CN112508350A - Vibration early warning method and system for steam turbine generator unit - Google Patents
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Abstract
The invention belongs to the technical field of thermal power, and particularly relates to a vibration early warning method and a system for a steam turbine generator unit, wherein the method comprises the steps of collecting real-time vibration data of the generator unit; preprocessing the acquired real-time vibration data to obtain sample data in normal operation; determining probability distribution in normal operation according to the sample data, and further determining an envelope curve; evaluating the vibration state according to the position of the envelope line where the vibration test data is located; and determining whether the unit has faults according to the vibration state evaluation result. The invention can monitor and analyze the running condition of the turbo generator unit in real time, can send out early warning before equipment fails, is beneficial to finding potential hidden dangers of the unit as soon as possible, and avoids non-stop of the unit due to vibration, thereby improving the safe running level of the turbo generator unit of the thermal power plant.
Description
Technical Field
The invention belongs to the technical field of thermal power, and particularly relates to a vibration early warning method and system for a steam turbine generator unit.
Background
At present, monitoring of power generation enterprises on abnormal vibration mainly depends on vibration alarm, equipment states can be changed violently for a unit with a small vibration base number when alarm occurs, so that the running state of the equipment is monitored in real time, early warning is given out before the equipment breaks down, vibration caused by abnormal running parameters is analyzed and diagnosed in time, measures are taken, and great significance is brought to the running safety of the unit.
In view of the above defects, the designer actively makes research and innovation to create a vibration early warning method and system for a steam turbine generator unit, which can detect abnormal vibration with small amplitude, timely perform operation adjustment and arrangement and maintenance, improve the management level of the steam turbine generator unit of the thermal power plant, and achieve the purpose of ensuring the operation safety of the steam turbine generator unit.
Disclosure of Invention
The invention aims to provide a vibration early warning method and a vibration early warning system for a steam turbine generator unit, and aims to solve the technical problems.
The invention provides a vibration early warning method and a system for a steam turbine generator unit, which comprises the following steps: collecting real-time vibration data of the unit;
preprocessing the acquired real-time vibration data to obtain sample data in normal operation;
determining probability distribution in normal operation according to the sample data, and further determining an envelope curve;
evaluating the vibration state according to the position of the envelope line where the vibration test data is located;
and determining whether the unit has faults according to the vibration state evaluation result.
As a further improvement of the invention, the vibration data comprises a relative shaft vibration displacement value in the radial direction of the rotating shaft of the unit and a bearing vibration displacement value.
As a further improvement of the invention, the step of preprocessing the acquired real-time vibration data to obtain sample data in normal operation comprises the following steps:
cleaning the collected vibration data, and eliminating noise data, wherein the noise data at least comprises error data and incomplete data;
carrying out Cartesian meshing on the data coordinate system after being cleaned and subjected to noise elimination, setting a unique number for each grid, calculating the number of samples in each grid, and calculating the sample density of each grid and 8 grids around the grid;
traversing all grids of which the grid sample density is not 0 and at least one of the 8 grid sample densities around the grids is 0, extracting the grids as edge grids, and extracting samples in the edge grids as samples for probability distribution estimation.
As a further improvement of the present invention, determining the probability distribution in normal operation according to the sample data, and further determining the envelope specifically includes: the method comprises the steps of obtaining multiple groups of random data when a unit normally operates, determining a probability distribution diagram according to the multiple groups of data, selecting a plurality of data in the probability distribution diagram, determining an envelope curve, and selecting the area of the envelope curve, wherein the envelope curve comprises multiple groups of compact sample data.
As a further improvement of the invention, a plurality of test data are selected, whether the test data are in an envelope curve or not is determined, and if the test data are in the envelope curve, the unit is determined to have no fault.
A turbo generator set vibration early warning system using the turbo generator set vibration early warning method comprises the following steps:
the data acquisition module is used for acquiring real-time vibration data of the unit;
the data preprocessing module is used for preprocessing the acquired real-time vibration data to obtain sample data in normal operation;
the probability distribution estimation module is used for determining probability distribution in normal operation according to the sample data and further determining an envelope curve;
the vibration state evaluation module is used for evaluating the vibration state according to the position of the envelope line where the vibration test data is located;
and the result output module is used for confirming whether the unit has a fault according to the vibration state evaluation result.
