CN114757376A - Power plant equipment operation fault diagnosis and maintenance system - Google Patents
Power plant equipment operation fault diagnosis and maintenance system Download PDFInfo
- Publication number
- CN114757376A CN114757376A CN202210437342.4A CN202210437342A CN114757376A CN 114757376 A CN114757376 A CN 114757376A CN 202210437342 A CN202210437342 A CN 202210437342A CN 114757376 A CN114757376 A CN 114757376A
- Authority
- CN
- China
- Prior art keywords
- power plant
- parameters
- fault
- plant equipment
- maintenance
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012423 maintenance Methods 0.000 title claims abstract description 65
- 238000003745 diagnosis Methods 0.000 title claims abstract description 51
- 238000013528 artificial neural network Methods 0.000 claims abstract description 8
- 238000004891 communication Methods 0.000 claims description 10
- 238000007781 pre-processing Methods 0.000 claims description 8
- 238000010276 construction Methods 0.000 claims description 7
- 230000002159 abnormal effect Effects 0.000 claims description 4
- 230000005684 electric field Effects 0.000 claims description 4
- 230000007613 environmental effect Effects 0.000 claims description 4
- 238000000034 method Methods 0.000 abstract description 5
- 238000012544 monitoring process Methods 0.000 abstract description 3
- 238000001514 detection method Methods 0.000 description 6
- 238000007689 inspection Methods 0.000 description 4
- 238000010586 diagram Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000010422 painting Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/20—Administration of product repair or maintenance
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Economics (AREA)
- Human Resources & Organizations (AREA)
- Tourism & Hospitality (AREA)
- General Health & Medical Sciences (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Entrepreneurship & Innovation (AREA)
- Biophysics (AREA)
- Water Supply & Treatment (AREA)
- Public Health (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Life Sciences & Earth Sciences (AREA)
- Artificial Intelligence (AREA)
- Biomedical Technology (AREA)
- Primary Health Care (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Evolutionary Computation (AREA)
- Molecular Biology (AREA)
- Computing Systems (AREA)
- General Engineering & Computer Science (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Testing And Monitoring For Control Systems (AREA)
Abstract
The invention relates to the field of state management of power plant equipment, in particular to a power plant equipment operation fault diagnosis and maintenance system, which comprises: the operation parameter sensing node is used for sensing operation condition parameters of the operation of each power plant device; the switch attitude sensing node is used for sensing attitude parameters of the on-load switches in the power plant equipment; the environment parameter sensing node is used for sensing internal environment parameters of each power plant device; and the fault diagnosis module is used for realizing the diagnosis of the operation fault of the power plant equipment according to the operation condition parameters, the attitude parameters of the switch and the internal environment parameters based on the fuzzy neural network algorithm, positioning the position of the fault according to the diagnosis result and generating a corresponding fault maintenance task. The invention can realize the comprehensive monitoring of the whole operation process of the power plant equipment, can quickly discover the fault problem of the operation of the power plant equipment and provides guarantee for the safe operation of the power plant equipment.
Description
Technical Field
The invention relates to the field of power plant equipment state management, in particular to a power plant equipment operation fault diagnosis and maintenance system.
Background
The types of equipment in the power plant are more, the working environment is more complex, once a fault occurs, the fault should be discovered as soon as possible and processed in time,
in daily management, the inspection of power plant equipment generally adopts a manual inspection mode, the period is long, labor is consumed, and meanwhile, the result of fault diagnosis usually has hysteresis.
In recent years, unmanned inspection systems and methods suitable for power plants have more research results. However, in the related technical achievements, the detection link needs to modify the equipment to be detected to a certain extent, and the detection link cannot be generally used for general equipment, for example, the detection of water leakage needs to be realized by changing color when painting sprayed on the equipment to be detected meets water. Or the data processing system architecture of the inspection system does not use related information acquisition auxiliary equipment in the aspect of information acquisition, so that the detection data acquisition is incomplete and inaccurate, and the detection is not enough to cope with the complex environment detection of the power plant.
