realized by utilizing a computer network service architecture and service, the downtime of the equipment is reduced, the maintenance cost of the equipment is reduced, and the loss of increased pollutant discharge caused by equipment damage is also reduced.
Description
Technical Field
The embodiment of the invention relates to the technical field of environmental protection monitoring, in particular to an online monitoring system and method of a VOCs (volatile organic Compounds) processing device.
Background
VOCs is used as a harmful gas, and high-concentration VOCs gas in industrial work can cause poisoning, so that the physical health, the working efficiency and the working environment of workers are seriously influenced. At the present stage, a plurality of post-treatment devices aiming at VOCs harmful gases are arranged on the market, and a plurality of industrial places are already put into use and achieve good treatment effect.
However, in the using process, the post-processing device can not avoid the condition of failure in the operation process, once the failure occurs, the worker can not be exposed to harmful gases of VOCs again by timely processing, the longer the downtime is, and the more serious the result is. Meanwhile, most post-processing devices cannot store the monitored VOCs gas data for a long time, no method is available for data accumulation, effects before and after processing cannot be compared and analyzed in detail, and the working state of post-processing equipment cannot be evaluated correctly. In addition, the periodic maintenance and management of the single device increases the operation and maintenance cost of the post-processing device used by the user.
Disclosure of Invention
The embodiment of the invention provides an online monitoring system and method of VOCs (volatile organic compounds) processing devices, which are used for monitoring the states of a plurality of VOCs processing devices in real time, predicting the trend of processing effect, reducing the downtime, reducing the maintenance cost and reducing the loss of increased pollutant discharge caused by equipment damage.
In a first aspect, an embodiment of the present invention provides an online monitoring system for a VOCs processing apparatus, including:
the signal acquisition and processing unit is connected with the plurality of VOCs processing devices and is used for acquiring operation condition data of the VOCs processing devices in real time and carrying out primary pretreatment on the operation condition data to generate an analysis data packet to be stored;
the data storage and analysis unit is in communication connection with the signal acquisition and processing unit and is used for carrying out secondary preprocessing on the data in the data packet to be stored and analyzed and classifying and storing the data subjected to the secondary preprocessing so as to establish a database; wherein the database comprises test data, sample data, real-time data and static data; the real-time data is operation condition data changing along with time; the static data comprises serial numbers and production information data of the VOCs processing device; the sample data and the test data are data to be analyzed in the real-time data; the data storage analysis unit is also used for establishing an algorithm analysis model according to the test data and the sample data in the database so as to perform data real-time analysis on the state of the VOCs processing device and storing a data analysis result in the database;
the monitoring application unit is used for calling data in the database, carrying out online monitoring on the operation conditions of the plurality of VOCs processing devices according to the data in the database, establishing an alarm model according to the data in the database, judging a fault alarm point, and establishing a performance analysis model according to the data in the database so as to predict and analyze the processing performance of the VOCs processing devices.
Optionally, the online monitoring system of the VOCs processing apparatus further includes a display unit, and the display unit is configured to visually display the online monitoring result, the analysis prediction result, and the abnormal state alarm information of the monitoring application unit.
Optionally, the signal acquiring and processing unit includes:
the signal acquisition subunit is used for acquiring the operating condition data of the VOCs processing devices through a data acquisition signal line;
the signal processing subunit is used for compiling and decoding the operating condition data, cleaning and classifying the data and forming a to-be-stored analysis data packet by the processed data;
and the signal gateway subunit is used for sending the to-be-stored analysis data packet to the data storage analysis unit.
Optionally, the data storage analysis unit includes:
the data storage subunit is used for receiving the analysis data packet to be stored and storing original data in the analysis data packet to be stored;
the data processing subunit is used for cleaning and classifying the original data in the to-be-stored analysis data packet through a machine learning algorithm, and returning the processed data to the data storage subunit for data updating and storage; the classified data comprises sample data, test data, real-time data and static data; the data storage subunit is also used for classifying and storing the updated data and constructing a data model, and the data model is used for establishing a relational database and a non-relational database; the data model comprises a test data model, a sample data model, a real-time data model and a static data model;
the data analysis subunit is used for establishing an algorithm analysis model according to the sample data in the sample data model and training the algorithm analysis model through the test data in the test data model; the data analysis subunit is further configured to process, through the algorithm analysis model, data to be analyzed in the real-time data model to obtain a data analysis result; the data storage subunit is also used for storing the data analysis result.
Optionally, the monitoring application unit includes:
the visual monitoring subunit is used for calling real-time data and static data in a database, determining the type and the change trend of the real-time data, determining the number of the VOCs processing device according to the static data, and dynamically and visually displaying the operation condition corresponding to the VOCs processing device in the display unit according to at least one of a histogram, a bar graph and a pie graph; displaying, classifying and comparing the effect states of different VOCs processing devices before and after VOCs processing in the display unit;
the alarm subunit is used for calling a plurality of historical fault alarm point data in a preset time period in the database and establishing an alarm model according to the fault alarm point data in the preset time period; the display unit is used for displaying the alarm information of the abnormal state when the current real-time data is the fault alarm point; the alarm models correspond to the monitoring working conditions one by one;
and the performance analysis subunit is used for calling a plurality of historical data analysis results in a preset time period in the database, establishing a performance analysis model based on data accumulation and change trend, and predicting and analyzing the pollutant treatment effect and/or service life of the VOCs treatment device according to the performance analysis model.
