CN106710160A - Decision-making tree system-based boiler clausilium smoke temperature early-warning method - Google Patents

Abstract

The invention discloses a decision-making tree system-based boiler clausilium smoke temperature early-warning method. The method comprises the following steps of (1) obtaining the data A of the environment of a boiler room and the operation parameters of a boiler, then obtaining the smoke temperature critical value B of a boiler clausilium, and establishing a clausilium smoke temperature error rate table T; (2) establishing a decision-making tree system, establishing a contradistinction system, and logically matching the decision-making tree system with the contradistinction system; (3) acquiring the real-time high and low value data of the boiler clausilium smoke temperature by an electronic sensor, transmitting the data to the decision-making tree system, and obtaining a high and low value probability P of the clausilium smoke temperature; (4) if P is larger than 0.8, judging the boiler clausilium smoke temperature to be abnormal, and sending out an alarm prompt by a center console; (5) obtaining the alarm prompt sent from the center console by the boiler staff, confirming the boiler clausilium smoke temperature by the boiler staff, and correcting the decision-making tree system if the boiler staff confirms the normal state of the boiler clausilium smoke temperature and the misjudgement of the decision-making tree system. According to the technical scheme of the invention, the automatic judgment of the boiler clausilium smoke temperature can be realized, and the judgment of the boiler clausilium smoke temperature is accurate.

Description

A kind of Boiler smoke tube cigarette temperature method for early warning based on decision tree system

Technical field

The invention belongs to early warning technology field, more particularly to a kind of Boiler smoke tube cigarette temperature early warning based on decision tree system Method.

Background technology

Current domestic each smoke pipe cigarette temperature early warning system is provided with electronic sensor prompt system.Traditional electronic sensor Principle is, by the low value high of smoke pipe cigarette temperature, to be perceived by electronic sensor and for the numerical value of each section timely to feed back to middle control System.Work points out to learn the low value high of Boiler smoke tube cigarette temperature by the picture and text of central control system.But high temperature due to generator tube, The corrosivity of stove water, a certain degree of influence is caused on electronic sensor so that cause mistake to estimate in smoke pipe cigarette temperature value of feedback Value, or there is falsity, cause major accident occur with the judgement for causing boiler staff generation mistake.And sensitivity is high Electronic sensor it is expensive, replacing is difficult, and is replaced as frequently as so that producing family's very headache.So current domestic cigarette Pipe cigarette temperature early warning system cannot accurately react the smoke pipe cigarette temperature low value high of boiler.Most electronic sensor uses electricity before this The principles of chemistry produce electrification to the free metal ion in water, and the low value high of smoke pipe cigarette temperature is pointed out by the transmission of electric signal. But it is that underwater gold belongs to that ion motion is active to cause certain interference to result that furnace temperature is too high.

The content of the invention

The purpose of the present invention is that and overcomes the deficiencies in the prior art, there is provided a kind of boiler smoke based on decision tree system Pipe cigarette temperature method for early warning, can immediate correction electronic sensor under circumstances data error, remind boiler staff's cigarette The situation of pipe cigarette temperature so that staff obtains an accurate smoke pipe cigarette tender feeling condition to ensure the operation of boiler normal table, To extend the life-span for using of electronic sensor, the maintenance cost of boiler is reduced, realizes the automatization judgement of Boiler smoke tube cigarette temperature, Accuracy of judgement, no longer needs artificial judgment, mitigates the labour intensity of staff.

To achieve these goals, the invention provides a kind of Boiler smoke tube Yan Wenyu police based on decision tree system Method, comprises the following steps：

Step (1), acquisition boiler room environment and boiler operating parameter data A, then Boiler smoke tube cigarette temperature critical value B is obtained, Mutual pace of learning in data A and critical value BCorrespondence goes out error rate table t, is by the numerical quantization in error rate table t Smoke pipe cigarette temperature error rate table T is set up after decimal between 0-1；

Step (2)：Smoke pipe cigarette temperature error rate table T in step (1) sets up decision tree as decision tree system skeleton System, while the historical data for obtaining staff's artificial judgment Boiler smoke tube cigarette temperature low value high sets up contradistinction system, by decision-making Tree system carries out logic and matches with contradistinction system；

Step (3)：Real-time Boiler smoke tube cigarette temperature data are obtained by electronic sensor, and is transmitted to decision tree system, certainly Smoke pipe cigarette temperature low value probability P high is obtained after the training of plan tree system repeatedly；

