CN103759277A - Intelligent soot blowing closed-loop control method, device and system for coal-fired power station boiler - Google Patents

Abstract

The invention discloses an intelligent soot blowing closed-loop control method, device and system for a coal-fired power station boiler. The method includes the steps that a cleaning factor, a time integral factor and a corresponding supplement factor of a heating surface are determined according to field data collected in real time and are converted into quantization levels respectively in the fuzzy field; the cleaning factor quantization level, the time integral factor quantization level and the supplement factor quantization level are input into a preset soot blowing fuzzy control model, and the soot blowing fuzzy control model is resolved to obtain a corresponding soot blowing confidence coefficient; a corresponding soot blowing instruction is generated according to the soot blowing confidence coefficient and working conditions of a unit and is then sent to a PLC so that the PLC can carry out corresponding soot blowing operation according to the soot blowing instruction. Closed-loop control over a soot blowing system is achieved by comprehensively considering operation factors affecting soot blowing, soot blowing frequency is reduced to the minimum under the condition that heat transfer characteristics of the heating surface are guaranteed, and the purposes of saving energy, reducing consumption and improving the operation economy and safety of the unit are achieved.

Description

Coal-fired power station boiler intelligent ash blowing closed loop control method, device and system

Technical field

The present invention relates to pulverized-coal fired boiler reducing energy consumption and information control field, particularly a kind of coal-fired power station boiler intelligent ash blowing closed loop control method, device and system.

Background technology

Thermoelectricity installation is because capacity is large, high having obtained of energy consumption used widely.But the slagging scorification dust stratification on Power Station Boiler Heating Surface is a current pulverized-coal fired boiler major issue that affects safe and economical boiler operation in service.Because dust stratification makes, heating surface heat transfer resistance increases, heat exchange worsens, and heat transfer efficiency is reduced.Generally speaking, compared with clean condition, be subject to polluting rear boiler efficiency and will reduce 1%-2.5%, exhaust gas temperature rising tens degree.It is a kind of technical measures of effectively avoiding serious dust stratification or slagging scorification that heating surface is purged, and still, no matter is air or steam soot blowing, all want lot of energy, as the steam consumption of steam soot blowing, account for 1% of steam total output, consume 0.7% of boiler thermal output, 0.1% of power plant efficiency.

At present, China power plant generally adopts timing, along flue gas flow, boiler heating surface is blown to the grey method of operation.This mode has the variety of issues such as blindness: on the one hand over-blowing meeting causes heating surface because thermal stress and wearing and tearing damage, and has shortened the life-span of heating surface.The opposing party's top blast ash deficiency can cause exhaust gas temperature to raise, the economy of impact operation, and the Serious Slagging of some heating surface even can cause boiler and fall slag accident, the security of serious threat boiler operatiopn.

Because existing soot blowing and optimal system is also in the open loop operation instruction stage, therefore there is following shortcoming: they cannot accomplish that real-time online carries out coal analysis calculating, to a certain extent the pollutional condition monitoring of heating surface is existed to deviation.In addition, existing system, often just by some parameters, as the clean factor, is monitored fouling of heating surface state, and do not consider impact, blows grey all kinds of factors.Meanwhile, due to the restriction of on-the-spot service condition, the effect of optimization of open cycle system cannot be guaranteed.

Summary of the invention

The embodiment of the present invention provides a kind of coal-fired power station boiler intelligent ash blowing closed loop control method, device and system.Other operation factor of blowing ash by considering impact on the basis at Real-Time Monitoring fouling of heating surface pollutional condition realizes closed-loop control to soot blower system.

According to an aspect of the present invention, provide a kind of coal-fired power station boiler intelligent ash blowing closed loop control method, comprising:

The field data arriving according to Real-time Collection, determine the clean factor, the time integral factor and the corresponding recruitment factor of heating surface, wherein the clean factor is associated with the contaminated degree of heating surface, the time integral factor is associated with the dust stratification speed of heating surface, and recruitment factor is associated with flue gas loss and desuperheating water flow;

Respectively the clean factor, the time integral factor and recruitment factor are converted to the quantification gradation in fuzzy domain;

To clean factor quantification grade, time integral factor quantification grade and recruitment factor quantification gradation and input the predefined grey fuzzy control model that blows, to blowing grey fuzzy control model, resolve, to obtain the corresponding grey confidence level of blowing;

According to blowing grey confidence level and unit operating mode, generate the corresponding grey instruction of blowing;

To blow grey instruction and send to PLC controller, so that PLC controller blows ash manipulation accordingly according to blowing grey instruction.

In one embodiment, clean factor CF=k _sj/ k _lx, wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient.

In one embodiment, clean factor CF=k _sj/ F (k _sj, k _lx), wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient, F is filter function, for retaining the low frequency characteristic of desirable heat transfer coefficient, and synchronizes with actual heat transfer coefficient on high frequency behavioral characteristics.

In one embodiment, actual heat transfer coefficient k _sjfor:

$k_{\mathrm{sj}}=\frac{Q\·B_{\mathrm{cal}}}{A\·\mathrm{\Δt}}\×{10}^3$

Wherein Q is the caloric receptivity that is subject to hot working fluid, B _calfor calculated fuel consumption, the heating surface area that A is heating surface, Δ t is temperature and pressure; Wherein Δ t is:

$\mathrm{\Δt}=\frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}-\mathrm{\Δ}{t}_M}{\ln \frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}}{\mathrm{\Δ}{t}_M}}$

Wherein at heating surface, import and export the temperature difference that respectively has a flue-gas temperature and Temperature of Working, use respectively parameter Δ t _σwith Δ t _mrepresent, and Δ t _σ> Δ t _m;

Wherein Q is associated with reheated steam flow, B _calwith enter stove ature of coal ash content and low heat valve and be associated.