Disclosure of Invention
The invention aims to provide a power plant equipment operation fault diagnosis and maintenance system, which can realize comprehensive monitoring of the whole process of power plant equipment operation, can quickly find out the problem of the operation fault of the power plant equipment and provides guarantee for the safe operation of the power plant equipment.
In order to achieve the purpose, the invention adopts the technical scheme that:
a power plant equipment operation fault diagnosis and maintenance system, comprising:
the operation parameter sensing node is used for sensing operation condition parameters of the operation of each power plant device;
the switch attitude sensing node is used for sensing attitude parameters of the on-load switches in the power plant equipment;
the environment parameter sensing node is used for sensing internal environment parameters of each power plant device;
and the fault diagnosis module is used for realizing the diagnosis of the operation fault of the power plant equipment according to the operation condition parameters, the attitude parameters of the switch and the internal environment parameters based on a fuzzy neural network algorithm, positioning the position of the fault according to the diagnosis result and generating a corresponding fault maintenance task.
The invention is further improved in that the operation parameter sensing node acquires operating condition parameters of each power plant device through a sensor group, wherein the operating condition parameters include voltage parameters, current parameters, frequency parameters and phase angle parameters of each power plant device.
The invention is further improved in that each switch is provided with a three-dimensional attitude sensor, and the acquisition of attitude parameters of the switches is realized through the three-dimensional attitude sensor.
The invention is further improved in that the environment parameter sensing node collects internal environment parameters of each power plant device through a sensor group, wherein the internal environment parameters comprise a temperature parameter, a pressure parameter, a vibration parameter, an electric field intensity parameter, a magnetic field intensity parameter and an abnormal gas parameter.
The invention further improves that the method also comprises the following steps:
and the fault diagnosis module realizes the diagnosis of the operation fault of the power plant equipment according to the operation condition parameter, the attitude parameter of the switch, the internal environment parameter and the communication state parameter based on a fuzzy neural network algorithm, positions the position of the fault according to the diagnosis result and generates a corresponding fault maintenance task.
The invention is further improved in that an emergency operation scheme is configured for each fault type, and the fault diagnosis module is further used for operating the corresponding emergency operation scheme according to the diagnosis result.
The invention further improves that:
and the data preprocessing module is used for realizing preprocessing of the operating condition parameters, the attitude parameters of the switch, the internal environment parameters and the communication state parameters by adopting a Hadoop attribute reduction algorithm based on the inter-class discrimination.
The invention is further improved in that the maintenance task comprises the model parameter and the position parameter of the power plant equipment where the fault is located, the corresponding fault type, the fault maintenance measure and the maintenance map, and the user realizes the direct positioning of the fault point by putting the maintenance map.
The invention is further improved in that the fault diagnosis module firstly calls a construction model of the corresponding power plant equipment according to the model of the power plant equipment where the fault is located, the construction model is used as a template of a maintenance map, then the construction model is marked at the corresponding position of the maintenance map according to the position parameter where the fault is located, and each maintenance person configures a maintenance mobile terminal with a projection function.
The invention has at least the following beneficial technical effects:
1) the operation condition parameters, the attitude parameters of the switch, the internal environment parameters and the communication state parameters are fully considered, the overall monitoring of the whole operation process of the power plant equipment can be realized, the fault problem of the operation of the power plant equipment can be rapidly found, and the safety operation of the power plant equipment is guaranteed.
2) The automatic identification of the power plant equipment fault can be realized, and meanwhile, the automatic positioning of the position of the fault can be realized, so that the subsequent maintenance work is greatly facilitated.
3) An emergency operation plan is allocated to each fault type, so that the influence caused by the fault of the power plant equipment can be reduced as much as possible.
Drawings
Fig. 1 is a system block diagram of a power plant operation fault diagnosis and maintenance system according to embodiment 1 of the present invention.
Fig. 2 is a system block diagram of a power plant operation fault diagnosis and maintenance system according to embodiment 2 of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications can be made by persons skilled in the art without departing from the spirit of the invention. All falling within the scope of the invention.
Example 1
As shown in fig. 1, an embodiment of the present invention provides a power plant equipment operation fault diagnosis and maintenance system, including:
the operation parameter sensing node is used for sensing operation condition parameters of the operation of each power plant device;
the switch attitude sensing node is used for sensing attitude parameters of the on-load switches in the power plant equipment;
the environment parameter sensing node is used for sensing the internal environment parameters of each power plant device;
the data preprocessing module is used for preprocessing the operating condition parameters, the attitude parameters of the switch and the internal environment parameters by adopting an attribute reduction algorithm based on the inter-class discrimination of Hadoop;
the fault diagnosis module is used for realizing the diagnosis of the operation fault of the power plant equipment according to the operation condition parameters, the attitude parameters of the switch and the internal environment parameters based on a fuzzy neural network algorithm, positioning the position of the fault according to the diagnosis result and generating a corresponding fault maintenance task; the system is also used for operating a corresponding emergency operation scheme according to the diagnosis result, and each fault type is configured with an emergency operation scheme; the system trains and constructs a fuzzy neural network algorithm according to historical operating condition parameters, attitude parameters and internal environment parameters of the switch and corresponding fault parameters (fault type and fault location).
In this embodiment, the operation parameter sensing node collects operating condition parameters of each power plant through the sensor group, including operating voltage parameters, operating current parameters, operating frequency parameters, and operating phase angle parameters of each power plant.
In this embodiment, each switch is configured with a three-dimensional attitude sensor, and acquisition of attitude parameters of the switch is realized through the three-dimensional attitude sensor.
In this embodiment, the environment parameter sensing node collects internal environment parameters of each power plant device through a sensor group, including a temperature parameter, a pressure parameter, a vibration parameter, an electric field intensity parameter, and an abnormal gas parameter.
In the embodiment, the maintenance task comprises the model parameter and the position parameter of the power plant equipment where the fault is located, and the corresponding fault type, fault maintenance measures and a maintenance map, and a user can directly position a fault point by putting the maintenance map; the fault diagnosis module calls a construction model of corresponding power plant equipment according to the model of the power plant equipment where the fault is located to serve as a template of a maintenance map, marks are marked at the corresponding position of the maintenance map according to the position parameter where the fault is located, each maintenance worker configures a maintenance mobile terminal with a projection function, and the maintenance mobile terminal is used for receiving distributed maintenance tasks and uploading maintenance task progress.
Example 2
As shown in fig. 2, an embodiment of the present invention provides a power plant equipment operation fault diagnosis and maintenance system, including:
the operation parameter sensing node is used for sensing operation condition parameters of the operation of each power plant device;
the switch attitude sensing node is used for sensing attitude parameters of the on-load switches in the power plant equipment;
the environment parameter sensing node is used for sensing the internal environment parameters of each power plant device;
the communication parameter sensing node is used for sensing the communication state parameters of the on-board communication lines of the power plant equipment;
the data preprocessing module is used for realizing preprocessing of operating condition parameters, attitude parameters of switches, internal environment parameters and communication state parameters by adopting a Hadoop attribute reduction algorithm based on inter-class discrimination;
the fault diagnosis module is used for realizing the diagnosis of the operation fault of the power plant equipment according to the operation condition parameters, the attitude parameters of the switch, the internal environment parameters and the communication state parameters based on a fuzzy neural network algorithm, positioning the position of the fault according to the diagnosis result and generating a corresponding fault maintenance task; and the system is also used for operating a corresponding emergency operation scheme according to the diagnosis result, and each fault type is configured with an emergency operation scheme.
In this embodiment, the operation parameter sensing node collects operating condition parameters of each power plant device through the sensor group, including operating voltage parameters, operating current parameters, operating frequency parameters, and operating phase angle parameters of each power plant device.
In this embodiment, each switch is configured with a three-dimensional attitude sensor, and the acquisition of the attitude parameters of the switch is realized through the three-dimensional attitude sensor.
In this embodiment, the environmental parameter sensing node collects internal environmental parameters of each power plant device through the sensor group, including a temperature parameter, a pressure parameter, a vibration parameter, an electric field intensity parameter, a magnetic field intensity parameter, and an abnormal gas parameter.
In the embodiment, the maintenance task comprises the model parameter and the position parameter of the power plant equipment where the fault is located, and the corresponding fault type, fault maintenance measures and a maintenance map, and a user can directly position a fault point by putting the maintenance map; the fault diagnosis module calls a construction model of corresponding power plant equipment according to the model of the power plant equipment where the fault is located to serve as a template of a maintenance map, marks are marked at the corresponding position of the maintenance map according to the position parameter where the fault is located, each maintenance worker configures a maintenance mobile terminal with a projection function, and the maintenance mobile terminal is used for receiving distributed maintenance tasks and uploading maintenance task progress.
The foregoing description of specific embodiments of the present invention has been presented. It is to be understood that the present invention is not limited to the specific embodiments described above, and that various changes or modifications may be made by one skilled in the art within the scope of the appended claims without departing from the spirit of the invention. The embodiments and features of the embodiments of the present application may be combined with each other arbitrarily without conflict.
Claims (9)
1. A power plant equipment operation fault diagnosis and maintenance system, characterized by comprising:
the operation parameter sensing node is used for sensing operation condition parameters of the operation of each power plant device;
the switch attitude sensing node is used for sensing attitude parameters of the on-load switches in the power plant equipment;
the environment parameter sensing node is used for sensing the internal environment parameters of each power plant device;
and the fault diagnosis module is used for realizing the diagnosis of the operation fault of the power plant equipment according to the operation condition parameters, the attitude parameters of the switch and the internal environment parameters based on the fuzzy neural network algorithm, positioning the position of the fault according to the diagnosis result and generating a corresponding fault maintenance task.
2. The power plant equipment operation fault diagnosis and maintenance system of claim 1, wherein the operation parameter sensing node collects operating condition parameters of each power plant equipment operation through a sensor group, including voltage parameters, current parameters, frequency parameters and phase angle parameters of each power plant equipment operation.
3. The power plant equipment operation fault diagnosis and maintenance system of claim 1, wherein each switch is configured with a three-dimensional attitude sensor, and acquisition of attitude parameters of the switch is achieved through the three-dimensional attitude sensor.
4. The power plant equipment operation fault diagnosis and maintenance system of claim 1, wherein the environmental parameter sensing node collects internal environmental parameters of each power plant equipment through a sensor group, including temperature parameters, pressure parameters, vibration parameters, electric field strength parameters, magnetic field strength parameters and abnormal gas parameters.
5. The power plant equipment operational fault diagnosis and maintenance system of claim 1, further comprising:
and the fault diagnosis module realizes the diagnosis of the operation fault of the power plant equipment according to the operation condition parameter, the attitude parameter of the switch, the internal environment parameter and the communication state parameter based on a fuzzy neural network algorithm, positions the position of the fault according to the diagnosis result and generates a corresponding fault maintenance task.
6. The power plant equipment operational fault diagnosis and maintenance system of claim 5, wherein an emergency operation plan is configured for each fault type, and the fault diagnosis module is further configured to operate the corresponding emergency operation plan according to the diagnosis result.
7. The power plant equipment operational failure diagnosis and maintenance system of claim 5, further comprising:
and the data preprocessing module is used for realizing preprocessing of the operating condition parameters, the attitude parameters of the switch, the internal environment parameters and the communication state parameters by adopting a Hadoop attribute reduction algorithm based on the inter-class discrimination.
