CN107045577A - The determination method of city rail vehicle wheelset profile detecting system testing result reliability - Google Patents
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Abstract
The invention discloses a kind of determination method of city rail vehicle wheelset profile detecting system testing result reliability.This method comprises the following steps：Obtain influence factor：Determine the influence factor of city rail vehicle wheelset profile detecting system testing result, and each influence factor index；Criterionization processing：Pair determine influence factor index be standardized；Agriculture products importance：On the basis of criterionization processing, with reference to VC Method, the computational methods of the importance of agriculture products；Calculate the Reliability Index of testing result：The Reliability Index of city rail vehicle wheelset profile detecting system testing result is calculated using TOPSIS methods；Obtain optimum measurement result：According to the Reliability Index calculated, it is determined that final wheelset profile detecting system testing result.Present invention, avoiding the different influences judged reliability of pointer type, achievement data is sufficiently used, and can intuitively reflect the reliability of wheelset profile detecting system measurement result.
Description
Technical field
The invention belongs to traffic safety engineering field, and in particular to a kind of city rail vehicle wheelset profile detecting system detection knot
The determination method of fruit reliability.
Background technology
Wheel not only carries the total weight of whole train, is also subjected to the important component as city rail vehicle
The brake force and various frictional force of train in the process of running, take turns to appearance and size directly affect train operation safety it is steady
It is fixed.In order to timely obtain the surface situation of city rail vehicle wheel pair, it is necessary to persistently obtain accurate wheelset profile ginseng
Number.Current many research and development institution and company develop a variety of wheelset profile detecting systems.The principle and method of each detecting system have
Institute is different, all inevitably produces Detection results common feature devious, so being joined by the wheelset profile of system detectio
Number can have the insecure problem of accuracy.
At present, on rail wheels geometric parameters measuring system measured value analysis on Uncertainty and error analysis, relevant scholar does
Substantial amounts of research, the Liu Liying of Southwest Jiaotong University is in paper《The accuracy studies of portable railway wheel profile measuring instrument》
The method for proposing measuring mechanism Evaluation of Uncertainty, further increases the measurement accuracy of wheelset profile detecting system；Southwest
The Zhang Yingchun of university of communications describes railway wheel profile measuring instrument diameter peg model, and uncertainty is analyzed, and is
The accuracy of measurement of measuring instrument, which is provided, to be ensured.But, existing wheelset profile detection technique can not intuitively judge detection
The degree of reliability of system testing result each time.
The content of the invention
It is an object of the invention to provide a kind of determination of city rail vehicle wheelset profile detecting system testing result reliability
Method, so as to intuitively judge the degree of reliability of detecting system testing result each time.
Realizing the technical solution of the object of the invention is：A kind of city rail vehicle wheelset profile detecting system testing result can
By the determination method of degree, comprise the following steps：
Step 1, influence factor is obtained：The influence factor of city rail vehicle wheelset profile detecting system testing result is determined, with
And each influence factor index；
Step 2, criterionization is handled：The influence factor index determined in step 1 is standardized；
Step 3, agriculture products importance：On the basis of the processing of step 2 criterionization, with reference to VC Method, really
Determine the computational methods of the importance of index；
Step 4, the Reliability Index of testing result is calculated：City rail vehicle wheelset profile detection system is calculated using TOPSIS methods
The Reliability Index for testing result of uniting；
Step 5, optimum measurement result is obtained：The Reliability Index calculated according to step 4, it is determined that final wheelset profile
Detecting system testing result.
Compared with prior art, its remarkable advantage is the present invention：(1) determine to refer under each influence factor using VC Method
Target importance, it is to avoid the different influences judged reliability of pointer type；(2) more sufficiently utilized using TOPSIS methods
Achievement data, to index without particular/special requirement；(3) reliability of wheelset profile detecting system measurement result is more intuitively reflected.
Brief description of the drawings
Fig. 1 is the flow chart of the determination method of city rail vehicle wheelset profile detecting system testing result reliability of the present invention.
Fig. 2 is the target layers figure under each influence factor in reliability calculating.
Embodiment
Below in conjunction with the accompanying drawings and specific embodiment is described in further detail to the present invention.
With reference to Fig. 1, the determination method of city rail vehicle wheelset profile detecting system testing result reliability of the present invention, including with
Lower step：
Step 1, influence factor is obtained：The influence factor of city rail vehicle wheelset profile detecting system testing result is determined, with
And each influence factor index；
With reference to Fig. 2, the influence factor of described city rail vehicle wheelset profile detecting system testing result, including sensor are set
Put factor, site environment factor, algorithm process factor and vehicle influence factor；
The sensor sets factor to include time for exposure and sensor sample frequency；The site environment factor includes light
According to disturbance degree and scene temperature disturbance degree；The algorithm process factor includes inner face inclination angle, degrees of fusion deviation and available frame count；
The vehicle influence factor includes coaxial detection error, with bogie detection error and with compartment detection error.
Step 2, criterionization is handled：The influence factor index determined in step 1 is standardized；It is described to refer to
Standardization is marked, it is specific as follows：
The influence factor index of city rail vehicle wheelset profile detecting system testing result includes positive index and reverse index,
Positive index and reverse index are done into standardization, same dimension pointer type is changed into；In each influence factor index system
Including m group testing results, every group of testing result includes n pointer types, wherein xijRepresent the corresponding shadow of i-th group of testing result
Jth index value in the factor of sound；
P is handled to obtain to positive index progressij：
P is handled to obtain to reverse index progressij：
After standardization, each influence factor achievement data matrix P such as following formulas are obtained：
Step 3, agriculture products importance：On the basis of the processing of step 2 criterionization, with reference to VC Method, really
Determine the computational methods of the importance of index, it is specific as follows：
(3.1) in the achievement data system under each influence factor, the average of each index is asked forMeter
Calculate the standard deviation of each index
Wherein, influence factor index system includes m group testing results, and every group of testing result includes n pointer types,
xijRepresent jth index value in the corresponding influence factor of i-th group of testing result；
(3.2) coefficient of variation of each index is calculatedFurther calculate the importance of indices
Step 4, the Reliability Index of testing result is calculated：City rail vehicle wheelset profile detection system is calculated using TOPSIS methods
The Reliability Index for testing result of uniting, it is specific as follows：
(4.1) TOPSIS methods are by calculating the level of intimate between each influence factor index and idealization index come ranking
Method；Each influence factor achievement data matrix P obtained by step 2, constitutes the decision matrix T of standardization：
Z in specified decision matrix TijCalculating process is shown below：
(4.2) the weighted decision matrix Q of specified decision matrix is constructed, its element is qij, qij=wj·Zij, i=1,2,
3,...,m；J=1,2,3 ..., n；wjThe importance of jth index；Weighted decision matrix Q is：
Determine weighted decision matrix Q optimal solution and most inferior solution：
Optimal solution：
Most inferior solution：
(4.3) the corresponding index of each testing result is calculated to the distance of optimal solutionThe corresponding index of each testing result is to most bad
The distance of solutionWith Euclid norm estimating as distance, then arbitrary feasible solution qijTo optimal solutionDistanceFor：
Arbitrary feasible solution qijTo most inferior solution qjDistanceFor：
Each testing result correspondence index is Reliability Index C for the relative proximities of optimal solutioni：
Step 5, optimum measurement result is obtained：The Reliability Index calculated according to step 4, it is determined that final wheelset profile
Detecting system testing result.
According to the Reliability Index of each testing result obtained in step 4, when Reliability Index closer to 1 when, wheel pair
The testing result of size detecting system is smaller to dimensional discrepancy with standard wheels, and the accuracy of testing result is higher；Reliability Index
Testing result closest to 1 is accuracy highest testing result.
Embodiment 1
Using field erected wheelset profile detecting system as research object, obtain the system and examine 4 groups of each shadows of survey result correspondence
Index under the factor of sound.The testing result of every group of wheelset profile detecting system all corresponds to one group of influence factor index, including sensing
Device sets factor, site environment factor, algorithm process factor and vehicle influence factor.Index under this four aspect influence factors
Reliability calculating object：xij=[time for exposure, sensor sample frequency, illumination effect degree, scene temperature disturbance degree, inner face
Inclination angle, degrees of fusion deviation, available frame count, coaxial detection error, with bogie detection error, with compartment detection error], every group is commented
Valency object includes 10 indexs, wherein 1≤i≤4.Then four groups of evaluation objects are respectively x1=[x1(1),x1(2),x1
(3),...,x1(10)], x2=[x2(1),x2(2),x2(3),...,x2(10)], x3=[x3(1),x3(2),x3(3),...,x3
(10)], x4=[x4(1),x4(2),x4(3),...,x4(10)]。
After achievement data standardization under each influence factor, standardized index data matrix P is obtained：
On the basis of criterionization processing, with reference to VC Method agriculture products importance W：W=(0.1430,
0.0667,0.1127,0.1639,0.0009,0.1555,0.1128,0.1096,0.0681,0.0670)。
According to TOPSIS method preferred process, specified decision matrix T is obtained according to standardized index data：
After construction specified decision matrix obtains weighted decision matrix Q, optimal solution and most inferior solution are determined, is obtained optimal
Solve Q+=(0.0452,0.0391,0.0356,0.0553,0.0007,0.0492,0.0357,0.0347,0.0222,
0.0262)；
Most inferior solution Q+=(0.0137,0.0163,0.0173,0.0,0.0003,0.0119,0.0139,0.0140,
0.0177,0.0196)。
Based on euclideam norm estimating as distance, the corresponding index of every group of testing result is calculated to optimal solution
DistanceThe distance of most inferior solutionFour groups of testing result correspondence indexs are obtained to the distance of optimal solution Most inferior solution distance
The corresponding index of every group of testing result is for Reliability Index C=that the degree of approach of optimal solution is testing result
(0.813,0.6843,0.1047,0.3681), judges that the good and bad relation for understanding four groups of testing result correspondence indexs is：C1>C2>
C4>C3, it is known that the measurement result of the corresponding wheelset profile detecting system of first group of testing result is ideal, and the 3rd group of detection
As a result corresponding measurement result is least preferable.The conclusion is consistent to the result of the variance analysis of dimensional measurements with actual wheel, should
Method meets the requirement of the reliability of live wheelset profile detecting system testing result.
Claims (5)
1. a kind of determination method of city rail vehicle wheelset profile detecting system testing result reliability, it is characterised in that including with
Lower step：
Step 1, influence factor is obtained：The influence factor of city rail vehicle wheelset profile detecting system testing result is determined, and respectively
Influence factor index；
Step 2, criterionization is handled：The influence factor index determined in step 1 is standardized；
Step 3, agriculture products importance：On the basis of the processing of step 2 criterionization, with reference to VC Method, it is determined that referring to
The computational methods of target importance；
Step 4, the Reliability Index of testing result is calculated：City rail vehicle wheelset profile detecting system is calculated using TOPSIS methods to examine
Survey the Reliability Index of result；
Step 5, optimum measurement result is obtained：The Reliability Index calculated according to step 4, it is determined that final wheelset profile detection
System detection results.
2. the determination method of city rail vehicle wheelset profile detecting system testing result reliability according to claim 1, its
It is characterised by, the influence factor of the city rail vehicle wheelset profile detecting system testing result described in step 1, including sensor is set
Factor, site environment factor, algorithm process factor and vehicle influence factor；
The sensor sets factor to include time for exposure and sensor sample frequency；The site environment factor includes illumination shadow
Loudness and scene temperature disturbance degree；The algorithm process factor includes inner face inclination angle, degrees of fusion deviation and available frame count；It is described
Vehicle influence factor includes coaxial detection error, with bogie detection error and with compartment detection error.
3. the determination method of city rail vehicle wheelset profile detecting system testing result reliability according to claim 1, its
It is characterised by, criterionization described in step 2 is handled, specific as follows：
The influence factor index of city rail vehicle wheelset profile detecting system testing result includes positive index and reverse index, will just
Standardization is done to index and reverse index, same dimension pointer type is changed into；Each influence factor index system includes m
Group testing result, every group of testing result includes n pointer types, wherein xijRepresent the corresponding influence of i-th group of testing result because
Jth index value in element；
P is handled to obtain to positive index progressij：
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4. the determination method of city rail vehicle wheelset profile detecting system testing result reliability according to claim 1, its
It is characterised by, the combination VC Method described in step 3, the computational methods of the importance of agriculture products are specific as follows：
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The standard deviation of item index
Wherein, influence factor index system includes m group testing results, and every group of testing result includes n pointer types, xijTable
Show jth index value in the corresponding influence factor of i-th group of testing result；
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5. the determination method of city rail vehicle wheelset profile detecting system testing result reliability according to claim 1, its
It is characterised by, the use TOPSIS methods described in step 4 calculate the reliability of city rail vehicle wheelset profile detecting system testing result
Index, it is specific as follows：
(4.1) TOPSIS methods are by calculating the level of intimate between each influence factor index and idealization index come the side of ranking
Method；Each influence factor achievement data matrix P obtained by step 2, constitutes the decision matrix T of standardization：
Z in specified decision matrix TijCalculating process is shown below：
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Determine weighted decision matrix Q optimal solution and most inferior solution：
Optimal solution：
Most inferior solution：
(4.3) the corresponding index of each testing result is calculated to the distance of optimal solutionThe corresponding index of each testing result is to most bad
The distance of solutionWith Euclid norm estimating as distance, then arbitrary feasible solution qijTo optimal solutionDistanceFor：
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Application publication date: 20170815 |