In one embodiment, for the light pipe curtain wall that directly obtains radiations heat energy from burner hearth, desirable heat transfer coefficient is:

$k_{\mathrm{lx}}=\frac{{\mathrm{\α}}_1}{1+(1+Q_f/Q)(\mathrm{\ϵ}+\frac{1}{{\mathrm{\α}}_2}){\mathrm{\α}}_1}$

Wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

In one embodiment, for the convection current light pipe that is directly obtained radiations heat energy by burner hearth, restrain, desirable heat transfer coefficient is:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+(1+Q_f/Q)\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor, and ψ is thermal effective coefficient;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

In one embodiment, for the convection current light pipe tube bank that does not obtain direct radiations heat energy from burner hearth, desirable heat transfer coefficient is:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, ψ is thermal effective coefficient;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

According to a further aspect in the invention, a kind of intelligent ash blowing server of realizing the closed-loop control of coal-fired power station boiler intelligent ash blowing is provided, comprise data receiver unit, clean factor determining unit, time integral factor determining unit, recruitment factor determining unit, converting unit, resolve unit, instruction generation unit and instruction sending unit, wherein:

Data receiver unit, for receiving the field data of data acquisition unit Real-time Collection;

Clean factor determining unit, for according to Real-time Collection to field data determine the clean factor of heating surface, wherein the clean factor is associated with the contaminated degree of heating surface;

Time integral factor determining unit, for according to Real-time Collection to field data determine the time integral factor, wherein the time integral factor is associated with the dust stratification speed of heating surface;

Recruitment factor determining unit, for according to Real-time Collection to field data determine corresponding recruitment factor, wherein recruitment factor is associated with flue gas loss and desuperheating water flow;

Converting unit, for being converted to the clean factor, the time integral factor and recruitment factor respectively the quantification gradation of fuzzy domain;

Resolve unit, for cleaning factor quantification grade, time integral factor quantification grade and recruitment factor quantification gradation, input the predefined grey fuzzy control model that blows, to blowing grey fuzzy control model, resolve, to obtain the corresponding grey confidence level of blowing;

Instruction generation unit, for generating the corresponding grey instruction of blowing according to blowing grey confidence level and unit operating mode;

Instruction sending unit, sends to PLC controller for blowing grey instruction, so that PLC controller blows ash manipulation accordingly according to blowing grey instruction.

In one embodiment, clean factor determining unit is specifically utilized formula CF=k _sj/ k _lxobtain the clean factor, wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient.

In one embodiment, clean factor determining unit is specifically utilized formula CF=k _sj/ F (k _sj, k _lx) obtain and clean the factor, wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient, F is filter function, for retaining the low frequency characteristic of desirable heat transfer coefficient, and synchronizes with actual heat transfer coefficient on high frequency behavioral characteristics.

In one embodiment, clean factor determining unit is specifically utilized formula:

$k_{\mathrm{sj}}=\frac{Q\·B_{\mathrm{cal}}}{A\·\mathrm{\Δt}}\×{10}^3$

Calculate actual heat transfer coefficient k _sj, wherein Q is the caloric receptivity that is subject to hot working fluid, B _calfor calculated fuel consumption, the heating surface area that A is heating surface, Δ t is temperature and pressure; Wherein Δ t is:

$\mathrm{\Δt}=\frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}-\mathrm{\Δ}{t}_M}{\ln \frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}}{\mathrm{\Δ}{t}_M}}$

Wherein at heating surface, import and export the temperature difference that respectively has a flue-gas temperature and Temperature of Working, use respectively parameter Δ t _σwith Δ t _mrepresent, and Δ t _σ> Δ t _m;

Wherein Q is associated with reheated steam flow, B _calwith enter stove ature of coal ash content and low heat valve and be associated.

In one embodiment, clean factor determining unit, specifically for the light pipe curtain wall that directly obtains radiations heat energy from burner hearth, is utilized formula:

$k_{\mathrm{lx}}=\frac{{\mathrm{\α}}_1}{1+(1+Q_f/Q)(\mathrm{\ϵ}+\frac{1}{{\mathrm{\α}}_2}){\mathrm{\α}}_1}$

Calculate desirable heat transfer coefficient k _lx, wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

In one embodiment, clean factor determining unit is specifically restrained for the convection current light pipe that is directly obtained radiations heat energy by burner hearth, utilizes formula:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+(1+Q_f/Q)\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Calculate desirable heat transfer coefficient k _lx, wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor, and ψ is thermal effective coefficient;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

In one embodiment, clean factor determining unit specifically, for the convection current light pipe tube bank that does not obtain direct radiations heat energy from burner hearth, is utilized formula:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Calculate desirable heat transfer coefficient k _lx, wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, ψ is thermal effective coefficient;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

According to a further aspect in the invention, provide a kind of coal-fired power station boiler intelligent ash blowing closed-loop control system, comprise data acquisition unit, intelligent ash blowing server, PLC controller and intelligent ash blowing operator station, wherein:

Data acquisition unit, for Real-time Collection field data, and sends to intelligent ash blowing server by the field data of collection;

Intelligent ash blowing server, the intelligent ash blowing server relating to for above-mentioned arbitrary embodiment;

PLC controller, blows ash manipulation accordingly for the grey instruction of blowing sending according to intelligent ash blowing server;

Intelligent ash blowing operator station, for being presented in the information that soot-blowing control is relevant, and sends the manual control instruction relevant to soot-blowing control by intelligent ash blowing server to PLC controller.

The present invention is by calculating and analyze in real time running status and the pollution level of boiler heating surface, to guarantee that unit economy and security are as prerequisite, by formulating rationally perfect soot-blowing control strategy, realize the intelligent ash blowing closed-loop control system that change " at regular time and quantity " is " appropriate as required ".In the guaranteed situation of heating surface heat transfer characteristic, reduce and blow grey frequency to greatest extent, reach energy-saving and cost-reducing, improve the object of unit operation economy and security.