Optionally, the monitoring application unit further includes:
the distributed equipment management subunit is used for displaying the basic device information and the monitoring and analyzing results of each VOCs processing device in a distributed manner through the display unit; the device basic information includes at least one of a number, a type, a manufacturer production date, and a lifetime in static data corresponding to the VOCs processing device.
Optionally, the display unit includes a PC-side display screen and/or a mobile-side display screen.
In a second aspect, an embodiment of the present invention provides an online monitoring method for a VOCs processing apparatus, including:
the method comprises the steps that a signal acquisition processing unit acquires operation condition data of a VOCs processing device in real time, and performs primary preprocessing on the operation condition data to generate an analysis data packet to be stored; the signal acquisition processing unit is connected with the plurality of VOCs processing devices;
the data storage and analysis unit carries out secondary pretreatment on the data in the data packet to be stored and analyzed and stores the data subjected to the secondary pretreatment in a classified manner so as to establish a database; wherein the database comprises test data, sample data, real-time data and static data; the data storage and analysis unit is in communication connection with the signal acquisition and processing unit;
the data storage analysis unit establishes an algorithm analysis model according to the test data and the sample data in the database so as to carry out data real-time analysis on the state of the VOCs processing device and store the data analysis result in the database;
the monitoring application unit calls data in the database, carries out online monitoring on the operating conditions of the plurality of VOCs processing devices according to the data in the database, establishes an alarm model according to the data in the database, judges a fault alarm point, and establishes a performance analysis model according to the data in the database so as to predict and analyze the processing performance of the VOCs processing devices.
Optionally, the data storage and analysis unit performs second preprocessing on the data in the to-be-stored and analyzed data packet, and stores the data subjected to the second preprocessing in a classified manner to establish a database, including:
receiving the analysis data packet to be stored, and storing original data in the analysis data packet to be stored;
cleaning and classifying the original data in the data packet to be stored and analyzed through a machine learning algorithm, and returning the processed data to a data storage subunit for data updating and storage; the classified data comprises sample data, test data, real-time data and static data;
storing the updated data in a classified manner and constructing a data model, wherein the data model is used for establishing a relational database and a non-relational database; the data model comprises a test data model, a sample data model, a real-time data model and a static data model;
optionally, the data storage and analysis unit establishes an algorithm analysis model according to the test data and the sample data in the database to perform data real-time analysis on the state of the VOCs processing apparatus and store the data analysis result in the database, and the method includes:
establishing an algorithm analysis model according to the sample data in the sample data model;
training the algorithm analysis model through the test data in the test data model;
and processing the data to be analyzed in the real-time data model through the algorithm analysis model to obtain a data analysis result, and storing the data analysis result in the database.
Optionally, the monitoring application unit calls data in the database, and performs online monitoring on the operating conditions of the plurality of VOCs processing apparatuses according to the data in the database, including:
calling real-time data and static data in a database;
determining the type and the variation trend of the real-time data, determining the number of the VOCs processing device according to the static data, and dynamically and visually displaying the operation condition corresponding to the VOCs processing device in the display unit by using at least one of a histogram, a bar graph and a pie graph;
displaying, classifying and comparing effect states before and after VOCs treatment by different VOCs treatment devices on the display unit;
optionally, the invoking, by the monitoring application unit, data in the database, and establishing an alarm model and determining a fault alarm point according to the data in the database includes:
judging whether the current real-time data is a fault alarm point or not according to the alarm model, and displaying abnormal state alarm information through the display unit when the current real-time data is the fault alarm point;
the alarm model is determined based on a plurality of historical fault alarm point data in a preset time period in a database, and the alarm model corresponds to monitoring working conditions one to one;
optionally, the invoking, by the monitoring application unit, data in the database, and establishing a performance analysis model according to the data in the database to predict and analyze the processing performance of the VOCs processing apparatus, includes:
calling a plurality of historical data analysis results in a preset time period in the database;
establishing a performance analysis model based on data accumulation and variation trend;
and predicting and analyzing the pollutant treatment effect and/or the service life of the VOCs treatment device according to the performance analysis model.
The embodiment of the invention provides an online monitoring system and method of a VOCs (volatile organic compounds) processing device, wherein the online monitoring system comprises a signal acquisition and processing unit, a data storage and analysis unit and a monitoring application unit, the signal acquisition and processing unit can simultaneously acquire real-time operating condition data of various VOCs processing devices in an operating state, carry out primary preprocessing on the operating condition data to generate a data packet to be stored and analyzed, and transmit the data packet to the data storage and analysis unit, the state monitoring data of processing device equipment is processed, classified and analyzed by using a machine learning algorithm, and the analysis result is uploaded to the monitoring application unit, so that functions of dynamic alarm, visual monitoring board, equipment management and waste gas processing state analysis are realized by using a computer network service architecture and service, a uniform integrated system is formed, and comprehensive, comprehensive and comprehensive effects of VOCs operating state are achieved, Real-time and on-line monitoring. The state of a plurality of VOCs processing apparatus of real-time supervision, prediction treatment effect trend have been realized, reduce down time, reduce cost of maintenance, reduce the loss of the pollutant emission increase that causes because of equipment damages.
