CN110782190A - Phase modulator remote diagnosis system based on ubiquitous power internet of things technology - Google Patents
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Abstract
The invention discloses a phase modifier remote diagnosis system based on a ubiquitous power Internet of things technology, which comprises an equipment ledger database, a standard database, a historical database, an evaluation model database, a fault diagnosis model database, a remote expert diagnosis database, online monitoring equipment, a workflow engine, a communication device and a management server. The invention takes the power grid as a hub, and constructs a data center through technologies such as a data warehouse, data replication and the like, thereby realizing the sharing and exchange of all information data; processing abnormal values, data standardization, data generalization and data aggregation are realized through data conversion, and then reasoning work of a fault diagnosis knowledge base is realized; the method has the advantages that various indexes in operation, production and management of the phase modulator are subjected to integrated index analysis by using a data warehouse and a data mining technology, a safety early warning evaluation system based on mass data is established, the healthy operation of the phase modulator can be guaranteed by combining a system operation state estimation technology, and refined prediction and coordination control are realized.
Description
Technical Field
The invention relates to the technical field of phase modulator remote diagnosis, in particular to a phase modulator remote diagnosis system based on the ubiquitous power Internet of things technology.
Background
Foreign countries have been applying phase modulation machine remote fault maintenance systems to improve the operation and maintenance level of phase modulation machines from the 50 s of the 20 th century. The national phase modulator remote fault maintenance system such as Sweden, Argentina, Canada, Egypt, Brazil and the like is widely applied to remote transmitting and receiving end transformer substations of large-scale hydropower bases. The intelligent energy consumption and reliability analysis is developed on-line technology, research and development at home and abroad have a certain history, and a phase modulation unit monitoring and diagnosis expert system is developed in the United states in the early 80 s of the 20 th century. By the end of the 80 s of the 20 th century, the American Power research institute (EPRI) developed a fault monitoring and diagnosis center for Eddystone power stations, and the center can monitor and diagnose all equipment of a whole station, so that the equipment availability of the whole plant is improved, and the purposes of improving the reliability of a unit, reducing maintenance cost and prolonging the service life of the unit are achieved. Particularly, it is worth mentioning that a great deal of research work is done in japan on the diagnosis of the remaining life of the electric power equipment, and many diagnostic methods are proposed. In the beginning of the 20 th century and the 80 s, mitsubishi corporation of japan developed an expert system for phase modulation unit fault diagnosis. By the beginning of the 90 s of the 20 th century, Hitachi, Japan, developed an expert system for directing the operation and maintenance of power stations. The equipment state monitoring and diagnosing technology is developed rapidly under the urgent demand of the market, artificial intelligence and expert systems are successfully applied to the power station state monitoring and fault diagnosing technology since 20 century and 80 s abroad, and huge economic benefits are generated, such as: the Westing-house company (Westing-house) establishes a power plant data PDC and a diagnosis operation center DOC, and corresponding intelligent diagnosis systems such as a steam turbine and a generator; power plant monitoring and diagnostic center of the american power research institute (EPRI); corresponding systems have also been developed by siemens germany and ABB. Therefore, the major direction for future development of the phase modifier safety early warning system is professional, intelligent and practical.
The ubiquitous power internet of things technology is an intelligent service system which is characterized by comprehensive state sensing, efficient information processing and convenient and flexible application, and fully applies modern information technologies such as 'cloud moving intelligence' and advanced communication technologies around each link of a power system to realize the mutual object interconnection and man-machine interaction in each link of the power system. With the improvement of informatization, the thermal power plants establish DCS data information systems based on internal local area networks, and form data banks covering the whole production process of the plants, but at present, advanced data analysis and statistical means are not adopted for classifying, summarizing and analyzing data, so that the data cannot be used deeply, and a data disaster is caused.
Disclosure of Invention
The invention aims to provide a phase modifier remote diagnosis system based on the ubiquitous power Internet of things technology, which takes a power grid as a hub, constructs a data center through technologies such as a data warehouse and data replication and the like, and realizes sharing and exchange of all information data; the method comprises the steps of performing data mining on production data by applying an advanced big data technology, and constructing a reliable, safe and linearly expanded big data system foundation; processing abnormal values, data standardization, data generalization and data aggregation are realized through data conversion, and then reasoning work of a fault diagnosis knowledge base is realized; the method has the advantages that various indexes in operation, production and management of the phase modulator are subjected to integrated index analysis by using a data warehouse and a data mining technology, a safety early warning evaluation system based on mass data is established, the healthy operation of the phase modulator can be guaranteed by combining a system operation state estimation technology, and refined prediction and coordination control are realized.
