CN106779235A - A kind of boiler feed early warning method for failure based on decision tree system - Google Patents

A kind of boiler feed early warning method for failure based on decision tree system Download PDF

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Publication number
CN106779235A
CN106779235A CN201611238761.6A CN201611238761A CN106779235A CN 106779235 A CN106779235 A CN 106779235A CN 201611238761 A CN201611238761 A CN 201611238761A CN 106779235 A CN106779235 A CN 106779235A
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decision tree
tree system
boiler
failure
boiler feed
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刘海涛
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Hunan Kun Yu Network Technology Co Ltd
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Hunan Kun Yu Network Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
    • G08B25/002—Generating a prealarm to the central station

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Human Resources & Organizations (AREA)
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  • Strategic Management (AREA)
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  • Game Theory and Decision Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Development Economics (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • General Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
  • Feeding And Controlling Fuel (AREA)

Abstract

The invention discloses a kind of boiler feed early warning method for failure based on decision tree system, comprise the following steps：Step (1), acquisition boiler room environment and boiler operating parameter data A, then boiler feed failure critical value B is obtained, set up oxygen-eliminating device failure error rate table T；Step (2)：Decision tree system is set up, contradistinction system is set up, decision tree system and contradistinction system are carried out into logic matches；Step (3)：Electronic sensor obtains real-time boiler feed data transfer to decision tree system, obtains oxygen-eliminating device failure low value probability P high；Step (4)：If P is more than 0.8, console provides alarm；Step (5)：Boiler staff is confirmed after obtaining the alarm that console sends, if it is confirmed that failure occurs in rear boiler feed then illustrates decision tree system misjudgment, amendment decision tree system.The present invention realizes the automatization judgement of boiler feed failure.