Accompanying drawing explanation

In order to be illustrated more clearly in the embodiment of the present invention or technical scheme of the prior art, to the accompanying drawing of required use in embodiment or description of the Prior Art be briefly described below, apparently, accompanying drawing in the following describes is only some embodiments of the present invention, for those of ordinary skills, do not paying under the prerequisite of creative work, can also obtain according to these accompanying drawings other accompanying drawing.

Fig. 1 is the schematic diagram of an embodiment of coal-fired power station boiler intelligent ash blowing closed loop control method of the present invention.

Fig. 2 is the schematic diagram of an embodiment of intelligent ash blowing server of the present invention.

Fig. 3 is the schematic diagram of an embodiment of coal-fired power station boiler intelligent ash blowing closed-loop control system of the present invention.

Fig. 4 is the structural representation that intelligent ash blowing of the present invention is optimized an embodiment of closed-loop control system.

Fig. 5 is the logic diagram of an embodiment of intelligent optimization closed-loop control system of the present invention.

The specific embodiment

Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the present invention's part embodiment, rather than whole embodiment.To the description only actually of at least one exemplary embodiment, be illustrative below, never as any restriction to the present invention and application or use.Based on the embodiment in the present invention, those of ordinary skills, not making the every other embodiment obtaining under creative work prerequisite, belong to the scope of protection of the invention.

Unless illustrate in addition, otherwise the parts of setting forth in these embodiments and positioned opposite, numeral expression formula and the numerical value of step not limited the scope of the invention.

, it should be understood that for convenience of description, the size of the various piece shown in accompanying drawing is not to draw according to actual proportionate relationship meanwhile.

For the known technology of person of ordinary skill in the relevant, method and apparatus, may not discuss in detail, but in suitable situation, described technology, method and apparatus should be regarded as authorizing a part for description.

In all examples with discussing shown here, it is exemplary that any occurrence should be construed as merely, rather than as restriction.Therefore, other example of exemplary embodiment can have different values.

It should be noted that: in similar label and letter accompanying drawing below, represent similar terms, therefore, once be defined in an a certain Xiang Yi accompanying drawing, in accompanying drawing subsequently, do not need it to be further discussed.

Fig. 1 is the schematic diagram of an embodiment of coal-fired power station boiler intelligent ash blowing closed loop control method of the present invention.As shown in Figure 1, the method step of the present embodiment is as follows:

Step 101, the field data arriving according to Real-time Collection, determines the clean factor, the time integral factor and the corresponding recruitment factor of heating surface.

Wherein the clean factor is associated with the contaminated degree of heating surface; The time integral factor is associated with the dust stratification speed of heating surface, and the larger expression dust stratification of this factor speed is faster; Recruitment factor is associated with flue gas loss and desuperheating water flow.

In one embodiment, the clean factor can be CF=k _sj/ k _lx, wherein CF is dimensionless factor, k _sjfor actual heat transfer coefficient (W/m ²℃), k _lxfor desirable heat transfer coefficient (W/m ²℃).

In another embodiment, the clean factor can also be CF=k _sj/ F (k _sj, k _lx), wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient, F is filter function, for retaining the low frequency characteristic of desirable heat transfer coefficient, and synchronizes with actual heat transfer coefficient on high frequency behavioral characteristics.

Preferably, can select to be easy to the filter construction form of Project Realization, the transfer function of wave filter is G (s)=Ts/ (Ts+1).The transfer function that wherein G (s) is wave filter, the complex variable that s is Laplace transformation, T is inertia time (s).

Step 102, is converted to the quantification gradation in fuzzy domain by the clean factor, the time integral factor and recruitment factor respectively.

Step 103, will clean factor quantification grade, time integral factor quantification grade and recruitment factor quantification gradation and input the predefined grey fuzzy control model that blows, and resolve, to obtain the corresponding grey confidence level of blowing to blowing grey fuzzy control model.

Step 104, generates the corresponding grey instruction of blowing according to blowing grey confidence level and unit operating mode.

Preferably, can consider unit unusual service condition, main reheated steam overtemperature here and owe the factors such as temperature, heating surface tube wall temperature overtemperature, heating surface blowing time interval, generate the final grey instruction of blowing.

Step 105, will blow grey instruction and send to PLC controller, so that PLC controller blows ash manipulation accordingly according to blowing grey instruction.

The coal-fired power station boiler intelligent ash blowing closed loop control method providing based on the above embodiment of the present invention, by running status and the pollution level of real-time calculating and analysis boiler heating surface, to guarantee that unit economy and security are as prerequisite, by formulating rationally perfect soot-blowing control strategy, realize the intelligent ash blowing closed-loop control system that change " at regular time and quantity " is " appropriate as required ".In the guaranteed situation of heating surface heat transfer characteristic, reduce and blow grey frequency to greatest extent, reach energy-saving and cost-reducing, improve the object of unit operation economy and security.

Here it should be noted that, it is complicated and changeable in power plant's actual moving process, affecting and blowing grey factor, is not also linear relationship between several factors, when blowing ash judgement, only considers that heating surface pollution level is far from being enough.Native system is introduced fuzzy control concept, utilize fuzzy message treatment technology process uncertain, nonlinear problem ability is strong, be applicable to expressing those fuzzy or knowledge qualitatively, and can express the feature such as experience of expert and operator in some field, set up and blown grey fuzzy judgement model.It chooses fuzzy control input and output according to the impact factor that top blast ash judges of being heated, then take heating surface pollution level as main other factors that consider the top blast ash that is heated are as principle formulation fuzzy control rule, design fuzzy controller, finally provide the grey confidence level of blowing of each heating surface, it is larger that the larger expression heating surface of this value need to blow grey tendency.In implementation process, construct fuzzy control model and be divided into the following steps:

A) fuzzy control input and output parameter chooses

For different heating surfaces, it is different that the grey factor of judging is blown in impact, for the actual demand of each top blast ash that is heated, can adopt above-mentioned heating surface to clean the factor, the time integral factor and recruitment factor.

