CN112093828B - Distributed sewage treatment intelligent platform based on cloud computing - Google Patents
Distributed sewage treatment intelligent platform based on cloud computing Download PDFInfo
- Publication number
- CN112093828B CN112093828B CN202010927353.1A CN202010927353A CN112093828B CN 112093828 B CN112093828 B CN 112093828B CN 202010927353 A CN202010927353 A CN 202010927353A CN 112093828 B CN112093828 B CN 112093828B
- Authority
- CN
- China
- Prior art keywords
- data
- sewage treatment
- module
- facility
- state
- 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.)
- Active
Links
Images
Classifications
-
- C—CHEMISTRY; METALLURGY
- C02—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F—TREATMENT OF WATER, WASTE WATER, SEWAGE, OR SLUDGE
- C02F1/00—Treatment of water, waste water, or sewage
- C02F1/008—Control or steering systems not provided for elsewhere in subclass C02F
-
- 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
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
- G06F9/5066—Algorithms for mapping a plurality of inter-dependent sub-tasks onto a plurality of physical CPUs
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/54—Interprogram communication
- G06F9/546—Message passing systems or structures, e.g. queues
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2209/00—Indexing scheme relating to G06F9/00
- G06F2209/54—Indexing scheme relating to G06F9/54
- G06F2209/548—Queue
-
- 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 invention relates to a distributed sewage treatment intelligent platform based on cloud computing, and compared with the prior art, the distributed sewage treatment intelligent platform solves the problems of storage and query of massive distributed sewage treatment monitoring data and difficulty in management of distributed sewage treatment facilities, and reduces the operation cost of the sewage treatment facilities. The system comprehensively monitors and collects various key elements of the sewage treatment facility, and performs high-efficiency storage, real-time analysis and feedback control on the key elements. The platform comprises a data monitoring module, a data transmission module, a data storage module, a facility control module, an intelligent analysis engine and a visualization module; through the platform, unified monitoring, data acquisition and transmission, unified data analysis, processing application and control of a large number of decentralized sewage treatment facilities are realized, intelligent abnormity identification control and visual management of the decentralized sewage treatment facilities are realized on the basis, and the monitoring management level and the operation efficiency are improved.
Description
Technical Field
The invention relates to the technical field of sewage treatment.
Background
In the prior art, the monitoring of the mass dispersed sewage treatment is difficult, the dispersed sewage treatment facilities are difficult to manage, and the running cost of the sewage treatment facilities is high.
Along with the rapid increase of the economy of China, the urbanization rate is continuously improved, the rural sewage environment problem is increasingly prominent, and sewage treatment facilities are continuously increased; decision makers continuously improve the management force and the management capacity of sewage treatment facilities, greatly improve the sewage treatment capacity, provide basic basis and scientific guidance thought of data analysis for accurate water treatment, and therefore the operation and maintenance cost is reduced.
Disclosure of Invention
The invention aims to provide an intelligent platform facing distributed sewage treatment facilities, and the intelligent monitoring control facing large-scale distributed sewage treatment facilities is realized by monitoring data acquisition, transmission, distributed storage, real-time intelligent analysis and remotely controlling the sewage treatment facilities in real time, so that the operating efficiency of the sewage treatment facilities is improved; and the platform provides intelligent analysis and visualization capability, and improves the operation management level of decentralized sewage treatment facilities.
Technical scheme
The utility model provides a distributed sewage treatment intelligent platform based on cloud calculates, includes data monitoring module, data transmission module, data receiving module, data storage module, facility control module, intelligent analysis module, visual module, through data monitoring module, data transmission module, data receiving module, data storage module, facility control module, intelligent analysis module, visual module's cooperation has constructed a complete closed loop from monitoring data acquisition, transmission, storage, analysis, control, has realized intelligent decentralized sewage treatment facility monitoring control: constructing a perfect dispersed sewage treatment database by collecting the basic information of each dispersed sewage treatment facility and collecting and transmitting the monitoring information of the dispersed sewage treatment facilities in real time, formulating operation parameters for each dispersed sewage treatment facility by a system intelligent analysis module according to the information in the database, and regulating and controlling the facilities by a control module; the platform realizes the collection, analysis and sharing of sewage treatment information, realizes the visualization of the spatial distribution of dispersed sewage treatment facilities in the form of geographic information through a visualization module, and realizes the visualization of the running state based on the geographic position; the alarm function of the platform gives an alarm to managers in time according to the intelligent analysis result, and the management capacity and the response speed are improved.
Specifically, the method comprises the following steps:
the data monitoring module is composed of sensors installed on each dispersed sewage treatment facility and used for collecting each operation index of each dispersed sewage treatment facility, including water inflow amount, water outflow amount, water inflow (PH, DO, SS, temperature, COD, ammonia nitrogen, TN, TP, turbidity and conductivity), water outflow and water inflow (PH, DO, SS, temperature, COD, ammonia nitrogen, TN, TP, turbidity and conductivity), power consumption, fan current, voltage, pump voltage, current and equipment power supply state.