In order to achieve the purpose, the invention provides a phase modulation machine remote diagnosis system based on the ubiquitous power internet of things technology, which comprises an equipment ledger database, a standard database, a historical database, an evaluation model database, a fault diagnosis model database, a remote expert diagnosis database, online monitoring equipment, a workflow engine, a communication device and a management server, wherein the equipment ledger database is used for storing a phase modulation machine remote diagnosis information;
the workflow engine is built in the management server and is used for establishing a workflow model, defining roles and realizing the remote diagnosis process control of the phase modulator by adopting a process controller;
the equipment ledger database is used for recording static and dynamic information, factory information and equipment parameter information of each electrical equipment and performing KKS coding on the electrical equipment;
the standard database is used for establishing and storing the detection period, the detection time, the data evaluation standard and the data grade of each electrical device;
the on-line monitoring equipment is connected with the management server through the communication device and used for acquiring the operation parameters and the state data of the on-site electrical equipment off line and on line and sending the acquired operation parameters and the state data of the electrical equipment to the historical database and the management server;
the historical database is used for storing operation parameters and state data acquired by the corresponding online monitoring equipment and trend analysis results made by the management server according to the operation parameters and the state data acquired by the online monitoring equipment;
the fault diagnosis model database is used for storing diagnosis models, inference engine rules and mechanisms of all online monitoring data;
the expert remote diagnosis database is used for storing the operation parameters and the state data of the electrical equipment and the corresponding diagnosis result;
the management server is embedded with fault diagnosis models of all electrical equipment, and is used for combining with an expert remote diagnosis database, calling corresponding diagnosis models and inference machines from the fault diagnosis model database, processing imported operation parameters and state data of the field electrical equipment so as to complete state diagnosis and fault early warning of each electrical equipment, and outputting corresponding diagnosis results.
In a further embodiment, the communication device includes 4G, WiFi, USB.
In a further embodiment, the on-line monitoring equipment comprises a phase modulator shaft/tile vibration monitoring module, a phase modulator partial discharge, shaft voltage, turn-to-turn short circuit and end vibration monitoring module, an oil on-line state monitoring module and a cooling system monitoring module.
In a further embodiment, the management server stores and processes data in the equipment ledger database, the standard database, the historical database, the evaluation model database, the fault diagnosis model database and the remote expert diagnosis database in the form of a data warehouse.
In a further embodiment, the online monitoring device comprises an industrial inspection device, and the industrial inspection device comprises: the device comprises one or more of vibration monitoring, oil monitoring, shaft voltage monitoring, temperature monitoring, oil ferrograph, current monitoring, granularity counting and the like.
In a further embodiment, the fault diagnosis model diagnoses faults which have occurred and which may occur based on a method of combining fault diagnosis rules and fault cases.
In a further embodiment, the format of the fault diagnosis rule is as follows:
if < precondition > then < conclusion/action > CF
r(confidence of rule)
The precondition part of the rule is the symptoms of the unit, including single symptoms and combined symptoms; the conclusion part of the rule is a certain failure of the device; the action score is an action or treatment suggested; the reliability of the rules themselves is given by domain experts, and the reliability of the conclusions is obtained by calculation, wherein, for a diagnostic rule containing symptoms with an and relationship, the fault reliability CF takes the product of the minimum value of the symptom reliability and the rule reliability:
CF＝CF
r×min(CF
S)
for a fault model with a plurality of diagnostic rules, the fault reliability takes the maximum value of the reliability of all diagnostic rules.
In a further embodiment, the inference engine uses a forward inference mode to deduce fault states, including determining existing faults, eliminating non-existing faults, and possible existing faults that need further confirmation.
In a further embodiment, the method for creating the fault diagnosis model includes:
and mining fault data with the same fault mechanism and different performances from discrete historical data of a plurality of similar devices, classifying, summarizing and reproducing the fault data, and finally forming a corresponding fault diagnosis model.
The phase modulation remote diagnosis system mainly applies a sensor technology, an internet technology, a cloud computing technology, a visual intelligent diagnosis technology and a reliability management technology to realize remote monitoring of the phase modulation of the power grid converter station, and comprises the steps of phase modulation operation parameter monitoring, reactive power remote control, equipment operation state remote monitoring, machine and grid coordinated operation state monitoring, and reliability management of electrical equipment, a lubricating system and a cooling system. The phase modulation machine remote diagnosis system is used for storing and processing data in the form of a data warehouse. The data warehouse collects and arranges the data of the whole phase modulator according to a certain data model, and can provide completely consistent business report data across departments according to the requirements of each functional module; providing high-quality information data, high-efficiency data organization form and high query efficiency for analysis type processing; and a conclusion which is instructive to the business is generated through data analysis and reasoning of the data warehouse, so that comprehensive data support is provided for leader decision making. The method can timely and accurately diagnose the real-time data of the phase modulator, and establishes an early warning mechanism and a maintenance strategy based on data mining of historical data in a big data mode.
