CN104636630A - Thermal power plant steam pressure filtering method based on mean filtering and constant gradient - Google Patents

Abstract

The invention discloses a thermal power plant steam pressure filtering method based on mean filtering and constant gradient. The method comprises the following steps: (1) collecting a group of steam pressure values according to the actual operation condition of a thermal power plant steam water system to serve as initial signals, and processing the initial signals by using mean filtering; (2) grouping the processed steam pressure signals, selecting a reference signal, and solving a corresponding gradient value of the reference signal through a loss function to obtain a steam pressure prediction signal; (3) comparing and analyzing a prediction result of the steam pressure prediction signal and an actual onsite collection result to carry out simulation verification. Aiming at the properties of large step amplitudes and sharp-pointed waveforms of the collected steam pressure signals, the mean filtering and constant gradient methods are used for filtering the steam pressure signals to provide relatively smooth steam pressure signals, provide reliable data information for a turbine, reduce the damage of steam pressure on the equipment, prolong the service life of the equipment and improve the economic benefit of production.

Description

A kind of cogeneration plant's vapor pressure filtering method based on mean filter and constant gradient

Technical field

The present invention relates to a kind of cogeneration plant's vapor pressure filtering method based on mean filter and constant gradient.

Background technology

In cogeneration plant's boiler circuit, done work by Steam Actuation steam turbine, the calorific potential with the steam of high pressure and temperature can be converted into mechanical energy.Vapor pressure is used to weigh the important indicator whether Boiler Steam turnout and load equipment steam consumption balance, and vapor pressure is too high or too low, all can cause the impaired of boiler and load equipment.Therefore, in order to reduce the damage of equipment, increase economic efficiency, research vapor pressure is significant.In actual production process, the vapor pressure signal hopping amplitude collected from scene is very large, and pressure trend is not easily observed, and need carry out filtering to gathered signal.

Mean filter is as a kind of traditional filtering method; be widely used in signal transacting field, but mean filter itself exists intrinsic defect, it well can not protect image detail; while image denoising sound, also destroy the detail section of image, image is thickened.

Summary of the invention

The present invention is in order to solve the problem, propose a kind of cogeneration plant's vapor pressure filtering method based on mean filter and constant gradient, the feature that vapor pressure signal hopping amplitude is large, waveform is sharp-pointed that this method collects for working site, the method of mean filter and constant gradient is adopted to carry out filtering process to vapor pressure signal, the basis of mean filter reduction noise adopt the method for constant gradient improve the sharpness of signal, for steam turbine provides reliable data message, reduce vapor pressure to the damage of equipment, improve serviceable life and the production economy benefit of equipment.

To achieve these goals, the present invention adopts following technical scheme:

Based on cogeneration plant's vapor pressure filtering method of mean filter and constant gradient, comprise the following steps:

(1) using one group of vapour pressure force value gathering according to cogeneration plant boiler circuit practical operation situation as initialize signal, adopt mean filter to process initialize signal;

(2) by the vapor pressure signal grouping after process, choose reference signal, solved the Grad of its correspondence by loss function, obtain vapor pressure prediction signal;

(3) comparative analysis vapor pressure prediction signal predict the outcome and on-the-spot actual acquisition result, carry out simulating, verifying.

In described step (1), concrete grammar is: according to cogeneration plant's boiler circuit practical operation situation, gathers vapor pressure signal x _i(i=0,1 ..., n-1), carry out emulation experiment, observe the curvilinear motion of vapor pressure, use mean filter to obtain signal corresponding to each moment (i=0,1 ..., n-1):

${\stackrel{\‾}{x}}_i=\frac{\underset{k=i}{\overset{p}{\mathrm{\Σ}}}(x_i+x_{i+k})}{p+1}---\left(1\right)$

Above formula represent x _ivapor pressure signal after mean filter process; P+1 represents and x _iadjacent vapor pressure signal number; I represents the sequence number of the vapor pressure signal from collection in worksite, and count from 0, namely 0 represent the 1st group, n-1 represents n-th group.

