CN113431800A - Method for distinguishing running state of fan in real time - Google Patents
Method for distinguishing running state of fan in real time Download PDFInfo
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- CN113431800A CN113431800A CN202110804108.6A CN202110804108A CN113431800A CN 113431800 A CN113431800 A CN 113431800A CN 202110804108 A CN202110804108 A CN 202110804108A CN 113431800 A CN113431800 A CN 113431800A
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- 238000000034 method Methods 0.000 title claims abstract description 13
- 238000010248 power generation Methods 0.000 claims abstract description 21
- 238000012423 maintenance Methods 0.000 description 11
- 238000010586 diagram Methods 0.000 description 5
- 238000007689 inspection Methods 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
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Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
- F04D27/001—Testing thereof; Determination or simulation of flow characteristics; Stall or surge detection, e.g. condition monitoring
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
- F04D—NON-POSITIVE-DISPLACEMENT PUMPS
- F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
- F04D27/008—Stop safety or alarm devices, e.g. stop-and-go control; Disposition of check-valves
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- Engineering & Computer Science (AREA)
- Mechanical Engineering (AREA)
- General Engineering & Computer Science (AREA)
- Wind Motors (AREA)
Abstract
The invention provides a method for judging the running state of a fan in real time, which is characterized in that the power generation power and the wind speed historical data of a certain fan in a certain time period are collected in real time, the slope of a linear formula of the power generation power and the wind speed of the fan is obtained by linear fitting, and when the slope of the fan deviates from a set normal value in a certain set range, the basic running state of the fan can be judged to have problems.
Description
Technical Field
The invention belongs to the technical field of equipment state data analysis in the new energy power industry, and particularly relates to a method for distinguishing the running state of a fan in real time.
Background
At present, the installed capacity of wind power generation is increased in a large scale in China, and the number of fans of one power generation group is about ten thousand. The maintenance cost of a wind turbine is one of the main costs of wind turbine power generation. At present, the running state of the fan needs personnel to be detected on site, if the basic running state of the fan can be judged quickly, accurate maintenance is carried out on the fan with a fault in a targeted mode, the number of inspection operation and maintenance personnel can be effectively reduced, and the maintenance cost is reduced. The construction of an intelligent power plant needs to realize a self-sensing function, and the operation state of a fan obtained by utilizing the operation data of the power plant is an important content of self-sensing of the intelligent power plant.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention aims to provide a method for judging the running state of a fan in real time.
In order to achieve the purpose, the invention adopts the technical scheme that:
a method for distinguishing the running state of a fan in real time comprises the following steps;
step 1:
collecting the generated power and the wind speed of any fan within a certain time period delta t according to a certain collection frequency f to obtain the generated power P of i fans at the moment ji,jAnd wind speed Wi,j；
Wherein, Pi,j-the generated power, MW, of the i fans at time j;
Wi,jand j is the wind speed of the i fans at moment m/s.
The collection times of the generated power and the wind speed in a certain time period delta t are as follows:
N＝fΔt
wherein, N-i is the power generated by the fan and the wind speed collection times;
f, i, collecting the power generation power and wind speed of the typhoon machine for times/s;
and delta t is the power generation power and wind speed acquisition time of the i typhoon fans, and s.
Thus, N groups of data (P) of the i fans are obtainedi,1，Wi,1)，(Pi,2，Wi,2)，…，(Pi,N，Wi,N)；
Step 2:
and performing linear fitting on the collected N groups of data fan power generation power and wind speed by using a least square method to obtain a linear relation between the i groups of data fan power generation power and the wind speed as follows:
Pi＝kiWi+Ci
wherein, Pi-the generated power of i fans, MW;
ki-linear coefficient of i fans, mw.s/m;
Wi-the wind speed of i fans, m/s;
Cii constant of the blower, MW.
And step 3:
judging the linear coefficient k of the i fansiAnd normalValue k0Deviation Δ k ofiAnd if the deviation is larger than the set value delta, judging that the running state of the fan is faulty: the criteria for discrimination are described below:
Δki＝|ki-k0|>delta, fault
Wherein, Δ ki-the linear coefficient deviation value of the i fans, mw.s/m;
k0the linear coefficient of the fan is a normal value, MW.s/m;
delta-the deviation set value of the linear coefficient of the fan, MW.s/m.
The invention has the beneficial effects that:
by utilizing the technology of the invention, the running state of a large-scale fan (thousands of scales) can be analyzed on line by utilizing the computer through the fan power generation power and the wind speed which are collected in real time, the basic running state of the fan can be judged quickly, the operation and maintenance personnel can be guided to carry out accurate maintenance on the fan with a fault in a targeted manner, the number of the inspection operation and maintenance personnel can be effectively reduced, and the maintenance cost can be reduced.