Compared with the prior art, the technical scheme of the invention has the following remarkable beneficial effects:
(1) set up a series of functions such as shafting monitoring, fluid on-line monitoring, cooling system monitoring, axle current monitoring, make comprehensive diagnostic analysis to the camera system through big data analysis, expert's algorithm, and the contrast of multidimension degree multiparameter, TDM on the market relatively, this application has effectively promoted in the aspect of integrated intelligent fault diagnosis and long-range distributed fault diagnosis network, and diagnostic effect is better.
(2) The phase modulator remote diagnosis platform provided by the invention is used for establishing a data center by taking a power grid as a hub and adopting technologies such as a data warehouse, data replication and the like under the background of the ubiquitous power Internet of things technology, so that the sharing and exchange of all information data are realized; and (3) data mining is carried out on the production data by adopting an advanced big data technology, and a reliable, safe and linearly expanded big data system foundation is constructed.
(3) And processing abnormal values, data standardization, data generalization and data aggregation are realized through data conversion, and the reasoning work of the fault diagnosis knowledge base is further realized.
(4) The method has the advantages that various indexes in operation, production and management of the phase modulator are subjected to integrated index analysis by using a data warehouse and a data mining technology, a safety early warning evaluation system based on mass data is established, the healthy operation of the phase modulator can be guaranteed by combining a system operation state estimation technology, and refined prediction and coordination control are realized.
(5) Practice proves that the vibration monitoring, oil monitoring, shaft voltage monitoring, temperature monitoring, oil ferrograph, current monitoring, granularity counting and maintaining system and method provided by the invention are realized by adopting a comprehensive means for camera state data acquisition, fault diagnosis and maintenance in a three-dimensional crossing manner, so that the equipment reliability can be improved, the phase modulator operation and maintenance cost of a factory can be reduced, and the production efficiency can be improved.
(6) And a workflow control flow is adopted, and an automatic data analysis and storage scheme is combined, so that the monitoring efficiency of the equipment and the reutilization rate of data are effectively improved.
It should be understood that all combinations of the foregoing concepts and additional concepts described in greater detail below can be considered as part of the inventive subject matter of this disclosure unless such concepts are mutually inconsistent. In addition, all combinations of claimed subject matter are considered a part of the presently disclosed subject matter.
The foregoing and other aspects, embodiments and features of the present teachings can be more fully understood from the following description taken in conjunction with the accompanying drawings. Additional aspects of the present invention, such as features and/or advantages of exemplary embodiments, will be apparent from the description which follows, or may be learned by practice of specific embodiments in accordance with the teachings of the present invention.
Drawings
The drawings are not intended to be drawn to scale. In the drawings, each identical or nearly identical component that is illustrated in various figures may be represented by a like numeral. For purposes of clarity, not every component may be labeled in every drawing. Embodiments of various aspects of the present invention will now be described, by way of example, with reference to the accompanying drawings, in which:
fig. 1 is a schematic structural diagram of a phase modulation machine remote diagnosis system based on the ubiquitous power internet of things technology.
Fig. 2 is a schematic work flow diagram of the phase modulation machine remote diagnosis system based on the ubiquitous power internet of things technology.
Fig. 3 is a schematic diagram of the forward reasoning of phase modulator faults of the present invention.
Detailed Description
In order to better understand the technical content of the present invention, specific embodiments are described below with reference to the accompanying drawings.
Detailed description of the preferred embodiment
With reference to fig. 1 and 2, the invention provides a phase modulation machine remote diagnosis system based on a ubiquitous power internet of things technology, which comprises an equipment ledger database, a standard database, a historical database, an evaluation model database, a fault diagnosis model database, a remote expert diagnosis database, online monitoring equipment, a workflow engine, a communication device and a management server.
The workflow engine is built in the management server and used for establishing a workflow model, defining roles and realizing the remote diagnosis process control of the phase modulator by adopting a process controller.
And the equipment ledger database is used for recording static and dynamic information, factory information and equipment parameter information of each electrical equipment and carrying out KKS coding on the electrical equipment.
And the standard database is used for establishing and storing the detection period, the detection time, the data evaluation standard and the data grade of each electrical device.
The on-line monitoring equipment is connected with the management server through the communication device and used for acquiring the operation parameters and the state data (such as vibration, oil, shaft voltage, partial discharge, end vibration, turn-to-turn short circuit and the like) of the on-site electrical equipment off line and on line, and sending the acquired operation parameters and the state data of the electrical equipment to the historical database and the management server to realize the functions of processing, recording, analyzing, displaying, downloading and calling the relevant data of the camera system.
Preferably, the communication device comprises 4G, WiFi and USB.