In described step (2), concrete grammar is:

Using vapor pressure signal first signal after device process after filtering as initialize signal, get a continuous print m signal successively as first group, again using vapor pressure signal second signal after device process after filtering as initialize signal, get a continuous print m signal successively as second group, by that analogy, divide into groups to the vapor pressure signal after device process after filtering, wherein 40≤m≤60, get the M signal of each group (j=0,1 ..., n-1) and as reference signal, if the Grad of each group correspondence is Δ _j, the vapor pressure prediction signal of each group represent with following formula respectively:

${\tilde{x}}_i={\stackrel{\‾}{x}}_j-{\mathrm{\Δ}}_j---\left(2\right)$

In above formula $\mathrm{mj}<i<\mathrm{mj}+\frac{m}{2},$ j＝0,1,…,n-1；

${\tilde{x}}_i={\stackrel{\&OverBar;}{x}}_j+{\mathrm{\&Delta;}}_j---\left(3\right)$

In above formula $\mathrm{mj}+\frac{m}{2}<i<m(j+1),$ j＝0,1,…,n-1，

Wherein j represents the sequence number of the group number that the vapor pressure signal after mean filter process is divided into, and counts, namely 0 represent the 1st group from 0.

In described step (2), the vapor pressure signal demand processed through formula (2) and formula (3) is assessed, namely need to determine a loss function, determine that the vapor pressure prediction signal represented by formula (2) and formula (3) is as estimated signal, the function of estimated signal about Grad represents, and determine that the vapor pressure signal after mean filter process is as actual value, using the quadratic sum of estimated value and true value difference as loss function J (Δ), loss function is as follows:

$J_j\left(\mathrm{\&Delta;}\right)=\underset{i=\mathrm{mj}}{\overset{\mathrm{mj}+m-1}{\mathrm{\&Sigma;}}}{({\tilde{x}}_i-{\stackrel{\&OverBar;}{x}}_i)}^2---\left(4\right)$

Wherein j=0,1 ..., n-1;

In same group, Grad is same value, be brought in formula (4) loss function by formula (2) and formula (3) by the vapor pressure prediction signal that Grad represents, obtaining loss function through abbreviation is quadratic equation with one unknown about Grad, when loss function gets minimum value, draw a Grad, this Grad is exactly make vapor pressure prediction signal get best value.

In described step (2), because loss function is a quadratic equation with one unknown, with least square method immediate derivation draw be loss function get minimum time Grad, the computing formula of loss function minimum value is as follows:

${\stackrel{\&CenterDot;}{J}}_j\left(\mathrm{\&Delta;}\right)=0---\left(5\right)$

The Grad of trying to achieve is substituted into respectively formula (2) and formula (3), draw the predicted value of all vapor pressure signals.

In described step (3), emulation experiment is carried out to vapor pressure signal estimation value, and itself and vapor pressure collection in worksite signal and the vapor pressure signal after mean filter process are compared analysis, find that vapor pressure signal is after mean filter and constant gradient process, vapor pressure signal saltus step range shorter, signal waveform becomes more level and smooth.

Beneficial effect of the present invention is:

(1) computation process is simple, and calculated amount is little;

(2) adopt the method for mean filter and constant gradient to carry out filtering process to vapor pressure signal, the signal transacting of confusion is become smoother signal, reduce the saltus step scope of signal;

(3) the vapor pressure signal of relative smooth is provided after filtering, reduces vapor pressure to the damage of equipment, improve serviceable life and the production economy benefit of equipment.

Accompanying drawing explanation

Fig. 1 is process flow diagram of the present invention;

Fig. 2 is the figure of the current value that the present invention chooses;

Fig. 3 is the figure of current value after mean filter process that the present invention chooses;

Fig. 4 is the figure of current value after mean filter and constant gradient process that the present invention chooses;

Fig. 5 is effect contrast figure of the present invention.

Embodiment:

Below in conjunction with figure, the invention will be further described with embodiment.

As shown in Figure 1, what collect under actual working environment at the scene goes out grinding machine current signal and cogeneration plant's vapor pressure signal similar, and has as similar characteristic.In the following description, grinding machine current signal is gone out for reference with reality, by analyzing mean filter and constant gradient in the reliability processed out in grinding machine current signal and validity, analyze mean filter and the validity of constant gradient method in process cogeneration plant vapor pressure signal.

As shown in Figure 1, be the present invention adopt mean filter and constant gradient method to collection in worksite to the process flow diagram going out grinding machine current signal.

As shown in Figure 2, that gets the collection of part actual job site at random goes out grinding machine current signal, has got 600 at random and go out grinding machine current signal x in the present invention _i(i=0,1 ..., 599), and carry out emulation experiment, draw oscillogram, make discovery from observation, the actual current waveform change that working site is taken out is sharp-pointed, disorderly and unsystematic.

Scheming attached 3 is the oscillogram that the data of grinding machine current signal after mean filter process carry out emulating.

Step 1, the one group of vapour pressure force value gathered according to cogeneration plant boiler circuit practical operation situation is as initialize signal x, and process data with mean filter, the signal after process is replace cogeneration plant's vapor pressure signal with going out grinding machine current signal, collection 600 is gone out grinding machine current signal as initialize signal x _i(i=0,1 ..., 599), often to organize 50 current signals for benchmark, adopt mean filter to process, gone out grinding machine current signal accordingly (i=0,1 ..., 599), and emulate.

Mean filter process current signal x _i(i=0,1 ..., 599) formula as follows:

${\stackrel{\&OverBar;}{x}}_i=\frac{\underset{k=i}{\overset{i+49}{\mathrm{\&Sigma;}}}(x_i+x_{i+k})}{50}---\left(1\right)$

For the 1st of the current signal collected from actual job site the to the 50th as the 1st group of signal.1st signal is x ₀, the 50th signal is x ₄₉, then obtain after substituting into formula (1) as the current signal of the 1st after mean filter process.In like manner, as the current signal of the 2nd after mean filter process, the 2nd to the 51st by the current signal collected from actual job site calculates as the 2nd group of signal substitution formula (1).By that analogy, obtain 600 current signals after mean filter process, and emulate.

Fig. 4 goes out the analogous diagram of grinding machine current signal after mean filter and constant gradient process.

Step 2, gets 50 current signals after filtering after device process as one group, gets the M signal of this group (j=0,1 ..., 599) and as reference signal, if the Grad of each group correspondence is Δ _j, the vapor pressure prediction signal of each group represents with following formula respectively:

${\tilde{x}}_i={\stackrel{\&OverBar;}{x}}_j-{\mathrm{\&Delta;}}_j---\left(2\right)$

50j < i < 50j+25, j=0 in above formula, 1 ..., 599;

${\tilde{x}}_i={\stackrel{\&OverBar;}{x}}_j+{\mathrm{\&Delta;}}_j---\left(3\right)$

50j+25 < i < 50 (j+1), j=0 in above formula, 1 ..., 599.

For the 1st of the current signal after mean filter process the to the 50th as the 1st group of signal.1st signal is 50th signal is reference signal is grad is Δ ₀, the current forecasting signal of this group is expressed as with the formula containing Grad:

${\tilde{x}}_i={\stackrel{\&OverBar;}{x}}_{25}-{\mathrm{\&Delta;}}_0---\left(4\right)$

Wherein i=0,1 ..., 24;

${\tilde{x}}_i={\stackrel{\&OverBar;}{x}}_{25}-{\mathrm{\&Delta;}}_0---\left(5\right)$

Wherein i=26,27 ..., 49.

The current forecasting signal represented by formula (2) and formula (3) is as estimated signal, estimated signal all can represent with the function about Grad, and determine that the current signal after mean filter process is as actual value, using the quadratic sum of estimated value and true value difference as loss function J (Δ), loss function is as follows:

$J_j\left(\mathrm{\&Delta;}\right)=\underset{i=\mathrm{mj}}{\overset{\mathrm{mj}+m-1}{\mathrm{\&Sigma;}}}{({\tilde{x}}_i-{\stackrel{\&OverBar;}{x}}_i)}^2---\left(6\right)$

Wherein j=0,1 ..., n-1.