Description

A kind of boiler feed early warning method for failure based on decision tree system
Technical field
The invention belongs to early warning technology field, more particularly to a kind of boiler feed failure based on decision tree system is pre- Alarm method.
Background technology
Current domestic each oxygen-eliminating device early warning failure system is provided with electronic sensor prompt system.Traditional electronic sensor Device principle is, in the low value high that oxygen-eliminating device fails, to be perceived by electronic sensor and timely feed back to the numerical value of each section Central control system.Work points out to learn the low value high that boiler feed fails by the picture and text of central control system.But due to generator tube High temperature, the corrosivity of stove water, a certain degree of influence is caused on electronic sensor so that oxygen-eliminating device failure value of feedback on make Into wrong estimate, or there is falsity, cause major accident occur with the judgement for causing boiler staff generation mistake.And Sensitivity electronic sensor high it is expensive, replacing is difficult, and is replaced as frequently as so that producing family's very headache.So at present Domestic oxygen-eliminating device early warning failure system cannot accurately react the oxygen-eliminating device of boiler and fail low value high.Most electronics before this Sensor produces electrification using electrochemical principle to the free metal ion in water, and oxygen-eliminating device is pointed out by the transmission of electric signal The low value high of failure.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 based on decision tree system is removed Oxygen device early warning method for failure, can immediate correction electronic sensor under circumstances data error, remind boiler staff The situation of oxygen-eliminating device failure so that staff obtains an accurate oxygen-eliminating device failure conditions to ensure boiler normal table Operation, to extend the life-span for using of electronic sensor, reduce boiler maintenance cost, realize boiler feed failure from Dynamicization judges that 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 feed early warning failure side based on decision tree system Method, comprises the following steps：
Step (1), acquisition boiler room environment and boiler operating parameter data A, then obtain boiler feed failure critical value B, the mutual pace of learning in data A and critical value BCorrespondence goes out error rate table t, by the numerical quantization in error rate table t To set up oxygen-eliminating device failure error rate table T after the decimal between 0-1；
Step (2)：Oxygen-eliminating device in step (1) fails error rate table T as decision tree system skeleton, sets up decision-making Tree system, while the historical data for obtaining staff's artificial judgment boiler feed failure low value high sets up contradistinction system, will Decision tree system carries out logic and matches with contradistinction system；
Step (3)：Real-time boiler feed data are obtained by electronic sensor, and is transmitted to decision tree system, decision-making Oxygen-eliminating device failure low value probability P high is obtained after tree system repeatedly training；
Step (4)：Decision tree system judges the size of oxygen-eliminating device failure low value probability P high, if P is more than 0.8, illustrates There is failure in boiler feed, 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 feed is normal, console will not provide alarm；
Step (5)：After boiler staff obtains the alarm that console sends, the actual oxygen-eliminating device situation of boiler is entered Row confirms that, if it is confirmed that rear boiler feed normally then illustrates 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 failure occurs in rear boiler feed then illustrates 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 oxygen-eliminating device failure conditions.
Further, the formula of decision tree system meets in step (2)：
Wherein：XSIt is feedback score, XBHIt is convolution constant, KXIt is the converse feedback number of plies, SOIt is vector convolution constant, KOHIt is fixed Adopted vector constant collection, fpIt is subset probability, bHIt is counts, KhFor 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 that boiler staff oxygen-eliminating device of waking up fails so that staff family obtains an accurate oxygen-eliminating device failure conditions, comes Ensure the operation of boiler normal table, to extend the life-span for using of electronic sensor, reduce the maintenance cost of boiler, realize pot The automatization judgement of stove oxygen-eliminating device failure, 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 feed early warning method for failure based on decision tree system that the present invention is provided, including Following steps：
Step (1), acquisition boiler room environment and boiler operating parameter data A, then obtain boiler feed failure critical value B, the mutual pace of learning in data A and critical value BCorrespondence goes out error rate table t, by the numerical quantization in error rate table t To set up oxygen-eliminating device failure error rate table T after the 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..Boiler operating parameter data include furnace temperature, cigarette temperature, hydraulic pressure, vapour pressure, water inlet pump discharge, combustor Temperature, air channel data, oxygen-eliminating device etc..
Step (2)：Oxygen-eliminating device in step (1) fails error rate table T as decision tree system skeleton, sets up decision-making Tree system, while the historical data for obtaining staff's artificial judgment boiler feed failure low value high sets up contradistinction system, will Decision tree system carries out logic and matches with contradistinction system；
Step (3)：Real-time boiler feed data are obtained by electronic sensor, and is transmitted to decision tree system, decision-making Oxygen-eliminating device failure low value probability P high is obtained after tree system repeatedly training；
Step (4)：Decision tree system judges the size of oxygen-eliminating device failure low value probability P high, if P is more than 0.8, illustrates There is failure in boiler feed, 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 feed is normal, console will not provide alarm；
Step (5)：After boiler staff obtains the alarm that console sends, the actual oxygen-eliminating device situation of boiler is entered Row confirms that, if it is confirmed that rear boiler feed normally then illustrates 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 failure occurs in rear boiler feed then illustrates 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 oxygen-eliminating device failure conditions.
The formula of decision tree system meets in step (2)：
Wherein：XSIt is feedback score, XBHIt is convolution constant, KXIt is the converse feedback number of plies, SOIt is vector convolution constant, KOHIt is fixed Adopted vector constant collection, fpIt is subset probability, bHIt is counts, KhFor error in judgement is counted.
The present invention can immediate correction electronic sensor under circumstances data error, remind boiler staff's deoxygenation The situation of device failure so that staff family obtains an accurate oxygen-eliminating device failure conditions to ensure boiler normal table Operation, to extend the life-span for using of electronic sensor, reduces the maintenance cost of boiler, realizes the automatic of boiler feed failure Change and judge, 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 feed early warning method for failure 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 obtain boiler feed failure critical value B, root According to the 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 oxygen-eliminating device failure error rate table T；
Step (2)：Oxygen-eliminating device in step (1) fails error rate table T as decision tree system skeleton, sets up decision tree system System, while the historical data for obtaining staff's artificial judgment boiler feed failure 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 feed data are obtained by electronic sensor, and is transmitted to decision tree system, decision tree system Oxygen-eliminating device failure low value probability P high is obtained after system repetition training；
Step (4)：Decision tree system judges the size of oxygen-eliminating device failure low value probability P high, if P is more than 0.8, illustrates boiler There is failure in oxygen-eliminating device, and result is transferred to console by decision tree system, and console provides alarm；If P is less than 0.8, Then explanation boiler feed is normal, and console will not provide alarm；
Step (5)：After boiler staff obtains the alarm that console sends, the actual oxygen-eliminating device situation of boiler is carried out really Recognize, if it is confirmed that rear boiler feed normally then illustrates decision tree system misjudgment, now boiler staff will correctly tie Fruit inputs to contradistinction system, and decision tree system is corrected after now contradistinction system is matched with decision tree system logic again；If There is failure then explanation decision tree system correct judgment in boiler feed after confirmation；
Step (6)：Repeat step (3)-(5), so constantly circulation constantly corrects decision tree system until decision tree system judges Accurately, staff's artificial judgment oxygen-eliminating device failure conditions are no longer needed.
2. a kind of boiler feed early warning method for failure based on decision tree system according to claim 1, its feature exists In the formula of decision tree system meets in step (2)：
dX S d t = ( 1 - f p ) b H X B H - k h ( X S X B H K X + X S X B H ) ( S O K O H + S O ) X B H ;
Wherein：XSIt is feedback score, XBHIt is convolution constant, KXIt is the converse feedback number of plies, SOIt is vector convolution constant, KOHFor define to Amount constant collection, fpIt is subset probability, bHIt is counts, KhFor error in judgement is counted.
CN201611238761.6A 2016-12-28 2016-12-28 A kind of boiler feed early warning method for failure based on decision tree system Pending CN106779235A (en)