The on-line monitoring equipment provided by the invention can effectively monitor the phase modulation camera system from a plurality of angles related to the phase modulation machine system, for example, the on-line monitoring equipment comprises a phase modulation machine shaft/tile vibration monitoring module, a phase modulation machine partial discharge, shaft voltage, turn-to-turn short circuit and end part vibration monitoring module, an oil on-line state monitoring module and a cooling system monitoring module, wherein the phase modulation machine shaft/tile vibration monitoring module, the phase modulation machine partial discharge, shaft voltage, turn-to-turn short circuit and end part vibration monitoring module respectively carry out effective monitoring on the phase modulation machine system from a plurality of angles such as vibration, electrical parameters, a lubricating oil.
To achieve this, the online monitoring device may comprise an industrial inspection tour device comprising: the device comprises one or more of vibration monitoring, oil monitoring, shaft voltage monitoring, temperature monitoring, oil ferrograph, current monitoring, granularity counting and other online acquisition devices, so that the monitoring data can be acquired smoothly.
The historical database is used for storing the operation parameters and the state data which are collected by the corresponding online monitoring equipment and the trend analysis result which is made by the management server according to the operation parameters and the state data which are collected by the online monitoring equipment.
And the fault diagnosis model database is used for storing diagnosis models, inference engine rules and mechanisms of all online monitoring data.
And the expert remote diagnosis database is used for storing the operating parameters and the state data of the electrical equipment and the corresponding diagnosis result.
Preferably, the management server stores and processes data in an equipment ledger database, a standard database, a history database, an evaluation model database, a fault diagnosis model database, and a remote expert diagnosis database in the form of a data warehouse.
The phase modulation machine remote diagnosis system stores and processes data in the form of a data warehouse. The data warehouse collects and arranges the data of the whole phase modulator according to a certain data model, and can provide cross-department and completely consistent business report data according to the requirements of each functional module; providing high-quality information data, high-efficiency data organization form and high query efficiency for analysis type processing; and a conclusion which is instructive to the business is generated through data analysis and reasoning of the data warehouse, so that comprehensive data support is provided for leader decision making. The method can timely and accurately diagnose the real-time data of the phase modulator, and establishes an early warning mechanism and a maintenance strategy based on data mining of historical data in a big data mode.
Preferably, the data of the database can be called by each functional module in the phase modulation machine remote diagnosis system so as to realize effective utilization of the data and synchronization and unification of the data between the databases.
The management server is embedded with fault diagnosis models of all electrical equipment, and is used for combining with an expert remote diagnosis database, calling corresponding diagnosis models and inference machines from the fault diagnosis model database, processing imported operation parameters and state data of the field electrical equipment so as to complete state diagnosis and fault early warning of each electrical equipment, and outputting corresponding diagnosis results.
Preferably, the method for creating the fault diagnosis model includes:
and mining fault data with the same fault mechanism and different performances from discrete historical data of a plurality of similar devices, classifying, summarizing and reproducing the fault data, and finally forming a corresponding fault diagnosis model.
In some examples, the on-line monitoring device can monitor the field device operation parameters and the device operation state (including vibration, oil, shaft voltage, partial discharge, end vibration and turn-to-turn short circuit) in real time, and realize the functions of processing, recording, analyzing, displaying and downloading the relevant data of the camera system.
(1) Phase modulator shaft/shoe vibration monitoring
The phase modulator shaft/tile vibration monitoring module is mainly used for deeply analyzing vibration data of a phase modulator in operation and acquiring vibration information including waveform, frequency spectrum, amplitude, phase and the like, so that data and related professional map tools are provided for professional fault diagnosis personnel, and the professional fault diagnosis personnel are assisted to deeply analyze the operation state of the phase modulator. Monitoring content of vibration state of phase modulator: the direct-current component of the shaft vibration sensor of the bearing X, Y is recorded in the cold state and the static state of the rotor of the phase modulator and is used as a reference value for real-time calculation of dynamic and static gaps such as the bearing gap, the sealing bush gap, the axial gap, the oil film thickness of the bearing and the like of the subsequent phase modulator. And the dynamic and static gaps such as shaft end sealing shoe gaps, bearing oil baffle gaps and the like can be approximately calculated by combining the vibration mode of the rotor.
(2) Phase modulator partial discharge, shaft voltage, turn-to-turn short circuit and end vibration monitoring
Through a sensor and installation technology, a signal processing technology, a hardware technology, a data communication technology, a data compression and storage technology, a fault diagnosis technology and the like, key parameters reflecting the state of the phase modulator are effectively obtained, processed and analyzed, and the condition of the phase modulator is analyzed, diagnosed and evaluated. The state of the phase modulator is identified in time, early fault signs of the phase modulator are found, and the fault reason, the severity and the development trend are judged, so that the hidden danger can be eliminated in time, and destructive accidents are avoided.
