CN107315405B

CN107315405B - Internet-based remote diagnosis system and method for unit self-starting control process

Info

Publication number: CN107315405B
Application number: CN201710751537.5A
Authority: CN
Inventors: 仵华南; 李华东; 张鹏; 王国成; 韩庆华; 韩江; 赵然; 吴迪; 李蕾; 王文青
Original assignee: Shandong Zhongshi Yitong Group Co Ltd
Current assignee: Shandong Zhongshi Yitong Group Co Ltd
Priority date: 2017-08-28
Filing date: 2017-08-28
Publication date: 2023-12-12
Anticipated expiration: 2037-08-28
Also published as: CN107315405A

Abstract

The invention discloses a remote diagnosis system and a remote diagnosis method for a unit self-starting control process based on the Internet, which are used for collecting starting process data in the unit self-starting control process, processing the starting process data to obtain data to be diagnosed, and sending the data to be diagnosed to a remote diagnosis data server through a local area network; the remote diagnosis data server carries out induction processing on the data to be diagnosed; sending the data to be diagnosed after induction processing to a remote expert diagnosis module through the Internet; and the remote expert diagnosis module acquires diagnosis results of the unit self-starting control according to the data to be diagnosed and expert experience model data, and gives measures according to the diagnosis results. The invention is convenient for diagnosing and evaluating the problems and the performance of the unit self-starting control process, overcomes the defect of the current remote diagnosis mode on the description accuracy of fault problem information, reduces the information asymmetry problem and the workload of fault and performance diagnosis, and increases the remote diagnosis accuracy and the rapidity.

Description

Internet-based remote diagnosis system and method for unit self-starting control process

Technical Field

The invention relates to the field of remote diagnosis of unit self-starting control, in particular to a diagnosis system and a method for remotely monitoring, diagnosing problems and analyzing performance indexes of a unit self-starting control process based on the Internet.

Background

The self-starting control of a large-sized turbine unit is developed in a domestic crossing mode, and the self-starting control of the unit is full-coverage automatic control and relates to control units such as a sequential control system, an analog quantity control closed-loop system, an alarm system, a digital electrohydraulic control system and the like. The unit self-starting control equipment is more, the related system is wide, the control coupling is strong, the control process is sometimes restricted by fault factors, and some control fault processing analysis and evaluation are complicated and urgent, so that an external expert with high technical level is usually required for diagnosis and evaluation. The current remote guided diagnostics generally take the following form:

(1) And the field technicians summarize faults occurring in the self-starting process of the unit, communicate and report to remote experts through contact modes such as a network, and the experts give processing suggestions according to the report data. The method has the defects that in the process of controlling the self-starting of the unit by field technicians, due to the fact that the technical understanding of difference factors is poor, description accuracy of data with fault problems is poor, data obtained by remote experts are asymmetric, and timely and reasonable diagnosis suggestions and treatment measures cannot be given.

(2) And the remote expert performs data summarization on the self-starting control process of the unit through the existing DCS remote diagnosis system of the distributed control system, and performs remote diagnosis and evaluation on fault problems and performance. The unit self-starting control process comprises more inclusion systems and stronger coupling, remote experts carry out fault problem data summarization analysis through a DCS remote diagnosis system, the related workload is larger, and the accuracy and the applicability of fault problems and performance diagnosis in the unit self-starting control process are restricted.

In summary, in order to adapt to the development of the unit self-starting control technology, to facilitate the diagnosis and evaluation of the problems and performance of the unit self-starting control process, make up for the shortages of the current remote diagnosis mode, reduce the data asymmetry problems and workload of fault and performance diagnosis, and greatly require a convenient and intelligent remote diagnosis system and method for the unit self-starting control process.

Disclosure of Invention

In order to overcome the defects of the prior art, the invention provides a remote diagnosis system and a remote diagnosis method for a unit self-starting control process based on the Internet, which are used for carrying out remote diagnosis on fault problems and performance evaluation of the unit self-starting control process, and the Internet is used as a transmission channel, so that the remote diagnosis system is used for providing important data for the self-starting control.

The technical scheme adopted by the invention is as follows:

an internet-based remote diagnosis system for a unit self-starting control process is characterized by comprising:

the data acquisition module is used for acquiring starting process data in the self-starting control process of the unit;

the data processing module is used for processing the starting process data to obtain data to be diagnosed and sending the data to a remote diagnosis data server through a local area network;

the remote diagnosis data server is used for receiving the data to be diagnosed and the starting process data through the local area network, summarizing the received data to be diagnosed, displaying the data on a diagnosis interface, receiving an access request of the remote expert diagnosis module, verifying the access request, and if the access request passes, transmitting the summarized data to be diagnosed to the remote expert diagnosis module;

and the remote expert diagnosis module is used for sending an access request to a remote diagnosis data server through the Internet, receiving data to be diagnosed sent by the remote diagnosis data server, and analyzing the fault problem of the unit self-starting control process according to the data to be diagnosed.

Further, the data acquisition module includes:

the unit self-starting and stopping control unit is used for collecting state data of a step sequence monitoring area in the unit self-starting control process;

The sequence control unit is used for collecting sequential control fault alarm data in the unit self-starting control process;

the data acquisition unit is used for acquiring parameter out-of-limit alarm data in the self-starting control process of the unit;

and the database is used for storing common parameter data in the self-starting control process of the unit.

Further, the data processing module includes:

the unit self-starting step process monitoring data processing unit is used for receiving the step monitoring area state data collected by the unit self-starting stop control unit and carrying out induction processing on unit self-starting breakpoint process information according to the step monitoring area state data;

the unit self-starting diagnosis alarm data processing unit is used for receiving the sequential control fault alarm data collected by the sequential control unit and the parameter out-of-limit alarm data collected by the data collection unit, judging whether faults occur in the unit self-starting process according to the sequential control fault alarm data and the parameter out-of-limit alarm data, and sending fault alarm signals if faults occur;

the unit self-starting key technology diagnosis data processing unit is used for receiving the parameter out-of-limit alarm data acquired by the data acquisition unit and the common parameter data stored in the database, and acquiring key technology diagnosis parameter data according to the parameter out-of-limit alarm data and the common parameter data;

The unit self-starting performance parameter diagnosis data processing unit is used for receiving the parameter out-of-limit alarm data acquired by the data acquisition unit and calculating and processing performance parameter index data in the unit self-starting process according to the parameter out-of-limit alarm data;

and the custom curve trend group data processing unit is used for receiving the common parameter data stored in the database, taking the common parameter data as a data source of the custom curve trend group, and custom drawing the parameter curve group according to the common parameter data.