And the data transmission module is used for transmitting the data monitored by the data monitoring module in real time to the cloud server.
The data receiving module receives a large amount of data transmitted by a large amount of dispersed sewage facilities in real time and delivers the data to the data storage module for storage. Further, the data receiving module runs on a cloud server; after the cloud server receives data through the data receiving module, the data are stored in a distributed mode through the data storage module according to the time stamp; and receiving real-time monitoring data to form a complete decentralized sewage treatment facility monitoring database, and writing the data into a Kafka message queue system.
The data storage module is used for storing high-performance monitoring data of a large amount of dispersed sewage treatment facilities and comprises a relational database and distributed storage. Furthermore, the data storage module is composed of three databases, wherein one database is a time sequence database infiluxdb used for storing data uploaded by the equipment, the other database is a relational database postgresql used for storing relational data, and the other database is an NO-SQL database redis used for caching and supporting reading of mass data.
The intelligent analysis module is used for intelligently analyzing the received real-time monitoring data, judging the running state and the sewage treatment effect of each sewage treatment facility and controlling the decentralized sewage treatment facilities by calling the facility control module according to the analysis result; the module also realizes various statistical analysis of the monitoring data, and the alarm module can alarm corresponding operation and maintenance companies and managers according to the analysis result of the intelligent analysis module so as to process the fault or the fault to be generated.
Further innovating, the intelligent analysis module comprises a distributed stream processing subsystem, a real-time calculation analysis algorithm module and a timing calculation analysis algorithm module:
wherein the content of the first and second substances,
the real-time calculation analysis algorithm module utilizes a distributed stream processing subsystem to process the received unbounded data stream in real time, and detects a complex alarm rule in real time by designing a complex event processing capability algorithm based on NFA;
the complex event processing capability algorithm in the distributed stream processing subsystem is used for describing and executing complex events: based on the pattern description, converting into NFA, namely a non-deterministic finite automaton; the NFA is a state diagram consisting of points and edges, starting with an initial state that disperses operating criteria of the wastewater treatment facility, through a series of intermediate states, to a final state. The points are divided into three types, namely an initial state, an intermediate state and a final state, and the edges are divided into three types, namely take, align and processed;
take: a condition judgment must exist, when the running index flow data of the incoming decentralized sewage treatment facility meets the take side condition judgment, the flow data is put into a result set, and the state is transferred to the next state;
an ignore: when the stream data comes, the stream data can be ignored, the state is self-rotated and is not changed at present, and the state is transferred to the self state;
processed: also called state empty transfer, the current state can be transferred directly to the next state independent of the arrival of a message;
and (4) flowing among various intermediate states according to the mode stream data, and triggering an event if the flow is converted into a final state.
The timing calculation analysis algorithm module self-defines the execution time of the task based on an APScheduler framework of python, checks the currently stored data according to different check rules, and generates detailed alarm information and informs a user in real time if the data is abnormal.
Drawings
FIG. 1 is a flow chart of the intermediate states of the intelligent analysis module according to the present invention
FIG. 2 is a flow chart of the steps of the distributed stream processing subsystem of the present invention
FIG. 3 is a block diagram of the platform of the present invention
FIG. 4 is a flow chart of the method of the present invention
Detailed Description
The following is further detailed by specific embodiments:
the invention provides a set of distributed sewage treatment intelligent platform based on cloud computing, which aims to perform centralized monitoring and intelligent analysis control on various distributed sewage treatment facilities, realize centralized management of the distributed sewage treatment facilities, realize effective monitoring of production and treatment processes and timely elimination and maintenance of faults, and improve the operating efficiency of the distributed sewage treatment facilities.
As shown in fig. 3 and 4:
the utility model provides a distributed sewage treatment intelligent platform based on cloud calculates, includes data monitoring module, data transmission module, data receiving module, data storage module, facility control module, intelligent analysis module, visual module, through the cooperation of data monitoring module, data transmission module, data receiving module, data storage module, facility control module, intelligent analysis module, visual module has constructed a complete closed loop from monitoring data collection, transmission, storage, analysis, control, has realized intelligent dispersed sewage treatment facility monitoring control: a perfect decentralized sewage treatment database is constructed by collecting basic information of all decentralized sewage treatment facilities and collecting and transmitting decentralized sewage treatment facility monitoring information in real time, a system intelligent analysis module formulates operation parameters for each decentralized sewage treatment facility according to the information in the database, and the facilities are regulated and controlled through a control module. The platform realizes the collection, analysis and sharing of sewage treatment information, realizes the visualization of the spatial distribution of dispersed sewage treatment facilities in the form of geographic information through the visualization module, and realizes the visualization of the running state based on the geographic position. The alarm function of the platform gives an alarm to managers in time according to the intelligent analysis result, and the management capacity and the response speed are improved.