(3) Oil on-line state monitoring
Lubricating oil is blood of a machine, and machine health state monitoring based on the performance of the lubricating oil is an important means for visual maintenance. The frictional wear performance and the lubrication state of a machine are important constituents of the health state of the machine, the tribological state of the machine has time-varying and systematic dynamic characteristics, and the cumulative nature of wear causes the wear of the friction pair of the machine to be unrecoverable, and furthermore, the lubrication state of the friction portion is closely related to the wear state, and for this reason, it is necessary to grasp the real-time wear and lubrication state of the machine. The oil analyzer is mainly used for performing visual intelligent safety pre-control on the ferrograph, the viscosity and the moisture of the lubricating oil. An online oil monitoring and analyzing system is integrated by three monitoring sensors, namely an online ferrograph sensor, an online viscosity sensor and a trace moisture sensor. Through the combination of the sensors, an integrated sensor is formed, the wear state and the lubricating performance of major equipment are monitored in a multi-dimensional mode, and the judgment, the fault prediction, the service life analysis and the like of the tribological state of a machine are realized by applying an information fusion technology.
(4) Cooling system monitoring
Through the visual intelligent safety pre-control of the internal pump of the cooling water system, the water quality (PH value, conductivity, copper content, oxygen content and the like) and the water temperature, the insulation monitoring voltmeter of the phase modulator excitation circuit is matched with one-point grounding protection of a rotor, the internal and external relative humidity of the phase modulator is intelligently and safely pre-controlled, and faults such as blockage or water leakage and the like possibly existing in the phase modulator cooling system are remotely monitored. The fault information is timely pushed to a computer, a mobile phone and other mobile terminals, so that the working condition of the phase modulator cooling water system can be more intuitively known.
Correspondingly, the intelligent safety early warning and intelligent decision of the phase modulator adopted by the fault diagnosis module comprise:
(1) phase modulator vibration safety early warning
The change of various gaps of a bearing and a shafting is visually displayed by calculating various dynamic and static gaps of a camera shafting in real time, the vibration level of a unit is combined, the state of the shafting is automatically identified according to the ratio of the minimum gap to the corresponding position design gap, and the real-time display is carried out in different colors; establishing a phase modulator vibration fault model according to a fault mechanism and a field case, strictly distinguishing different types of faults with different properties by automatically identifying signal characteristics according to sufficiency and necessary conditions of the faults, realizing accurate judgment of the faults and providing a feasible vibration elimination measure;
(2) safety early warning for oil liquid and electric monitoring and cooling system
Researching an oil system online safety early warning technology based on an online ferrograph, viscosity and trace moisture sensor real-time data three-dimensional modeling and data processing technology; the online safety early warning technology for shaft grounding faults, friction, turn-to-turn short circuit, electric corrosion and bearing seat insulation based on real-time voltage monitoring data of a phase modulator RSV rotor shaft is researched; the on-line safety early warning technology of the cooling water system based on the internal pump of the cooling water system, water quality (PH value, conductivity, copper content, oxygen content and the like) and water temperature real-time data is researched.
(3) Remote fault diagnosis and intelligent decision-making for phase modulator
Based on a data mining technology and an expert knowledge base, the multi-time scale rapid safety risk early warning and state evaluation are carried out on the camera body and the auxiliary system thereof through fault model identification and credibility evaluation, and operation and maintenance personnel are assisted to make scientific operation and maintenance decisions.
In some examples, the fault diagnosis model diagnoses faults that have occurred and may occur based on a method that combines fault diagnosis rules and fault cases.
The research of the failure mechanism deeply reveals the necessity and the expression characteristics of the failure, shows the sufficient condition and the necessary condition of the failure and the essential difference between the failures, and has important guiding function for solving the practical problems. For a large number of similar devices, the probability of similar failures reaches over 80%. Therefore, the method based on the fault diagnosis rule and the fault case can be adopted to diagnose the faults which occur and are possible to occur.
Preferably, the format of the fault diagnosis rule is as follows:
if < precondition > then < conclusion/action > CF
r(confidence of rule)
The precondition part of the rule is the symptoms of the unit, including single symptoms and combined symptoms; the conclusion part of the rule is a certain failure of the device; the action score is an action or treatment suggested; the credibility of the rule is given by domain experts, and the credibility of the conclusion is obtained through calculation.
For example, one rule for diagnosing an imbalance fault is as follows:
if one frequency multiplication in the vibration frequency spectrum is larger
And the amplitude difference between the horizontal direction and the vertical direction is not great
And the amplitude is basically unchanged when the rotating speed is unchanged
And the phase of one frequency multiplication is basically unchanged when the rotating speed is unchanged
The mass imbalance CF
r＝0.95
For a diagnostic rule with an and relationship between the contained symptoms, the fault confidence CF takes the product of the minimum of the symptom confidence and the rule confidence:
CF＝CF
r×min(CF
S)
for a fault model with a plurality of diagnostic rules, the fault reliability takes the maximum value of the reliability of all diagnostic rules.