B) obfuscation of fuzzy control parameter

The actual domain of each input parameter is adjusted and is drawn by power plant's actual operating data, and their fuzzy domain is all [33], 3 linguistic variable N of domain definition for this reason, O, P.The basic domain that output parameter blows grey confidence level is [01], and fuzzy domain is [33], 5 linguistic variable N of domain definition for this reason, NM, O, PM, P.

C) membership function chooses

First, membership function be exactly at certain domain to the mapping on [0,1], be used for reflecting that certain object has certain fuzzy quality or belongs to the degree of certain fuzzy concept, through the analysis verification of a large amount of historical datas of this unit, the membership function of each input, output parameter all adopts Gaussian function.

Secondly, basic domain is carried out to quantification gradation processing, the object of this processing is by discrete point continuous on basic domain, several parameter areas are converted into domain scope, then by the membership function of having tried to achieve, ask for the corresponding each fuzzy subset's of each quantification gradation degree of membership, can complete the obfuscation of accurate amount, obtain parameter assignment table.Concrete conversion formula is as follows:

If accurately measuring the real variable scope of x is [a, b], [a, b] interval precision and quantity-variation is converted to [m, m] interval variable y changing, adopt following formula:

Y=2m[x-(a+b)/2]/(b-a)

The quantizing range that this project adopts is [3,3], and the m in above formula is taken as 3.

D) be heated the determining of top blast ash fuzzy rule

The principle that grey fuzzy control rule is blown in foundation is: take heating surface actual levels of pollution as main, consider the factors such as safety in production, status of equipment, determine and reasonably blow grey frequency.Fuzzy control rule table is as shown in table 1.

Table 1

In table 1,1～9 of rule represents the relation of the basic pollution level of heating surface and the blowing time frequency, and Design with Rule implication is, first under normal circumstances, heating surface is unlikely at short notice to repeat to send and blows grey instruction in assurance.Secondly, at heating surface, there is certain dust stratification but not serious or more serious dust stratification in the situation that, suitable elongation or shorten the grey process of next time blowing.

In addition, rule 10～14 logic of supplementaritys participate in forming, effect was in some special occasions, as soot blower under heating surface does not come into operation completely, to cause blowing ash unclean, or purge thoroughly but external factor still makes heating surface have extremely strong fouling and slagging tendentiousness etc. comparatively under emergency, can be suitable ignore temporal frequency limit value and send in time and blow grey instruction.

E) fuzzy reasoning and de-fuzzy method

Fuzzy reasoning and de-fuzzy method are Mamdani rationalistic method.The Output rusults of reasoning is to blow grey confidence level.To the top blast ash Fuzzy Identification Model of being respectively heated, can utilize threshold value to blow ash judgement.Set a threshold value, use the grey confidence value that blows obtaining in real time to compare with it, when being greater than this value, heating surface need blow ash.Blow the setting of grey threshold value, according to off-line test in early stage, consider the normal blowing time of heating surface under various conditions and adjust definite.

Preferably, actual heat transfer coefficient k _sjfor:

$k_{\mathrm{sj}}=\frac{Q\·B_{\mathrm{cal}}}{A\·\mathrm{\Δt}}\×{10}^3$

Wherein Q is the caloric receptivity (kJ/kg) that is subject to hot working fluid, B _calfor calculated fuel consumption (kg/s), the heating surface area (m that A is heating surface ²), Δ t be temperature and pressure (℃).Wherein Δ t is:

$\mathrm{\Δt}=\frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}-\mathrm{\Δ}{t}_M}{\ln \frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}}{\mathrm{\Δ}{t}_M}}$

Wherein at heating surface, import and export the temperature difference that respectively has a flue-gas temperature and Temperature of Working, use respectively parameter Δ t _σwith Δ t _mrepresent, and Δ t _σ> Δ t _m.Wherein Q is associated with reheated steam flow, B _calwith enter stove ature of coal ash content and low heat valve and be associated.

For desirable heat transfer coefficient, can there is following several situation:

For the light pipe curtain wall that directly obtains radiations heat energy from burner hearth, desirable heat transfer coefficient is:

$k_{\mathrm{lx}}=\frac{{\mathrm{\α}}_1}{1+(1+Q_f/Q)(\mathrm{\ϵ}+\frac{1}{{\mathrm{\α}}_2}){\mathrm{\α}}_1}$

Wherein α ₁for fume side exothermic coefficient (W/m ²℃), α ₂for working medium side coefficient of convective heat transfer (W/m ²℃), Q _ffor heating surface, accept the radiations heat energy (kJ/kg) of burner hearth, Q is the caloric receptivity (kJ/kg) that is subject to hot working fluid, and ε is contamination factor (m ²℃/W).Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

For the convection current light pipe that is directly obtained radiations heat energy by burner hearth, restrain, desirable heat transfer coefficient is:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+(1+Q_f/Q)\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor, and ψ is thermal effective coefficient (dimensionless).Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

For the convection current light pipe tube bank that does not obtain direct radiations heat energy from burner hearth, desirable heat transfer coefficient is:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, ψ is thermal effective coefficient.Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

Fig. 2 is the schematic diagram of an embodiment of intelligent ash blowing server of the present invention.As shown in Figure 2, intelligent ash blowing server comprises data receiver unit 201, clean factor determining unit 202, time integral factor determining unit 203, recruitment factor determining unit 204, converting unit 205, resolves unit 206, instruction generation unit 207 and instruction sending unit 208.Wherein:

Data receiver unit 201, for receiving the field data of data acquisition unit Real-time Collection.

Clean factor determining unit 202, for according to Real-time Collection to field data determine the clean factor of heating surface, wherein the clean factor is associated with the contaminated degree of heating surface.

Time integral factor determining unit 203, for according to Real-time Collection to field data determine the time integral factor, wherein the time integral factor is associated with the dust stratification speed of heating surface.