Specifically, the method comprises the following steps:
the data monitoring module is composed of sensors installed on each dispersed sewage treatment facility and used for collecting each operation index of each dispersed sewage treatment facility, including water inflow amount, water outflow amount, water inflow (PH, DO, SS, temperature, COD, ammonia nitrogen, TN, TP, turbidity, conductivity), water outflow and water inflow (PH, DO, SS, temperature, COD, ammonia nitrogen, TN, TP, turbidity, conductivity), power consumption, fan current, voltage, pump voltage, current, equipment power supply state and the like. The frequency of data acquisition is not less than 1 time per second. Meanwhile, image and video acquisition sensors are arranged in the monitoring of part of dispersed sewage treatment facilities, and the real-time images or videos of the sewage treatment facilities can be acquired according to the instruction requirements. In this embodiment, the data monitoring module is installed in each decentralized sewage treatment facility, and each facility is different according to the sensing type of the actual situation and the type of the monitored data, and the system can be supported in a self-adaptive manner. The data monitoring module in the embodiment is also provided with a local storage capacity, and can store the detection data of the station for a period of time.
And the data transmission module is mainly used for transmitting the data monitored by the data monitoring module in real time to the cloud server. The data transmission in the embodiment is used for transmitting the monitoring data acquired by the data monitoring module to a remote server. In the embodiment, the module is realized based on a DTU (data transmission module), and based on a MODBUS protocol, the transmission frequency is 1 time per minute. The embodiment also sets monitoring data transmitted by the mobile detection vehicle. Further, the data transmission module supports the HTTP-based restful API protocol and supports the TCP/IP or PLC-based MODBUS protocol. The data transmission of the monitoring equipment can be well supported.
And the data receiving module is mainly used for realizing a high-performance data receiving task, can simultaneously receive a large amount of data transmitted by a large amount of dispersed sewage facilities in real time, and delivers the data to the data storage module for storage. The data receiving module in the embodiment runs on a cloud server. And receiving the monitoring data transmitted by the data transmission module. The module is based on the Restful interface of HTTP and the MODBUS protocol of Ethernet TCP/IP. The module receives monitoring data transmitted by a large number of dispersed sewage treatment facilities in real time and receives monitoring data transmitted by the mobile detection vehicle. The module is based on Web Service, data Json format or binary coding form. The module can simultaneously support data receiving work of a large number of facilities by utilizing multithreading and multi-path IO technology.
By way of example and not limitation, the data receiving module in the embodiment may build a restful interface based on a flash framework of python, receive data in json format, and perform simple check, such as whether a field transmits a value according to an interface specification, whether a key field device code has a value, and the like, and if an exception exists, return detailed exception information to a caller. The MODBUS protocol interface provides services through a socket. The client is connected with the server, the server sends the specification to the client to inquire whether the client is ready, and if so, the client can send data to the server. When receiving data, the server can automatically judge whether the current data belongs to new addition or update, and then stores the data into the database. This part is realized by general mature technology.
The data storage module is mainly used for storing high-performance monitoring data of a large amount of dispersed sewage treatment facilities and mainly comprises a relational database and distributed storage. By way of example and not limitation, the data storage module of an embodiment may be composed of three databases, one is a time sequence database infiluxdb for storing data uploaded by the device, one is a relational database postgresql for storing relational data, and one is a NO-SQL database redis for caching and supporting reading of mass data. Based on a relational database and a distributed storage technology, all the basic information and monitoring data of the decentralized sewage treatment facility are stored. The quantity of dispersed sewage treatment facilities is large, and the real-time monitoring data frequency is high, and the number of elements is large, so that the data volume is huge. The module stores mass data on a plurality of storage nodes according to a timestamp mode and element types, and uses a memory as a cache; therefore, the high-speed storage and retrieval capacity of the time series data monitored by the massive decentralized sewage treatment facility is realized. The part is realized by general mature technology.
The intelligent analysis module is mainly used for intelligently analyzing the received real-time monitoring data, judging the running state, the sewage treatment effect and the like of each sewage treatment facility, and controlling the decentralized sewage treatment facilities by calling the facility control module according to the analysis result; the module can also realize various statistical analyses on the monitoring data, and the alarm module can give an alarm to corresponding operation and maintenance companies and managers according to the analysis result of the intelligent analysis module. So that it handles the failure or the failure that is about to occur.
The facility control module is mainly used for realizing the real-time control of the cloud platform on each decentralized sewage treatment facility device, consists of a cloud control program, a communication program and a device end controller, and can realize the real-time control on the main device of the sewage treatment facility; and sending a data abnormal judgment instruction to a designated decentralized sewage treatment facility according to the analysis result and the treatment strategy of the intelligent abnormal recognition analysis module. The equipment of the system is controlled, including various fans, various pumps, valves, power supplies and the like, so that the real-time control of the dispersed sewage treatment facility is realized, and the operation efficiency and the cost control of the dispersed sewage treatment facility are improved.