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Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1841422A (en) * 2005-02-08 2006-10-04 神马科技公司 Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques
US20090125155A1 (en) * 2007-11-08 2009-05-14 Thomas Hill Method and System for Optimizing Industrial Furnaces (Boilers) through the Application of Recursive Partitioning (Decision Tree) and Similar Algorithms Applied to Historical Operational and Performance Data
CN101476715A (en) * 2009-01-20 2009-07-08 西安交通大学 Early warning method for failure of water-cooling wall of power boiler
CN101752866A (en) * 2008-12-10 2010-06-23 上海申瑞电力科技股份有限公司 Automatic heavy-load equipment early warning implementation method based on decision tree
CN105573329A (en) * 2015-12-16 2016-05-11 上海卫星工程研究所 Attitude and orbit control data analysis method based on decision tree
CN106054104A (en) * 2016-05-20 2016-10-26 国网新疆电力公司电力科学研究院 Intelligent ammeter fault real time prediction method based on decision-making tree

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1841422A (en) * 2005-02-08 2006-10-04 神马科技公司 Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques
US20090125155A1 (en) * 2007-11-08 2009-05-14 Thomas Hill Method and System for Optimizing Industrial Furnaces (Boilers) through the Application of Recursive Partitioning (Decision Tree) and Similar Algorithms Applied to Historical Operational and Performance Data
CN101752866A (en) * 2008-12-10 2010-06-23 上海申瑞电力科技股份有限公司 Automatic heavy-load equipment early warning implementation method based on decision tree
CN101476715A (en) * 2009-01-20 2009-07-08 西安交通大学 Early warning method for failure of water-cooling wall of power boiler
CN105573329A (en) * 2015-12-16 2016-05-11 上海卫星工程研究所 Attitude and orbit control data analysis method based on decision tree
CN106054104A (en) * 2016-05-20 2016-10-26 国网新疆电力公司电力科学研究院 Intelligent ammeter fault real time prediction method based on decision-making tree

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