Step (4)：Decision tree system judges the size of smoke pipe cigarette temperature low value probability P high, if P is more than 0.8, illustrates pot Stove pipe cigarette temperature is abnormal, and result is transferred to console by decision tree system, and console provides alarm；If P is less than 0.8, then illustrate that Boiler smoke tube cigarette temperature is normal, console will not provide alarm；

Step (5)：After boiler staff obtains the alarm that console sends, to the actual smoke pipe cigarette tender feeling condition of boiler Confirmed, if it is confirmed that the normal then explanation decision tree system misjudgment of rear Boiler smoke tube cigarette temperature, now boiler staff Correct result is inputed into contradistinction system, decision tree system is corrected after now contradistinction system is matched with decision tree system logic again System；If it is confirmed that rear Boiler smoke tube cigarette temperature is abnormal then to illustrate decision tree system correct judgment；

Step (6)：Repeat step (3)-(5), so constantly circulation constantly corrects decision tree system until decision tree system Accuracy of judgement, no longer needs staff's artificial judgment Boiler smoke tube cigarette tender feeling condition.

Further, the formula of decision tree system meets in step (2)：

Wherein：X_SIt is feedback score, X_BHIt is convolution constant, K_XIt is the converse feedback number of plies, S_OIt is vector convolution constant, K_OHIt is fixed Adopted vector constant collection, f_pIt is subset probability, b_HIt is counts, K_hFor error in judgement is counted.

Beneficial effects of the present invention：The present invention can immediate correction electronic sensor under circumstances data error, carry The situation of boiler staff's smoke pipe cigarette temperature of waking up so that staff family obtains an accurate smoke pipe cigarette tender feeling condition to ensure The operation of boiler normal table, to extend the life-span for using of electronic sensor, reduces the maintenance cost of boiler, realizes boiler smoke The automatization judgement of pipe cigarette temperature, accuracy of judgement no longer needs artificial judgment, mitigates the labour intensity of staff.

Brief description of the drawings

In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this Some embodiments of invention, for those of ordinary skill in the art, on the premise of not paying creative work, can be with Other accompanying drawings are obtained according to these accompanying drawings.

Fig. 1 is the flow chart of the embodiment of the present invention.

Specific embodiment

Invention is further illustrated below in conjunction with the accompanying drawings, but is not limited to the scope of the present invention.

Embodiment

As shown in figure 1, a kind of Boiler smoke tube cigarette temperature method for early warning based on decision tree system that the present invention is provided, including such as Lower step：

Step (1), acquisition boiler room environment and boiler operating parameter data A, then Boiler smoke tube cigarette temperature critical value B is obtained, Mutual pace of learning in data A and critical value BCorrespondence goes out error rate table t, is by the numerical quantization in error rate table t Smoke pipe cigarette temperature error rate table T is set up after decimal between 0-1；

Boiler room environmental data includes：Boiler room size, there is a several usable boilers, the species of boiler, uses Time, energy supply type etc..Each item data furnace temperature of boiler operatiopn, cigarette temperature, hydraulic pressure, vapour pressure, water inlet pump discharge, combustor temperature Degree, air channel data, smoke pipe data etc..

Step (2)：Smoke pipe cigarette temperature error rate table T in step (1) sets up decision tree as decision tree system skeleton System, while the historical data for obtaining staff's artificial judgment Boiler smoke tube cigarette temperature low value high sets up contradistinction system, by decision-making Tree system carries out logic and matches with contradistinction system；

Step (3)：Real-time Boiler smoke tube cigarette temperature data are obtained by electronic sensor, and is transmitted to decision tree system, certainly Smoke pipe cigarette temperature low value probability P high is obtained after the training of plan tree system repeatedly；

Step (4)：Decision tree system judges the size of smoke pipe cigarette temperature low value probability P high, if P is more than 0.8, illustrates pot Stove pipe cigarette temperature is abnormal, and result is transferred to console by decision tree system, and console provides alarm；If P is less than 0.8, then illustrate that Boiler smoke tube cigarette temperature is normal, console will not provide alarm；

Step (5)：After boiler staff obtains the alarm that console sends, to the actual smoke pipe cigarette tender feeling condition of boiler Confirmed, if it is confirmed that the normal then explanation decision tree system misjudgment of rear Boiler smoke tube cigarette temperature, now boiler staff Correct result is inputed into contradistinction system, decision tree system is corrected after now contradistinction system is matched with decision tree system logic again System；If it is confirmed that rear Boiler smoke tube cigarette temperature is abnormal then to illustrate decision tree system correct judgment；

Step (6)：Repeat step (3)-(5), so constantly circulation constantly corrects decision tree system until decision tree system Accuracy of judgement, no longer needs staff's artificial judgment Boiler smoke tube cigarette tender feeling condition.