Recruitment factor determining unit 204, for according to Real-time Collection to field data determine corresponding recruitment factor, wherein recruitment factor is associated with flue gas loss and desuperheating water flow.

Converting unit 205, for being converted to the clean factor, the time integral factor and recruitment factor respectively the quantification gradation of fuzzy domain.

Resolve unit 206, for cleaning factor quantification grade, time integral factor quantification grade and recruitment factor quantification gradation, input the predefined grey fuzzy control model that blows, to blowing grey fuzzy control model, resolve, to obtain the corresponding grey confidence level of blowing.

Instruction generation unit 207, for generating the corresponding grey instruction of blowing according to blowing grey confidence level and unit operating mode.

Instruction sending unit 208, sends to PLC controller for blowing grey instruction, so that PLC controller blows ash manipulation accordingly according to blowing grey instruction.

The intelligent ash blowing server providing based on the above embodiment of the present invention, by running status and the pollution level of real-time calculating and analysis boiler heating surface, to guarantee that unit economy and security are as prerequisite, by formulating rationally perfect soot-blowing control strategy, realize the intelligent ash blowing closed-loop control system that change " at regular time and quantity " is " appropriate as required ".In the guaranteed situation of heating surface heat transfer characteristic, reduce and blow grey frequency to greatest extent, reach energy-saving and cost-reducing, improve the object of unit operation economy and security

Preferably, clean factor determining unit 202 is specifically utilized formula CF=k _sj/ k _lxobtain the clean factor, wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient.

Preferably, clean factor determining unit 202 is specifically utilized formula CF=k _sj/ F (k _sj, k _lx) obtain and clean the factor, wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient, F is filter function, for retaining the low frequency characteristic of desirable heat transfer coefficient, and synchronizes with actual heat transfer coefficient on high frequency behavioral characteristics.

Preferably, clean factor determining unit 202 is specifically utilized formula:

$k_{\mathrm{sj}}=\frac{Q\·B_{\mathrm{cal}}}{A\·\mathrm{\Δt}}\×{10}^3$

Calculate actual heat transfer coefficient k _sj, wherein Q is the caloric receptivity that is subject to hot working fluid, B _calfor calculated fuel consumption, the heating surface area that A is heating surface, Δ t is temperature and pressure; Wherein Δ t is:

$\mathrm{\Δt}=\frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}-\mathrm{\Δ}{t}_M}{\ln \frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}}{\mathrm{\Δ}{t}_M}}$

Wherein at heating surface, import and export the temperature difference that respectively has a flue-gas temperature and Temperature of Working, use respectively parameter Δ t _σwith Δ t _mrepresent, and Δ t _σ> Δ t _m;

Wherein Q is associated with reheated steam flow, B _calwith enter stove ature of coal ash content and low heat valve and be associated.

Preferably, clean factor determining unit 202, specifically for the light pipe curtain wall that directly obtains radiations heat energy from burner hearth, is utilized formula:

$k_{\mathrm{lx}}=\frac{{\mathrm{\α}}_1}{1+(1+Q_f/Q)(\mathrm{\ϵ}+\frac{1}{{\mathrm{\α}}_2}){\mathrm{\α}}_1}$

Calculate desirable heat transfer coefficient k _lx, wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

Preferably, clean factor determining unit 202 is specifically restrained for the convection current light pipe that is directly obtained radiations heat energy by burner hearth, utilizes formula:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+(1+Q_f/Q)\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Calculate desirable heat transfer coefficient k _lx, wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor, and ψ is thermal effective coefficient;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

Preferably, clean factor determining unit 202 specifically, for the convection current light pipe tube bank that does not obtain direct radiations heat energy from burner hearth, is utilized formula:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Calculate desirable heat transfer coefficient k _lx, wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, ψ is thermal effective coefficient;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

Fig. 3 is the schematic diagram of an embodiment of coal-fired power station boiler intelligent ash blowing closed-loop control system of the present invention.As shown in Figure 3, this system comprises data acquisition unit 301, intelligent ash blowing server 302, PLC controller (Programmable Logic Controller, programmable logic controller (PLC)) 303 and intelligent ash blowing operator station 304.Wherein:

Data acquisition unit 301, for Real-time Collection field data, and sends to intelligent ash blowing server 302 by the field data of collection.

Intelligent ash blowing server 302, the intelligent ash blowing server relating to for arbitrary embodiment in Fig. 2.

PLC controller 303, blows ash manipulation accordingly for the grey instruction of blowing sending according to intelligent ash blowing server.

Intelligent ash blowing operator station 304, for being presented in the information that soot-blowing control is relevant, and sends the manual control instruction relevant to soot-blowing control by intelligent ash blowing server to PLC controller.

The coal-fired power station boiler intelligent ash blowing closed-loop control system providing based on the above embodiment of the present invention, by running status and the pollution level of real-time calculating and analysis boiler heating surface, to guarantee that unit economy and security are as prerequisite, by formulating rationally perfect soot-blowing control strategy, realize the intelligent ash blowing closed-loop control system that change " at regular time and quantity " is " appropriate as required ".In the guaranteed situation of heating surface heat transfer characteristic, reduce and blow grey frequency to greatest extent, reach energy-saving and cost-reducing, improve the object of unit operation economy and security.

Corresponding intelligent ash blowing is optimized closed-loop control system structure chart as shown in Figure 4.Wherein, operate in the on-the-spot DCS(Distributed Control System that the data communication module on intelligent ash blowing server is calculated for model by communications protocol collection, dcs) data in system, and they are written in the real-time data base on intelligent ash blowing server.Secondly, on intelligent ash blowing server, the running intelligent ash blowing computing platform that has configured algorithm can calculate the grey instruction of blowing of each heating surface and they are sent to PLC controller.Again, PLC controller receives from the instruction of intelligent ash blowing server and the critical data relevant to operation monitoring, then will blow grey instruction and send to DCS by hardwire, and critical data is write to DCS system by communications protocol.Finally, the intelligent ash blowing monitor supervision platform in operator station can be monitored and report to the police the real-time pollution situation of each heating surface, and soot blower running status is carried out real time monitoring and can manually be controlled the start and stop of slag-blowing equipmemt.