For the 1st group of current signal after mean filter process, namely with (i=0,1 ..., 49) and be estimated signal, and be expressed as about Grad Δ by formula (4) and formula (5) ₀algebraic expression, with the current signal after mean filter process (i=0,1 ..., 49) and as actual value, substitute into formula (6), namely

$J_0\left(\mathrm{\&Delta;}\right)=\underset{i=0}{\overset{49}{\mathrm{\&Sigma;}}}{({\tilde{x}}_i-{\stackrel{\&OverBar;}{x}}_i)}^2---\left(7\right)$

Wherein i=0,1 ..., 49;

By to loss function differentiate, solving is the Grad Δ of loss function when getting minimum value ₀, namely use following formula (8) to solve Δ ₀, Grad will be solved and substitute into formula, obtain current estimating signal namely grinding machine current forecasting signal is gone out.

${\stackrel{\&CenterDot;}{J}}_j\left(\mathrm{\&Delta;}\right)=0---\left(8\right)$

In like manner, using the 2nd of the current signal after mean filter process the to the 51st as the 2nd group of signal, repeat step 2, solve Grad Δ ₁, and obtain out grinding machine current forecasting signal by that analogy, can in the hope of Grad Δ _i(i=0,1 ..., 599) and go out grinding machine current forecasting signal (i=0,1 ..., 599).

The obtained grinding machine current forecasting signal that goes out is emulated, can Fig. 4 be obtained.

As shown in Figure 5, waveform is placed on inside same Simulation Interface, the current signal waveform after pre-process and post-process can be contrasted more intuitively.

Step 3, carry out emulation experiment, draw the oscillogram of current forecasting signal, analysis mean filter and constant gradient method are to the validity of current signal process, and the method is used in cogeneration plant's vapor pressure signal waveform processing procedure, to the validity of vapor pressure waveform by analysis.

Can see intuitively from Fig. 5 after mean filter and constant gradient process to go out grinding machine current signal saltus step scope minimum, be also minimum to the damage caused of equipment, to raising device context actual motion, there is certain economic benefit.

Cogeneration plant's vapor pressure signal of collection in worksite with go out grinding machine current signal there is identical characteristic.The principle of mean filter and constant gradient method process current signal, same may be used for process vapor pressure signal, to change sharp-pointed, the vapor pressure signal transacting that saltus step atmosphere is large becomes relative smooth, stably vapor pressure signal, in minimizing cogeneration plant boiler circuit, steam is to the damage of steam turbine, and increases economic efficiency.

Although above-mentioned composition graphs is described the specific embodiment of the present invention; but not limiting the scope of the invention; one of ordinary skill in the art should be understood that; on the basis of technical scheme of the present invention, those skilled in the art do not need to pay various amendment or distortion that creative work can make still within protection scope of the present invention.

Claims (6)

1., based on cogeneration plant's vapor pressure filtering method of mean filter and constant gradient, it is characterized in that: comprise the following steps:

(1) using one group of vapour pressure force value gathering according to cogeneration plant boiler circuit practical operation situation as initialize signal, adopt mean filter to process initialize signal;

(2) by the vapor pressure signal grouping after process, choose reference signal, solved the Grad of its correspondence by loss function, obtain vapor pressure prediction signal;

(3) comparative analysis vapor pressure prediction signal predict the outcome and on-the-spot actual acquisition result, carry out simulating, verifying.

2. a kind of cogeneration plant's vapor pressure filtering method based on mean filter and constant gradient as claimed in claim 1, it is characterized in that: in described step (1), concrete grammar is: according to cogeneration plant's boiler circuit practical operation situation, gathers vapor pressure signal x _i(i=0,1 ..., n-1), carry out emulation experiment, observe the curvilinear motion of vapor pressure, use mean filter to obtain signal corresponding to each moment (i=0,1 ..., n-1):

${\stackrel{\&OverBar;}{x}}_i=\frac{\underset{k=i}{\overset{p}{\mathrm{\&Sigma;}}}(x_i+x_{i+k})}{p+1}---\left(1\right)$

Above formula represent x _ivapor pressure signal after mean filter process; P+1 represents and x _iadjacent vapor pressure signal number; I represents the sequence number of the vapor pressure signal from collection in worksite, and count from 0, namely 0 represent the 1st group, n-1 represents n-th group.

3. a kind of cogeneration plant's vapor pressure filtering method based on mean filter and constant gradient as claimed in claim 2, is characterized in that: in described step (2), concrete grammar is:

Using vapor pressure signal first signal after device process after filtering as initialize signal, get a continuous print m signal successively as first group, again using vapor pressure signal second signal after device process after filtering as initialize signal, get a continuous print m signal successively as second group, by that analogy, divide into groups to the vapor pressure signal after device process after filtering, wherein 40≤m≤60, get the M signal of each group (j=0,1 ..., n-1) and as reference signal, if the Grad of each group correspondence is Δ _j, the vapor pressure prediction signal of each group represent with following formula respectively:

${\tilde{x}}_i={\stackrel{\&OverBar;}{x}}_j-{\mathrm{\&Delta;}}_j---\left(2\right)$

In above formula j=0,1 ..., n-1;

${\tilde{x}}_i={\stackrel{\&OverBar;}{x}}_j+{\mathrm{\&Delta;}}_j---\left(3\right)$

In above formula $\mathrm{mj}+\frac{m}{2}<i<m(j+1),$ j＝0,1,…,n-1，

Wherein j represents the sequence number of the group number that the vapor pressure signal after mean filter process is divided into, and counts, namely 0 represent the 1st group from 0.

4. a kind of cogeneration plant's vapor pressure filtering method based on mean filter and constant gradient as claimed in claim 2, it is characterized in that: in described step (2), the vapor pressure signal demand processed through formula (2) and formula (3) is assessed, namely need to determine a loss function, determine that the vapor pressure prediction signal represented by formula (2) and formula (3) is as estimated signal, the function of estimated signal about Grad represents, and determine that the vapor pressure signal after mean filter process is as actual value, using the quadratic sum of estimated value and true value difference as loss function J (Δ), loss function is as follows:

$J_j\left(\mathrm{\&Delta;}\right)=\underset{i=\mathrm{mj}}{\overset{\mathrm{mj}+m-1}{\mathrm{\&Sigma;}}}{({\stackrel{\&OverBar;}{x}}_i-{\stackrel{\&OverBar;}{x}}_i)}^2---\left(4\right)$

Wherein j=0,1 ..., n-1;

In same group, Grad is same value, be brought in formula (4) loss function by formula (2) and formula (3) by the vapor pressure prediction signal that Grad represents, obtaining loss function through abbreviation is quadratic equation with one unknown about Grad, when loss function gets minimum value, draw a Grad, this Grad is exactly make vapor pressure prediction signal get best value.

5. a kind of cogeneration plant's vapor pressure filtering method based on mean filter and constant gradient as claimed in claim 4, it is characterized in that: in described step (2), because loss function is a quadratic equation with one unknown, with least square method immediate derivation draw be loss function get minimum time Grad, the computing formula of loss function minimum value is as follows:

${\stackrel{.}{J}}_j\left(\mathrm{\&Delta;}\right)=0---\left(5\right)$

The Grad of trying to achieve is substituted into respectively formula (2) and formula (3), draw the predicted value of all vapor pressure signals.

6. a kind of cogeneration plant's vapor pressure filtering method based on mean filter and constant gradient as claimed in claim 1, it is characterized in that: in described step (3), emulation experiment is carried out to vapor pressure signal estimation value, and itself and vapor pressure collection in worksite signal and the vapor pressure signal after mean filter process are compared analysis, find that vapor pressure signal is after mean filter and constant gradient process, vapor pressure signal saltus step range shorter, signal waveform becomes more level and smooth.