Further, the remote diagnosis data server comprises a controller, a memory and a display module, wherein the controller is used for carrying out induction processing on received data to be diagnosed and storing the data to be diagnosed in the memory, and the display module is used for displaying the data to be diagnosed after induction processing;

the remote expert diagnostic module includes:

the remote mobile expert diagnosis end is used for accessing a remote diagnosis data server through a wireless network, acquiring data to be diagnosed in the remote diagnosis data server, and analyzing fault problems of the unit self-starting control process according to the data to be diagnosed;

and the remote fixed expert diagnosis end is connected with the Internet through the network router to remotely access the remote diagnosis data server, acquires data to be diagnosed in the remote diagnosis data server, and analyzes the fault problem of the unit self-starting control process according to the data to be diagnosed.

Further, the system also comprises a network transmission device, wherein the network transmission device comprises a first network architecture and a second network architecture, and the first network architecture is used for establishing a local area network between the data processing module and the remote diagnosis data server, and comprises an Ethernet switch, a firewall and an isolation lock; the second network architecture is configured to establish a VPN connection between the remote expert diagnostic module and the remote diagnostic data server, including a VPN router and a switch.

A remote diagnosis method for a self-starting control process of a unit based on the Internet comprises the following steps:

collecting starting process data in a self-starting control process of the unit, wherein the starting process data comprises step sequence monitoring area state data, sequential control fault alarm data, parameter out-of-limit alarm data and common parameter data;

processing the starting process data through a data processing module to obtain data to be diagnosed, wherein the data to be diagnosed comprises step sequence monitoring area state data, alarm data, key technology related data and performance parameter calculation data;

establishing a local area network between the data processing module and the remote diagnosis data server, and sending the data to be diagnosed to the remote diagnosis data server through the local area network;

The remote diagnosis data server carries out induction processing on the data to be diagnosed, and displays the data information to be diagnosed on a diagnosis interface of the remote diagnosis data server;

establishing VPN connection between a remote expert diagnosis module and a remote diagnosis data server, and sending an access request to the remote diagnosis data server by the remote expert diagnosis module through the Internet;

the remote diagnosis data server receives the access request of the remote expert diagnosis module and verifies the authority of the remote expert diagnosis module, and if the authority passes the verification, the remote diagnosis data server responds to the access request of the remote expert diagnosis module;

the remote expert accesses the remote diagnosis data server through the remote expert diagnosis module, obtains the data information to be diagnosed from the diagnosis interface of the remote diagnosis data server, and performs fault diagnosis in an online evaluation analysis and fault problem backtracking analysis mode.

Further, the specific process of processing the starting process data to obtain the data to be diagnosed is as follows:

acquiring step sequence monitoring area state data from a unit self-starting and stopping control unit through a unit self-starting step sequence process monitoring data processing unit, and carrying out induction processing on unit self-starting breakpoint process information according to the step sequence monitoring area state data;

Acquiring sequential control fault alarm data and parameter out-of-limit alarm data from a sequential control unit and a data acquisition unit through a unit self-starting diagnosis alarm data processing unit, judging whether faults occur in the unit self-starting process according to the sequential control fault alarm data and the parameter out-of-limit alarm data, and sending a fault alarm signal if faults occur;

acquiring parameter out-of-limit alarm data and common parameter data from a data acquisition unit and a database by a unit self-starting key technology diagnosis data processing unit, and acquiring key technology diagnosis parameter data according to the parameter out-of-limit alarm data and the common parameter data, wherein the key technology diagnosis parameter data comprises fan parallel function diagnosis parameter data, automatic grid-connected function diagnosis parameter data, dry-wet state conversion function diagnosis parameter data and feed pump parallel function diagnosis parameter data;

acquiring parameter out-of-limit alarm data from a data acquisition unit through a unit self-starting performance parameter diagnosis data processing unit, and carrying out logic statistics calculation on performance parameter index data in the unit self-starting process according to the parameter out-of-limit alarm data, wherein the performance parameter index data comprises unit fault times, water supplementing amount, fuel quantity and fuel quantity;

And acquiring common parameter data from the database through the custom curve trend group data processing unit, and custom drawing a parameter curve group according to the common parameter data.

Further, the diagnosis interface of the remote diagnosis data server comprises a step sequence monitoring diagnosis module, a custom curve group diagnosis module, a fault alarm diagnosis module, a performance parameter diagnosis module and a unit self-starting control key technology diagnosis module.

Further, the specific process of diagnosing by the remote expert in the starting process by adopting an online evaluation analysis mode through the remote expert diagnosis module is as follows:

in the self-starting process of the unit, an expert accesses a remote diagnosis data server through a remote expert diagnosis module, sequentially starts a breakpoint 1, a breakpoint 2, a breakpoint 3, a breakpoint 4, a breakpoint 5 and a breakpoint 6 of a sequence monitoring diagnosis module on a diagnosis interface of the remote diagnosis data server, starts sequential control faults and parameter out-of-limit fault data in the starting process according to the breakpoints 1, the breakpoints 3, the breakpoints 4, the breakpoints 5 and the breakpoints 6 displayed by a fault alarm diagnosis module, and carries out fault cause real-time analysis by adding diagnosis data trends through a custom curve group diagnosis module;

after the unit is started automatically, a remote expert evaluates the diagnosis according to a parameter stick diagram of a performance parameter diagnosis module on a diagnosis interface of a remote diagnosis data server, analyzes consumption values of water supplementing quantity, fuel quantity and fuel quantity in each starting stage according to a performance parameter diagnosis trend curve set of the performance parameter diagnosis module on a display interface of the remote diagnosis data server, gives an energy-saving suggestion, and gives a targeted optimization suggestion according to statistics of failure times.