As a further improvement, the system also comprises an alarm module which is used for giving an alarm when the unit fails.
As a further improvement of the invention, the data preprocessing module is further configured to perform data cleaning on the acquired vibration data and remove noise data, where the noise data at least includes error data and incomplete data;
carrying out Cartesian meshing on the data coordinate system after being cleaned and subjected to noise elimination, setting a unique number for each grid, calculating the number of samples in each grid, and calculating the sample density of each grid and 8 grids around the grid;
traversing all grids of which the grid sample density is not 0 and at least one of the 8 grid sample densities around the grids is 0, extracting the grids as edge grids, and extracting samples in the edge grids as samples for probability distribution estimation.
As a further improvement of the present invention, the probability distribution estimating module is further configured to determine a probability distribution in normal operation according to the sample data, and further determine the envelope specifically includes: the method comprises the steps of obtaining multiple groups of random data when a unit normally operates, determining a probability distribution diagram according to the multiple groups of data, selecting a plurality of data in the probability distribution diagram, determining an envelope curve, and selecting the area of the envelope curve, wherein the envelope curve comprises multiple groups of compact sample data.
As a further improvement of the invention, the vibration state evaluation module is further configured to select a plurality of test data, determine whether the test data is within an envelope, and if so, determine that the unit has no fault.
By means of the scheme, the vibration early warning method and the vibration early warning system for the steam turbine generator unit are used for analyzing and evaluating the vibration state of the steam turbine generator unit, searching abnormal vibration data, detecting small-amplitude abnormal vibration, timely carrying out operation adjustment and reasonable arrangement and maintenance, reducing non-stop risks of the steam turbine generator unit and improving the safe operation level of the steam turbine generator unit of the thermal power plant.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings.
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FIG. 1 is a schematic diagram of a vibration early warning method for a turbo generator set according to the present invention;
FIG. 2 is a flow chart of a vibration early warning method for a turbo generator set according to the present invention;
fig. 3 is a schematic diagram of probability distribution.
Detailed Description
As shown in fig. 1, the invention discloses a schematic diagram of a vibration early warning method for a steam turbine generator unit, and the method specifically includes:
s1, collecting real-time vibration data of the unit, wherein the vibration data comprise a radial relative shaft vibration displacement value of a rotating shaft of the unit and a vibration displacement value of a bearing;
s2, preprocessing the collected real-time vibration data to obtain sample data in normal operation; specifically, the step of preprocessing the collected real-time vibration data to obtain sample data in normal operation comprises the following steps:
cleaning the collected vibration data, and eliminating noise data, wherein the noise data at least comprises error data and incomplete data;
carrying out Cartesian meshing on the data coordinate system after being cleaned and subjected to noise elimination, setting a unique number for each grid, calculating the number of samples in each grid, and calculating the sample density of each grid and 8 grids around the grid;
traversing all grids of which the grid sample density is not 0 and at least one of the 8 grid sample densities around the grids is 0, extracting the grids as edge grids, and extracting samples in the edge grids as samples for probability distribution estimation.
S3, determining probability distribution in normal operation according to the sample data, and further determining envelope curve; determining probability distribution in normal operation according to the sample data, and further determining the envelope specifically comprises: the method comprises the steps of obtaining multiple groups of random data when a unit normally operates, determining a probability distribution graph according to the multiple groups of data, selecting a plurality of data in the probability distribution graph, determining an envelope curve, selecting the area of the envelope curve, wherein the envelope curve comprises multiple groups of compact sample data, selecting a plurality of test data, determining whether the test data are in the envelope curve or not, and if yes, determining that the unit has no fault.
Before carrying out statistics on probability distribution conditions, probability distribution needs to be estimated, an optimal classification hyperplane algorithm is selected for the probability distribution estimation to calculate, and independent same-distribution training data x meeting a certain distribution P are considered1,x2,L,xlE.x, wherein X1l is the number of observation samples, and X is the observation space of the diagnostic object; assuming that the training data can be separated from the origin by a hyperplane and that the distance of the hyperplane from the origin is greatest among all hyperplanes separating the training data from the origin, the function of the optimal hyperplane is f (x) - ρ -0;
further carrying out probability estimation through a high-dimensional probability distribution function; specifically, the method for introducing the optimal hyperplane algorithm into the kernel function is expanded to a high-dimensional inseparable condition, phi is set as a feature mapping X → F, and a kernel function in a feature space is obtained, namely k (X, y) ═ phi (X) · phi (y)). Introducing lagrange multiplier alphai≥0,βiNot less than 0, all satisfy { x through equivalence transformationi:ai>A sample of 0, i ═ 1,2, Ll } is called a support vector, and the form of the decision function becomes f (x) ═ sgn (∑ a)ik(xi,x)-r)；
After the high-order probability distribution function is estimated, a sample set in normal operation needs to be used as a mode class, and after the unit operates for a period of time, historical vibration data of the unit in fault-free operation is random numbers which accord with certain probability distribution. When a unit fails, the oscillations deviate from this probability distribution, i.e. the probability of such oscillations occurring is very small.
S4, carrying out vibration state evaluation according to the position of an envelope line where the vibration test data are located, wherein the selected envelope line area is as small as possible, and simultaneously, the selected envelope line area surrounds sample data as much as possible, so that the evaluation accuracy can be ensured;
and S5, determining whether the unit has faults according to the vibration state evaluation result, if the vibration test sample is in the envelope curve, determining that no faults occur, otherwise, determining that faults occur, and early warning.
As shown in fig. 2, a flow chart of a vibration early warning method for a steam turbine generator unit is disclosed, which discloses a specific implementation method, firstly, a plurality of groups of real-time vibration data are collected by the steam turbine generator unit, the data comprise unavailable data, such as error data or incomplete data, the collected data are further cleaned, redundant and error data are removed, the processed data are further subjected to vibration vector extraction, namely, cartesian meshing is performed on the processed data, a unique number is set for each mesh, the number of samples in each mesh is calculated, and the sample density of each mesh and 8 meshes around each mesh is calculated; traversing all grids of which the grid sample density is not 0 and at least one of the 8 grid sample densities is 0 around the grids, extracting the grids as edge grids, extracting samples in the edge grids as samples for probability distribution estimation, and further determining probability distribution during normal operation according to the sample data, wherein fig. 3 is a schematic diagram of probability distribution conditions.
The invention also discloses a vibration early warning system of the steam turbine generator unit applying the vibration early warning method of the steam turbine generator unit, which specifically comprises the following steps:
the data acquisition module is used for acquiring real-time vibration data of the unit;
the data preprocessing module is used for preprocessing the acquired real-time vibration data to obtain sample data in normal operation;
the probability distribution estimation module is used for determining probability distribution in normal operation according to the sample data and further determining an envelope curve;
the vibration state evaluation module is used for evaluating the vibration state according to the position of the envelope line where the vibration test data is located;
and the result output module is used for confirming whether the unit has a fault according to the vibration state evaluation result.
The intelligent control system also comprises an alarm module, wherein the alarm module is used for giving an alarm when the unit breaks down.
The data preprocessing module is further used for carrying out data cleaning on the acquired vibration data and eliminating noise data, and the noise data at least comprises error data and incomplete data;
carrying out Cartesian meshing on the data coordinate system after being cleaned and subjected to noise elimination, setting a unique number for each grid, calculating the number of samples in each grid, and calculating the sample density of each grid and 8 grids around the grid;
traversing all grids of which the grid sample density is not 0 and at least one of the 8 grid sample densities around the grids is 0, extracting the grids as edge grids, and extracting samples in the edge grids as samples for probability distribution estimation.
The probability distribution estimation module is further configured to determine a probability distribution in normal operation according to the sample data, and further determine an envelope specifically including: the method comprises the steps of obtaining multiple groups of random data when a unit normally operates, determining a probability distribution graph according to the multiple groups of data, selecting a plurality of data in the probability distribution graph, determining an envelope curve, selecting the area of the envelope curve, finding the envelope curve, enabling the area of the envelope curve to be as small as possible, and surrounding sample data as much as possible.
The vibration state evaluation module is further used for selecting a plurality of test data, determining whether the test data are in an envelope curve, and if so, determining that the unit has no fault.
The method can be used for analyzing and evaluating the vibration state of the unit, searching abnormal vibration data, detecting small-amplitude abnormal vibration, performing operation adjustment and reasonable arrangement and maintenance in time, reducing the non-stop risk of the unit and improving the safe operation level of the steam turbine generator unit of the thermal power plant.