The main faults of the phase modifier include mass unbalance, thermal state unbalance, dynamic and static rubbing, bearing loosening, bearing bush abrasion, oil film oscillation, misalignment, asymmetric rotor rigidity, structural resonance, electromagnetic excitation and the like.
Forward reasoning is data-based reasoning that determines the presence of faults with certainty, eliminates non-presence faults, and fails to determine whether faults are present, based on the symptoms of the current unit, requiring further experimentation. The forward reasoning can effectively avoid misdiagnosis and missed diagnosis. In the current phase modulator fault diagnosis, fault data with the same fault mechanism and different performances are mined from discrete historical data of a large number of similar devices, and are classified, summarized and fault reappeared to finally form a certain fault diagnosis model and establish an expert knowledge base. Fig. 3 is a schematic diagram of one of the forward inferences.
The phase modulator fault diagnosis system based on rule and case forward reasoning performs data mining on production data by applying an advanced big data technology on the basis of establishing a data warehouse, constructs a reliable, safe and linearly expanded big data platform, performs unified management, realizes safe sharing of data resources and expands information display modes; according to a scientific fault diagnosis theory, faults are diagnosed from signal symptoms.
The design system architecture of the phase modulation remote diagnosis system is as follows.
The system main body program adopts a multilayer B/S architecture, the architecture of the whole system consists of a database server, a plurality of application servers, a Web server and a client, the mode of separating data, control and service is realized, and the system architecture is high in multiplexing and strictly hierarchically divided.
The database server supports a large mainstream database system; the application server supports a large-scale mainstream application server; the client supports a mainstream browser. The system is based on an SOA design mode, accords with J2EE specifications, adopts a middleware technology and a workflow technology, supports a component-based development mode, embodies the idea of 'server-side control', and has extremely strong scalability, expandability and easy maintainability, thereby being convenient for safety management.
The data management of the phase modulator remote diagnosis system is divided into a data source layer, an acquisition layer, a storage layer, a calculation layer, a model layer and an interface layer.
(1) Data source layer: the system platform data is from various effective data sources on site, such as a DCS/PMS system, a phase modulator vibration visual intelligent safety pre-control system, a phase modulator electrical visual intelligent safety pre-control system, a partial discharge sensor, an inter-turn short circuit sensor, an oil visual intelligent safety pre-control system, a third-party database and the like.
(2) A data acquisition layer: and the acquisition of the production process and historical data of the bottom layer system is realized by adopting an ODBC (optical distribution controller), OPC (optical proximity correction), PITOPI (particle optical top plane), Webservices or other acquisition modes with specific interfaces through a private network not lower than 5M. The system provides an advanced data integration method, supports data acquisition and combination from different types of databases such as a real-time database, a relational database and the like, and is open, so that system expansion and promotion in the future are facilitated. The system collects and writes data from different types into a specified relational database through an intelligent assembly, the collected data can be integrated and then directly issued, and a user can flexibly define a data integration mode. The system can integrate various data sources of real-time databases and relational databases such as a real-time system, an enterprise information management system and the like.
(3) A data storage layer: data collected by a data collection layer are stored in a real-time database and a relational database after being subjected to unified time scale, description and classification, and big data is selected as a distributed storage mode (HDFS and HBASE).
(4) Calculating a layer: the method takes memory calculation and flow calculation as cores, and realizes real-time reasoning analysis and scheduling service of large equipment amount through concurrent calculation.
(5) A model layer: and standard application and algorithm model components are solidified in the platform, and monitoring and diagnosis business processing is mainly carried out. And on the basis of the data storage layer, converting the data of the data storage layer into a data format required by each sub-module through the platform application module, and performing related business processing. And sending the intermediate result generated after the processing to a core diagnosis system for processing and early warning. And then, sending the analysis report and the result generated by each subsystem and the core diagnosis system to a data display layer, and pushing the analysis report and the result to each level of users for use. And simultaneously, an extensible model component is reserved, so that a user can conveniently define and customize the customized application and algorithm component.
The invention adopts a big data platform construction technology to create a phase modulation machine remote diagnosis system, and the big data platform construction technology comprises the following steps:
(1) data access techniques
The real-time one-way transmission technology of the unit data with low bandwidth and high frequency, which is suitable for the DCS system, is adopted, the technical problem of DCS data acquisition under different types of unit equipment and different control system brands is solved, and the rapid real-time refreshing of the DCS data is realized; and (4) building a data center to establish a data base for centralized management, unified allocation and real-time online monitoring of resources.