The specific implementation steps are as follows: the method comprises the steps of firstly collecting the power generation power and the wind speed of each fan in real time, then calculating and analyzing the power generation power and the wind speed of each fan within a period of time according to the method, alarming the fan with the linear coefficient deviation larger than a set value and pushing the alarm to operation and maintenance personnel, and the operation and maintenance personnel carry out field maintenance or overhaul on the alarm fan.
Drawings
FIG. 1 is a X-Y scatter diagram of the power generation and wind speed of a fan according to the present invention.
FIG. 2 is a X-Y scatter diagram of the power generation and wind speed of the wind turbine according to the present invention.
FIG. 3 is a X-Y scatter diagram of the power generation and wind speed of the wind turbine according to the present invention.
FIG. 4 is a X-Y scatter diagram of the power generation and wind speed of the wind turbine according to the present invention.
FIG. 5 is a X-Y scatter diagram of the power generation and wind speed of the wind turbine according to the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings.
The method comprises the steps of collecting the generated power and the wind speed of any 5 fans (#1, #6, #10, #15, #20) in a certain wind power plant, collecting data for 3 days, and collecting the data once every 5 seconds, wherein each fan can collect 51840 groups of generated power and wind speed arrays.
The 5 fans are respectively subjected to linearity by a least square method, and the linear formula of the 5 fans is as follows:
#1、Y＝0.14*X-0.22
#6Y＝0.15*X-0.44
#10Y＝0.69*X-1.49
#15Y＝0.16*X-0.35
#20Y＝0.15*X-0.32
for the type of fan, the normal value of the linear coefficient of the fan is 0.15MW.s/m, and the deviation value of the linear coefficient of the fan is set to be 0.015MW.s/m, so that the operating state of the #10 fan can be judged to be faulty.
As shown in fig. 1: the relation graph of the generated power of the fan and the wind speed reflects normal operation of the fan.
As shown in fig. 2: the relation graph of the generated power of the fan and the wind speed reflects normal operation of the fan.
As shown in fig. 3: the relation graph of the generated power of the fan and the wind speed reflects the abnormal operation of the fan.
As shown in fig. 4: the relation graph of the generated power of the fan and the wind speed reflects normal operation of the fan.
As shown in fig. 5: the relation graph of the generated power of the fan and the wind speed reflects normal operation of the fan.
Claims (1)
1. A method for distinguishing the running state of a fan in real time is characterized by comprising the following steps;
step 1:
collecting the generated power and the wind speed of any fan within a certain time period delta t according to a certain collection frequency f to obtain the generated power P of i fans at the moment ji,jAnd wind speed Wi,j；
Wherein, Pi,j-the generated power, MW, of the i fans at time j;
Wi,jand j is the wind speed of the i fans at moment m/s.
The collection times of the generated power and the wind speed in a certain time period delta t are as follows:
N＝fΔt
wherein, N-i is the power generated by the fan and the wind speed collection times;
f, i, collecting the power generation power and wind speed of the typhoon machine for times/s;
and delta t is the power generation power and wind speed acquisition time of the i typhoon fans, and s.
Thus, N groups of data (P) of the i fans are obtainedi,1，Wi,1)，(Pi,2，Wi,2)，…，(Pi,N，Wi,N)；
Step 2:
and performing linear fitting on the collected N groups of data fan power generation power and wind speed by using a least square method to obtain a linear relation between the i groups of data fan power generation power and the wind speed as follows:
Pi＝kiWi+Ci
wherein, Pi-the generated power of i fans, MW;
ki-linear coefficient of i fans, mw.s/m;
Wi-the wind speed of i fans, m/s;
Cii constant of the blower, MW.
And step 3:
judging the linear coefficient k of the i fansiFrom the normal value k0Deviation Δ k ofiAnd if the deviation is larger than the set value delta, judging that the running state of the fan is faulty: the criteria for discrimination are described below:
Δki＝|ki-k0|>delta, fault
Wherein, Δ ki-the linear coefficient deviation value of the i fans, mw.s/m;
k0the linear coefficient of the fan is a normal value, MW.s/m;
delta-the deviation set value of the linear coefficient of the fan, MW.s/m.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202110804108.6A CN113431800A (en) | 2021-07-16 | 2021-07-16 | Method for distinguishing running state of fan in real time |
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| CN202110804108.6A CN113431800A (en) | 2021-07-16 | 2021-07-16 | Method for distinguishing running state of fan in real time |
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| CN113431800A true CN113431800A (en) | 2021-09-24 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114881375A (en) * | 2022-07-11 | 2022-08-09 | 浙江科维节能技术股份有限公司 | Diagnosis and tuning system and method of fan system |
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2021
- 2021-07-16 CN CN202110804108.6A patent/CN113431800A/en active Pending
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| CN107742053A (en) * | 2017-11-28 | 2018-02-27 | 国华（河北）新能源有限公司 | Wind turbines abnormality recognition method and device |
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| CN114881375A (en) * | 2022-07-11 | 2022-08-09 | 浙江科维节能技术股份有限公司 | Diagnosis and tuning system and method of fan system |
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