The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention, it should be noted that, for those skilled in the art, many modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (10)
1. A vibration early warning method for a steam turbine generator unit is characterized by comprising the following steps:
collecting real-time vibration data of the unit;
preprocessing the acquired real-time vibration data to obtain sample data in normal operation;
determining probability distribution in normal operation according to the sample data, and further determining an envelope curve;
evaluating the vibration state according to the position of the envelope line where the vibration test data is located;
and determining whether the unit has faults according to the vibration state evaluation result.
2. The vibration early warning method for the steam turbine generator unit according to claim 1, wherein the vibration data comprises a radial relative shaft vibration displacement value of a rotating shaft of the steam turbine generator unit and a bearing vibration displacement value.
3. The vibration early warning method for the steam turbine generator unit according to claim 2, wherein the step of preprocessing the acquired real-time vibration data to obtain sample data in normal operation comprises the following steps:
cleaning the collected vibration data, and eliminating noise data, wherein the noise data at least comprises error data and incomplete data;
carrying out Cartesian meshing on the data coordinate system after being cleaned and subjected to noise elimination, setting a unique number for each grid, calculating the number of samples in each grid, and calculating the sample density of each grid and 8 grids around the grid;
traversing all grids of which the grid sample density is not 0 and at least one of the 8 grid sample densities around the grids is 0, extracting the grids as edge grids, and extracting samples in the edge grids as samples for probability distribution estimation.
4. The vibration early warning method for the steam turbine generator unit according to any one of claims 1 to 3, wherein the determining the probability distribution during normal operation according to the sample data and further determining the envelope specifically includes: the method comprises the steps of obtaining multiple groups of random data when a unit normally operates, determining a probability distribution diagram according to the multiple groups of data, selecting a plurality of data in the probability distribution diagram, determining an envelope curve, and selecting the area of the envelope curve, wherein the envelope curve comprises multiple groups of compact sample data.
5. The vibration early warning method of the steam turbine generator unit according to claim 4, characterized in that a plurality of test data are selected, whether the test data are within an envelope curve or not is determined, and if yes, the unit is determined to be free of faults.
6. A vibration warning system for a steam turbine generator unit, to which the vibration warning method for a steam turbine generator unit according to any one of claims 1 to 5 is applied, comprising:
the data acquisition module is used for acquiring real-time vibration data of the unit;
the data preprocessing module is used for preprocessing the acquired real-time vibration data to obtain sample data in normal operation;
the probability distribution estimation module is used for determining probability distribution in normal operation according to the sample data and further determining an envelope curve;
the vibration state evaluation module is used for evaluating the vibration state according to the position of the envelope line where the vibration test data is located;
and the result output module is used for confirming whether the unit has a fault according to the vibration state evaluation result.
7. The vibration early warning system of the steam turbine generator unit according to claim 6, further comprising an alarm module for alarming when the unit fails.
8. The vibration early warning system of the steam turbine generator unit according to claim 7, wherein the data preprocessing module is further configured to perform data cleaning on the collected vibration data and eliminate noise data, and the noise data at least includes error data and incomplete data;
carrying out Cartesian meshing on the data coordinate system after being cleaned and subjected to noise elimination, setting a unique number for each grid, calculating the number of samples in each grid, and calculating the sample density of each grid and 8 grids around the grid;
traversing all grids of which the grid sample density is not 0 and at least one of the 8 grid sample densities around the grids is 0, extracting the grids as edge grids, and extracting samples in the edge grids as samples for probability distribution estimation.
9. The vibration warning system of the turbo generator set according to any one of claims 6 to 8, wherein the probability distribution estimation module is further configured to determine a probability distribution during normal operation according to the sample data, and further determining the envelope specifically includes: the method comprises the steps of obtaining multiple groups of random data when a unit normally operates, determining a probability distribution diagram according to the multiple groups of data, selecting a plurality of data in the probability distribution diagram, determining an envelope curve, and selecting the area of the envelope curve, wherein the envelope curve comprises multiple groups of compact sample data.
10. The vibration early warning system of the steam turbine generator unit according to claim 9, wherein the vibration state evaluation module is further configured to select a plurality of test data, determine whether the test data is within an envelope curve, and if so, determine that the unit is free of faults.
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Cited By (1)
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