And the visualization module is mainly used for visualizing the stored dispersed sewage treatment monitoring data and the analysis result of the intelligent analysis module in the forms of geographic information, charts and graphs so that a user can quickly know information and make decisions. The visualization module in the embodiment visualizes the geographical position distribution and the operation state of the decentralized sewage treatment facility in the geographical position meaning based on the geographical information; visualizing the running state of the facility and the real-time monitoring data in a graphical mode; visualizing the results of the intelligent analysis in the form of various charts; visual results can help managers to quickly know the conditions of a large number of decentralized sewage treatment facilities.
The above embodiment provides functions of basic information and real-time data monitoring query, historical data browsing, data export and the like, and helps managers to carry out secondary utilization on data.
The platform of the embodiment receives, stores and intelligently analyzes real-time data of each facility according to the information of each dispersed sewage treatment facility by acquiring the information of geographical position information, real-time running state information, real-time water quality and the like of each dispersed sewage treatment facility in real time through self-checking of each functional module, and remotely controls the facility according to the result of intelligent analysis; meanwhile, the platform carries out intelligent analysis on all dispersed sewage treatment facilities in the platform according to basic data, real-time monitoring data and historical monitoring data in the database, and results are formed to provide decision-making bases for managers. And finally, a visualization module of the platform visualizes all the processing processes, the running states and the analysis results. Through the operation of whole platform, effectively solved dispersion sewage facility and mastered its running state difficulty, monitoring data big, management efficiency low grade problem. The system realizes effective monitoring and control in the dispersed sewage treatment process, improves the monitoring efficiency of sewage treatment, reduces the fault rate, improves the management level, and provides guarantee for stable and effective operation of each dispersed sewage treatment facility.
Further, based on the foregoing platform, as shown in fig. 4, the implementation steps include:
step 1: data collection and monitoring
The basic information of the decentralized sewage treatment facility collected mainly comprises the following steps: various basic information such as geographical position information, facility information, construction units, personnel information and the like;
the data monitoring is used for monitoring various operation indexes of the decentralized sewage treatment facility in real time, and mainly comprises water inflow and outflow rates, various water quality indexes, various equipment operation condition indexes, power consumption indexes and the like, and specifically, data such as PH, DO, SS, temperature, COD, ammonia nitrogen, TN, TP, turbidity, conductivity, power consumption, fan operation condition, pump operation condition and the like are acquired by a sewage treatment facility sensor;
and 2, step: data transmission
The data are transmitted to a cloud server in real time through a DTU (data transmission unit);
and step 3: receiving and storing
After the cloud server receives data through the data receiving module, the data are stored in a distributed mode through the data storage module according to the time stamp; receiving real-time monitoring data to form a complete decentralized sewage treatment facility monitoring database; while data is written to the Kafka message queue system.
And 4, step 4: analyzing and controlling monitoring data in real time
Analyzing the operation condition of the monitoring device according to the received monitoring data; controlling and adjusting equipment such as a lift pump, a sludge pump, a fan, the water inlet quantity and the like of the sewage treatment facility in real time;
and 5: intelligent analysis of platforms
Various statistical analyses are carried out according to the long-term received data, and decision support is provided;
step 6: visualization
And visualizing the facility running state and the intelligent analysis result based on the GIS technology. The method is used for retrieving, viewing, editing, exporting and the like the detection data.
Step 4, analyzing and controlling the monitoring data in real time, reading the data in the database by an intelligent abnormity identification analysis module, and judging the running state of the facility according to the following rules:
when the daily water amount of the sewage treatment facility is larger than the designed water amount, determining that the production running state of the sewage treatment facility is an abnormal state;
when the water inlet amount of the sewage treatment facility exceeds the designed water amount within a certain time, determining that the production running state of the sewage treatment facility is a water amount abnormal state;
when the concentration of the influent pollutants of the sewage treatment facility exceeds the average value within a certain time, determining that the production running state of the sewage treatment facility is the abnormal state of water quality, and controlling the facility to reduce the water inflow by an intervention strategy;
when the quality of inlet water of the sewage treatment facility is lower than the average value within a certain time, determining that the production running state of the sewage treatment facility is a water quality abnormal state, and controlling the facility to increase the water inflow by an intervention strategy;
when the effluent concentration of the sewage treatment facility is lower than the average value within a certain time, determining that the production running state of the sewage treatment facility is a water quality abnormal state, and controlling the facility to increase the water inflow by an intervention strategy;
when the fan of the sewage treatment facility is not started or cannot be remotely started within a set time, the current and the voltage of the fan are abnormal, and the current and the voltage of the water pump are abnormal, the production running state of the sewage treatment facility is determined to be an equipment abnormal state, the intervention strategy is to try to remotely restart equipment, and if the intervention strategy is invalid, an alarm is given to the equipment for artificial ready confirmation;
when the ammonia nitrogen output by the sewage treatment facility is more than a standard value of 25 (mg/L), the COD (chemical oxygen demand) of the effluent is more than a standard value of 100 (mg/L) and the TP of the effluent is about a standard value of 3 (mg/L), the production running state of the sewage treatment facility is determined to be an abnormal effect state, if the system is in an emergency treatment state, the intervention strategy is not controlled, otherwise, the facility is controlled to carry out aeration and water inflow parameter optimization.
Step 5, intelligently analyzing the platform, analyzing the dispersed sewage treatment facilities according to the received running state monitoring data, wherein the main analysis content comprises the following steps:
analyzing the total number of facilities, the total treatment capacity of the facilities, the number and proportion of accessed and benefited farmers, the distribution of the treatment scale of the facilities, the distribution of the treatment process of the facilities, the investment cost of a single household (the construction cost of the facilities/the benefited number of the farmers) and the operation and maintenance management cost according to regions, treatment processes, treatment scales and year, month and day;
analyzing the standard reaching rate of sewage treatment according to regions, treatment processes, treatment scales and year, month and day;
analyzing the sewage treatment removal rate according to regions, treatment processes, treatment scales and year, month and day;
analyzing the effective operation rate, the facility online rate, the facility alarm rate, the facility fault rate and the energy consumption of the sewage treatment facility according to regions, treatment processes, treatment scales, years, months and days;
analyzing the sewage treatment overproof factor according to areas, treatment processes, treatment scales and year, month and day;
and analyzing the abnormal value of the sewage treatment removal rate, the abnormal value of the influent water concentration and the correlation of the concentration of each index of the influent water according to regions, treatment processes, treatment scales and year, month and day.
Further innovating, the intelligent analysis module comprises a distributed stream processing subsystem, a real-time calculation analysis algorithm module and a timing calculation analysis algorithm module:
the intelligent analysis module is realized in two modes, namely, the intelligent analysis module comprises a real-time calculation analysis algorithm module and a timing calculation analysis algorithm module:
1. the method belongs to a real-time calculation analysis mode, utilizes a distributed stream processing subsystem to process a received unbounded data stream in real time, and detects a complex alarm rule in real time by designing a complex event processing capability algorithm based on NFA (non-deterministic finite automata).
The complex event processing capability algorithm in the distributed stream processing subsystem is used for describing and executing complex events: based on the pattern description, converting into NFA, namely a non-deterministic finite automaton; the NFA is a state diagram consisting of points and edges, starting from an initial state that disperses operating criteria of a wastewater treatment facility, through a series of intermediate states, to a final state. The point is divided into three types of initial state, intermediate state and final state, and the edge is divided into three types of take, align and processed.
take: there must be a condition judgment that puts the stream data into the result set when the stream data of the operation index of the incoming decentralized sewage treatment facility satisfies the take edge condition judgment, and shifts the state to the next state.
An ignore: when the stream data comes, the stream data can be ignored, the state is not changed at present, and the state is transferred to the state of the user.
processed: also called null transition of states, the current state can be directly transitioned to the next state independent of the arrival of a message.
As shown in fig. 1, flow is between the various intermediate states according to the mode stream data, and if the flow goes to the final state, an event is triggered.
2. The other type belongs to a timing calculation analysis mode, an APSchedule framework based on python self-defines the execution time of a task, checks the current stored data according to different check rules, and generates detailed alarm information and informs a user in real time if the data are abnormal.
The distributed stream processing subsystem has the operation (as shown in fig. 2) steps of:
step 1: and reading operation indexes of the dispersed sewage treatment facilities, namely mass multi-source sewage treatment state monitoring data in real time from a Kafka message queue system of the platform.
And 2, step: after data enters the distributed stream processing subsystem, filtering the data on a distributed architecture to eliminate abnormal values and error values;
and step 3: the method is characterized in that each alarm rule is defined based on the form of a complex event model, the description of the complex event model is based on patterns, and managers describe complex events by the patterns which are connected in series.
And 4, step 4: the distributed stream processing subsystem converts the complex event model into NFA (non-deterministic finite automata) through an NFA compiler, continuously loads data into the NFA and executes the data to obtain an alarm result, and finally outputs the alarm result.
The embodiment provides a distributed sewage treatment intelligent platform based on cloud computing, and relates to data acquisition, data transmission, data storage, data analysis and sewage treatment facility control. Each station is provided with a PLC (programmable logic controller) device, and the state parameters of the sensors of the station are checked in real time to be used as a data acquisition mode; the method comprises the following steps of (1) carrying out REStful API protocol based on HTTP, and supporting MODBUS protocol data transmission based on TCP/IP or PLC; storing the data by adopting a PostgreSQL relational database and an InfluxDB time sequence database; the real-time processing of mass stream data is realized by utilizing a distributed stream processing technology; the data analysis applies the principles of design statistics, mathematics and the like, and combines data indexes to carry out the processes of inputting, counting, calculating, dumping, outputting, converting, matching and displaying on mass data.