8. The power plant equipment operation fault diagnosis and maintenance system of claim 5, wherein the maintenance task comprises a model parameter and a location parameter of the power plant equipment where the fault is located, and a corresponding fault type, a fault maintenance measure and a maintenance map, and a user realizes direct positioning of a fault point through putting in the maintenance map.
9. The power plant equipment operation fault diagnosis and maintenance system according to claim 5, wherein the fault diagnosis module first calls a construction model of corresponding power plant equipment according to the model of the power plant equipment where the fault is located, the construction model is used as a template of a maintenance map, then marks the corresponding position of the maintenance map according to the position parameter of the fault, and each maintenance person configures a maintenance mobile terminal with a projection function.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210437342.4A CN114757376A (en) | 2022-04-21 | 2022-04-21 | Power plant equipment operation fault diagnosis and maintenance system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210437342.4A CN114757376A (en) | 2022-04-21 | 2022-04-21 | Power plant equipment operation fault diagnosis and maintenance system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN114757376A true CN114757376A (en) | 2022-07-15 |
Family
ID=82332408
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210437342.4A Pending CN114757376A (en) | 2022-04-21 | 2022-04-21 | Power plant equipment operation fault diagnosis and maintenance system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114757376A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116088398A (en) * | 2023-04-10 | 2023-05-09 | 中国电力工程顾问集团西南电力设计院有限公司 | Be used for wisdom prison dish alarm system of thermal power plant |
-
2022
- 2022-04-21 CN CN202210437342.4A patent/CN114757376A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116088398A (en) * | 2023-04-10 | 2023-05-09 | 中国电力工程顾问集团西南电力设计院有限公司 | Be used for wisdom prison dish alarm system of thermal power plant |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105867245B (en) | A kind of electric power information monitoring system | |
| CN109032099A (en) | Engineering machinery assemble production line online awareness system | |
| CN107748546A (en) | A kind of factory's intelligent inspection system based on LoRa technologies | |
| CN108931972A (en) | A kind of substation secondary device condition intelligent diagnostic method based on model-driven | |
| CN103235562A (en) | Patrol-robot-based comprehensive parameter detection system and method for substations | |
| CN110544038B (en) | Intelligent operation and maintenance method and system for ship equipment | |
| CN105515184A (en) | Wireless sensor network-based cooperative monitoring system of multi-sensor and multi-parameter distribution network | |
| CN110430078B (en) | Method and system for recognizing type, configuring and functionally enabling electric power automation terminal | |
| CN114757376A (en) | Power plant equipment operation fault diagnosis and maintenance system | |
| CN111900801A (en) | Power distribution network power supply guarantee system based on power internet of things | |
| CN109767063A (en) | Stability control device operation information system and online power grid risk assessment method thereof | |
| CN110083135A (en) | Air compressor machine remotely monitor and control system | |
| CN113867128A (en) | Intelligent redundancy control system and method for numerical control equipment | |
| CN110533345A (en) | A kind of boat diesel engine state evaluating method and system | |
| CN107102633B (en) | A kind of distribution terminal fault self-diagnosis method and system | |
| CN111582657A (en) | Intelligent community electricity utilization safety management system | |
| CN117491845A (en) | Accurate direct current shunt metering method for multipath direct current load equipment | |
| CN112104085A (en) | Multifunctional electric power and electric automation control system | |
| CN104678206A (en) | Ship power equipment monitoring system | |
| CN111210092A (en) | Stacking machine predictive maintenance method and system based on deep learning | |
| CN116512264A (en) | Remote robot inspection system | |
| CN110471386A (en) | A kind of digital workshop environmental monitoring system | |
| CN113282123B (en) | Intelligent building indoor environment monitoring system | |
| CN215300269U (en) | High-safety intelligent power distribution terminal system | |
| CN114006471A (en) | Substation direct current system monitoring method and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |