CN111692035B - Method for detecting uneven opening degree of guide vane - Google Patents

Method for detecting uneven opening degree of guide vane Download PDF

Info

Publication number
CN111692035B
CN111692035B CN202010573572.4A CN202010573572A CN111692035B CN 111692035 B CN111692035 B CN 111692035B CN 202010573572 A CN202010573572 A CN 202010573572A CN 111692035 B CN111692035 B CN 111692035B
Authority
CN
China
Prior art keywords
water
parameter
guide
characteristic value
guide vane
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN202010573572.4A
Other languages
Chinese (zh)
Other versions
CN111692035A (en
Inventor
杨洋
李太斌
苟平
延帅
郭良波
张鹏程
颜天成
宁美江
张冲
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Huaneng Sichuan Energy Development Co ltd
Sichuan Huaneng Jialingjiang Hydropower Co Ltd
Original Assignee
Huaneng Sichuan Energy Development Co ltd
Sichuan Huaneng Jialingjiang Hydropower Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Huaneng Sichuan Energy Development Co ltd, Sichuan Huaneng Jialingjiang Hydropower Co Ltd filed Critical Huaneng Sichuan Energy Development Co ltd
Priority to CN202010573572.4A priority Critical patent/CN111692035B/en
Publication of CN111692035A publication Critical patent/CN111692035A/en
Application granted granted Critical
Publication of CN111692035B publication Critical patent/CN111692035B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03B—MACHINES OR ENGINES FOR LIQUIDS
    • F03B11/00—Parts or details not provided for in, or of interest apart from, the preceding groups, e.g. wear-protection couplings, between turbine and generator
    • F03B11/008—Measuring or testing arrangements
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00—Energy generation through renewable energy sources
    • Y02E10/20—Hydro energy

Landscapes

  • Engineering & Computer Science (AREA)
  • Chemical & Material Sciences (AREA)
  • Combustion & Propulsion (AREA)
  • Mechanical Engineering (AREA)
  • General Engineering & Computer Science (AREA)
  • Control Of Water Turbines (AREA)

Abstract

The invention discloses a method for detecting uneven opening of a guide vane, which is characterized in that characteristic quantities of the opening of the guide vane, a water-guide vibration parameter and a water-guide swing parameter are calculated and then stored in a database, a characteristic value change rate is calculated, a characteristic value change rate component capable of reflecting a fault is determined, and finally logic calculation judgment is carried out to realize hydropower station fault prediction; the invention enhances the accuracy of the monitoring and analysis of the guide vane and avoids the situations of false alarm and missed alarm.

Description

Method for detecting uneven opening degree of guide vane
Technical Field
The invention relates to monitoring of a guide vane of a water turbine, in particular to a method for detecting uneven opening degree of the guide vane.
Background
The guide vane of the water turbine is easy to have the phenomena of water guide vibration, excessive swing, obvious noise, deformation and hairpin of an operating mechanism or a connecting mechanism and the like. The existing equipment cannot accurately analyze a large amount of data, realizes the monitoring of basic parameters of the water turbine only through a small amount of single data, and is easy to generate false alarm; meanwhile, because the low-frequency, frequency-multiplication and frequency-conversion water guide bearing vibration values representing the essential change of equipment are not extracted by frequency division, early warning cannot be carried out before the bolt is broken; the condition of alarm leakage even occurs due to inaccurate data analysis.
Disclosure of Invention
In order to solve the above problems, an object of the present invention is to provide a method for detecting unevenness in opening degree of a guide vane, including:
s1, water in-situ data acquisition: the method comprises the following steps that a sensor collects unit state monitoring data including water-conduction vibration parameters and water-conduction swing parameters and sends the data to a server;
s2, the server divides the frequency of the data and filters: the server performs frequency division filtering on the water-conduction vibration parameters and the water-conduction swing parameters, and stores the filtered data components into a database;
s3, calculating characteristic values of the water-conduction vibration parameters and the water-conduction swing degree parameters;
s4, setting an alarm threshold value of the characteristic value: setting an alarm value of a characteristic value according to state monitoring data of each unit in stable operation;
and S5, calculating the change rate of the characteristic value: carrying out weighted sliding average on the calculated characteristic values and the guide vane opening, the water-guide vibration parameter and the water-guide swing parameter again according to different working conditions, and taking the characteristic value of the unit state monitoring data measured in the latest time window as the maximum weight;
s6, setting a threshold value of the change rate of the characteristic value and alarming according to the threshold value of the change rate of the characteristic value: calculating a current ramp rate according to the set characteristic value threshold value, and calculating the time reaching the characteristic value threshold value according to the ramp rate; the current characteristic value is set as Z, t is the time of deterioration,
Figure GDA0003180865240000021
for slow rate, ZtCharacteristic values after t hours:
Figure GDA0003180865240000022
then:
Figure GDA0003180865240000023
the invention has the beneficial effects that: the characteristic quantities of the guide vane opening degree, the water guide vibration parameter and the water guide swing degree parameter are calculated and then stored in a database, the characteristic value change rate is calculated, the characteristic value change rate component capable of reflecting the fault is determined, and finally logic calculation judgment is carried out to realize hydropower station fault prediction; the invention enhances the accuracy of the monitoring and analysis of the guide vane and avoids the situations of false alarm and missed alarm.
Drawings
FIG. 1 is a flow chart of the present invention.
Detailed Description
The invention will be further described with reference to the accompanying drawings in which:
as shown in fig. 1, the method for detecting the opening unevenness of the guide vane according to the present invention is characterized by including the steps of:
s1, water in-situ data acquisition: the method comprises the following steps that a sensor collects unit state monitoring data including water-conduction vibration parameters and water-conduction swing parameters and sends the data to a server;
s2, the server divides the frequency of the data and filters: the server performs frequency division filtering on the water-conduction vibration parameters and the water-conduction swing parameters, and stores the filtered data components into a database;
s3, calculating the characteristic values of the water-conduction vibration parameter and the water-conduction swing degree parameter: let FtIs the corrected value of the fixed guide vane opening, the water guide vibration parameter and the water guide swing parameter at the time of t, Xt-nIs the real-time values of the opening degree of the fixed guide vane, the water-guided vibration parameter and the water-guided swing degree parameter before n time, n is a time window, wnWeighting the water-conduction vibration parameter and the water-conduction swing parameter value with respect to the time window before the time n;
w1+w2+w3+......+wn＝1；
carrying out weighted moving average based on time series on the real-time values (in hours) and the n-time previous parameter values of the collected guide vane opening, water-guided vibration parameter and water-guided swing parameter:
Ft＝w1*Xt-1+w2*Xt-2+w3*Xt-3+......+wn*Xt-n；
let FtF (x), the opening of the guide vane is x, the water head is y, and the calculated parameter FtAnd fitting and calculating with the guide vane opening, the water guide vibration parameter and the water guide swing parameter:
then:
f(x)＝a0+a1x+a2x2+......+akxk；
let xiIs the guide vane opening with a time window of i,
Figure GDA0003180865240000031
the partial derivative of each coefficient of the function is solved to be zero, and the optimal solution is obtained, namely:
Figure GDA0003180865240000032
the partial derivative is equal to zero and is simplified:
Figure GDA0003180865240000033
setting all coefficients containing only X as the first matrix X, then:
Figure GDA0003180865240000041
the polynomial coefficients to be solved are set as the second matrix a:
Figure GDA0003180865240000042
setting the coefficients containing Y as the third matrix Y, then:
Figure GDA0003180865240000043
the function equation for a partial derivative of zero is:
XA＝Y；
and obtaining a characteristic value result if Y is equal to 0.
S4, setting an alarm threshold value of the characteristic value: setting an alarm value of a characteristic value according to state monitoring data of each unit in stable operation;
and S5, calculating the change rate of the characteristic value: carrying out weighted sliding average on the calculated characteristic values and the guide vane opening, the water-guide vibration parameter and the water-guide swing parameter again according to different working conditions, and taking the characteristic value of the unit state monitoring data measured in the latest time window as the maximum weight;
s6, setting a threshold value of the change rate of the characteristic value and alarming according to the threshold value of the change rate of the characteristic value: calculating a current ramp rate according to the set characteristic value threshold value, and calculating the time reaching the characteristic value threshold value according to the ramp rate; the current characteristic value is set as Z, t is the time of deterioration,
Figure GDA0003180865240000051
for slow rate, ZtCharacteristic values after t hours:
Figure GDA0003180865240000052
then:
Figure GDA0003180865240000053
specifically, hydropower station in-situ data acquisition: the in-situ water guide vibration and oscillation monitoring and collecting box is internally provided with a sensor for collecting unit state data and comprises two groups of analog quantity collecting channels; the unit state monitoring data comprises a water-guided vibration parameter and a water-guided swing parameter; the water-conduction vibration and the water-conduction swing degree are divided into + X direction and + Y direction, the water-conduction vibration and swing degree waveform is recorded by a local acquisition device, data intercommunication is carried out between the water-conduction vibration and swing degree waveform and a unit LCU control screen through a Modbus communication protocol, all local parameters of the unit, which can judge the fault, are converged to a server through an optical fiber by a state monitoring device, the server carries out unified coding management, the server carries out frequency division filtering on all water-conduction vibration parameters and water-conduction swing degree parameters and stores the parameters into an Npgsql relation database, and the frequency division is as follows:
low-frequency components: the component with frequency lower than 0.7X frequency multiplication is set as f3Then;
Figure GDA0003180865240000054
let the frequency multiplication component be f2：
f2＝nX；(n≥2，n∈Z)；
Let the frequency conversion component be f1：
f1＝1X～2X；
Figure GDA0003180865240000055
Let the rotational component be f0：
f0＝1X。
The server frequency division filters the data: the server performs frequency division filtering on the water-conduction vibration parameters and the water-conduction swing parameters, and stores the filtered data components into a database;
and (3) calculating a characteristic value: let FtIs the corrected value of the fixed guide vane opening, the water guide vibration parameter and the water guide swing parameter at the time of t, Xt-nIs the real-time values of the opening degree of the fixed guide vane, the water-guided vibration parameter and the water-guided swing degree parameter before n time, n is a time window, wnWeighting the water-conduction vibration parameter and the water-conduction swing parameter value with respect to the time window before the time n;
w1+w2+w3+......+wn＝1；
the time window shows that the passenger flow data at the time t is influenced by the data at the previous time n, and the value n is selected according to the granularity of the parameter, wherein n is 5.
Carrying out weighted moving average based on time series on the real-time values (in hours) and the n-time previous parameter values of the collected guide vane opening, water-guided vibration parameter and water-guided swing parameter:
Ft＝w1*Xt-1+w2*Xt-2+w3*Xt-3+......+wn*Xt-n；
let FtZ, the opening of the guide vane is x, the water head is y, and the calculated parameter FtAnd fitting and calculating with the guide vane opening, the water guide vibration parameter and the water guide swing parameter:
setting an alarm threshold value of the characteristic value: setting an alarm value of a characteristic value according to state monitoring data of each unit in stable operation;
calculating the change rate of the characteristic value: carrying out weighted sliding average on the calculated characteristic values and the guide vane opening, the water-guide vibration parameter and the water-guide swing parameter again according to different working conditions, and taking the characteristic value of the unit state monitoring data measured in the latest time window as the maximum weight;
setting a threshold value of the change rate of the characteristic value and alarming according to the threshold value of the change rate of the characteristic value: calculating a current ramp rate according to the set characteristic value threshold value, and calculating the time reaching the characteristic value threshold value according to the ramp rate; the current characteristic value is set as Z, t is the time of deterioration,
Figure GDA0003180865240000061
for slow rate, ZtCharacteristic values after t hours:
Figure GDA0003180865240000062
then:
Figure GDA0003180865240000071
if the change amplitude of the recent runout value is increased, the change rate of the characteristic value is very high, so that the time for reaching the threshold value of the characteristic value by the current ramp rate can be calculated according to the threshold value of the characteristic value.
Setting an alarm condition: any one of the yaw frequency component slow rate of the water guide bearing, the vibration frequency component slow rate of the water guide bearing, the characteristic value of the vibration frequency component of the water guide bearing, the vibration low-frequency component slow rate of the water guide bearing and the yaw low-frequency component slow rate of the water guide bearing reaches a set threshold value.
The fault warning of uneven guide vane opening is realized, the fault early warning is realized 20 days in advance when the fault occurs for the first time, the fault early warning is realized 15 days in advance when the fault occurs for the second time, and the fault early warning is realized 21 days in advance when the fault occurs for the third time.
The hydropower station fault prediction method comprises the steps of calculating characteristic quantities of a guide vane opening degree, a water guide vibration parameter and a water guide swing degree parameter, storing the characteristic quantities into a database, calculating a characteristic value change rate, determining a characteristic value change rate component capable of reflecting a fault, and finally performing logic calculation and judgment to realize hydropower station fault prediction.
The technical solution of the present invention is not limited to the limitations of the above specific embodiments, and all technical modifications made according to the technical solution of the present invention fall within the protection scope of the present invention.

Claims (2)

1. The method for detecting the uneven opening degree of the guide vane is characterized by comprising the following steps of:
s1, water in-situ data acquisition: the method comprises the following steps that a sensor collects unit state monitoring data including water-conduction vibration parameters and water-conduction swing parameters and sends the data to a server;
s2, the server divides the frequency of the data and filters: the server performs frequency division filtering on the water-conduction vibration parameters and the water-conduction swing parameters, and stores the filtered data components into a database;
s3, calculating characteristic values of the water-conduction vibration parameters and the water-conduction swing degree parameters;
s4, setting an alarm threshold value of the characteristic value: setting an alarm value of a characteristic value according to state monitoring data of each unit in stable operation;
and S5, calculating the change rate of the characteristic value: carrying out weighted sliding average on the calculated characteristic values and the guide vane opening, the water-guide vibration parameter and the water-guide swing parameter again according to different working conditions, and taking the characteristic value of the unit state monitoring data measured in the latest time window as the maximum weight;
s6, setting a threshold value of the change rate of the characteristic value and alarming according to the threshold value of the change rate of the characteristic value: calculating a current ramp rate according to the set characteristic value threshold value, and calculating the time reaching the characteristic value threshold value according to the ramp rate; the current characteristic value is set as Z, t is the time of deterioration,
Figure FDA0003180865230000011
for slow rate, ZtCharacteristic values after t hours:
Figure FDA0003180865230000012
then:
Figure FDA0003180865230000013
2. the guide vane opening unevenness detection method according to claim 1, characterized in that the specific process of calculating the S3 characteristic value is as follows: let FtIs the corrected value of the fixed guide vane opening, the water guide vibration parameter and the water guide swing parameter at the time of t, Xt-nIs the real-time values of the opening degree of the fixed guide vane, the water-guided vibration parameter and the water-guided swing degree parameter before n time, n is a time window, wnWeighting the water-conduction vibration parameter and the water-conduction swing parameter value with respect to the time window before the time n;
w1+w2+w3+......+wn＝1；
carrying out weighted moving average based on time series on the acquired real-time values of the guide vane opening, the water-guide vibration parameter and the water-guide swing parameter and the parameter value before n time:
Ft＝w1*Xt-1+w2*Xt-2+w3*Xt-3+......+wn*Xt-n；
let Ft＝f(x) The opening degree of the guide vane is x, the water head is y, and the calculated parameter FtAnd fitting and calculating with the guide vane opening, the water guide vibration parameter and the water guide swing parameter:
then:
f(x)＝a0+a1x+a2x2+......+akxk；
let xiIs the guide vane opening with a time window of i,
Figure FDA0003180865230000021
the partial derivative of each coefficient of the function is solved to be zero, and the optimal solution is obtained, namely:
Figure FDA0003180865230000022
Figure FDA0003180865230000023
Figure FDA0003180865230000024
......
Figure FDA0003180865230000025
the partial derivative is equal to zero and is simplified:
Figure FDA0003180865230000026
setting all coefficients containing only X as the first matrix X, then:
Figure FDA0003180865230000031
the polynomial coefficients to be solved are set as the second matrix a:
Figure FDA0003180865230000032
setting the coefficients containing Y as the third matrix Y, then:
Figure FDA0003180865230000033
the function equation for a partial derivative of zero is:
XA＝Y；
and obtaining a characteristic value result if Y is equal to 0.
CN202010573572.4A 2020-06-22 2020-06-22 Method for detecting uneven opening degree of guide vane Active CN111692035B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202010573572.4A CN111692035B (en) 2020-06-22 2020-06-22 Method for detecting uneven opening degree of guide vane

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202010573572.4A CN111692035B (en) 2020-06-22 2020-06-22 Method for detecting uneven opening degree of guide vane

Publications (2)

Publication Number Publication Date
CN111692035A CN111692035A (en) 2020-09-22
CN111692035B true CN111692035B (en) 2021-09-07

Family

ID=72482819

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202010573572.4A Active CN111692035B (en) 2020-06-22 2020-06-22 Method for detecting uneven opening degree of guide vane

Country Status (1)

Country Link
CN (1) CN111692035B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113092096A (en) * 2021-04-13 2021-07-09 哈动国家水力发电设备工程技术研究中心有限公司 Guide bearing parameter-based hydraulic turbine runner damage detection method

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2019065762A (en) * 2017-09-29 2019-04-25 電源開発株式会社 Hybrid servo system
CN110513243A (en) * 2019-08-21 2019-11-29 国家电网有限公司 A kind of stable section of wicket gate control rule determines method and device
CN111222205A (en) * 2019-12-19 2020-06-02 四川华能嘉陵江水电有限责任公司 Paddle opening monitoring and management system and method

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2019065762A (en) * 2017-09-29 2019-04-25 電源開発株式会社 Hybrid servo system
CN110513243A (en) * 2019-08-21 2019-11-29 国家电网有限公司 A kind of stable section of wicket gate control rule determines method and device
CN111222205A (en) * 2019-12-19 2020-06-02 四川华能嘉陵江水电有限责任公司 Paddle opening monitoring and management system and method

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
基于设备特征值的电站设备状态检修;朱卫列等;《热力发电》;20181231;第47卷(第12期);第72-75页 *

Also Published As

Publication number Publication date
CN111692035A (en) 2020-09-22

Similar Documents

Publication Publication Date Title
CN110208019A (en) A kind of dynamic equipment condition monitoring dynamic threshold method for early warning
CN111669123B (en) Method and device for fault diagnosis of photovoltaic string
CN110907170B (en) Wind turbine generator gearbox bearing temperature state monitoring and fault diagnosis method
CN108599724A (en) A kind of photovoltaic module on-line monitoring system and monitoring method
CN111692035B (en) Method for detecting uneven opening degree of guide vane
CN103912448A (en) Method for monitoring power characteristics of units of regional wind farms
CN113632025B (en) Method, system and computer program product for assessing energy consumption in an industrial environment
CN107656156A (en) A kind of equipment fault diagnosis and running status appraisal procedure and system based on cloud platform
CN109583075A (en) Permanent magnet direct-drive wind-force machine military service quality evaluating method based on temperature parameter prediction
CN110730234A (en) Electrical fire monitoring system and intelligent early warning analysis method thereof
CN116795009A (en) Energy-saving control system of variable-flow variable-pressure water supply unit
CN114580852A (en) Water pump breakwater clearance real-time warning system based on industry big data
CN118242331B (en) Mechanical state detection method for hydraulic motor
CN114781143A (en) Method and system for monitoring, early warning and evaluating generated energy of wind power plant
CN115165274A (en) Self-adaptive intelligent monitoring device and method for vibration state of engineering mechanical equipment
CN110578659B (en) System and method for processing SCADA data of wind turbine generator
CN117195136B (en) Power grid new energy abnormal data monitoring method
CN112532615B (en) Smart grid worm detection method
CN112597607B (en) Predictive maintenance method and system for high-speed bearing of wind driven generator
CN111931969A (en) Merging unit equipment state prediction method based on time sequence analysis
CN113218653B (en) Offshore wind power gear box monitoring method and device based on low-frequency disturbance elimination
CN115144052A (en) Hydropower station water head calculation method and system
Agayev et al. Control algorithm based on corrective filter for measuring channel errors
CN117951456B (en) Equipment state intelligent monitoring system based on digital twinning
CN118673448B (en) Electric chain saw chain equipment and work safety detection method

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
CB02 Change of applicant information
CB02 Change of applicant information

Address after: Huaneng building, No.47, section 4, Renmin South Road, Chengdu, Sichuan 610000

Applicant after: Huaneng Sichuan Energy Development Co.,Ltd.

Applicant after: SICHUAN HUANENG JIALINGJIANG HYDROPOWER Co.,Ltd.

Address before: Huaneng building, No.47, section 4, Renmin South Road, Chengdu, Sichuan 610000

Applicant before: Huaneng Sichuan Hydropower Co.,Ltd.

Applicant before: SICHUAN HUANENG JIALINGJIANG HYDROPOWER Co.,Ltd.

GR01 Patent grant
GR01 Patent grant