The above-mentioned embodiments are further described in detail for the purpose of illustrating the invention, and it should be understood that the above-mentioned embodiments are only exemplary of the invention, and are not intended to limit the scope of the invention, and any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the invention should be included in the scope of the invention.
Claims (1)
1. The utility model provides a distributed sewage treatment intelligent platform based on cloud calculates, its characterized in that, including data monitoring module, data transmission module, data receiving module, data storage module, facility control module, intelligent analysis module, visual module, through the cooperation of data monitoring module, data transmission module, data receiving module, data storage module, facility control module, intelligent analysis module, visual module has constructed a complete closed loop from monitoring data acquisition, transmission, storage, analysis, control, has realized intelligent decentralized sewage treatment facility monitoring control: constructing a perfect dispersed sewage treatment database by collecting the basic information of each dispersed sewage treatment facility and collecting and transmitting the monitoring information of the dispersed sewage treatment facilities in real time, formulating operation parameters for each dispersed sewage treatment facility by a system intelligent analysis module according to the information in the database, and regulating and controlling the facilities by a control module; the platform realizes the collection, analysis and sharing of sewage treatment information, realizes the visualization of the spatial distribution of dispersed sewage treatment facilities in the form of geographic information through a visualization module, and realizes the visualization of the running state based on the geographic position; the alarm function of the platform gives an alarm to the manager in time according to the intelligent analysis result, so that the management capability and the response speed are improved;
the data monitoring module consists of sensors arranged on each dispersed sewage treatment facility and is used for acquiring various operation indexes of each dispersed sewage treatment facility, including water inlet amount, water outlet amount, water inlet pH, water inlet DO, water inlet SS, water inlet temperature, water inlet COD, water inlet ammonia nitrogen, water inlet TN, water inlet TP, water inlet turbidity, water inlet conductivity, water outlet pH, water outlet DO, water outlet SS, water outlet temperature, water outlet COD, water outlet ammonia nitrogen, water outlet TN, water outlet TP, water outlet turbidity, water outlet conductivity, power consumption, fan current, voltage, pump voltage, current and equipment power supply state;
the data transmission module is used for transmitting the data monitored by the data monitoring module in real time to the cloud server;
the data receiving module receives a large amount of data transmitted by a large amount of dispersed sewage facilities in real time at the same time and delivers the data to the data storage module for storage;
the data receiving module runs on a cloud server; after the cloud server receives data through the data receiving module, the data are stored in a distributed mode through the data storage module according to the time stamp; the received real-time monitoring data form a complete decentralized sewage treatment facility monitoring database, and meanwhile, the data are written into a Kafka message queue system;
the data storage module is used for storing high-performance monitoring data of a large amount of dispersed sewage treatment facilities and consists of a relational database and distributed storage; furthermore, the data storage module consists of three databases, wherein one database is a time sequence database infiluxdb used for storing data uploaded by the equipment, the other database is a relational database postgresql used for storing relational data, and the other database is an NO-SQL database redis used for caching and supporting reading of mass data;
the intelligent analysis module is used for intelligently analyzing the received real-time monitoring data, judging the running state and the sewage treatment effect of each sewage treatment facility and controlling the decentralized sewage treatment facilities by calling the facility control module according to the analysis result; the module also realizes various statistical analyses on the monitoring data, and the alarm module can alarm corresponding operation and maintenance companies and managers according to the analysis result of the intelligent analysis module so as to process faults or faults to be generated;
the intelligent analysis module comprises a distributed stream processing subsystem, a real-time calculation analysis algorithm module and a timing calculation analysis algorithm module:
wherein, the first and the second end of the pipe are connected with each other,
the real-time calculation analysis algorithm module utilizes a distributed stream processing subsystem to process the received unbounded data stream in real time, and detects a complex alarm rule in real time by designing a complex event processing capability algorithm based on NFA;
the complex event processing capability algorithm in the distributed stream processing subsystem is used for describing and executing complex events: based on the pattern description, converting into NFA, namely a non-deterministic finite automaton; the NFA is a state diagram consisting of points and edges, and takes an initial state of dispersing the operation indexes of the sewage treatment facility as a starting point to reach a final state through a series of intermediate states; the points are divided into three types, namely an initial state, an intermediate state and a final state, and the edges are divided into three types, namely take, align and processed;