Further, the specific process of diagnosing by the remote expert in the starting process by adopting the fault problem backtracking analysis mode through the remote expert diagnosis module is as follows:

the remote expert searches the specific type and the specific time period of occurrence of the fault according to the diagnostic parameter trend curve and the fault alarm information on the diagnostic interface of the remote diagnostic data server, and performs backtracking analysis according to the fault; if the fault belongs to one of fan parallel control, automatic grid-connected control, dry-wet state conversion control and water supply pump parallel control in the key technology of the unit self-starting control, rapidly calling out diagnostic parameter trend curve data information from a key technology diagnostic area on a diagnostic interface of a remote diagnostic data server for fault analysis; if the fault does not belong to the key technical control, an expert defines a relevant data curve in the custom curve trend group according to fault alarm information on a diagnosis interface of the remote diagnosis data server, performs fault analysis and gives out fault treatment measures.

Compared with the prior art, the invention has the beneficial effects that:

(1) The method comprises the steps that a data processing module is adopted to collect starting process data in a unit self-starting control process, the starting process data are processed through the data processing module to obtain to-be-diagnosed data, the to-be-diagnosed data are sent to a remote diagnosis data server through a local area network, the remote diagnosis data server stores and generalizes the to-be-diagnosed data, and manages diagnosis request access of a remote expert diagnosis module, the remote expert diagnosis module obtains the starting process data and the to-be-diagnosed data in the unit self-starting control process from the remote diagnosis data server through the Internet, obtains diagnosis results of the unit self-starting control according to the to-be-diagnosed data, gives reasonable diagnosis suggestions and treatment measures, facilitates diagnosis and evaluation of unit self-starting control process problems and performance, compensates for the defect of accuracy of description of fault problem information in the current remote diagnosis mode, leads to asymmetrical information, cannot give timely and reasonable diagnosis suggestions and insufficient treatment measures, and reduces information asymmetry problems and workload of fault and performance diagnosis;

(2) Combining with the VPN information technology of the Internet, transmitting data to a remote diagnosis data server and transmitting data of the remote diagnosis data server and a remote expert diagnosis module, ensuring the real-time performance and the safety of the diagnosis data transmission in the self-starting control process of the unit, and better avoiding the problem of information asymmetry in the diagnosis process;

(3) The data acquisition module and the data processing module are adopted to acquire and process the data in the self-starting control process of the unit, so that the reliability of the system data information is improved, the system structure is greatly simplified, and the cost is low;

(4) The remote diagnosis data server is used for summarizing the data to be diagnosed and displaying the data on the display module in a modularized form of the key technology diagnosis module, the alarm diagnosis module and the performance parameter index diagnosis module, so that the information processing labor intensity of the diagnostic personnel is reduced, and the accuracy and the rapidity of the remote diagnosis are improved.

Drawings

The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application.

FIG. 1 is a schematic diagram of the overall structure of a remote diagnostic system for an Internet-based unit self-starting control process according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a diagnostic interface on a remote diagnostic data server according to an embodiment of the present application;

FIG. 3 is a flow chart of a remote diagnostic method for an Internet-based crew self-starting control process according to an embodiment of the present application;

the system comprises a unit 1, a unit self-starting and stopping control unit, a sequence control unit, a unit 3, a data acquisition unit, a unit 4, a database, a unit 5, a unit self-starting step process monitoring data processing unit, a unit self-starting diagnosis alarm data processing unit, a unit self-starting key technology diagnosis data processing unit, a unit self-starting performance parameter diagnosis data processing unit, a unit 9, a self-defining curve trend group data processing unit, a remote diagnosis data server, a VPN router, a unit 12, a remote mobile expert diagnosis end, a unit 13, a remote special expert diagnosis end, a unit 14, a network router, a unit 15, a data acquisition module, a unit 16 and a data processing module.

Detailed Description

It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of exemplary embodiments according to the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.

As introduced by the background technology, in the prior art, the defect of poor accuracy of description of fault problem information exists in the unit self-starting control process by field technicians due to the technical understanding of difference factors, so that remote experts can not give timely and reasonable diagnosis suggestions and processing measures, the remote experts can carry out summarized analysis of the fault problem information through a DCS remote diagnosis system, the related workload is large, the defects of accuracy and applicability of fault problems and performance diagnosis in the unit self-starting control process are restricted, and in order to solve the technical problems, the application provides a remote diagnosis system and a remote diagnosis method for the unit self-starting control process based on the Internet.

In an exemplary embodiment of the present application, as shown in fig. 1, there is provided an internet-based remote diagnosis system for a unit self-starting control process, the diagnosis system comprising:

the data acquisition module 15 is used for acquiring starting process data in the self-starting control process of the unit;

the data processing module 16 is configured to process the starting process data to obtain data to be diagnosed, and send the data to a remote diagnosis data server through a local area network;

the remote diagnosis data server 10 is configured to receive data to be diagnosed and starting process data through a local area network, perform induction processing on the received data to be diagnosed, display the data on a diagnosis interface, receive an access request of a remote expert diagnosis module, verify the authority of the remote expert diagnosis module, and if the access request of the remote expert diagnosis module passes the verification, the remote diagnosis data server responds to the access request of the remote expert diagnosis module and sends the induction processed data to the remote expert diagnosis module; if the remote expert diagnosis module is not verified, the remote diagnosis data server does not respond to the access request of the remote expert diagnosis module;

and the remote expert diagnosis module is used for sending an access request to the remote diagnosis data server through the Internet, displaying the starting process data and diagnosis interface information of the unit self-starting control diagnosis system to an expert, and analyzing the fault problem of the unit self-starting control process according to the data to be diagnosed.

