CN103678877A - Elevator sub-health evaluation method based on fuzzy mathematics - Google Patents
Elevator sub-health evaluation method based on fuzzy mathematics Download PDFInfo
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- CN103678877A CN103678877A CN201310563201.8A CN201310563201A CN103678877A CN 103678877 A CN103678877 A CN 103678877A CN 201310563201 A CN201310563201 A CN 201310563201A CN 103678877 A CN103678877 A CN 103678877A
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- 238000011156 evaluation Methods 0.000 title claims abstract description 32
- 239000011159 matrix material Substances 0.000 claims description 18
- 238000013507 mapping Methods 0.000 claims description 2
- 238000000034 method Methods 0.000 abstract description 7
- 238000012423 maintenance Methods 0.000 description 3
- 241000894006 Bacteria Species 0.000 description 2
- 230000002159 abnormal effect Effects 0.000 description 2
- 238000003915 air pollution Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 231100000749 chronicity Toxicity 0.000 description 1
- 230000034994 death Effects 0.000 description 1
- 231100000517 death Toxicity 0.000 description 1
- 230000005802 health problem Effects 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
Abstract
The invention relates to an elevator sub-health evaluation method based on fuzzy mathematics, and belongs to the technical field of elevator sub-health. The method comprises the steps that (1) a fuzzy comprehensive evaluation set is built; (2) the membership degree of factors influencing elevator sub-health is determined; (3) the weight of each influence factor for elevator sub-health is determined; (4) elevator sub-health is evaluated comprehensively. The elevator sub-health evaluation method based on fuzzy mathematics is different from an existing elevator sub-health evaluation method, the elevator sub-health degree is judged by comprehensively considering various factors influencing elevator sub-health rather than judging the certain elevator sub-health degree according to one factor, and multiple factors are effectively considered.
Description
Technical field
The present invention relates to a kind of elevator inferior health evaluation method based on fuzzy mathematics, belong to elevator inferior health technical field.
Background technology
28.5 ten thousand 163 ten thousand of increasing to the end of the year 2011 of China's elevator quantity at the bottom of by calendar year 2001, and increasing with the speed of 20% left and right every year, China has been the country of elevator owning amount maximum in the world at present.And the elevator accident taking place frequently in recent years causes government and the extensive concern of various circles of society to the safety of elevator.According to the statistics of State General Administration for Quality Supervision, show, there are every year on average 40 left and right of elevator accident in the whole nation in recent years, injures and deaths more than 40 people, and since 2011, elevator accident has obvious ascendant trend.
It is abnormal that the inferior health of elevator refers to that elevator occurs in some operational factor, and abnormal conditions do not reach peak value, and its sign shows as and works well, but has potential safety hazard, as do not found in time to correct, will cause great public safety accident.Elevator inferior health has the features such as disguise, indirect, chronicity.Therefore the inferior health problem ubiquity of elevator is but difficult to qualitative and evaluates, and causes government regulation, repair and maintenance organizational maintenance and accident prevention to judge by rule of thumb, occur that supervision is at present ineffective, repair and maintenance not in time, prevent present situation not in place.
Summary of the invention
The technical problem to be solved in the present invention is: build a kind of elevator inferior health evaluation method based on fuzzy mathematics.According to elevator, detect data feature qualitatively, adopt existing fuzzy mathematics theory to evaluate, method is simple, feasible, and use value is higher.
Technical scheme of the present invention is:
An elevator inferior health evaluation method based on fuzzy mathematics, is characterized in that, comprises the steps:
(1) set up fuzzy overall evaluation set, establishing affects the sets of factors of elevator inferior health and is
the set of choice comment is
(2) determine the degree of membership of each factor that affects elevator inferior health.First on affecting inferior health factor
usingle factor in set
make simple element evaluation, from factor
have in mind and determine that this things is to choice grade
degree of membership
, draw
iindividual factor
simple element evaluation collection
, it is choice comment collection
von fuzzy subset,
mthe evaluation collection of individual influence factor just constructs a total evaluation matrix
r, reflected two set
u, Vbetween certain correlationship of existing,
Wherein,
expression factor
to choice grade
subjection degree.