take: a condition judgment must exist, when the running index flow data of the incoming decentralized sewage treatment facility meets the condition judgment of take, the flow data is put into a result set, and the state is transferred to the next state;
an ignore: when the stream data comes, the stream data can be ignored, the state is not changed at present, and the state is transferred from the current state to the current state;
processed: also called state null transition, the current state can be directly transitioned to the next state independent of the arrival of a message;
transferring between each intermediate state according to the mode stream data, and triggering an event if the transfer is transferred to a final state;
the timing calculation analysis algorithm module self-defines the execution time of the task based on an APScheduler framework of python, checks the currently stored data according to different check rules, and generates detailed alarm information and informs a user in real time if the data is abnormal;
further, based on the above platform, the implementation steps include:
step 1: data collection and monitoring
The collected data comprises basic information of the decentralized sewage treatment facility and various operation indexes of the decentralized sewage treatment facility;
step 2: data transmission
The data are transmitted to a cloud server in real time through a data transmission unit;
and step 3: receiving and storing
After the cloud server receives data through the data receiving module, the data storage module is used for distributed storage according to the time stamp; receiving real-time monitoring data to form a complete decentralized sewage treatment facility monitoring database; simultaneously writing data into a Kafka message queue system;
and 4, step 4: analyzing and controlling monitoring data in real time
Analyzing the operation condition of the monitoring device according to the received monitoring data; a lift pump, a sludge pump, a fan and a water inlet device for controlling and adjusting the sewage treatment facility are made in real time;
and 5: intelligent analysis of platforms
Various statistical analyses are carried out according to the long-term received data, and decision support is provided;
step 6: visualization
Visualizing the facility running state and the intelligent analysis result based on the GIS technology; the system is used for retrieving, checking, editing and exporting the detection data;
and 4, analyzing and controlling the monitoring data in real time, reading the data in the database by an intelligent abnormity identification analysis module, and judging the running state of the facility according to the following rules:
when the daily water amount of the sewage treatment facility is larger than the designed water amount, determining that the production running state of the sewage treatment facility is an abnormal state;
when the water inlet amount of the sewage treatment facility exceeds the designed water amount within a certain time, determining that the production running state of the sewage treatment facility is a water amount abnormal state;
when the concentration of the influent pollutants of the sewage treatment facility exceeds the average value within a certain time, determining that the production running state of the sewage treatment facility is the abnormal state of water quality, and controlling the facility to reduce the water inflow by an intervention strategy;
when the quality of inlet water of the sewage treatment facility is lower than the average value within a certain time, determining that the production running state of the sewage treatment facility is a water quality abnormal state, and controlling the facility to increase the water inflow by an intervention strategy;
when the effluent concentration of the sewage treatment facility is lower than the average value within a certain time, determining that the production running state of the sewage treatment facility is a water quality abnormal state, and controlling the facility to increase the water inflow by an intervention strategy;
when the fan of the sewage treatment facility is not started within a set time or cannot be remotely started, the current and the voltage of the fan are abnormal, and the current and the voltage of the water pump are abnormal, the production running state of the sewage treatment facility is determined to be an equipment abnormal state, the intervention strategy is to try to remotely restart the equipment, and if the operation is invalid, an alarm is given to the operator for ready confirmation;
when the ammonia nitrogen output by the sewage treatment facility is more than a standard value of 25 (mg/L), the COD (chemical oxygen demand) of the effluent is more than a standard value of 100 (mg/L) and the TP (total phosphorus) of the effluent is more than a standard value of 3 (mg/L), determining that the production running state of the sewage treatment facility is an effect abnormal state, and if the system is in an emergency treatment state, performing no control on the intervention strategy, otherwise, controlling the facility to perform aeration and water inflow parameter optimization;
the intelligent analysis of the platform in the step 5 analyzes the dispersed sewage treatment facilities according to the received running state monitoring data, and the analysis content comprises:
analyzing the total number of facilities, the total treatment capacity of facilities, the number of accessed and benefited farmers, the distribution of the treatment scale of facilities, the distribution of the treatment process of facilities, the investment cost of a single household and the operation and maintenance management cost according to regions, treatment processes, treatment scales and year, month and day;
analyzing the standard reaching rate of sewage treatment according to regions, treatment processes, treatment scales and year, month and day;
analyzing the sewage treatment removal rate according to regions, treatment processes, treatment scales and year, month and day;