Fig. 5 is the logic diagram of an embodiment of intelligent optimization closed-loop control system of the present invention.Lower mask body describes the module in this system logic block diagram.

(1) real-time thermal parameter acquisition module

This module is passed through communications protocol image data, and uses interface that image data is write in real-time data base.It mainly obtains following data: boiler load, heating surface working medium side out temperatures at different levels and pressure, fume side out temperature, economizer exit flue gas oxygen content, air preheater fume side inlet and outlet pressure, soot blower actuating signal, main steam temperature, main vapour pressure, feed temperature, feedwater flow, reheat steam temperature, reheat pressure, high pressure cylinder delivery temperature, high pressure cylinder pressure at expulsion, exhaust gas temperature, cold wind temperature, total blast volume, desuperheating water of superheater flow, feed pump outlet temperature, fuel flow, coal-supplying amount, O in back-end ductwork ₂volume share and SO ₂concentration etc., coal machine import wind-warm syndrome, pulverizer capacity, electric mill stream, electric mill are pressed, coal pulverizer goes out one's intention as revealed in what one says powder mixing temperature, wind inlet flow rate of coal pulverizer, environment temperature etc.

(2) the soft measurement module of power plant's operational factor

It is one of restriction boiler heating surface pollution monitoring model realization major reason real-time, that accurately calculate that the disappearance of power plant's part important state parameter or measurement are forbidden.The technology path that native system adopts Analysis on Mechanism to combine with data fitting, the soft-measuring techniques such as crucial flue gas oxygen content, coal industry analysis and reheated steam flow are furtherd investigate, solved the soot blowing and optimal model calculation deviation problem that the drift of oxygen amount, coal data hysteresis and flow disappearance etc. cause, the real-time online of having realized heating surface pollution monitoring model calculates, and has improved calculating accuracy.This module specifically comprises:

A) the soft measurement module of Oxygen Amount in Flue Gas

The soft Measurement Algorithm of oxygen amount is analyzed therrmodynamic system basic principle and moving law according to matter energy law of conservation, by studying domestic and international more than 400 kinds of coal datas, analyze the inherent restriction relation of boiler heat, air quantity, oxygen amount three, find that it all obeys specific statistical law.

In implementation process, adopt the service datas such as main steam temperature and pressure, feed temperature, feedwater flow, reheated steam flow, reheat steam temperature and pressure, exhaust temperature of HP and pressure, exhaust gas temperature, cold wind temperature to obtain every loss and boiler efficiency and the boiler total oxygen demand heat in boiler heat balance, then in conjunction with total blast volume, obtain the soft measurement result of oxygen amount.

B) the soft measurement module of coal industry analysis

The chemism of the soft Measurement Algorithm of coal industry analysis by coal combustion, heat balance principle, mass balance principle etc. are set up computation model, according to coal pulverizer ventilation, boiler oil amount, boiler oil amount, main steam pressure, exhaust gas temperature etc., be easy to the reliable numerical value of measuring, calculate moisture, ash content and the low heat valve of the stove ature of coal of coming in and going out.

In implementation process, adopt coal pulverizer inlet air temperature, air quantity, coal-supplying amount, coal pulverizer power and coal pulverizer to go out one's intention as revealed in what one says powder mixing temperature and draw moisture by the heat balance solving equation of coal pulverizer.

Secondly, by coal-supplying amount, steam pressure, vapor (steam) temperature, obtain the heat of main steam and reheated steam absorption, then cut the heat that heated feed water and desuperheating water consume, then obtain ature of coal low heat valve in conjunction with heat loss due to exhaust gas.

Finally, based on the conventional coal data of 53 kinds of thermal power plants, by the statistical law of moisture, low heat valve and ature of coal ash content, draw ature of coal ash content.

C) reheated steam flow soft measurement module

Reheated steam flow soft measurement algorithm obtains high-precision stable state reheated steam flow formula by the mass balance equation of reheated steam cold junction.By Fu Liugeer formula, obtain dynamically again heat flow and calculate formula, after the two is merged, obtain reheated steam flow.

In implementation process, by the high throttle (steam) temperatures that add at different levels, pressure and inflow temperature pressure heat balance by height and obtain the amounts of drawing gas at different levels, are deducted to draw gas to measure stable state reheated steam flow value by main steam flow.By Fu Liugeer formula, by the matching of boiler side reheat steam temperature pressure, obtain dynamic reheated steam flow, then by the method for dynamic compensation, the two is merged.

Because those skilled in the art understand how specifically to carry out computing to obtain the result of above-mentioned three soft measurement modules, therefore do not launch here to describe.

(3) heating surface pollutional condition monitoring modular

Native system has been set up take single heating surface as unit, reflects in real time the monitoring algorithm of heating surface pollution level, and unified employing of heating surface cleaned factor representation heating surface pollutional condition.The concrete processing of the clean factor can be referring to the embodiment providing above.

(4) blow grey fuzzy Judgment module

It is complicated and changeable in power plant's actual moving process, affecting and blowing grey factor, is not also linear relationship between several factors, when blowing ash judgement, only considers that heating surface pollution level is far from being enough.Here introduce fuzzy control concept, utilize fuzzy message treatment technology process uncertain, nonlinear problem ability is strong, be applicable to expressing those fuzzy or knowledge qualitatively, and can express the feature such as experience of expert and operator in some field, set up and blown grey fuzzy control model.It chooses fuzzy control input and output according to the impact factor that top blast ash judges of being heated, then take heating surface pollution level as main other factors that consider the top blast ash that is heated are as principle formulation fuzzy control rule, design fuzzy controller, finally provide the grey confidence level of blowing of each heating surface, it is larger that the larger expression heating surface of this value need to blow grey tendency.The clean factor, the time integral factor and the predefined recruitment factor that above can considering in implementation process, in embodiment, relate to, to clean the factor, the time integral factor and predefined recruitment factor is input to and blows in grey fuzzy control model, to blowing grey fuzzy control model, resolve, to obtain the corresponding grey confidence level of blowing.

(5) heating surface soot-blowing control module

In this module, according to blowing grey confidence level, determine whether to send the final grey instruction of blowing.In addition, also can consider unit unusual service condition, main reheated steam overtemperature and owe the factors such as temperature, heating surface tube wall temperature overtemperature, heating surface blowing time interval.

(6) blow grey automatic control module

This module is for operating accordingly according to blowing grey instruction control slag-blowing equipmemt.In addition, this module also can provide intelligent ash blowing monitoring interface, for the real-time pollution situation of each heating surface is monitored and reported to the police, soot blower running status is carried out real time monitoring and can manually be controlled the start and stop of slag-blowing equipmemt.

In implementation process, configuration issue intelligent ash blowing real time monitoring picture, intelligent ash blowing real time monitoring comprises heating surface watch circle and soot blower watch circle, by heating surface watch circle, can monitor the real-time pollutional condition of each heating surface, and blowing grey confidence level while exceeding alarm threshold, can report to the police by corresponding warning setting; By soot blower watch circle, can carry out real time monitoring and can manually control the start and stop of slag-blowing equipmemt the running status of soot blower.

The present invention has realized the quantification monitoring of boiler heating surface pollution level, for heating surface pollution monitoring digitized process, the visual reliable means that provides are provided, be conducive to improve the fine-grained management level of soot blower system operation and operation, to reducing operation personnel working strength, increase work efficiency and power plant's operation and management level significant.

The present invention makes to blow grey frequency and blows the grey steam consumption and power consumption obviously reduces, and has not only extended the service life of slag-blowing equipmemt, has saved corresponding depreciation and maintenance cost, has reduced boiler exhaust gas loss and has promoted boiler efficiency.

One of ordinary skill in the art will appreciate that all or part of step that realizes above-described embodiment can complete by hardware, also can carry out the hardware that instruction is relevant by program completes, described program can be stored in a kind of computer-readable recording medium, the above-mentioned storage medium of mentioning can be read-only storage, disk or CD etc.

Description of the invention provides for example with for the purpose of describing, and is not exhaustively or limit the invention to disclosed form.Many modifications and variations are obvious for the ordinary skill in the art.Selecting and describing embodiment is for better explanation principle of the present invention and practical application, thereby and makes those of ordinary skill in the art can understand the present invention's design to be suitable for the various embodiment with various modifications of special-purpose.

Claims (15)

1. a coal-fired power station boiler intelligent ash blowing closed loop control method, is characterized in that, comprising:

The field data arriving according to Real-time Collection, determine the clean factor, the time integral factor and the corresponding recruitment factor of heating surface, wherein the clean factor is associated with the contaminated degree of heating surface, the time integral factor is associated with the dust stratification speed of heating surface, and recruitment factor is associated with flue gas loss and desuperheating water flow;

Respectively the clean factor, the time integral factor and recruitment factor are converted to the quantification gradation in fuzzy domain;

To clean factor quantification grade, time integral factor quantification grade and recruitment factor quantification gradation and input the predefined grey fuzzy control model that blows, to blowing grey fuzzy control model, resolve, to obtain the corresponding grey confidence level of blowing;

According to blowing grey confidence level and unit operating mode, generate the corresponding grey instruction of blowing;

To blow grey instruction and send to PLC controller, so that PLC controller blows ash manipulation accordingly according to blowing grey instruction.

2. method according to claim 1, is characterized in that,

Clean factor CF=k _sj/ k _lx, wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient.

3. method according to claim 1, is characterized in that,

Clean factor CF=k _sj/ F (k _sj, k _lx), wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient, F is filter function, for retaining the low frequency characteristic of desirable heat transfer coefficient, and synchronizes with actual heat transfer coefficient on high frequency behavioral characteristics.

4. according to the method in claim 2 or 3, it is characterized in that,

Actual heat transfer coefficient k _sjfor:

$k_{\mathrm{sj}}=\frac{Q\·B_{\mathrm{cal}}}{A\·\mathrm{\Δt}}\×{10}^3$

Wherein Q is the caloric receptivity that is subject to hot working fluid, B _calfor calculated fuel consumption, the heating surface area that A is heating surface, Δ t is temperature and pressure; Wherein Δ t is:

$\mathrm{\Δt}=\frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}-\mathrm{\Δ}{t}_M}{\ln \frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}}{\mathrm{\Δ}{t}_M}}$

Wherein at heating surface, import and export the temperature difference that respectively has a flue-gas temperature and Temperature of Working, use respectively parameter Δ t _σwith Δ t _mrepresent, and Δ t _σ> Δ t _m;

Wherein Q is associated with reheated steam flow, B _calwith enter stove ature of coal ash content and low heat valve and be associated.