(3) determine the weight of each influence factor to elevator inferior health.
For being passed judgment on things, owing to having factor in mind and can obtain different resolutely conclusions from different, and in many factors that affects elevator inferior health
in, the influence degree of elevator inferior health is differed, exist fuzzy preferentially factor, therefore the starting point of evaluating can be regarded the plain domain of impact as
uon fuzzy subset
a, be denoted as
(4) comprehensive evaluation
Determining fuzzy matrix
rand fuzzy vector
atime, can comprehensively pass judgment on do blurring mapping;
Further comprise following operation:
(5) first determine the principal element that affects elevator inferior health, and set up standard separately for affecting each factor of elevator inferior health, to represent its influence degree to elevator inferior health;
(6) determine to evaluate set, form and evaluate domain, can be divided into healthy, healthy, more healthy, critical, dangerous especially, danger close etc.;
(7) determine the degree of membership of each influence factor, by expert opinion, obtain degree of membership.
(8) calculate the comparison judgment matrix between adjacent layer
, wherein
it is element
iwith
jthe ratio scale of importance.
Being further operable to of (8) wherein:
(9) described comparison judgment matrix ratio scale is
According to ratio scale table, compare between two, try to achieve comparison judgment matrix, by existing root method, obtain
weight.
(10) judgment matrix is done to consistency check, use existing consistency check method, whether judged result is reasonable.
(11) described degree of membership
reach element numerical value in matrix is all between 0～1.Described weight
aeach element numerical value in matrix is all between 0～1.
The invention has the beneficial effects as follows:
(1) the present invention is different from existing elevator inferior health evaluation method, not only according to a factor, just to judge some elevator inferior health degree, but consider various affect elevator inferior health because usually judging, be a kind of effectively with reference to multifactorial method.
(2) method practicality of the present invention is stronger, under different application scenarioss, according to actual conditions, proposes specific evaluation criterion.Influence factor set U, choice comment set V etc. can change according to actual conditions, can really reflect realistic elevator inferior health level.
Embodiment
Below in conjunction with embodiment, the invention will be further described.
Embodiment one:
Certain elevator is carried out to inferior health evaluation, analyzing influence inferior health because have, air pollution in noise pollution, railway carriage or compartment, button bacterium, form domain and be:
Evaluating collection has 6, and the evaluation domain forming is thus:
Secondly determine the degree of membership of each factor: in expert's 16 people's groups,, in the evaluation of noise pollution, nobody thinks and " safe especially " accounts for 0%; 4 people think and " safety " account for 25%; 10 people think and " safer " account for 62.5%; 2 people think and " critical " account for 12.5%; Nobody thinks and " danger " and " danger close " accounts for 0%; :
The degree of membership of " noise pollution " is:
{ 0,0.25,0.625,0.125,0,0};
The degree of membership of " air pollution " is
{ 0,0.125,0.75,0.125,0,0};
The degree of membership of " button bacterium " is
{ 0,0.125,0.875,0,0,0};
So the evaluation matrix that 3 factors of this elevator form is:
Then determine relatively judgment matrix
, according to the implication of each scale, relatively judgment matrix is as follows between two for structure
, adopt root method solution matrix to obtain weight
, then judgment matrix is done to consistency check,
,
, by consistency check.
The comprehensive evaluation that thus, can obtain this elevator inferior health is:
Therefore evaluated: the probability of this elevator inferior health 0.691 is in compared with safe condition, and 0.111 probability, in critical conditions, needs to safeguard.
Above the specific embodiment of the present invention is explained in detail, but the present invention is not limited to above-mentioned embodiment, in the ken possessing those of ordinary skills, can also under the prerequisite that does not depart from aim of the present invention, makes various variations.