analyzing the effective operation rate, the facility online rate, the facility alarm rate, the facility fault rate and the energy consumption of the sewage treatment facility according to regions, treatment processes, treatment scales, years, months and days;
analyzing the sewage treatment overproof factor according to regions, treatment processes, treatment scales and year, month and day;
and analyzing the abnormal value of the sewage treatment removal rate, the abnormal value of the influent water concentration and the correlation of the concentration of each index of the influent water according to regions, treatment processes, treatment scales and year, month and day.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010927353.1A CN112093828B (en) | 2020-09-04 | 2020-09-04 | Distributed sewage treatment intelligent platform based on cloud computing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010927353.1A CN112093828B (en) | 2020-09-04 | 2020-09-04 | Distributed sewage treatment intelligent platform based on cloud computing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112093828A CN112093828A (en) | 2020-12-18 |
| CN112093828B true CN112093828B (en) | 2022-10-04 |
Family
ID=73757832
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010927353.1A Active CN112093828B (en) | 2020-09-04 | 2020-09-04 | Distributed sewage treatment intelligent platform based on cloud computing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112093828B (en) |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112749887A (en) * | 2020-12-30 | 2021-05-04 | 中海油天津化工研究设计院有限公司 | Intelligent offshore platform domestic sewage treatment system |
| CN112863134B (en) * | 2020-12-31 | 2022-11-18 | 浙江清华长三角研究院 | Intelligent diagnosis system and method for rural sewage treatment facility abnormal operation |
| CN112777654A (en) * | 2021-01-07 | 2021-05-11 | 桂林电子科技大学 | Distributed sewage treatment method, system and storage medium based on FPGA |
| CN113484057A (en) * | 2021-07-20 | 2021-10-08 | 杭州塞博环境科技有限公司 | Method, equipment and system for calculating and evaluating energy efficiency of water treatment facility |
| CN113962493B (en) * | 2021-12-08 | 2022-08-19 | 云南省设计院集团有限公司 | Rapid prediction method based on combined overflow sewage pollutant removal rate |
| CN114003013B (en) * | 2022-01-04 | 2022-04-15 | 北京清源华建环境科技有限公司 | Control system of layered interconnected intelligent drainage pipe network system |
| CN116186101A (en) * | 2022-07-28 | 2023-05-30 | 安徽万舟清环境科技有限公司 | System for monitoring sewage collection, storage and discharge processes |
| CN116233199B (en) * | 2023-05-09 | 2023-07-28 | 北京德众国良环保科技有限公司 | Sewage treatment equipment intelligent water mist detection cloud platform based on wireless data communication |
| CN116862417B (en) * | 2023-06-28 | 2024-04-16 | 北京泷涛环境科技有限公司 | Water quality supervision method and system for sewage treatment facility |
| CN117517607A (en) * | 2023-11-07 | 2024-02-06 | 江苏汇海环境科技有限公司 | Intelligent monitoring method and system for integrated water treatment equipment based on visualization |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109976270A (en) * | 2019-02-28 | 2019-07-05 | 重庆工商大学 | Municipal sewage treatment cloud management platform |
-
2020
- 2020-09-04 CN CN202010927353.1A patent/CN112093828B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109976270A (en) * | 2019-02-28 | 2019-07-05 | 重庆工商大学 | Municipal sewage treatment cloud management platform |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112093828A (en) | 2020-12-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112093828B (en) | Distributed sewage treatment intelligent platform based on cloud computing | |
| CN107741738A (en) | A kind of sewage disposal process monitoring intelligent early warning cloud system and sewage disposal monitoring and pre-alarming method | |
| CN111367241A (en) | Enterprise comprehensive energy management and control system and method | |
| CN112863134B (en) | Intelligent diagnosis system and method for rural sewage treatment facility abnormal operation | |
| CN107703826A (en) | Sewage disposal process supervisory systems | |
| CN103546536A (en) | Internet of things system of sewage treatment plant | |
| CN108107832A (en) | A kind of sewage disposal real time monitoring and optimization system based on data-driven | |
| CN102591284A (en) | Sewage treatment engineering monitoring system based on wireless sensor network | |
| CN111899143A (en) | Regional water environment intelligent management and control system based on big data analysis strategy | |
| CN110995783B (en) | Remote monitoring system | |
| CN111121874A (en) | Water quality monitoring and evaluating system and method for water source area | |
| CN105892363B (en) | The water utilities data acquisition control intelligent terminal and water utilities centralized monitoring system of NC series | |
| CN113112169A (en) | Sewage treatment plant's wisdom cloud service system | |
| CN112437116A (en) | Sewage treatment wisdom operation system based on thing networking and cloud platform | |
| CN115063058B (en) | Comprehensive energy situation perception system based on model driving and data driving | |
| CN103616883A (en) | Direct drinking machine remote monitoring and intelligent network client managing system | |
| CN113902288A (en) | Management system and method for water resource regulation and control and operation | |
| CN106292596A (en) | A kind of sewage treatment plant intelligent management expert diagnostic system | |
| CN115936923A (en) | Intelligent water affair management information system | |
| CN116027722A (en) | Energy consumption monitoring management system | |
| CN115049297A (en) | Wisdom sewage factory operating system | |
| CN114640828A (en) | Factory network river and lake integrated operation monitoring and early warning system based on pipe network GIS | |
| CN106673209A (en) | River and lake ecological restoration regulating system and repairing method | |
| CN114358555A (en) | Rail transit wisdom energy management system | |
| CN1300991A (en) | Real-time monitor and information management integrated system |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |