CN-121977750-A - Thermal power plant desulfurization equipment sealing detection method and system

CN121977750ACN 121977750 ACN121977750 ACN 121977750ACN-121977750-A

Abstract

The invention relates to the technical field of seal detection, and discloses a seal detection method and a seal detection system for desulfurization equipment of a thermal power plant, wherein the seal detection method for the desulfurization equipment of the thermal power plant comprises the following steps of S101, calculating a time window average value; step S102, obtaining the enthalpy difference between the sealed wind and the environment, step S103, calculating the spatial gradient of the enthalpy field and the Laplacian quantity of the enthalpy field, step S104, fitting the adaptive equivalent diffusion coefficient, step S105, reconstructing the enthalpy equivalent source term field, step S106, calculating the dipole moment abnormality index of the sealed wind cavity source, step S107, calculating the coordinates of leakage points, and step S108, and determining the intensity level. According to the invention, the convection and diffusion comprehensive effects of the flow field of the detection area are comprehensively considered, the equivalent diffusion coefficient is self-adaptively fitted, the spatial positioning of the leakage points is realized through the inversion of the enthalpy equivalent source term field, and the identification and positioning of multiple leakage sources are respectively completed.

Inventors

WANG XUECHEN
LI WEI
SONG JIXIANG
JIANG WENBIN

Assignees

山东鲁华清洁能源有限公司

Dates

Publication Date: 20260505
Application Date: 20260313

Claims (10)

1. The sealing detection method for the desulfurization equipment of the thermal power plant is characterized by comprising the following steps of: Step S101, arranging a meshed sensor array in a monitoring area, collecting the temperature, the relative humidity and the local wind speed of each grid point, and calculating the time window average value of signals of each grid point; step S102, calculating wet air specific enthalpy of each grid point according to temperature and relative humidity, and obtaining the enthalpy difference between seal wind and environment; Step S103, calculating the space gradient of the enthalpy field and the Laplacian quantity of the enthalpy field based on the wet air specific enthalpy of each grid point; step S104, screening a stable region by utilizing the enthalpy field spatial gradient, and fitting a self-adaptive equivalent diffusion coefficient; step S105, reconstructing an enthalpy equivalent source term field of each grid point by using the local wind speed, the enthalpy field spatial gradient, the self-adaptive equivalent diffusion coefficient and the enthalpy field Laplacian amount in the time window mean value; Step S106, calculating a sealed wind cavity source junction dipole moment abnormality index according to the absolute source intensity sum of the enthalpy equivalent source term field and the space first moment relative to the geometric reference point of the monitoring area; Step S107, generating dipole weights by utilizing the dipole moment abnormality indexes of the sealed wind cavity source, performing weighted connected domain decomposition on the enthalpy equivalent source term field, and outputting leakage point coordinates; Step S108, calculating the weighted absolute flux sum of the positive source item and the negative source item in the enthalpy equivalent source item field, dividing the weighted absolute flux sum by the enthalpy difference between the seal wind and the environment to obtain the integral leakage rate, and determining the intensity level according to the fractional number distribution of the integral leakage rate.
2. The method for detecting the sealing of the desulfurization equipment in the thermal power plant according to claim 1, wherein a regularly distributed meshed sensor array is arranged in the monitoring area; For each grid point in the array, acquiring a temperature signal, a relative humidity signal and a local wind speed signal according to fixed frequency in a set time window; The temperature signals at each sampling time in the time window are accumulated and divided by the total sampling times to obtain the time window average value of the temperature; Accumulating the relative humidity signals at each sampling time in the time window and dividing the relative humidity signals by the total sampling times to obtain a time window average value of the relative humidity; And adding up the local wind speed signals at each sampling time in the time window, and dividing the local wind speed signals by the total sampling times to obtain the time window average value of the local wind speed.
3. The method for detecting the sealing of the desulfurization equipment in the thermal power plant according to claim 1, wherein the saturated water vapor pressure is calculated by using the temperature time window average value of the grid points; Multiplying the relative humidity time window mean value of the grid points by saturated water vapor pressure to obtain water vapor partial pressure; Calculating the moisture content of the grid points based on the partial pressure of water vapor and the atmospheric pressure; calculating the wet air specific enthalpy of each grid point according to the dry air constant pressure specific heat capacity, the vaporization latent heat of water at zero ℃, the water vapor constant pressure specific heat capacity, the temperature time window average value and the moisture content; calculating specific enthalpy of sealed air according to the temperature and moisture content of sealed air; calculating the specific enthalpy of the ambient humid air according to the ambient temperature and the ambient moisture content; and subtracting the specific enthalpy of the ambient wet air from the specific enthalpy of the sealed rheumatic air to obtain the difference between the sealed wind and the ambient enthalpy.
4. The method for detecting the sealing of the desulfurization equipment of the thermal power plant according to claim 1, wherein the wet air specific enthalpy of each grid point is processed by a center difference method to obtain the enthalpy field spatial gradient; Subtracting the wet air specific enthalpy of the previous grid point from the wet air specific enthalpy of the next grid point adjacent to the current grid point in the horizontal direction, and dividing the obtained difference by twice the grid spacing in the horizontal direction to obtain a horizontal direction gradient component; subtracting the wet air specific enthalpy of the previous grid point from the wet air specific enthalpy of the next grid point adjacent to the current grid point in the vertical direction, and dividing the obtained difference by twice the grid spacing in the vertical direction to obtain a vertical direction gradient component; forming an enthalpy field spatial gradient by a horizontal gradient component and a vertical gradient component; the wet air specific enthalpy of each grid point is processed by using a center difference method so as to obtain the Laplacian quantity of the enthalpy field; adding the wet air specific enthalpy of the next grid point adjacent to the current grid point in the horizontal direction with the wet air specific enthalpy of the previous grid point, subtracting twice the wet air specific enthalpy of the current grid point, dividing the obtained result by the square of the grid spacing in the horizontal direction, and obtaining a horizontal direction second order difference term; Adding the wet air specific enthalpy of the next grid point adjacent to the current grid point in the vertical direction with the wet air specific enthalpy of the previous grid point, subtracting twice the wet air specific enthalpy of the current grid point, dividing the obtained result by the square of the grid spacing in the vertical direction, and obtaining a second order difference item in the vertical direction; And adding the horizontal second-order difference term and the vertical second-order difference term to obtain the Laplacian enthalpy field.
5. The method for detecting the sealing of the desulfurization equipment of the thermal power plant according to claim 1, wherein the modular length of the enthalpy field spatial gradient of each grid point is calculated, the modular length of the enthalpy field spatial gradients of all the grid points is statistically ordered, grid points with the modular length value smaller than or equal to sixty percent of the quantile of the integral gradient modular length set are selected, and a stable area is formed by the grid points; calculating a self-adaptive equivalent diffusion coefficient based on a least square method principle; Multiplying the dot product result of the local wind speed time window mean value of each grid point in the stable region and the spatial gradient of the enthalpy field by the Laplace quantity of the enthalpy field, carrying out accumulation and summation on all the grid points in the stable region to obtain a molecular term, carrying out accumulation and summation on the square of the Laplace quantity of the enthalpy field of each grid point in the stable region to obtain a denominator term, and dividing the molecular term by the denominator term to obtain the self-adaptive equivalent diffusion coefficient.
6. The method for detecting the sealing of the desulfurization equipment of the thermal power plant according to claim 1, wherein the vector dot product operation is carried out on the time window mean value of the local wind speed of each grid point and the enthalpy field space gradient to obtain the convection transport component; Scalar multiplication operation is carried out on the self-adaptive equivalent diffusion coefficient and Laplacian quantity of the enthalpy field of each grid point, so that a diffusion transport component is obtained; and subtracting the diffusion transport component from the convection transport component to obtain the enthalpy equivalent source term field of each grid point.
7. The method for detecting the sealing of the desulfurization equipment of the thermal power plant according to claim 1, wherein the enthalpy equivalent source term of each grid point takes an absolute value and then multiplies the absolute value by the corresponding unit area, and the multiplication results of all grid points are accumulated and summed to obtain an absolute source intensity sum; subtracting the coordinate vector of the geometric reference point of the monitoring area from the coordinate vector of each grid point to obtain a relative position vector; multiplying the relative position vector by the enthalpy equivalent source item and the unit area of each grid point, carrying out vector accumulation on the calculation results of all the grid points, and obtaining a space first moment relative to the geometric reference point of the monitoring area by taking the modular length of the vector obtained by accumulation; Adding the absolute source intensity sum and the tiny positive number to form a calculation denominator, taking the space first moment as a calculation numerator, and dividing the calculation numerator by the calculation denominator to obtain the sealed wind cavity source sink dipole moment abnormality index.
8. The method for detecting the sealing of the desulfurization equipment of the thermal power plant according to claim 1, wherein the normalized coefficient is obtained by dividing the sealing wind cavity source sink dipole moment abnormality index by one plus the sum of the sealing wind cavity source sink dipole moment abnormality indexes; calculating the modular length of the difference between the coordinate vector of each grid point and the coordinate vector of the geometric reference point of the monitoring area, dividing the modular length by the average distance from the grid point in the area to the geometric reference point of the monitoring area, and obtaining a distance ratio; multiplying the normalized coefficient by the distance ratio and then adding one to obtain dipole weights of all grid points; Carrying out connected domain division on the enthalpy equivalent source term field to obtain a connected domain grid point set; For each connected domain, multiplying the coordinate vector of each grid point in the connected domain by dipole weight, enthalpy equivalent source term absolute value and unit area, and accumulating and summing the product results of all grid points in the connected domain to obtain a coordinate molecular term; multiplying dipole weights of all grid points in the connected domain by the absolute value of the enthalpy equivalent source term and the unit area, and accumulating and summing the product results of all grid points in the connected domain to obtain a coordinate denominator term; and dividing the coordinate numerator term by the coordinate denominator term to obtain the coordinates of the leakage point.
9. The thermal power plant desulfurization equipment sealing detection method according to claim 1, wherein positive source term weighted absolute flux and negative source term weighted absolute flux are calculated respectively; Multiplying and accumulating dipole weights, enthalpy equivalent source items and unit areas aiming at the positive source item grid point set to obtain positive source item weighted absolute flux; multiplying and accumulating dipole weights, enthalpy equivalent source term absolute values and unit areas aiming at the negative source term grid point set to obtain negative source term weighted absolute flux; Adding the positive source weighted absolute flux and the negative source weighted absolute flux, dividing by the enthalpy difference between the sealed wind and the environment, and obtaining the integral leakage rate; Counting the whole leakage rate data set obtained by calculation of a plurality of time windows, and calculating twenty percent, forty percent, sixty percent and eighty percent quantile values respectively; Comparing the current overall leak rate with the fractional values to determine an intensity level; if the overall leakage rate is less than twenty percent of the fractional value, judging the strength grade as a first grade; If the overall leakage rate is greater than or equal to twenty percent of the fractional value and less than forty percent of the fractional value, the intensity level is judged to be a second level; if the overall leakage rate is greater than or equal to forty percent of the quantile value and less than sixty percent of the quantile value, the intensity level is judged to be three levels; if the overall leakage rate is greater than or equal to sixty percent of the quantile value and less than eighty percent of the quantile value, the intensity level is judged to be four-level; If the overall leak rate is greater than or equal to eighty percent of the quantile value, the intensity level is determined to be five.
10. Thermal power plant desulfurization equipment seal detection system, characterized in that a thermal power plant desulfurization equipment seal detection method according to any one of claims 1 to 9 is performed, comprising: The data acquisition module is used for arranging a meshed sensor array in a monitoring area, acquiring the temperature, the relative humidity and the local wind speed of each grid point, and calculating the time window average value of signals of each grid point; the wet air specific enthalpy calculation module is used for calculating wet air specific enthalpy of each grid point according to the temperature and the relative humidity and obtaining enthalpy difference between the seal wind and the environment; The enthalpy field Laplace calculation module is used for calculating the enthalpy field spatial gradient and the enthalpy field Laplace based on the wet air specific enthalpy of each grid point; The equivalent diffusion coefficient drawing-up module utilizes the enthalpy field space gradient to screen a stable region and fits the self-adaptive equivalent diffusion coefficient; The enthalpy equivalent source term field calculation module is used for reconstructing the enthalpy equivalent source term field of each grid point by utilizing the local wind speed, the enthalpy field spatial gradient, the self-adaptive equivalent diffusion coefficient and the enthalpy field Laplacian quantity in the time window mean value; the abnormality index calculation module calculates the sealed wind cavity source junction dipole moment abnormality index according to the absolute source intensity sum of the enthalpy equivalent source term field and the space first moment relative to the geometric reference point of the monitoring area; The leakage point coordinate calculation module generates dipole weights by utilizing the dipole moment abnormality indexes of the sealed air cavity source, performs weighted connected domain decomposition on the enthalpy equivalent source term field and outputs the leakage point coordinates; And the integral leakage rate calculation module is used for calculating the weighted absolute flux sum of the positive source item and the negative source item in the enthalpy equivalent source item field, dividing the weighted absolute flux sum by the enthalpy difference between the sealing wind and the environment to obtain the integral leakage rate, and determining the intensity level according to the fractional number distribution of the integral leakage rate.

Description

Thermal power plant desulfurization equipment sealing detection method and system Technical Field The invention relates to the technical field of seal detection, in particular to a seal detection method and a seal detection system for desulfurization equipment of a thermal power plant. Background The sealing performance of the thermal power plant desulfurization equipment directly influences the operation efficiency of a desulfurization system, and is an important guarantee for the field operation safety of the power plant. The connection part of the desulfurization sealing cavity and the sealing air pipeline is a high-incidence area of leakage problem, and the part is easy to cause leakage due to various factors such as component aging caused by long-term operation of equipment, assembly deviation in the installation process, equipment vibration caused by on-site working condition fluctuation and the like, so that the sealing state of the desulfurization equipment is subjected to normalized detection, and the desulfurization equipment becomes necessary work for operation and maintenance of a desulfurization system of a thermal power plant. In the current detection method for sealing of desulfurization equipment in industry, single temperature or humidity parameters are mostly adopted for on-site monitoring, and the mode can only preliminarily judge whether the equipment has leakage or not, cannot further determine the specific space position of the leakage, and cannot effectively quantify the leakage. Meanwhile, the conventional detection method does not consider the comprehensive effects of convection and diffusion of the flow field of the detection area, key parameters such as a diffusion coefficient and the like are preset manually in the detection process, so that the deviation between the preset parameters and the on-site actual flow field characteristics is large, the method does not carry out systematic quantization analysis on the spatial distribution characteristics of the wet air enthalpy field, and the related information of the leakage source cannot be inverted through the enthalpy transportation rule. The existing detection method is mainly used for empirically estimating the leakage quantity, lacks clear physical rule support and has limited reference value of calculation results. The single detection result is also easily affected by factors such as on-site flow field instantaneous disturbance, sensor acquisition errors and the like, and the data stability is insufficient. The sealing leakage strength grading standard based on statistical characteristics is not relied on in the industry, the problems of fuzzy positioning of leakage points and superposition calculation distortion of leakage quantity are easy to occur in the actual scene of multiple leakage sources, and finally, the detection result cannot effectively guide the on-site sealing repair operation and is difficult to support the scientific operation and maintenance of desulfurization equipment. Disclosure of Invention The invention provides a sealing detection method and a sealing detection system for desulfurization equipment of a thermal power plant, which solve the technical problems in the background technology. The invention provides a sealing detection method of desulfurization equipment of a thermal power plant, which comprises the following steps: Step S101, arranging a meshed sensor array in a monitoring area, collecting the temperature, the relative humidity and the local wind speed of each grid point, and calculating the time window average value of signals of each grid point; step S102, calculating wet air specific enthalpy of each grid point according to temperature and relative humidity, and obtaining the enthalpy difference between seal wind and environment; Step S103, calculating the space gradient of the enthalpy field and the Laplacian quantity of the enthalpy field based on the wet air specific enthalpy of each grid point; step S104, screening a stable region by utilizing the enthalpy field spatial gradient, and fitting a self-adaptive equivalent diffusion coefficient; step S105, reconstructing an enthalpy equivalent source term field of each grid point by using the local wind speed, the enthalpy field spatial gradient, the self-adaptive equivalent diffusion coefficient and the enthalpy field Laplacian amount in the time window mean value; Step S106, calculating a sealed wind cavity source junction dipole moment abnormality index according to the absolute source intensity sum of the enthalpy equivalent source term field and the space first moment relative to the geometric reference point of the monitoring area; Step S107, generating dipole weights by utilizing the dipole moment abnormality indexes of the sealed wind cavity source, performing weighted connected domain decomposition on the enthalpy equivalent source term field, and outputting leakage point coordinates; Step S108, calculating the weighted absolute