5. according to the method in claim 2 or 3, it is characterized in that,

For the light pipe curtain wall that directly obtains radiations heat energy from burner hearth, desirable heat transfer coefficient is:

$k_{\mathrm{lx}}=\frac{{\mathrm{\α}}_1}{1+(1+Q_f/Q)(\mathrm{\ϵ}+\frac{1}{{\mathrm{\α}}_2}){\mathrm{\α}}_1}$

Wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

6. according to the method in claim 2 or 3, it is characterized in that,

For the convection current light pipe that is directly obtained radiations heat energy by burner hearth, restrain, desirable heat transfer coefficient is:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+(1+Q_f/Q)\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor, and ψ is thermal effective coefficient;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

7. according to the method in claim 2 or 3, it is characterized in that,

For the convection current light pipe tube bank that does not obtain direct radiations heat energy from burner hearth, desirable heat transfer coefficient is:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, ψ is thermal effective coefficient;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

8. realize the intelligent ash blowing server of coal-fired power station boiler intelligent ash blowing closed-loop control for one kind, it is characterized in that, comprise data receiver unit, clean factor determining unit, time integral factor determining unit, recruitment factor determining unit, converting unit, resolve unit, instruction generation unit and instruction sending unit, wherein:

Data receiver unit, for receiving the field data of data acquisition unit Real-time Collection;

Clean factor determining unit, for according to Real-time Collection to field data determine the clean factor of heating surface, wherein the clean factor is associated with the contaminated degree of heating surface;

Time integral factor determining unit, for according to Real-time Collection to field data determine the time integral factor, wherein the time integral factor is associated with the dust stratification speed of heating surface;

Recruitment factor determining unit, for according to Real-time Collection to field data determine corresponding recruitment factor, wherein recruitment factor is associated with flue gas loss and desuperheating water flow;

Converting unit, for being converted to the clean factor, the time integral factor and recruitment factor respectively the quantification gradation of fuzzy domain;

Resolve unit, for cleaning factor quantification grade, time integral factor quantification grade and recruitment factor quantification gradation, input the predefined grey fuzzy control model that blows, to blowing grey fuzzy control model, resolve, to obtain the corresponding grey confidence level of blowing;

Instruction generation unit, for generating the corresponding grey instruction of blowing according to blowing grey confidence level and unit operating mode;

Instruction sending unit, sends to PLC controller for blowing grey instruction, so that PLC controller blows ash manipulation accordingly according to blowing grey instruction.

9. intelligent ash blowing server according to claim 8, is characterized in that,

Clean factor determining unit is specifically utilized formula CF=k _sj/ k _lxobtain the clean factor, wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient.

10. intelligent ash blowing server according to claim 8, is characterized in that,

Clean factor determining unit is specifically utilized formula CF=k _sj/ F (k _sj, k _lx) obtain and clean the factor, wherein k _sjfor actual heat transfer coefficient, k _lxfor desirable heat transfer coefficient, F is filter function, for retaining the low frequency characteristic of desirable heat transfer coefficient, and synchronizes with actual heat transfer coefficient on high frequency behavioral characteristics.

11. according to the intelligent ash blowing server described in claim 9 or 10, it is characterized in that,

Clean factor determining unit is specifically utilized formula:

$k_{\mathrm{sj}}=\frac{Q\·B_{\mathrm{cal}}}{A\·\mathrm{\Δt}}\×{10}^3$

Calculate actual heat transfer coefficient k _sj, wherein Q is the caloric receptivity that is subject to hot working fluid, B _calfor calculated fuel consumption, the heating surface area that A is heating surface, Δ t is temperature and pressure; Wherein Δ t is:

$\mathrm{\Δt}=\frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}-\mathrm{\Δ}{t}_M}{\ln \frac{\mathrm{\Δ}{t}_{\mathrm{\σ}}}{\mathrm{\Δ}{t}_M}}$

Wherein at heating surface, import and export the temperature difference that respectively has a flue-gas temperature and Temperature of Working, use respectively parameter Δ t _σwith Δ t _mrepresent, and Δ t _σ> Δ t _m;

Wherein Q is associated with reheated steam flow, B _calwith enter stove ature of coal ash content and low heat valve and be associated.

12. according to the intelligent ash blowing server described in claim 9 or 10, it is characterized in that,

Clean factor determining unit, specifically for the light pipe curtain wall that directly obtains radiations heat energy from burner hearth, is utilized formula:

$k_{\mathrm{lx}}=\frac{{\mathrm{\α}}_1}{1+(1+Q_f/Q)(\mathrm{\ϵ}+\frac{1}{{\mathrm{\α}}_2}){\mathrm{\α}}_1}$

Calculate desirable heat transfer coefficient k _lx, wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

13. according to the intelligent ash blowing server described in claim 9 or 10, it is characterized in that,

Clean factor determining unit is specifically restrained for the convection current light pipe that is directly obtained radiations heat energy by burner hearth, utilizes formula:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+(1+Q_f/Q)\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Calculate desirable heat transfer coefficient k _lx, wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, Q _ffor heating surface, accept the radiations heat energy of burner hearth, Q is the caloric receptivity that is subject to hot working fluid, and ε is contamination factor, and ψ is thermal effective coefficient;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

14. according to the intelligent ash blowing server described in claim 9 or 10, it is characterized in that,

Clean factor determining unit specifically, for the convection current light pipe tube bank that does not obtain direct radiations heat energy from burner hearth, is utilized formula:

$k_{\mathrm{lx}}=\frac{\mathrm{\ψ}{\mathrm{\α}}_1}{1+\frac{{\mathrm{\α}}_1}{{\mathrm{\α}}_2}}$

Calculate desirable heat transfer coefficient k _lx, wherein α ₁for fume side exothermic coefficient, α ₂for working medium side coefficient of convective heat transfer, ψ is thermal effective coefficient;

Wherein α ₁with enter stove ature of coal moisture and Oxygen Amount in Flue Gas and be associated.

15. 1 kinds of coal-fired power station boiler intelligent ash blowing closed-loop control systems, is characterized in that, comprise data acquisition unit, intelligent ash blowing server, PLC controller and intelligent ash blowing operator station, wherein:

Data acquisition unit, for Real-time Collection field data, and sends to intelligent ash blowing server by the field data of collection;

Intelligent ash blowing server, the intelligent ash blowing server relating to for any one in claim 8-14;

PLC controller, blows ash manipulation accordingly for the grey instruction of blowing sending according to intelligent ash blowing server;

Intelligent ash blowing operator station, for being presented in the information that soot-blowing control is relevant, and sends the manual control instruction relevant to soot-blowing control by intelligent ash blowing server to PLC controller.

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