The data acquisition module of the internet-based unit self-starting control process diagnosis system disclosed by the embodiment takes the decentralized control system as a core, performs starting process data acquisition in the unit self-starting control process, performs data processing according to unit self-starting step process monitoring, alarming, key technology diagnosis, custom curve trend groups and performance parameter index functions through the data processing module, obtains to-be-diagnosed data, sends the to-be-diagnosed data to a remote diagnosis data server through a local area network, stores the to-be-diagnosed data, performs induction processing according to unit self-starting step process monitoring, alarming, key technology diagnosis, custom curve trend groups and performance parameter index functions, and performs management on remote expert diagnosis module diagnosis request access, and the remote expert diagnosis module obtains the starting process data and the to-be-diagnosed data in the unit self-starting control process from the remote diagnosis data server through the internet, obtains diagnosis results of the unit self-starting control according to-be-diagnosed data and expert experience model data, and gives reasonable diagnosis suggestions and processing measures.

In another embodiment of the present application, the data acquisition module 15 includes a unit automatic start-stop control unit 1, a sequence control unit 2, a data acquisition unit 3 and a database 4; the unit self-starting and stopping control unit 1 is used for collecting state data of a step sequence monitoring area in the unit self-starting control process; the sequence control unit 2 is used for collecting sequential control fault alarm data in the unit self-starting control process; the data acquisition unit 3 is used for acquiring parameter out-of-limit alarm data in the self-starting control process of the unit; the database 4 is used for storing common parameter data in the self-starting control process of the unit.

The data processing module 16 comprises a unit self-starting step process monitoring data processing unit 5, a unit self-starting diagnosis alarm data processing unit 6, a unit self-starting key technology diagnosis data processing unit 7, a unit self-starting performance parameter diagnosis data processing unit 8 and a self-defined curve trend group data processing unit 9, wherein the unit self-starting step process monitoring data processing unit 5 is connected with the unit self-starting stop control system 1, the unit self-starting diagnosis alarm data processing unit 6 is respectively connected with the sequence control system 2 and the data acquisition system 3, the unit self-starting key technology diagnosis data processing unit 7 is respectively connected with the data acquisition system 3 and the database 4, the unit self-starting performance parameter diagnosis data processing unit 8 is connected with the data acquisition system 3, and the self-defined curve trend group data processing unit 9 is connected with the database 4.

The unit self-starting step sequence process monitoring data processing unit 5 is used for receiving the step sequence monitoring area state data collected by the unit self-starting stop control unit and carrying out induction processing on unit self-starting breakpoint process information according to the step sequence monitoring area state data; the machine set self-starting breakpoint process information comprises machine set self-starting breakpoint step sequence state, step sequence program control execution, pause, completion state and current step sequence program control execution time information.

The unit self-starting diagnosis alarm data processing unit 6 is used for receiving the sequential control fault alarm data collected by the sequential control unit and the parameter out-of-limit alarm data collected by the data collection unit, judging whether faults occur in the unit self-starting process according to the sequential control fault alarm data and the parameter out-of-limit alarm data, and sending fault alarm signals if faults occur.

The unit self-starting key technology diagnosis data processing unit 7 is used for receiving the parameter out-of-limit alarm data acquired by the data acquisition unit and the common parameter data stored in the database, and acquiring key technology diagnosis parameter data according to the parameter out-of-limit alarm data and the common parameter data.

The key technical diagnosis parameter data consists of 4 parts of function parameter data, including fan parallel function diagnosis parameters, automatic grid-connected function diagnosis parameters, dry-wet state conversion function diagnosis parameters and feed pump parallel function diagnosis parameters.

The fan parallel function diagnosis parameters relate to primary fan movable blade opening, primary air main pipe pressure, primary fan current, primary air and sealing air differential pressure and primary fan shafting data parameters.

The automatic grid-connected function diagnosis parameters comprise turbine rotating speed, active power, reactive power, exciting voltage, exciting current, generator stator current, power factor, frequency, generator body temperature parameters, generator grid-connected state, magnetic-extinction switch state and AVR control mode data parameters.

The dry-wet state conversion function diagnosis parameters relate to fuel quantity, water supply flow, water-coal ratio, load, air quantity, main steam pressure, main steam temperature, hot reheat steam pressure, hot reheat steam temperature, water level of a water storage tank of a separator, outlet temperature of the separator, boiler water circulating pump parameters and coal supply quantity data parameters of a coal feeder.

The parallel function diagnosis parameters of the water supply pump relate to water supply flow, water-coal ratio, main steam pressure, main steam temperature, a steam pump instruction, an electric pump instruction, load, a steam pump recirculation opening, an electric pump recirculation opening, steam pump shafting parameters and electric pump shafting parameter data parameters.

The unit self-starting performance parameter diagnosis data processing unit 8 is used for receiving the parameter out-of-limit alarm data acquired by the data acquisition system and calculating and processing performance parameter index data in the unit self-starting process according to the parameter out-of-limit alarm data; the performance parameter index data comprise starting time, fault times, water supplementing quantity, fuel quantity and coal burning quantity, and the starting time is calculated according to the parameter out-of-limit alarm data, specifically: the control of the unit input unit automatic start-stop control system and the start button of the unit automatic start-stop control system are t ₁ At moment, the load of the unit is more than 50% in the starting mode of the unit self-starting and stopping control system, and the input CCS is controlled to be t ₂ Time, start time is t ₂ Time and t ₁ The moment difference value is automatically cleared after the unit generates the MFT; according to the parameter out-of-limit alarm data, carrying out logic statistics calculation on the fault times, water supplementing quantity, fuel oil quantity and coal burning quantity of the unit, wherein the logic statistics calculation specifically comprises the following steps: and in the starting time, carrying out integral accumulation calculation statistics on the failure times, the water supplementing quantity, the fuel oil quantity and the coal burning quantity, and automatically clearing the failure times, the water supplementing quantity, the fuel oil quantity and the coal burning quantity when the unit is put into the APS control and the APS starting button again.

The custom curve trend group data processing unit 9 is configured to receive the common parameter data stored in the database, use the common parameter data as a data source of the custom curve trend group, and custom draw the parameter curve group according to the common parameter data.

Establishing local area network connection between a data processing module and a remote diagnosis data server, and transmitting data to be diagnosed to the remote diagnosis data server through the local area network, wherein the remote diagnosis data server comprises a controller, a memory and a display module, the controller is used for carrying out induction processing on the received data to be diagnosed and storing the data to be diagnosed in the memory, and the display module is used for displaying the data to be diagnosed in a modularized mode through a diagnosis interface, and the diagnosis interface shown in fig. 2 is composed of 5 parts of functional modules and comprises a step sequence monitoring diagnosis module, a fault alarm diagnosis module, a custom curve group diagnosis module, a performance parameter diagnosis module and a unit self-starting control key technology diagnosis module; the step sequence monitoring and diagnosing module consists of related program control step sequence monitoring and diagnosing modules such as a breakpoint 1, a breakpoint 2, a breakpoint 3, a breakpoint 4, a breakpoint 5, a breakpoint 6 and the like; the fault alarm diagnosis module consists of a sequential control fault alarm diagnosis module and a parameter out-of-limit alarm diagnosis module, and each fault alarm diagnosis module consists of 3 alarm groups; the custom curve group diagnosis module consists of a custom trend group 1, a custom trend group 2, a custom trend group 3, a custom trend group 4, a custom trend group 5 and a custom trend group 6; the performance parameter diagnosis module comprises a starting time, fault times, water supplementing quantity parameters and related performance parameter trend curve groups; the unit self-starting control key technology diagnosis module consists of a fan parallel diagnosis area, an automatic grid-connected diagnosis area, a dry-wet state conversion diagnosis area, a water supply pump parallel diagnosis area and the like; and the step sequence monitoring diagnosis module, the alarm diagnosis module, the custom curve group diagnosis module, the performance parameter diagnosis module and the unit self-starting control key technology diagnosis module adopt a conventional histogram to display each parameter.

In yet another embodiment of the present application, the remote expert diagnostic module includes:

the remote mobile expert diagnosis end 12 is used for accessing a remote diagnosis data server through a wireless network, acquiring data to be diagnosed in the remote diagnosis data server, and acquiring a diagnosis result of the unit self-starting control according to the data to be diagnosed and expert experience model data; the remote mobile expert diagnosis end adopts a portable computer, such as notebook electric energy.

The plurality of remote fixed expert diagnosis ends 13 are connected with the Internet through the network router 14 to remotely access a remote diagnosis data server, acquire data to be diagnosed in the remote diagnosis data server, and acquire diagnosis results of the unit self-starting control according to the data to be diagnosed and expert experience model data; and the remote fixed expert diagnosis end collects a desktop computer.

The diagnostic system also comprises a network transmission device, wherein the network transmission device comprises a first network architecture and a second network architecture, and the first network architecture is used for establishing a local area network between the data processing module and the remote diagnostic data server, and comprises an Ethernet switch, a firewall and an isolation lock; the second network architecture is configured to establish a VPN connection between the remote expert diagnostic module and the remote diagnostic data server, and includes a VPN router 11 and a switch.

In still another exemplary embodiment of the present application, as shown in fig. 3, there is provided a remote diagnosis method for a self-starting control process of an internet-based unit, comprising the steps of:

the remote diagnosis data server generalizes the data to be diagnosed and displays the data on a diagnosis interface;

the remote diagnosis data server receives the access request of the remote expert diagnosis module and verifies the authority of the remote expert diagnosis module, and if the remote diagnosis data server passes the verification, the remote diagnosis data server responds to the access request of the remote expert diagnosis module and sends the summarized data to be diagnosed to the remote expert diagnosis module;

The remote expert accesses the remote diagnosis data server through the remote expert diagnosis module, obtains the data information to be diagnosed from the diagnosis interface of the remote diagnosis data server, and diagnoses the data information by adopting an online evaluation analysis and fault problem backtracking analysis mode.

In another embodiment of the present application, the specific process of starting process data in the self-starting control process of the collection unit is as follows:

acquiring state data of a step sequence monitoring area in the self-starting control process of the unit by a unit self-starting stop control unit;

the sequential control unit is used for collecting sequential control fault alarm data in the unit self-starting control process;

acquiring parameter out-of-limit alarm data in the self-starting control process of the unit through a data acquisition unit;

and storing the common parameter data in the unit self-starting control process into a database.

The specific process of processing the starting process data to obtain the data to be diagnosed is as follows:

acquiring step sequence monitoring area state data from a unit automatic start-stop control unit through a unit automatic start step sequence process monitoring data processing unit;

In another embodiment of the present application, the specific process of the remote diagnosis data server to generalize the data to be diagnosed is:

And the remote diagnosis data server stores the received data to be diagnosed, and processes, generalizes and summarizes the data to be diagnosed according to the unit self-starting step process monitoring, fault alarming, key technology diagnosis, custom curve trend groups and performance parameter index functional areas.

In this embodiment, the specific process of performing diagnosis by the remote expert through the remote expert diagnosis module in the on-line evaluation analysis mode in the starting process is:

(1) In the self-starting process of the unit, an expert accesses a remote diagnosis data server through a remote expert diagnosis module, starts a breakpoint 1 of a step monitoring diagnosis module on a diagnosis interface of the remote diagnosis data server, enters an auxiliary system start preparation breakpoint function group, monitors the system start processes of circulating water start, closed cooling water start, air compressor system start, condensate water system start, auxiliary header system start, host oil system start, seal oil system start, EH oil system and the like; in the breakpoint 1 starting process, forward control faults and parameter out-of-limit fault data are started in the breakpoint 1 starting process displayed by the fault alarm diagnosis module, and diagnosis data trends are added by the custom curve group diagnosis module to analyze fault causes in real time.

(2) In the self-starting process of the unit, an expert accesses a remote diagnosis data server through a remote expert diagnosis module, starts a breakpoint 2 of a step monitoring diagnosis module on a diagnosis interface of the remote diagnosis data server, enters a boiler cold flushing and vacuum establishment breakpoint functional group, monitors the starting processes of a condensate system, condensate water discharging flushing and deaerator water feeding, deaerator heating, water feeding pipeline static water injection, water feeding pump starting, boiler cold flushing, host shaft seal system starting, vacuum system starting and other system starting processes; in the breakpoint 2 starting process, according to the data of the sequential control fault and the parameter out-of-limit fault which are displayed by the fault alarm diagnosis module in the breakpoint 1 starting process, a diagnosis data trend is added by the custom curve group diagnosis module to analyze the fault cause in real time; and the data trend curve sets such as condensate water discharge flushing, boiler cold water feeding and the like pre-stored by the custom curve set diagnosis module can be called at any time to monitor and analyze the control process.

(3) In the self-starting process of the unit, an expert accesses a remote diagnosis data server through a remote expert diagnosis module, starts a breakpoint 3 of a step monitoring diagnosis module on a diagnosis interface of the remote diagnosis data server, enters a boiler ignition heating breakpoint function group, monitors a hearth smoke temperature probe and flame television input, a fire detection cooling fan system start, a smoke system start, a hearth blowing, a powder preparation system preparation, an oil system ignition, a lower grinding input, a boiler side exhaust valve closing and other system start processes; in the starting process of the breakpoint 3, according to the data of the sequential control fault and the parameter out-of-limit fault which are displayed by the fault alarm diagnosis module in the starting process of the breakpoint 1, a diagnosis data trend is added by the custom curve group diagnosis module to analyze the fault cause in real time; and the data trend curve sets such as the starting of the air and smoke system pre-stored by the self-defined curve set diagnosis module can be called at any time to monitor and analyze the control process.

The primary air blower parallel control in the key technology diagnosis module plays a diagnosis role in the process of preparing and starting the pulverizing system at the breakpoint 3, and when the pulverizing system is prepared and started to parallel the primary air blower, the color of the primary air blower parallel diagnosis photon card is changed (green) and raised in the key technology diagnosis module, and when the primary air blower parallel is ended, the primary air blower parallel diagnosis photon card is recovered (grey). By clicking a primary fan shafting parameter button through a parameter stick diagram, observing the numerical value of each parameter in the primary fan parallel process; clicking a primary air fan parallel diagnosis parameter trend curve group, diagnosing a primary air fan parallel control process, diagnosing a primary air fan pressure control effect through the curve, judging whether PID parameter setting is reasonable or not, and diagnosing the primary air fan current change condition to judge whether the opening degree and the change rate of the movable blades of the two primary air fans are matched or not.

(4) In the self-starting process of the unit, an expert accesses a remote diagnosis data server through a remote expert diagnosis module, starts a breakpoint 4 of a step monitoring diagnosis module on a diagnosis interface of the remote diagnosis data server, enters a turbine switching grid-connected breakpoint functional group, monitors a second set of powder making system starting, turbine hanging brake, low adding system investment, turbine switching, high adding system heating pipes and unit grid-connected with-primary load system starting process; in the starting process of the breakpoint 4, according to the data of the sequential control fault and the parameter out-of-limit fault which are displayed by the fault alarm diagnosis module in the starting process of the breakpoint 1, a diagnosis data trend is added by the custom curve group diagnosis module to analyze the fault cause in real time; and the data trend curve sets such as turbine running and the like pre-stored in the custom curve set diagnosis module can be called at any time to monitor and analyze the control process.

The machine set automatic grid-connected control in the key technology diagnosis module plays a diagnosis role in the grid-connected primary load process of the breakpoint 4. When the machine set is connected, the automatic grid-connected control photon card of the machine set in the key technology diagnosis module changes color (green) to be convex, and the automatic grid-connected control photon card of the machine set is recovered (grey). Through the parameter stick diagram, clicking a temperature parameter button of the generator body, observing the numerical values of each parameter involved in the grid connection process of the generator; the method comprises the steps of clicking a set of automatic grid-connected diagnosis parameter trend curve sets, diagnosing grid-connected control process, diagnosing automatic synchronous turbine rotating speed control effect through curves, judging whether PID parameter setting is reasonable, diagnosing excitation device voltage response control effect through excitation voltage change trend, and diagnosing whether weighted initial load valve position value in turbine valve management meets requirements (initial load is more than 5%) through generator active power change trend.

(5) In the self-starting process of the unit, an expert accesses a remote diagnosis data server through a remote expert diagnosis module, starts a breakpoint 5 of a step monitoring diagnosis module on a diagnosis interface of the remote diagnosis data server, enters a unit load-lifting (to 40% load) breakpoint functional group, and monitors a system starting process of a water supply system, such as automatic process of switching power for a plant, dry and wet state conversion, steam source switching and the like; in the starting process of the breakpoint 5, according to the data of the sequential control fault and the parameter out-of-limit fault which are displayed by the fault alarm diagnosis module in the starting process of the breakpoint 1, a diagnosis data trend is added by the custom curve group diagnosis module to analyze the fault cause in real time; and the data trend curve sets such as deaerator steam source switching and the like pre-stored in the custom curve set diagnosis module can be called at any time to monitor and analyze the control process.

The dry-wet state conversion control in the key technology diagnosis module plays a diagnosis role in the process that the load of the breakpoint 5 unit is increased to 30%. When the dry-wet state conversion is carried out, the color change (green) bulge of the unit dry-wet state conversion control photon card in the key technology diagnosis module is formed, and the unit dry-wet state conversion control photon card is recovered (gray). Observing the values of all parameters involved in the dry-wet state conversion process by means of a parameter stick diagram, clicking a furnace water circulating pump parameter button and a coal supply button; the dry-wet state conversion is ensured by clicking the dry-wet state conversion diagnosis parameter trend curve group to diagnose the dry-wet state control process and diagnosing the rationality of the water and coal control process and the proportioning parameters through the curves, so that the dry-wet state conversion is successful once, and the main steam temperature does not have great fluctuation.

(6) In the self-starting process of the unit, an expert accesses a remote diagnosis data server through a remote expert diagnosis module, starts a breakpoint 6 of a step monitoring diagnosis module on a diagnosis interface of the remote diagnosis data server, enters a unit load lifting coordination control breakpoint function group, monitors the parallel control of a water supply pump, the starting of a grinding group, the automatic management of fuel main control, the coordination control of unit input and other system control processes; in the starting process of the breakpoint 6, according to the data of the sequential control fault and the parameter out-of-limit fault which are displayed by the fault alarm diagnosis module in the starting process of the breakpoint 1, a diagnosis data trend is added by the custom curve group diagnosis module to analyze the fault cause in real time; and the user-defined curve group diagnosis module can be used for pre-storing data trend curve groups such as coordinated control of the unit at any time to monitor and analyze the control process.

The water supply pump automatic parallel control in the key technology diagnosis module plays a diagnosis role in the process that the breakpoint 6 unit load rises to 45%, and when the water supply pump parallel conversion is carried out, the unit water supply pump parallel control photon cards in the key technology diagnosis module change color (green) bulge, and the unit water supply pump parallel control photon cards are recovered (grey). Through the parameter stick diagram, clicking a pump shaft system parameter button, observing the numerical values of each parameter involved in the parallel control process of the water supply pump; clicking a trend curve group of parallel control diagnosis parameters of the water feed pump, diagnosing the parallel control process of the water feed pump, and diagnosing the rationality of the PID parameters of the water feed control and the lifting speed of the water feed command in the water feed pump parallel through the curve to ensure the stable water feed flow and normal pump shaft system parameters in the parallel process of the water feed pump.

(7) After the unit is started automatically, a remote expert evaluates the diagnosis according to a parameter stick diagram of a performance parameter diagnosis module on a diagnosis interface of a remote diagnosis data server, analyzes consumption values of water supplementing quantity, fuel quantity and fuel quantity in each starting stage according to a performance parameter diagnosis trend curve set of the performance parameter diagnosis module on a display interface of the remote diagnosis data server, gives an energy-saving suggestion, and gives a targeted optimization suggestion according to statistics of failure times.

In this embodiment, the specific process of diagnosing by the remote expert through the remote expert diagnosis module in the fault problem backtracking analysis mode in the starting process is as follows:

The invention adopts a data processing module to collect starting process data in the self-starting control process of the unit, processes the starting process data through the data processing module to obtain data to be diagnosed, sends the data to be diagnosed to a remote diagnosis data server through a local area network, stores and generalizes the data to be diagnosed, manages the diagnosis request access of a remote expert diagnosis module, and obtains the starting process data and the data to be diagnosed in the self-starting control process of the unit from the remote diagnosis data server through the Internet;

The invention combines the VPN information technology of the Internet virtual private network to transmit data to the remote diagnosis data server and transmit the data of the remote diagnosis data server and the remote expert diagnosis module, thereby ensuring the real-time performance and the safety of the diagnosis data transmission in the self-starting control process of the unit and better avoiding the problem of information asymmetry in the diagnosis process;

the invention adopts the data acquisition module and the data processing module to acquire and process the data in the self-starting control process of the unit, thereby increasing the reliability of the data information of the system, greatly simplifying the structure of the system and having low cost;

according to the invention, the remote diagnosis data server is used for summarizing the data to be diagnosed, and the data to be diagnosed are displayed on the display module in a modularized form of the key technology diagnosis module, the alarm diagnosis module and the performance parameter index diagnosis module, so that the information processing labor intensity of the diagnostician is reduced, and the accuracy and the rapidness of remote diagnosis are improved.

While the foregoing description of the embodiments of the present invention has been presented in conjunction with the drawings, it should be understood that it is not intended to limit the scope of the invention, but rather, it is intended to cover all modifications or variations within the scope of the invention as defined by the claims of the present invention.

Claims

1. An internet-based remote diagnosis system for a unit self-starting control process is characterized by comprising:

the remote expert diagnosis module is used for sending an access request to a remote diagnosis data server through the Internet, receiving data to be diagnosed sent by the remote diagnosis data server, and analyzing fault problems of the unit self-starting control process by adopting a fault problem backtracking analysis mode according to the data to be diagnosed;

the specific process of diagnosing by the remote expert in the starting process by adopting a fault problem backtracking analysis mode through the remote expert diagnosis module is as follows:

The remote expert searches the specific type and the specific time period of occurrence of the fault according to the diagnostic parameter trend curve and the fault alarm information on the diagnostic interface of the remote diagnostic data server, and performs backtracking analysis according to the fault; if the fault belongs to one of fan parallel control, automatic grid-connected control, dry-wet state conversion control and water supply pump parallel control in the key technology of the unit self-starting control, rapidly calling out diagnostic parameter trend curve data information from a key technology diagnostic area on a diagnostic interface of a remote diagnostic data server for fault analysis; if the fault does not belong to the key technical control, an expert defines a relevant data curve in the custom curve trend group according to fault alarm information on a diagnosis interface of the remote diagnosis data server, performs fault analysis and gives out fault treatment measures;

the diagnosis parameters of the parallel functions of the fans relate to the opening degree of a movable blade of the primary fan, the pressure of a primary air main pipe, the current of the primary fan, the differential pressure between primary air and sealing air and the data parameters of a primary fan shafting;

the diagnosis parameters of the automatic grid-connected function comprise turbine rotating speed, active power, reactive power, exciting voltage, exciting current, generator stator current, power factor, frequency, generator body temperature parameters, generator grid-connected state, magnetic-extinction switch state and AVR control mode data parameters;

The diagnosis parameters of the dry-wet state conversion function relate to fuel quantity, water supply flow, water-coal ratio, load, air quantity, main steam pressure, main steam temperature, hot reheat steam pressure, hot reheat steam temperature, water level of a water storage tank of a separator, outlet temperature of the separator, furnace water circulating pump parameters and coal supply quantity data parameters of a coal feeder;

the diagnosis parameters of the parallel functions of the water supply pump relate to water supply flow, water-coal ratio, main steam pressure, main steam temperature, steam pump instruction, electric pump instruction, load, steam pump recirculation opening, electric pump recirculation opening, steam pump shafting parameters and electric pump shafting parameter data parameters;

the remote expert performs diagnosis by adopting an online evaluation analysis mode in the starting process through a remote expert diagnosis module, and the specific process is as follows:

in the self-starting process of the unit, a remote expert accesses a remote diagnosis data server through a remote expert diagnosis module, and sequentially starts a breakpoint 1, a breakpoint 2, a breakpoint 3, a breakpoint 4, a breakpoint 5 and a breakpoint 6 of a sequence monitoring diagnosis module on a diagnosis interface of the remote diagnosis data server;

wherein, breakpoint 1: entering an auxiliary system start preparation breakpoint functional group, and monitoring the processes of circulating water start, closed cooling water start, air compressor system start, condensate water supplement system start, auxiliary header system start, main engine oil system start, seal oil system start and EH oil system start;

Breakpoint 2: entering a boiler cold state flushing and vacuum building breakpoint functional group, and monitoring the starting process of a condensate system, condensate water discharge flushing and deaerator water supply, deaerator heating, water supply pipeline static water injection, water supply pump starting, boiler cold state flushing, main engine shaft seal system starting and vacuum system starting;

breakpoint 3: entering a boiler ignition heating breakpoint functional group, and monitoring the starting processes of a hearth smoke temperature probe and flame television input, a fire detection cooling fan system start, a smoke system start, a hearth blowing and pulverizing system preparation, an oil system ignition, a lower layer grinding input and a boiler side exhaust valve closing;

breakpoint 4: the method comprises the steps of entering a turbine flushing-turning grid-connected breakpoint functional group, and monitoring the starting process of a second powder making system, turbine gate hanging, low system input, turbine flushing-turning, high system heating pipes and a grid-connected unit with a primary load system;

breakpoint 5: entering a set load lifting breakpoint functional group, and monitoring an automatic feeding process of a water supply system, switching station service electricity, switching a dry state and a wet state and switching a steam source;

breakpoint 6: entering a unit load lifting coordination control breakpoint functional group, and monitoring parallel control of a water supply pump, starting of a grinding group, automatic management of fuel main control and unit input coordination control;

According to the data of the sequential control faults and the parameter out-of-limit faults, which are displayed by the fault alarm diagnosis module, in the starting process of the break points 1, 2, 3, 4, 5 and 6, the fault cause is analyzed in real time by adding diagnostic data trends through the custom curve group diagnosis module;

after the self-starting of the unit is completed, a remote expert evaluates the diagnosis according to a parameter stick diagram of a performance parameter diagnosis module on a diagnosis interface of a remote diagnosis data server, analyzes consumption values of water supplementing quantity, fuel quantity and fuel quantity in each starting stage according to a performance parameter diagnosis trend curve set of the performance parameter diagnosis module on a display interface of the remote diagnosis data server, gives an energy-saving suggestion, and gives a targeted optimization suggestion according to statistics of failure times;

the data acquisition module comprises:

the database is used for storing common parameter data in the self-starting control process of the unit;

The data processing module comprises:

2. The remote diagnosis system of the self-starting control process of the unit based on the Internet as claimed in claim 1, wherein the remote diagnosis data server comprises a controller, a memory and a display module, wherein the controller is used for carrying out induction processing on received data to be diagnosed and storing the data to be diagnosed in the memory, and the display module is used for displaying the data to be diagnosed after induction processing;

the remote expert diagnostic module includes:

3. The remote diagnosis system of the self-starting control process of the machine set based on the Internet as claimed in claim 1, further comprising a network transmission device, wherein the network transmission device comprises a first network architecture and a second network architecture, and the first network architecture is used for establishing a local area network between the data processing module and a remote diagnosis data server, and comprises an Ethernet switch, a firewall and an isolation lock; the second network architecture is configured to establish a VPN connection between the remote expert diagnostic module and the remote diagnostic data server, including a VPN router and a switch.

4. An internet-based remote diagnosis method for a unit self-starting control process, which is characterized by adopting the internet-based remote diagnosis system for the unit self-starting control process according to any one of claims 1-3, and comprising the following steps:

the remote expert accesses the remote diagnosis data server through the remote expert diagnosis module, obtains the data information to be diagnosed from the diagnosis interface of the remote diagnosis data server, and performs fault diagnosis by adopting an online evaluation analysis and fault problem backtracking analysis mode;

breakpoint 4: the method comprises the steps of entering a turbine flushing-turning grid-connected breakpoint functional group, and monitoring a second powder making system starting process, a turbine gate hanging process, a low system input process, a turbine flushing-turning process, a high system heating pipe process and a unit grid-connected primary load system starting process;

breakpoint 5: entering a set load lifting breakpoint functional group, and monitoring an automatic process of a water supply system, switching power for a plant, switching dry and wet states and switching a steam source;

Breakpoint 6: entering a unit load lifting coordination control breakpoint functional group, and monitoring a parallel control process of a water supply pump, a grinding group starting process, a fuel main control automatic management process and a unit input coordination control process;

the diagnosis parameters of the parallel function of the water supply pump relate to water supply flow, water-coal ratio, main steam pressure, main steam temperature, steam pump instruction, electric pump instruction, load, steam pump recirculation opening, electric pump recirculation opening, steam pump shafting parameters and electric pump shafting parameter data parameters.

5. The remote diagnosis method for the self-starting control process of the unit based on the Internet as claimed in claim 4, wherein the specific process of processing the starting process data to obtain the data to be diagnosed is as follows:

6. The method for remote diagnosis of the self-starting control process of the machine set based on the Internet according to claim 4, wherein the diagnosis interface of the remote diagnosis data server comprises a step sequence monitoring diagnosis module, a custom curve group diagnosis module, a fault alarm diagnosis module, a performance parameter diagnosis module and a self-starting control key technology diagnosis module of the machine set.