(2) Data transfer technique
By adopting a data transmission and processing technology in a network or equipment interruption state, various types of data which are invalid, unreasonable, not refreshed and the like are analyzed, counted and repaired in real time.
(3) Big data platform building technology
The method comprises the steps of applying an advanced big data technology, constructing a reliable, safe and linearly expanded big data platform, managing uniformly, realizing safe sharing of data resources and expanding information display modes; according to the national network related technical standards and specifications, a distributed cluster file system is built by utilizing the advanced Internet of things technology, cloud computing and big data technology, so that the resource utilization rate of a server and a storage system is greatly improved, and the system construction cost is reduced.
(4) Data mining techniques
Detecting whether the real-time data accords with the current operating condition of the phase modulator or not based on a multivariable data verification technology, and ensuring that unqualified data is removed in later-stage model calculation; and performing integrated index analysis on various indexes in the operation, production and management of the camera by using a data mining technology, and establishing a safety early warning evaluation system based on mass data.
(5) Network data security techniques
Establishing an integrated physical network structure of a converter station production area, a power grid dispatching area, a power grid office area and the like by combining a ubiquitous power Internet of things strategy, realizing a safe and controllable network control and deployment scheme of each interval and forming a network safety strategy for a supervision environment; by adopting the one-way transmission serial port transmission equipment and the access standard, the problem of one-way transmission of data of the DCS is solved by utilizing the Internet of things technology, and the safety of the DCS is ensured.
Detailed description of the invention
A phase modulator remote diagnosis system of a certain power plant A is used for monitoring the running state of a certain steam turbine, and comprises the steps of realizing comprehensive monitoring on vibration, oil, electric monitoring, a cooling system and turn-to-turn short circuit. In the experimental process, when the #2 unit is loaded with 316MW, the opening degree of the GV2 is 17%, and the rest of the adjusting doors are fully opened. In the process of load reduction, when GV2 is completely closed and GV1 is closed to 21.6%, an operator monitors that the 1X/1Y shaft vibration quickly climbs, and measures such as load reduction, single valve cutting and the like are taken, when the load is reduced to 258MW, #1 watt vibration 21 mu m, 1X shaft vibration 80 mu m, 1Y shaft vibration 93 mu m, and 1 watt shaft vibration exceeds an early warning value.
According to a phase modulator remote diagnosis system, a 1 watt shaft vibration waveform spectrogram is analyzed, and the frequency spectrum has rich higher harmonic components besides the working frequency of a rotor, and belongs to typical nonlinear dynamic and static rub. Before the unit trips, the main steam pressure, the temperature, the vacuum, the lubricating oil temperature and the oil pressure are all in a normal range, and after the unit trips, the vibration is slightly increased in the idle running process compared with the past, which indicates that the rotor has transient thermal bending caused by collision and abrasion. The phenomenon is integrated to judge the reason of dynamic and static rubbing is steam flow disturbance. The staff has effectively realized the demonstration of unit vibration characteristic according to phase modulation machine remote diagnosis system, and the staff of being convenient for carries out the maintenance of machine at the more accurate judgement unit fault characteristic of scene.
Detailed description of the preferred embodiment
A remote diagnosis system for phase modulators of a power plant B is used for monitoring a coal-fired unit. In the experimental process, at a certain moment, the #5 machine set #4 watt shaft vibration starts to rise, the back #4 watt shaft vibration is large, the ultrasonic low warning value is high, and the diagnosis system prompts and gives an alarm. And immediately checking that the operating parameters such as vacuum, lubricating oil temperature, bearing temperature and the like are normal after the operator finds out. Looking up a historical curve to find that the outlet oil temperature of the A, B lubrication oil cooler is 37.6 ℃ and 36.5 ℃ (the control range is 35-45 ℃ according to the specification of a manufacturer) respectively and is close to the lower limit of the control value; meanwhile, 4W of X-axis vibration is in an inverse relation with the reduction of the oil temperature, and when the oil temperature is lower than 38 ℃, the 4X-axis amplitude value fluctuation is increased; the low temperature of the lubricating oil can cause the oscillation of an oil film and cause the vibration of a bearing bush of the steam turbine. And then the adjustment and the timely treatment are carried out, so that one-time non-stop accidents are avoided.
In this disclosure, aspects of the present invention are described with reference to the accompanying drawings, in which a number of illustrative embodiments are shown. Embodiments of the present disclosure are not necessarily defined to include all aspects of the invention. It should be appreciated that the various concepts and embodiments described above, as well as those described in greater detail below, may be implemented in any of numerous ways, as the disclosed concepts and embodiments are not limited to any one implementation. In addition, some aspects of the present disclosure may be used alone, or in any suitable combination with other aspects of the present disclosure.