Claims (4)
1. the elevator inferior health evaluation method based on fuzzy mathematics, is characterized in that: according to elevator, detect data feature qualitatively, adopt existing fuzzy mathematics theory to evaluate, step is as follows:
(1) set up fuzzy overall evaluation set, establishing affects the sets of factors of elevator inferior health and is
the set of choice comment is
(2) determine the degree of membership of each factor that affects elevator inferior health:
First on affecting inferior health factor
usingle factor in set
make simple element evaluation, from factor
have in mind and determine that this things is to choice grade
degree of membership
, draw
iindividual factor
simple element evaluation collection
, it is choice comment collection
von fuzzy subset,
mthe evaluation collection of individual influence factor just constructs a total evaluation matrix
r, reflected two set
u, Vbetween certain correlationship of existing, that is:
Wherein,
expression factor
to choice grade
subjection degree;
(3) determine the weight of each influence factor to elevator inferior health:
For being passed judgment on things, owing to having factor in mind and can obtain different resolutely conclusions from different, and in many factors that affects elevator inferior health
in, the influence degree of elevator inferior health is differed, exist fuzzy preferentially factor, therefore the starting point of evaluating can be regarded the plain domain of impact as
uon fuzzy subset
a, be denoted as:
, in formula
for
right
adegree of membership, it is single factor
a kind of tolerance of influence degree in overall merit,
abe called
weight;
(4) comprehensive evaluation:
Determining fuzzy matrix
rand fuzzy vector
atime, can comprehensively pass judgment on do blurring mapping:
.
2. the elevator inferior health evaluation method based on fuzzy mathematics according to claim 1, is characterized in that: adopt fuzzy integrated judgement model, evaluate elevator inferior health degree, further comprise following operation:
(1) first determine the principal element that affects elevator inferior health, and set up standard separately for affecting each factor of elevator inferior health, to represent its influence degree to elevator inferior health;
(2) determine and evaluate set, form and evaluate domain, can be divided into healthy, healthy, more healthy, critical, dangerous especially, danger close;
(3) determine the degree of membership of each influence factor;
(4) calculate the comparison judgment matrix between adjacent layer
, wherein
it is element
iwith
jthe ratio scale of importance.
3. the elevator inferior health evaluation method based on fuzzy mathematics according to claim 1, is characterized in that: described degree of membership
reach element numerical value in matrix is all between 0～1.
4. the elevator inferior health evaluation method based on fuzzy mathematics according to claim 1, is characterized in that: each element numerical value in described weight A matrix is all between 0～1.
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Cited By (4)
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| CN104537197A (en) * | 2014-10-10 | 2015-04-22 | 中国神华能源股份有限公司 | Comprehensive evaluation method reflecting running conditions of boiler system |
| CN105035902A (en) * | 2015-08-10 | 2015-11-11 | 广州特种机电设备检测研究院 | Elevator safety condition evaluation method |
| CN109205426A (en) * | 2017-07-07 | 2019-01-15 | 奥的斯电梯公司 | Elevator health monitoring systems |
| CN110790105A (en) * | 2019-11-20 | 2020-02-14 | 上海电气集团股份有限公司 | Elevator door system diagnosis and decline time prediction method and diagnosis and prediction system |
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Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104537197A (en) * | 2014-10-10 | 2015-04-22 | 中国神华能源股份有限公司 | Comprehensive evaluation method reflecting running conditions of boiler system |
| CN105035902A (en) * | 2015-08-10 | 2015-11-11 | 广州特种机电设备检测研究院 | Elevator safety condition evaluation method |
| CN105035902B (en) * | 2015-08-10 | 2017-11-21 | 广州特种机电设备检测研究院 | A kind of elevator safety condition evaluation method |
| CN109205426A (en) * | 2017-07-07 | 2019-01-15 | 奥的斯电梯公司 | Elevator health monitoring systems |
| CN109205426B (en) * | 2017-07-07 | 2020-10-09 | 奥的斯电梯公司 | Elevator health monitoring system |
| US11286133B2 (en) | 2017-07-07 | 2022-03-29 | Otis Elevator Company | Elevator health monitoring system |
| CN110790105A (en) * | 2019-11-20 | 2020-02-14 | 上海电气集团股份有限公司 | Elevator door system diagnosis and decline time prediction method and diagnosis and prediction system |
| CN110790105B (en) * | 2019-11-20 | 2021-11-16 | 上海电气集团股份有限公司 | Elevator door system diagnosis and decline time prediction method and diagnosis and prediction system |
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Application publication date: 20140326 |