The formula of decision tree system meets in step (2)：

Wherein：X_SIt is feedback score, X_BHIt is convolution constant, K_XIt is the converse feedback number of plies, S_OIt is vector convolution constant, K_OHIt is fixed Adopted vector constant collection, f_pIt is subset probability, b_HIt is counts, K_hFor error in judgement is counted.

The present invention can immediate correction electronic sensor under circumstances data error, remind boiler staff's smoke pipe The situation of cigarette temperature so that staff family obtains an accurate smoke pipe cigarette tender feeling condition to ensure the operation of boiler normal table, To extend the life-span for using of electronic sensor, the maintenance cost of boiler is reduced, realizes the automatization judgement of Boiler smoke tube cigarette temperature, Accuracy of judgement, no longer needs artificial judgment, mitigates the labour intensity of staff.

General principle of the invention, principal character and advantages of the present invention has been shown and described above.The technology of the industry Personnel it should be appreciated that the present invention is not limited to the above embodiments, simply explanation described in above-described embodiment and specification this The principle of invention, various changes and modifications of the present invention are possible without departing from the spirit and scope of the present invention, these changes Change and improvement all fall within the protetion scope of the claimed invention.The claimed scope of the invention by appending claims and its Equivalent is defined.

Claims (2)

1. a kind of Boiler smoke tube cigarette temperature method for early warning based on decision tree system, it is characterised in that comprise the following steps：

Step (1), acquisition boiler room environment and boiler operating parameter data A, then Boiler smoke tube cigarette temperature critical value B is obtained, according to Mutual pace of learning in data A and critical value BCorrespondence goes out error rate table t, is 0-1 by the numerical quantization in error rate table t Between decimal after set up smoke pipe cigarette temperature error rate table T；

Step (2)：Smoke pipe cigarette temperature error rate table T in step (1) sets up decision tree system as decision tree system skeleton System, while the historical data for obtaining staff's artificial judgment Boiler smoke tube cigarette temperature low value high sets up contradistinction system, by decision tree System carries out logic and matches with contradistinction system；

Step (3)：Real-time Boiler smoke tube cigarette temperature data are obtained by electronic sensor, and is transmitted to decision tree system, decision tree Smoke pipe cigarette temperature low value probability P high is obtained after system repeatedly training；

Step (4)：Decision tree system judges the size of smoke pipe cigarette temperature low value probability P high, if P is more than 0.8, illustrates boiler smoke Pipe cigarette temperature is abnormal, and result is transferred to console by decision tree system, and console provides alarm；If P is less than 0.8, Illustrate that Boiler smoke tube cigarette temperature is normal, console will not provide alarm；

Step (5)：After boiler staff obtains the alarm that console sends, the actual smoke pipe cigarette tender feeling condition of boiler is carried out Confirm, if it is confirmed that rear Boiler smoke tube cigarette temperature is normal then to illustrate decision tree system misjudgment, now boiler staff will just True result inputs to contradistinction system, and decision tree system is corrected after now contradistinction system is matched with decision tree system logic again； If it is confirmed that rear Boiler smoke tube cigarette temperature is abnormal then to illustrate decision tree system correct judgment；

Step (6)：Repeat step (3)-(5), so constantly circulation constantly corrects decision tree system until decision tree system judges Accurately, staff's artificial judgment Boiler smoke tube cigarette tender feeling condition is no longer needed.

2. a kind of Boiler smoke tube cigarette temperature method for early warning based on decision tree system according to claim 1, it is characterised in that The formula of decision tree system meets in step (2)：

$\frac{{\mathrm{dX}}_S}{dt}=(1-f_p)b_H{X}_{BH}-k_h\left(\frac{\frac{X_S}{X_{BH}}}{K_X+\frac{X_S}{X_{BH}}}\right)\left(\frac{S_O}{K_{OH}+S_O}\right)X_{BH};$

Wherein：X_SIt is feedback score, X_BHIt is convolution constant, K_XIt is the converse feedback number of plies, S_OIt is vector convolution constant, K_OHFor define to Amount constant collection, f_pIt is subset probability, b_HIt is counts, K_hFor error in judgement is counted.