Although the present invention has been described with reference to the preferred embodiments, it is not intended to be limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the invention. Therefore, the protection scope of the present invention should be determined by the appended claims.
Claims (9)
1. A phase modulation machine remote diagnosis system based on the ubiquitous power Internet of things technology is characterized by comprising an equipment ledger database, a standard database, a historical database, an evaluation model database, a fault diagnosis model database, a remote expert diagnosis database, online monitoring equipment, a workflow engine, a communication device and a management server;
the workflow engine is built in the management server and is used for establishing a workflow model, defining roles and realizing the remote diagnosis process control of the phase modulator by adopting a process controller;
the equipment ledger database is used for recording static and dynamic information, factory information and equipment parameter information of each electrical equipment and performing KKS coding on the electrical equipment;
the standard database is used for establishing and storing the detection period, the detection time, the data evaluation standard and the data grade of each electrical device;
the on-line monitoring equipment is connected with the management server through the communication device and used for acquiring the operation parameters and the state data of the on-site electrical equipment off line and on line and sending the acquired operation parameters and the state data of the electrical equipment to the historical database and the management server;
the historical database is used for storing operation parameters and state data acquired by the corresponding online monitoring equipment and trend analysis results made by the management server according to the operation parameters and the state data acquired by the online monitoring equipment;
the fault diagnosis model database is used for storing diagnosis models, inference engine rules and mechanisms of all online monitoring data;
the expert remote diagnosis database is used for storing the operation parameters and the state data of the electrical equipment and the corresponding diagnosis result;
the management server is embedded with fault diagnosis models of all electrical equipment, and is used for combining with an expert remote diagnosis database, calling corresponding diagnosis models and inference machines from the fault diagnosis model database, processing imported operation parameters and state data of the field electrical equipment so as to complete state diagnosis and fault early warning of each electrical equipment, and outputting corresponding diagnosis results.
2. The system for remotely diagnosing the phase modulator based on the ubiquitous power internet of things technology as claimed in claim 1, wherein the communication device comprises 4G, WiFi or USB.
3. The phase modulation machine remote diagnosis system based on the ubiquitous power internet of things technology as claimed in claim 1, wherein the online monitoring equipment comprises a phase modulation machine shaft/tile vibration monitoring module, a phase modulation machine partial discharge, shaft voltage, turn-to-turn short circuit and end vibration monitoring module, an oil online state monitoring module and a cooling system monitoring module.
4. A phase modulation machine remote diagnosis system based on the ubiquitous power internet of things technology as claimed in claim 1, wherein the management server stores and processes data in an equipment ledger database, a standard database, a history database, an evaluation model database, a fault diagnosis model database, a remote expert diagnosis database in the form of a data warehouse.
5. The phase modulation machine remote diagnosis system based on the ubiquitous power internet of things technology of claim 1, wherein the online monitoring equipment comprises industrial inspection equipment, and the industrial inspection equipment comprises: the device comprises one or more of vibration monitoring, oil monitoring, shaft voltage monitoring, temperature monitoring, oil ferrograph, current monitoring, granularity counting and the like.
6. The system for remotely diagnosing the phase modulator based on the ubiquitous power internet of things technology as claimed in claim 1, wherein the fault diagnosis model diagnoses faults which have occurred and are likely to occur based on a method combining fault diagnosis rules and fault cases.
7. The ubiquitous power internet of things technology-based phase modulation machine remote diagnosis system according to claim 6, wherein the fault diagnosis rule is in a format of:
if < precondition > then < conclusion/action > CF
r(confidence of rule)
The precondition part of the rule is the symptoms of the unit, including single symptoms and combined symptoms; the conclusion part of the rule is a certain failure of the device; the action score is an action or treatment suggested; the reliability of the rules themselves is given by domain experts, and the reliability of the conclusions is obtained by calculation, wherein, for a diagnostic rule containing symptoms with an and relationship, the fault reliability CF takes the product of the minimum value of the symptom reliability and the rule reliability:
CF＝CF
r×min(CF
S)
for a fault model with a plurality of diagnostic rules, the fault reliability takes the maximum value of the reliability of all diagnostic rules.
8. A phase modulation machine remote diagnosis system based on ubiquitous power internet of things technology as claimed in claim 1, wherein the inference machine employs forward reasoning to deduce fault states, including fault determination, fault elimination and fault possibility requiring further confirmation.
9. The system for remotely diagnosing the phase modulation machine based on the ubiquitous power internet of things technology according to claim 1, wherein the method for creating the fault diagnosis model comprises the following steps:
and mining fault data with the same fault mechanism and different performances from discrete historical data of a plurality of similar devices, classifying, summarizing and reproducing the fault data, and finally forming a corresponding fault diagnosis model.
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