Drawings
Fig. 1 is a block diagram of an online monitoring system of a VOCs processing apparatus according to an embodiment of the present invention;
fig. 2 is a flowchart of an on-line monitoring method for a VOCs processing apparatus according to an embodiment of the present invention;
fig. 3 is a flow chart of another method for online monitoring of a VOCs processing apparatus according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
An embodiment of the present invention provides an online monitoring system for a VOCs processing apparatus, and fig. 1 is a block diagram of the online monitoring system for a VOCs processing apparatus provided in an embodiment of the present invention, and referring to fig. 1, the online monitoring system for a VOCs processing apparatus includes:
the signal acquisition and processing unit 10 is connected with the plurality of VOCs processing devices 1, and the signal acquisition and processing unit 10 is used for acquiring the operation condition data of the VOCs processing devices 1 in real time and carrying out primary preprocessing on the operation condition data to generate an analysis data packet to be stored;
the data storage and analysis unit 20 is in communication connection with the signal acquisition and processing unit 10, and the data storage and analysis unit 20 is used for performing second preprocessing on data in an analysis data packet to be stored and storing the data subjected to the second preprocessing in a classified manner to establish a database; the database comprises test data, sample data, real-time data and static data; the real-time data is operation condition data changing along with time; the static data includes the numbers and production information data of the VOCs processing apparatus 1; the sample data and the test data are data to be analyzed in the real-time data; the data storage analysis unit 20 is further configured to establish an algorithm analysis model according to the test data and the sample data in the database to perform data real-time analysis on the state of the VOCs processing apparatus 1, and store the data analysis result in the database;
and the monitoring application unit 30 is used for calling data in the database, performing online monitoring on the operation conditions of the plurality of VOCs processing devices 1 according to the data in the database, establishing an alarm model according to the data in the database, judging a fault alarm point, and establishing a performance analysis model according to the data in the database so as to predict and analyze the processing performance of the VOCs processing devices 1.
Specifically, a plurality of VOCs processing devices 1 are connected, a data signal source (a current signal or a voltage signal corresponding to operation condition data) of each VOCs processing device 1 in an operation state is connected to a signal acquisition processing unit 10 in the system through a data acquisition signal line, and the signal acquisition processing unit 10 is used for preprocessing the operation condition data for the first time to generate an analysis data packet to be stored. The first preprocessing may include compiling and decoding a data signal source corresponding to the operating condition data. Compiling and decoding may be understood as generating corresponding operating condition data from the collected current and/or voltage signals. The first preprocessing may also include cleaning and sorting of the operating condition data. The operation condition data includes, for example, the temperature and concentration of a harmful gas in the VOCs, the switching value of the VOCs processing apparatus 1, the alarm point data of the VOCs processing apparatus 1, and the like. The signal acquisition and processing unit 10 is further configured to form a to-be-stored analysis data packet from the preprocessed data. The signal acquisition processing unit 10 may transmit data by using a 4G network, a TCP/HTTP, and the like, and transmit the acquired data to the data storage analysis unit 20 by using an architecture of the internet of things.
The data storage analysis unit 20 is used for collectively managing data of the plurality of VOCs processing apparatuses 1. The data storage analysis unit 20 may classify and store the data by using the data storage hard disk to construct the data model. The data storage and analysis unit 20 preprocesses, cleans, and classifies a large amount of raw data, and classifies the data into several categories, such as test data, sample data, real-time data, and static data. The real-time data is operation condition data which changes along with time, such as the temperature and concentration of all harmful gases in all the VOCs devices, the switching value of the VOCs processing device 1, the alarm point data of the VOCs processing device 1 and the like. The static data includes the numbers of the VOCs processing apparatuses 1 and production information data, which do not change with time. The sample data and the test data include data to be analyzed in the real-time data. It will be understood that the sample data and test data include data to be analyzed, such as temperature, concentration, etc. of a certain harmful gas, which are copied from the real-time data, and the number, type, etc. of the VOCs processing apparatus 1, which are copied from the static data. The data storage and analysis unit 20 has data edge processing at the same time, enhances the performance of data processing and storage through a machine learning algorithm, and returns the processing result to the data model for storage and updating. And (3) analyzing the optimized modes and states of the VOCs processing device 1 aiming at different pollutants to perform real-time data analysis by taking a data analysis terminal as a hardware basis. An algorithm analysis model can be established according to test data and sample data in a database by using a python language so as to perform data real-time analysis on the state of the VOCs processing device 1, and then, a data analysis result is returned to the data model.
The monitoring application unit 30 calls and utilizes the monitoring data and the data analysis result based on the data of the data storage and analysis unit 20 to perform online monitoring on the VOCs post-processing device 1. The method comprises the steps of carrying out online monitoring on the operation conditions of a plurality of VOCs processing devices 1 according to data in a database; establishing an alarm model according to data in a database and judging a fault alarm point; and establishing a performance analysis model according to the data in the database so as to predict and analyze the processing performance of the VOCs processing device 1.
The online monitoring system of the VOCs processing device provided by the embodiment of the invention comprises a signal acquisition and processing unit, a data storage and analysis unit and a monitoring application unit, wherein the signal acquisition and processing unit can simultaneously acquire real-time operating condition data of various VOCs processing devices in an operating state, and the operation condition data is preprocessed for the first time to generate a data packet to be stored and analyzed, and then the data packet is transmitted to the data storage and analysis unit, the machine learning algorithm is used for processing, classifying and analyzing the state monitoring data of the processing device equipment, meanwhile, analysis results are uploaded to a monitoring application unit, functions of dynamic alarming, visual monitoring boards, equipment management and waste gas treatment state analysis are achieved by means of computer network service architecture and services, a unified integrated system is formed, and the effect of comprehensive, real-time and online monitoring of the running state of the VOCs is achieved. The state of a plurality of VOCs processing apparatus of real-time supervision, prediction treatment effect trend have been realized, reduce down time, reduce cost of maintenance, reduce the loss of the pollutant emission increase that causes because of equipment damages.
Optionally, referring to fig. 1, the online monitoring system of the VOCs processing apparatus 1 further includes a display unit 40, where the display unit 40 is configured to visually display the online monitoring result, the analysis prediction result, and the abnormal state alarm information of the monitoring application unit 30.
Specifically, the monitoring, alarming, analyzing, managing and other functions established by the monitoring application unit 30 are applied online, and can be adapted to PC terminal display and mobile terminal display. The user can monitor the running states of the VOCs equipment in real time on line through a computer, a mobile phone and a mobile platform to obtain an abnormal state alarm and analysis result.
Optionally, the signal acquiring and processing unit 10 includes: the signal acquisition subunit 11 is used for acquiring the operation condition data of the plurality of VOCs processing devices 1 through a data acquisition signal line; the signal processing subunit 12, the signal processing subunit 12 is used for compiling and decoding the operation condition data, cleaning and classifying the data, and forming the processed data into a data packet to be stored and analyzed; and the signal gateway subunit 13, the signal gateway subunit 13 is configured to send the analysis data packet to be stored to the data storage and analysis unit 20. And compiling and processing the signal channel according to different equipment signal sources by the data acquisition subunit, and completing the data transmission channel. And transmitting the acquired original data through a signal transmission gateway and communication. The signal acquisition and processing unit 10 may be a local control center.
Optionally, the data storage analysis unit 20 includes:
the data storage subunit 21, where the data storage subunit 21 is configured to receive the analysis data packet to be stored, and store the original data in the analysis data packet to be stored;
the data processing subunit 22, the data processing subunit 22 is configured to perform cleaning and classification processing on the original data in the to-be-stored analysis data packet through a machine learning algorithm, and return the processed data to the data storage subunit 21 for data updating and storage; the classified data comprises sample data, test data, real-time data and static data; the data storage subunit 21 is further configured to perform classified storage on the updated data and construct a data model, where the data model is used to establish a relational database and a non-relational database; the data model comprises a test data model, a sample data model, a real-time data model and a static data model;
the data analysis subunit 23 is configured to establish an algorithm analysis model according to sample data in the sample data model, and train the algorithm analysis model through test data in the test data model; the data analysis subunit 23 is further configured to process, through the algorithmic analysis model, data to be analyzed in the real-time data model to obtain a data analysis result; the data storage subunit 21 is also used for storing the data analysis result.
Specifically, the data storage subunit 21 is configured to receive an analysis data packet to be stored, and store original data in the analysis data packet to be stored. If missing and incomplete dirty data occur in the original data, the data processing subunit 22 performs cleaning and preprocessing on the data by using a machine learning algorithm, and the data storage subunit 21 reclassifies and establishes a data model. If the acquired original data is complete, the data storage subunit 21 directly stores the data and establishes a data model at the same time. The data models are divided into a real-time data model, a test data model, a sample data model and a static data model. When the data storage subunit 21 is used for classified storage, a relational database and a non-relational database are established by using a Hadoop big data distributed storage architecture, and data is classified and stored. The relational database includes static data, and the non-relational database includes real-time data. Static data in the relational database is associated with real-time data in the non-relational database. The real-time data is operating condition data which changes along with time and is acquired by a VOCs processing device which is acquired by a signal acquisition subunit. The static data includes the numbers of the VOCs processing apparatus 1 and production information data, which do not change with time, and can be obtained by acquiring the VOCs processing apparatus through the signal acquisition subunit, or can be obtained by a direct input mode of a user.
The data in the real-time data model and the static data model can be directly applied and displayed in real time without analysis, and the result is output. And the data in the sample data model and the data in the test data are analyzed and then applied and displayed in real time. The data analysis subunit 23 is configured to establish an algorithm analysis model according to sample data in the sample data model, and train the algorithm analysis model through test data in the test data model; the data analysis subunit 23 is further configured to process data to be analyzed in the real-time data through the algorithmic analysis model to obtain a data analysis result. The data storage subunit 21 is also used to store data analysis results. The data analysis result is calculated from the real-time data, and therefore, the data analysis result can be stored in a non-relational database. For example, the data analysis result may be calculated as a treatment rate of a harmful gas in the VOCs at a time point by a VOCs treatment apparatus 1. The treatment rate may be understood as a ratio of the amount of the harmful gas treated to the total amount of the harmful gas before treatment. The data analysis result may also be the current remaining service life of the VOCs processing apparatus 1.
Optionally, the monitoring application unit 30 includes:
the visual monitoring subunit 31 is configured to call real-time data and static data in the database, determine the type and the change trend of the real-time data, determine the number of the VOCs processing apparatus 1 according to the static data, and dynamically and visually display the operating condition corresponding to the VOCs processing apparatus 1 in the display unit 40 according to at least one of a histogram, a bar graph, and a pie graph; and displaying, classifying and comparing the effect states before and after the VOCs are processed by different VOCs processing devices 1 on the display unit 40;
the alarm subunit 32 is configured to call a plurality of historical fault alarm point data in a preset time period in the database, and establish an alarm model according to the fault alarm point data in the preset time period; and is used for judging whether the current real-time data is a fault alarm point according to the alarm model, and displaying abnormal state alarm information through the display unit 40 when the current real-time data is the fault alarm point; the alarm models correspond to the monitoring working conditions one by one;
and the performance analysis subunit 33 is configured to call a plurality of historical data analysis results in the database within a preset time period, establish a performance analysis model based on data accumulation and a change trend, and predict and analyze the pollutant treatment effect and/or the service life of the VOCs treatment apparatus 1 according to the performance analysis model.
Specifically, the monitoring application unit 30 calls and utilizes the monitoring data and the data analysis result based on the data of the data management center to perform online monitoring on the VOCs processing apparatus 1, and displays different data monitoring functions in a system billboard in a modularized manner. The visualization monitoring subunit 31 performs dynamic visualization display on the data in a manner of graphical display such as a bar chart, a pie chart and the like by using the change trend and the type of the data. Can demonstrate the classification with the operation operating mode data of a VOCs processing apparatus 1 according to the effect state before and after handling, like pollutant discharge state, particulate matter discharge state etc.. It is also possible to display only the current operating condition data, or the past operating condition data, or the operating condition data for a period of time. The effect states before and after the VOCs are processed by different VOCs processing devices 1 can be displayed, classified and compared on the display unit 40.
The alarm subunit 32 constructs a real-time alarm model, and determines a fault alarm point by using a real-time data change mode to establish an alarm mechanism. The alarm can be pre-alarm, for example, the alarm point of the temperature of a harmful gas in the VOCs processed by the VOCs processing device 1 is 50 ℃, and when the temperature of the harmful gas is monitored to be 45 ℃, the pre-alarm is triggered to remind the working personnel to take precautions against the treatment in advance. The alarm point or the pre-alarm point can also be set in a mode of direct input by a user. The alarm subunit 32 may also prompt some switching values processed by the VOCs processing apparatus 1, such as: a desorption fan operation switch, an adsorption fan operation switch, a cooling fan operation switch, an emergency stop and the like. Besides the character alarm can be carried out through the display screen, the alarm modes such as sound-light alarm and the like can also be adopted. The alarm points and pre-alarm points determined by the alarm subunit 32, or the input alarm points and pre-alarm points, may all be stored in a database.
The performance analysis subunit 33 predicts and analyzes the operating state of the VOCs processing apparatus 1 by using the long-term data accumulation and the change trend, establishes a state analysis model, and displays the pollutant treatment effect of the VOCs processing apparatus 1 through the display unit 40. The performance analysis subunit 33 is configured to invoke a plurality of historical data analysis results in a database within a preset time period, for example, the data analysis subunit calculates a processing rate of the VOCs processing apparatus 1 to a plurality of time points of a harmful gas in the VOCs, establishes a performance analysis model based on the data accumulation and the variation trend, and predicts and analyzes the pollutant processing effect of the VOCs processing apparatus 1 according to the performance analysis model. The method can also be used for calling the residual service lives of a plurality of time points of the VOCs processing device 1 calculated by the data analysis subunit, establishing a performance analysis model based on the data accumulation and the change trend, and predicting and analyzing the service life of the VOCs processing device 1 according to the performance analysis model. The prediction and analysis results can be returned to the database and stored in the database.
Optionally, the monitoring application unit 30 further includes:
a distributed equipment management subunit 34, where the distributed equipment management subunit 34 is configured to distributively display the device basic information and the monitoring analysis result of each VOCs processing device 1 through a display unit 40; the device basic information includes at least one of the number, type, manufacturer production date, and service life in the static data corresponding to the VOCs processing device 1.
Specifically, the distributed device management subunit 34 manages the individual devices according to the different VOCs processing apparatuses 1. The corresponding operation state data is associated with the VOCs processing device 1 through an independent primary key id to carry out distributed equipment management, and basic information of each equipment, such as the number, the type, the production date of a manufacturer and the service life, can be displayed; the analysis result of the functional module can also be displayed on the display screen.
An embodiment of the present invention further provides an online monitoring method for a VOCs processing apparatus, which is executed by an online monitoring system for a VOCs processing apparatus according to any of the above embodiments, where fig. 2 is a flowchart of an online monitoring method for a VOCs processing apparatus according to an embodiment of the present invention, and referring to fig. 2, the online monitoring method for a VOCs processing apparatus includes:
s110, a signal acquisition processing unit acquires operation condition data of the VOCs processing device in real time, and performs primary preprocessing on the operation condition data to generate an analysis data packet to be stored; the signal acquisition processing unit is connected with a plurality of VOCs processing apparatus.
S120, the data storage and analysis unit carries out secondary pretreatment on data in the data packet to be stored and analyzed, and the data after the secondary pretreatment is classified and stored to establish a database; the database comprises test data, sample data, real-time data and static data; the data storage and analysis unit is in communication connection with the signal acquisition and processing unit.
S130, the data storage analysis unit establishes an algorithm analysis model according to the test data and the sample data in the database so as to perform data real-time analysis on the state of the VOCs processing device and store the data analysis result in the database.
S140, the monitoring application unit calls the data in the database, online monitors the operating conditions of the VOCs processing devices according to the data in the database, establishes an alarm model according to the data in the database, judges a fault alarm point, and establishes a performance analysis model according to the data in the database so as to predict and analyze the processing performance of the VOCs processing devices.
Optionally, the data storage and analysis unit performs second preprocessing on the data in the data packet to be stored and analyzed, and performs classified storage on the data after the second preprocessing to establish the database, including:
receiving an analysis data packet to be stored, and storing original data in the analysis data packet to be stored;
cleaning and classifying original data in a to-be-stored analysis data packet through a machine learning algorithm, and returning the processed data to a data storage subunit for data updating and storage; the classified data comprises sample data, test data, real-time data and static data;
storing the updated data in a classified manner and constructing a data model, wherein the data model is used for establishing a relational database and a non-relational database; the data model comprises a test data model, a sample data model, a real-time data model and a static data model.
Optionally, the data storage and analysis unit establishes an algorithm analysis model according to the test data and the sample data in the database to perform data real-time analysis on the state of the VOCs processing apparatus and store the data analysis result in the database, and the method includes:
establishing an algorithm analysis model according to sample data in the sample data model;
training the algorithm analysis model through test data in the test data model;
and processing the data to be analyzed in the real-time data model through the algorithm analysis model to obtain a data analysis result, and storing the data analysis result in the database.
Optionally, the monitoring application unit calls data in the database, and performs online monitoring on the operating conditions of the plurality of VOCs processing apparatuses according to the data in the database, including:
calling real-time data and static data in a database;
determining the type and the variation trend of real-time data, determining the number of the VOCs processing device according to static data, and dynamically and visually displaying the operation condition corresponding to the VOCs processing device in the display unit by using at least one of a histogram, a bar graph and a pie graph;
and displaying, classifying and comparing the effect states of different VOCs processing devices before and after VOCs processing by the display unit.
Optionally, the monitoring application unit calls data in the database, establishes an alarm model according to the data in the database, and determines a fault alarm point, including:
judging whether the current real-time data is a fault alarm point or not according to the alarm model, and displaying abnormal state alarm information through a display unit when the current real-time data is the fault alarm point;
the alarm model is determined based on a plurality of historical fault alarm point data in a preset time period in the database, and the alarm model corresponds to the monitoring working conditions one to one.
Optionally, the monitoring application unit calls data in the database, and establishes a performance analysis model according to the data in the database to predict and analyze the processing performance of the VOCs processing apparatus, including:
calling a plurality of historical data analysis results in a preset time period in a database;
establishing a performance analysis model based on data accumulation and variation trend;
and predicting and analyzing the pollutant treatment effect and/or the service life of the VOCs treatment device according to the performance analysis model.
Fig. 3 is a flowchart of another online monitoring method for a VOCs processing apparatus according to an embodiment of the present invention, which is executed by the online monitoring system for a VOCs processing apparatus according to any of the embodiments described above, and with reference to fig. 3, the method includes:
and S210, collecting operating condition data of the VOCs processing device.
And S220, analyzing, cleaning and classifying the operation condition data.
And S230, uploading the acquired operation condition data through the signal transmission gateway.
And S240, storing the original data of the operation condition data.
S250, judging whether missing or incomplete data exists or not; if yes, go to step S260; if not, go to step S270.
And S260, cleaning and preprocessing the data.
S270, classifying the stored data and constructing a data model.
S280, judging whether the data need to be analyzed; if necessary, step S290 is executed, and if not necessary, step S2110 is executed.
And S290, analyzing the VOCs data by using a python language.
And S2100, building an analysis model and giving an analysis result, and returning to execute the step S270.
And S2110, classifying data according to the functional modules.
And S2120, displaying real-time operation data and analysis results.
Specifically, the data acquisition unit compiles and processes the signal channel according to different equipment signal sources, and gets through the data transmission channel. And transmitting the acquired original data through a signal transmission gateway and communication. If missing and incomplete dirty data occur in the original data, the data is cleaned and preprocessed in a machine learning algorithm mode, and then the data model is established by reclassification. If the acquired original data are complete, directly storing the acquired original data, and simultaneously establishing a data model; the data model comprises a test data model, a real-time data model, a sample data model and a static data model. The data in the real-time data model and the static data model can be directly applied and displayed in real time without analysis, and the result is output. The sample data model and the test data model are used for constructing an algorithm model. And performing performance analysis and alarm mechanism analysis according to the running state and the processing effect of the VOCs equipment, and constructing an algorithm model on the basis of python language. And returning the model output result to the data model, and outputting and displaying the analysis data result.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. An on-line monitoring system for VOCs processing apparatus, comprising:
the signal acquisition and processing unit is connected with the plurality of VOCs processing devices and is used for acquiring operation condition data of the VOCs processing devices in real time and carrying out primary pretreatment on the operation condition data to generate an analysis data packet to be stored;
the data storage and analysis unit is in communication connection with the signal acquisition and processing unit and is used for carrying out secondary preprocessing on the data in the data packet to be stored and analyzed and classifying and storing the data subjected to the secondary preprocessing so as to establish a database; wherein the database comprises test data, sample data, real-time data and static data; the real-time data is operation condition data changing along with time; the static data comprises serial numbers and production information data of the VOCs processing device; the sample data and the test data are data to be analyzed in the real-time data; the data storage analysis unit is also used for establishing an algorithm analysis model according to the test data and the sample data in the database so as to perform data real-time analysis on the state of the VOCs processing device and storing a data analysis result in the database;
the monitoring application unit is used for calling data in the database, carrying out online monitoring on the operation conditions of the plurality of VOCs processing devices according to the data in the database, establishing an alarm model according to the data in the database, judging a fault alarm point, and establishing a performance analysis model according to the data in the database so as to predict and analyze the processing performance of the VOCs processing devices.
2. The online monitoring system for processing the VOCs as claimed in claim 1, further comprising a display unit for visually displaying the online monitoring result, the analysis prediction result and the abnormal state alarm information of the monitoring application unit.
3. The system of claim 1, wherein the signal acquisition and processing unit comprises:
the signal acquisition subunit is used for acquiring the operating condition data of the VOCs processing devices through a data acquisition signal line;
the signal processing subunit is used for compiling and decoding the operating condition data, cleaning and classifying the data and forming a to-be-stored analysis data packet by the processed data;
and the signal gateway subunit is used for sending the to-be-stored analysis data packet to the data storage analysis unit.
4. The system of claim 2, wherein the data storage analysis unit comprises:
the data storage subunit is used for receiving the analysis data packet to be stored and storing original data in the analysis data packet to be stored;
the data processing subunit is used for cleaning and classifying the original data in the to-be-stored analysis data packet through a machine learning algorithm, and returning the processed data to the data storage subunit for data updating and storage; the classified data comprises sample data, test data, real-time data and static data; the data storage subunit is also used for classifying and storing the updated data and constructing a data model, and the data model is used for establishing a relational database and a non-relational database; the data model comprises a test data model, a sample data model, a real-time data model and a static data model;
the data analysis subunit is used for establishing an algorithm analysis model according to the sample data in the sample data model and training the algorithm analysis model through the test data in the test data model; the data analysis subunit is further configured to process, through the algorithm analysis model, data to be analyzed in the real-time data model to obtain a data analysis result; the data storage subunit is also used for storing the data analysis result.
5. The system of claim 2, wherein the monitoring application unit comprises:
the visual monitoring subunit is used for calling real-time data and static data in a database, determining the type and the change trend of the real-time data, determining the number of the VOCs processing device according to the static data, and dynamically and visually displaying the operation condition corresponding to the VOCs processing device in the display unit according to at least one of a histogram, a bar graph and a pie graph; displaying, classifying and comparing the effect states of different VOCs processing devices before and after VOCs processing in the display unit;
the alarm subunit is used for calling a plurality of historical fault alarm point data in a preset time period in the database and establishing an alarm model according to the fault alarm point data in the preset time period; the display unit is used for displaying the alarm information of the abnormal state when the current real-time data is the fault alarm point; the alarm models correspond to the monitoring working conditions one by one;
and the performance analysis subunit is used for calling a plurality of historical data analysis results in a preset time period in the database, establishing a performance analysis model based on data accumulation and change trend, and predicting and analyzing the pollutant treatment effect and/or service life of the VOCs treatment device according to the performance analysis model.
6. The system of claim 5, wherein the monitoring application unit further comprises:
the distributed equipment management subunit is used for displaying the basic device information and the monitoring and analyzing results of each VOCs processing device in a distributed manner through the display unit; the device basic information includes at least one of a number, a type, a manufacturer production date, and a lifetime in static data corresponding to the VOCs processing device.
7. The system of claim 2, wherein the display unit comprises a PC display screen and/or a mobile display screen.
8. An online monitoring method for VOCs processing device is characterized by comprising the following steps:
the method comprises the steps that a signal acquisition processing unit acquires operation condition data of a VOCs processing device in real time, and performs primary preprocessing on the operation condition data to generate an analysis data packet to be stored; the signal acquisition processing unit is connected with the plurality of VOCs processing devices;
the data storage and analysis unit carries out secondary pretreatment on the data in the data packet to be stored and analyzed and stores the data subjected to the secondary pretreatment in a classified manner so as to establish a database; wherein the database comprises test data, sample data, real-time data and static data; the data storage and analysis unit is in communication connection with the signal acquisition and processing unit;
the data storage analysis unit establishes an algorithm analysis model according to the test data and the sample data in the database so as to carry out data real-time analysis on the state of the VOCs processing device and store the data analysis result in the database;
the monitoring application unit calls data in the database, carries out online monitoring on the operating conditions of the plurality of VOCs processing devices according to the data in the database, establishes an alarm model according to the data in the database, judges a fault alarm point, and establishes a performance analysis model according to the data in the database so as to predict and analyze the processing performance of the VOCs processing devices.
9. The on-line monitoring method for the VOCs processing apparatus according to claim 8, wherein the data storage analysis unit performs a second preprocessing on the data in the analysis data packet to be stored, and classifies and stores the data after the second preprocessing to build the database, comprising:
receiving the analysis data packet to be stored, and storing original data in the analysis data packet to be stored;
cleaning and classifying the original data in the data packet to be stored and analyzed through a machine learning algorithm, and returning the processed data to a data storage subunit for data updating and storage; the classified data comprises sample data, test data, real-time data and static data;
storing the updated data in a classified manner and constructing a data model, wherein the data model is used for establishing a relational database and a non-relational database; the data model comprises a test data model, a sample data model, a real-time data model and a static data model;
the data storage and analysis unit establishes an algorithm analysis model according to test data and sample data in a database so as to perform data real-time analysis on the state of the VOCs processing device and store a data analysis result in the database, and the data storage and analysis unit comprises:
establishing an algorithm analysis model according to the sample data in the sample data model;
training the algorithm analysis model through the test data in the test data model;
and processing the data to be analyzed in the real-time data model through the algorithm analysis model to obtain a data analysis result, and storing the data analysis result in the database.
10. The online monitoring method for the processing devices of the VOCs according to claim 1, wherein the monitoring application unit calls data in the database, and performs online monitoring on the operating conditions of the plurality of VOCs processing devices according to the data in the database, and the method comprises:
calling real-time data and static data in a database;
determining the type and the variation trend of the real-time data, determining the number of the VOCs processing device according to the static data, and dynamically and visually displaying the operation condition corresponding to the VOCs processing device in the display unit by using at least one of a histogram, a bar graph and a pie graph;
displaying, classifying and comparing effect states before and after VOCs treatment by different VOCs treatment devices on the display unit;
the monitoring application unit calls the data in the database, establishes an alarm model according to the data in the database and judges a fault alarm point, and the method comprises the following steps:
judging whether the current real-time data is a fault alarm point or not according to the alarm model, and displaying abnormal state alarm information through the display unit when the current real-time data is the fault alarm point;
the alarm model is determined based on a plurality of historical fault alarm point data in a preset time period in a database, and the alarm model corresponds to monitoring working conditions one to one;
the monitoring application unit calls data in the database, and establishes a performance analysis model according to the data in the database to predict and analyze the processing performance of the VOCs processing device, and the method comprises the following steps:
calling a plurality of historical data analysis results in a preset time period in the database;
establishing a performance analysis model based on data accumulation and variation trend;
and predicting and analyzing the pollutant treatment effect and/or the service life of the VOCs treatment device according to the performance analysis model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111419132.4A CN114090681A (en) | 2021-11-26 | 2021-11-26 | VOCs processing apparatus on-line monitoring system and method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111419132.4A CN114090681A (en) | 2021-11-26 | 2021-11-26 | VOCs processing apparatus on-line monitoring system and method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114090681A true CN114090681A (en) | 2022-02-25 |
Family
ID=80304827
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111419132.4A Pending CN114090681A (en) | 2021-11-26 | 2021-11-26 | VOCs processing apparatus on-line monitoring system and method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114090681A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115184440A (en) * | 2022-07-22 | 2022-10-14 | 武汉理工大学 | VOCs monitoring and data processing system based on Internet of things |
-
2021
- 2021-11-26 CN CN202111419132.4A patent/CN114090681A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115184440A (en) * | 2022-07-22 | 2022-10-14 | 武汉理工大学 | VOCs monitoring and data processing system based on Internet of things |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10013866B2 (en) | Production equipment monitoring method and system | |
| US8484150B2 (en) | Systems and methods for asset condition monitoring in electric power substation equipment | |
| US20220035361A1 (en) | Systems and Methods for Artificial Intelligence-Based Maintenance of An Air Conditioning System | |
| EP1291772A2 (en) | Failure prediction apparatus and method | |
| CN111162949A (en) | Interface monitoring method based on Java byte code embedding technology | |
| CN112686402A (en) | Method for combining daily inspection and intelligent operation and maintenance management platform | |
| CN116070802B (en) | Intelligent monitoring operation and maintenance method and system based on data twinning | |
| CN114090681A (en) | VOCs processing apparatus on-line monitoring system and method | |
| CN117761444B (en) | Method and system for monitoring service life of surge protector | |
| CN112562277A (en) | Equipment fault early warning method and system | |
| CN116166499A (en) | Data monitoring method and device, electronic equipment and nonvolatile storage medium | |
| CN114371752A (en) | Environmental regulation and control method and system for precision instrument laboratory | |
| CN110765633A (en) | Intelligent management method and device for power device | |
| CN112036694B (en) | Highway electromechanical equipment life cycle prediction method and system | |
| JP2009009538A (en) | Method and system for analyzing operating condition | |
| Andrade et al. | Analysis of software aging impacts on plant anomaly detection with edge computing | |
| CN111475495A (en) | Mass analysis method, system and storage medium based on big data | |
| CN116345691A (en) | Power equipment operation monitoring system | |
| CN111274107A (en) | Fault repair system and method for live broadcast | |
| CN113156906B (en) | Activated carbon saturation analysis and management method based on pollution source online monitoring | |
| CN115222181A (en) | Robot operation state monitoring system and method | |
| KR101069653B1 (en) | Precaution maintenance system and method for automation equipment | |
| CN114697234B (en) | Intelligent data reporting cable | |
| CN113421031B (en) | Warning method and system for additional device of cigarette production line | |
| CN117880055B (en) | Network fault diagnosis method, device, equipment and medium based on transmission layer index |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |