CN106768743A - A kind of linear appraisal procedure of bridge main beam based on real time data processing technology - Google Patents
A kind of linear appraisal procedure of bridge main beam based on real time data processing technology Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G01M5/00—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings
- G01M5/0008—Investigating the elasticity of structures, e.g. deflection of bridges or air-craft wings of bridges
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Abstract
The present invention relates to a kind of linear appraisal procedure of the bridge main beam based on real time data processing technology, solving cannot carry out the defect of linear assessment compared with prior art to bridge main beam.The present invention is comprised the following steps：Define assessment strategy；Perturb the acquisition of initial data；Perturb the filtering of data；The calculating of a reference value；Evaluate the health characteristics index of girder.The present invention can be such that bridge monitoring personnel quickly judge when front axle beam holistic health and location data abnormity point.
Description
Technical field
The present invention relates to big data processing technology field, a kind of specifically bridge based on real time data processing technology
The linear appraisal procedure of girder.
Background technology
Recently as continuing to develop for the technologies such as computer technology, the communication technology, embedded type sensor, using computer
System carries out automatic health monitoring and has become bridge monitoring and take main method.The linear assessment of bridge main beam is reflection bridge
One important indicator of security, by the linear monitoring to bridge main beam, can not only direct reaction bridge under operation state
Whether Main Girder Deflection can also observe the change in long term rule of main beam linear beyond risk range and the overall working condition of girder
Rule, therefore the linear assessment of bridge main beam is detected for load carrying capacity of bridge and the protection against and mitigation of earthquake disasters of bridge has great significance.
The exploratory stage is also in for the research of the linear Assessment theory of bridge main beam at present, it is domestic temporarily without unified assessment side
Method, the layer whether monitoring Main Girder Deflection initial data exceeds danger threshold is remained in for the method for the linear assessment of bridge main beam
On face, not data are standardized with assessment.
So how big data treatment technology is utilized, the initial data of Main Girder Deflection is integrated so that data assessment
Standardize, reach assessment efficiency high and have become the technical problem that need to be solved.
The content of the invention
The invention aims to solve that bridge main beam cannot be carried out the linear defect assessed in the prior art, there is provided
A kind of bridge main beam based on real time data processing technology linear appraisal procedure solves the above problems.
To achieve these goals, technical scheme is as follows：
A kind of linear appraisal procedure of bridge main beam based on real time data processing technology, comprises the following steps：
Assessment strategy is defined, the exceptional value scope and a reference value time range of Main Girder Deflection data is defined；
The acquisition of initial data is perturbed, the amount of deflection initial data obtained installed in i sensor on girder is read in real time, and
Deposited into internal memory with array form, array is defined as rawdatai{{id0,time,value}…{idn,time,value}}；
The filtering of data is perturbed, is classified to perturbing initial data based on assessment strategy, by rawdataiArray is divided into
refdataiA reference value array and candataiArray to be assessed；
The calculating of a reference value, by refdataiA reference value array calculates baseline mean ai0, benchmark variance yields bi0, benchmark
Shift value di0, numerical benchmark sequence L0；
The health characteristics index of girder is evaluated, Change in Mean coefficient, variance change system are calculated according to data to be assessed
Number, maximum variance variation coefficient, maximum displacement variation coefficient, smooth-going property coefficient and Curvature varying coefficient.
The described filtering for perturbing data is comprised the following steps：
Setting refdataiA reference value array and candataiArray to be assessed, refdataiA reference value array is defined as
refdatai{ { id0, time, value } ... { idn, time, value } }, candataiArray to be assessed is defined as candatai
{{id0,time,value}…{idn,time,value}}；
On the basis of the exceptional value scope of Main Girder Deflection data, to rawdataiProperty value value in array was carried out
Filter, the array array in the range of exceptional value is abandoned, being not in the range of exceptional value is retained in rawdataiIn array；
On the basis of a reference value time range of Main Girder Deflection data, to rawdataiProperty value time in array is carried out
Filtering, refdata is divided into by the array in a reference value time rangeiA reference value array, it is not at a reference value time range
Interior array is divided into candataiArray to be assessed.
The calculating of described a reference value is comprised the following steps：
Calculating benchmark average ai0, computational methods are as follows：
Wherein, i is measuring point number；refdatainIt is n-th measured value of the i-th measuring point；
Calculating benchmark variance yields bi0, computational methods are as follows：
Wherein, i is measuring point number；refdataijIt is j-th measured value of the i-th measuring point；
Calculating benchmark shift value di0, computational methods are as follows：
；Wherein, i is measuring point number；refdatainIt is n-th measured value of the i-th measuring point；
It is L to calculate displacement monitoring data base sequence of values0, computational methods are as follows：
L0={ a00, a10... ..., ai0,
Wherein, a00It is first baseline mean of measuring point, ai0It is i-th baseline mean of measuring point.
The described health characteristics index for evaluating girder is comprised the following steps：
Change in Mean coefficient is calculated, the data mean value situation of change of the deflection monitoring point being distributed along girder is calculated, definition is equal
Value changes coefficient is Δ a, and its computing formula is as follows：
In formula, Δ a is amount of deflection measuring point Change in Mean coefficient, n is measuring point number, candataiIt is the i-th measuring point actual measurement average, ai0
On the basis of average；
Variance variation coefficient is calculated, the data entirety amount of deflection variance for calculating the deflection monitoring point being distributed along girder changes, fixed
Right way of conduct difference variation coefficient is Δ b, and its computing formula is shown below.
Wherein, Δ b is amount of deflection measuring point variance variation coefficient, biIt is the i-th measuring point actual measurement variance, bi0On the basis of variance yields；
Maximum variance variation coefficient is calculated, it is Δ c to define maximum variance variation coefficient, and its computing formula is as follows：
Wherein, Δ c is maximum variance variation coefficient, biIt is the i-th measuring point actual measurement variance, bi0On the basis of variance yields；
Maximum displacement variation coefficient is calculated, it is Δ d to define maximum displacement variation coefficient, and its computing formula is as follows：
Wherein, Δ d is maximum displacement variation coefficient, diIt is the i-th measuring point measured displacements, di0On the basis of shift value；
Calculate smooth-going property coefficientIt is L to define each monitoring point jth time data sequence to be assessedj,
Lj={ candataj(1), candataj(2), candataj(3) ... ..., candataj(i)}
Wherein, candataj(1) it is first j-th measured value of measuring point, candatajI () is i-th jth of measuring point
Individual measured value；
It is p to define degree of association coefficientj, its computing formula is shown below：
In formula, k=1,2,3 ..., i-1,
Wherein, L0(k+1) sequence of values kth+1 is worth on the basis of, L0Sequence of values kth value, L on the basis of (k)j(k+1) it is to treat
Assessment data sequence kth+1 is worth, LjK () is data sequence kth value to be assessed；
Degree of association coefficient is done into normalized, p is takenjUsed as smooth-going property coefficient, definition smoothes out property coefficient and is average value
Its computing formula is shown below：
Wherein, j is sampling number, pjThe degree of association coefficient tried to achieve by the corresponding vector of jth sampled point,It is ride comfort
Coefficient；
Curvature varying coefficient is calculated, it is s to obtain benchmark deflection deformation curvature by benchmark Value Datai0, define number to be assessed
It is s according to deflection deformation curvaturei, its computing formula is as follows：
In formula, siIt is i-th Deformation Curvature of measuring point, di+1、di、di-1Respectively i+1 measuring point, i measuring points, i-1 measuring points
Deflection deformation value, Δ x is the distance between adjacent 2 measuring points；
Deflection deformation curvature is done into normalized, its vectorial difference average value is taken as Curvature varying coefficient, definition
Curvature varying coefficient is Δ s, and its computing formula is as follows：
In formula, Δ s is the n Curvature varying coefficient of measuring point, siAnd si0Respectively the measured value of the i-th wet environment curvature and
A reference value, n is measuring point quantity.
Also include calculating health status scoring step, data are scored based on score by rules and weight table, its is specific
Step is as follows：
It is F to define health status scoring；
Calculate and define health status scoring F, its formula is as follows：
Wherein, F is the total score value of linear assessment, and full marks are 100 points, and (Δ a) is Change in Mean coefficient score value, w to SaFor
Change in Mean coefficient weights, (Δ b) is variance variation coefficient score value, w to SbIt is variance variation coefficient weight, (Δ c) is maximum to S
Variance variation coefficient score value, wcIt is maximum variance variation coefficient weight, SIt is smooth-going property coefficient score value, wpIt is ride comfort
Coefficient weights, (Δ s) is Curvature varying coefficient score value, w to SsIt is Curvature varying coefficient weights.
Beneficial effect
The linear appraisal procedure of a kind of bridge main beam based on real time data processing technology of the invention, compared with prior art
Bridge monitoring personnel can be made quickly to judge when front axle beam holistic health and location data abnormity point.The method causes bridge
Monitoring Data has the characteristics of standardizing and assess efficiency high, the robustness and ease for use of system is improve, with work higher
Journey application value.
Brief description of the drawings
Fig. 1 is flow chart of the method for the present invention.
Specific embodiment
To make have a better understanding and awareness to architectural feature of the invention and the effect reached, to preferably
Embodiment and accompanying drawing coordinate detailed description, are described as follows：
As shown in figure 1, the linear appraisal procedure of a kind of bridge main beam based on real time data processing technology of the present invention,
Comprise the following steps：
The first step, defines assessment strategy.Define the exceptional value scope and a reference value time range of Main Girder Deflection data.Due to
Main Girder Deflection data dependence sensor real-time monitoring, and sensor belongs to electronic equipment, has probability and abnormal data occurs.In order to
Ensure the correctness and robustness of assessment, it is necessary to define exceptional value scope, so as to ensure that system does not extract abnormal Value Data and enters
Evaluation process.Due in actual applications, the off-period that network of highways level bridge is not fixed, so it needs to be determined that one section is current
Vehicle few a reference value time, for calculating the bridge main beam amount of deflection benchmark Value Data.
Wherein it is possible to the exceptional value scope for defining Main Girder Deflection data is (- ∞, -100), (100 ,+∞), in the interval
Data will not read without exception.Meanwhile, can be daily (1 with definition datum value time range generally:00–3:00), should
The vehicle that passed through in time period is less.
Second step, perturbs the acquisition of initial data.Read in real time original installed in the amount of deflection of i sensor acquisition on girder
Data, and deposited into internal memory with array form, array is defined as rawdatai{{id0,time,value}…{idn,time,
value}}。
3rd step, perturbs the filtering of data.Classified to perturbing initial data based on assessment strategy, by rawdataiNumber
Component is refdataiA reference value array and candataiArray to be assessed, it is comprised the following steps that：
(1) refdata is setiA reference value array and candataiArray to be assessed, refdataiA reference value array is defined as
refdatai{ { id0, time, value } ... { idn, time, value } }, candataiArray to be assessed is defined as candatai
{{id0,time,value}…{idn,time,value}}。
(2) on the basis of the exceptional value scope of Main Girder Deflection data, to rawdataiProperty value value in array is carried out
Filtering, the array array in the range of exceptional value is abandoned, being not in the range of exceptional value is retained in rawdataiArray
In, abnormal data is filtered out.
(3) on the basis of a reference value time range of Main Girder Deflection data, to rawdataiProperty value time in array
Filtered, the array in a reference value time range is divided into refdataiA reference value array, it is not at a reference value time
In the range of array be divided into candataiArray to be assessed so that refdataiIt is worth the time on the basis of data in a reference value array
Scope, its actual conditions that can more reflect bridge, candataiArray to be assessed for not in a reference value time range, that reflects
Situation of the bridge when (use) is loaded.
4th step, the calculating of a reference value, by refdataiA reference value array calculates baseline mean ai0, benchmark variance yields
bi0, basis displacement value di0, numerical benchmark sequence L0.It is comprised the following steps that：
(1) calculating benchmark average ai0, computational methods are as follows：
Wherein, i is measuring point number；refdatainIt is n-th measured value of the i-th measuring point.
(2) calculating benchmark variance yields bi0, computational methods are as follows：
Wherein, i is measuring point number；refdataijIt is j-th measured value of the i-th measuring point.
(3) calculating benchmark shift value di0, computational methods are as follows：
；Wherein, i is measuring point number；refdatainIt is n-th measured value of the i-th measuring point.
(4) it is L to calculate displacement monitoring data base sequence of values0, computational methods are as follows：
L0={ a00, a10... ..., ai0,
Wherein, a00It is first baseline mean of measuring point, ai0It is i-th baseline mean of measuring point.
5th step, evaluates the health characteristics index of girder.Change in Mean coefficient, variance are calculated according to data to be assessed
Variation coefficient, maximum variance variation coefficient, maximum displacement variation coefficient, smooth-going property coefficient and Curvature varying coefficient.It is specifically walked
It is rapid as follows：
(1) Change in Mean coefficient is calculated, the data mean value situation of change of the deflection monitoring point being distributed along girder is calculated.Definition
Change in Mean coefficient is Δ a, and its computing formula is as follows：
In formula, Δ a is amount of deflection measuring point Change in Mean coefficient, n is measuring point number, candataiIt is the i-th measuring point actual measurement average, ai0
On the basis of average.
(2) variance variation coefficient is calculated, the data entirety amount of deflection variance for calculating the deflection monitoring point being distributed along girder changes,
It is Δ b to define variance variation coefficient, and its computing formula is shown below.
Wherein, Δ b is amount of deflection measuring point variance variation coefficient, biIt is the i-th measuring point actual measurement variance, bi0On the basis of variance yields.
Here, the i-th measuring point actual measurement variance biCalculated according to prior art.
(3) maximum variance variation coefficient is calculated, it is Δ c to define maximum variance variation coefficient, and its computing formula is as follows：
Wherein, Δ c is maximum variance variation coefficient, biIt is the i-th measuring point actual measurement variance, bi0On the basis of variance yields.
(4) maximum displacement variation coefficient is calculated, it is Δ d to define maximum displacement variation coefficient, and its computing formula is as follows：
Wherein, Δ d is maximum displacement variation coefficient, diIt is the i-th measuring point measured displacements, di0On the basis of shift value, similarly,
I measuring point measured displacements are calculated according to prior art.
(5) smooth-going property coefficient is calculatedIt is L to define each monitoring point jth time data sequence to be assessedj,
Lj={ candataj(1), candataj(2), candataj(3) ... ..., candataj(i)}
Wherein, candataj(1) it is first j-th measured value of measuring point, candatajI () is i-th jth of measuring point
Individual measured value.
It is p to define degree of association coefficientj, its computing formula is shown below：
In formula, k=1,2,3 ..., i-1,
Wherein, L0(k+1) sequence of values kth+1 is worth on the basis of, L0Sequence of values kth value, L on the basis of (k)j(k+1) it is to treat
Assessment data sequence kth+1 is worth, LjK () is data sequence kth value to be assessed.
Degree of association coefficient is done into normalized, p is takenjUsed as smooth-going property coefficient, definition smoothes out property coefficient and is average value
Its computing formula is shown below：
Wherein, j is sampling number, pjThe degree of association coefficient tried to achieve by the corresponding vector of jth sampled point,It is ride comfort
Coefficient.
(6) Curvature varying coefficient is calculated, it is s to obtain benchmark deflection deformation curvature by benchmark Value Datai0, define to be assessed
Data deflection deformation curvature is si, its computing formula is as follows：
In formula, siIt is i-th Deformation Curvature of measuring point, di+1、di、di-1Respectively i+1 measuring point, i measuring points, i-1 measuring points
Deflection deformation value, Δ x is the distance between adjacent 2 measuring points.
Deflection deformation curvature is done into normalized, its vectorial difference average value is taken as Curvature varying coefficient, definition
Curvature varying coefficient is Δ s, and its computing formula is as follows：
In formula, Δ s is the n Curvature varying coefficient of measuring point, siAnd si0Respectively the measured value of the i-th wet environment curvature and
A reference value, n is measuring point quantity.
By calculating Change in Mean coefficient, variance variation coefficient, maximum variance variation coefficient, maximum displacement change system
Number, smooth-going property coefficient and Curvature varying coefficient can reflect the linear case of girder, in order to more visually show girder
Health status, herein can also be according to Ministry of Communications《Highway bridge and culvert Maintenance specification》The deflection data of table 1 score by rules and power
Weight table, provides specific score value.
The score by rules of table 1 and weight table
6th step, calculates health status scoring step.Data are scored based on score by rules and weight table, its is specific
Step is as follows：
(1) it is F to define health status scoring.
(2) calculate and define health status scoring F, its formula is as follows：
Wherein, F is the total score value of linear assessment, and full marks are 100 points, and (Δ a) is Change in Mean coefficient score value, w to SaFor
Change in Mean coefficient weights, (Δ b) is variance variation coefficient score value, w to SbIt is variance variation coefficient weight, (Δ c) is maximum to S
Variance variation coefficient score value, wcIt is maximum variance variation coefficient weight, SIt is smooth-going property coefficient score value, wpIt is ride comfort
Coefficient weights, (Δ s) is Curvature varying coefficient score value, w to SsIt is Curvature varying coefficient weights.
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, the simply present invention described in above-described embodiment and specification
Principle, various changes and modifications of the present invention are possible without departing from the spirit and scope of the present invention, these change and
Improvement is both fallen within the range of claimed invention.The protection domain of application claims by appending claims and its
Equivalent is defined.
Claims (5)
1. the linear appraisal procedure of a kind of bridge main beam based on real time data processing technology, it is characterised in that comprise the following steps：
11) assessment strategy is defined, the exceptional value scope and a reference value time range of Main Girder Deflection data is defined；
12) acquisition of initial data is perturbed, the amount of deflection initial data obtained installed in i sensor on girder is read in real time, and
Deposited into internal memory with array form, array is defined as rawdatai{{id0,time,value}…{idn,time,value}}；
13) filtering of data is perturbed, is classified to perturbing initial data based on assessment strategy, by rawdataiArray is divided into
refdataiA reference value array and candataiArray to be assessed；
14) calculating of a reference value, by refdataiA reference value array calculates baseline mean ai0, benchmark variance yields bi0, benchmark
Shift value di0, numerical benchmark sequence L0；
15) the health characteristics index of girder is evaluated, Change in Mean coefficient, variance change system is calculated according to data to be assessed
Number, maximum variance variation coefficient, maximum displacement variation coefficient, smooth-going property coefficient and Curvature varying coefficient.
2. the linear appraisal procedure of a kind of bridge main beam based on real time data processing technology according to claim 1, it is special
Levy and be, the described filtering for perturbing data is comprised the following steps：
21) refdata is setiA reference value array and candataiArray to be assessed, refdataiA reference value array is defined as
refdatai{ { id0, time, value } ... { idn, time, value } }, candataiArray to be assessed is defined as candatai
{{id0,time,value}…{idn,time,value}}；
22) on the basis of the exceptional value scope of Main Girder Deflection data, to rawdataiProperty value value in array is filtered,
Array array in the range of exceptional value is abandoned, being not in the range of exceptional value is retained in rawdataiIn array；
23) on the basis of a reference value time range of Main Girder Deflection data, to rawdataiProperty value time in array was carried out
Filter, refdata is divided into by the array in a reference value time rangeiA reference value array, it is not in a reference value time range
Array be divided into candataiArray to be assessed.
3. the linear appraisal procedure of a kind of bridge main beam based on real time data processing technology according to claim 1, it is special
Levy and be, the calculating of described a reference value is comprised the following steps：
31) calculating benchmark average ai0, computational methods are as follows：
Wherein, i is measuring point number；refdatainIt is n-th measured value of the i-th measuring point；
32) calculating benchmark variance yields bi0, computational methods are as follows：
Wherein, i is measuring point number；refdataijIt is j-th measured value of the i-th measuring point；
33) calculating benchmark shift value di0, computational methods are as follows：
；
Wherein, i is measuring point number；refdatainIt is n-th measured value of the i-th measuring point；
34) it is L to calculate displacement monitoring data base sequence of values0, computational methods are as follows：
L0={ a00, a10... ..., ai0,
Wherein, a00It is first baseline mean of measuring point, ai0It is i-th baseline mean of measuring point.
4. the linear appraisal procedure of a kind of bridge main beam based on real time data processing technology according to claim 1, it is special
Levy and be, the described health characteristics index for evaluating girder is comprised the following steps：
51) Change in Mean coefficient is calculated, the data mean value situation of change of the deflection monitoring point being distributed along girder is calculated, average is defined
Variation coefficient is Δ a, and its computing formula is as follows：
In formula, Δ a is amount of deflection measuring point Change in Mean coefficient, n is measuring point number, candataiIt is the i-th measuring point actual measurement average, ai0It is base
Quasi- average；
52) variance variation coefficient is calculated, the data entirety amount of deflection variance for calculating the deflection monitoring point being distributed along girder changes, definition
Variance variation coefficient is Δ b, and its computing formula is shown below.
Wherein, Δ b is amount of deflection measuring point variance variation coefficient, biIt is the i-th measuring point actual measurement variance, bi0On the basis of variance yields；
53) maximum variance variation coefficient is calculated, it is Δ c to define maximum variance variation coefficient, and its computing formula is as follows：
Wherein, Δ c is maximum variance variation coefficient, biIt is the i-th measuring point actual measurement variance, bi0On the basis of variance yields；
54) maximum displacement variation coefficient is calculated, it is Δ d to define maximum displacement variation coefficient, and its computing formula is as follows：
Wherein, Δ d is maximum displacement variation coefficient, diIt is the i-th measuring point measured displacements, di0On the basis of shift value；
55) smooth-going property coefficient is calculatedIt is L to define each monitoring point jth time data sequence to be assessedj,
Lj={ candataj(1), candataj(2), candataj(3) ... ..., candataj(i)}
Wherein, candataj(1) it is first j-th measured value of measuring point, candatajI () is real i-th j-th of measuring point
Measured value；
It is p to define degree of association coefficientj, its computing formula is shown below：
In formula, k=1,2,3 ..., i-1,
Wherein, L0(k+1) sequence of values kth+1 is worth on the basis of, L0Sequence of values kth value, L on the basis of (k)j(k+1) it is to be assessed
Data sequence kth+1 is worth, LjK () is data sequence kth value to be assessed；
Degree of association coefficient is done into normalized, p is takenjUsed as smooth-going property coefficient, definition smoothes out property coefficient and is average valueIts meter
Formula is calculated to be shown below：
Wherein, j is sampling number, pjThe degree of association coefficient tried to achieve by the corresponding vector of jth sampled point,It is smooth-going property coefficient；
56) Curvature varying coefficient is calculated, it is s to obtain benchmark deflection deformation curvature by benchmark Value Datai0, define data to be assessed
Deflection deformation curvature is si, its computing formula is as follows：
In formula, siIt is i-th Deformation Curvature of measuring point, di+1、di、di-1Respectively i+1 measuring point, i measuring points, the amount of deflection of i-1 measuring points
Deformation values, △ x are the distance between adjacent 2 measuring points；
Deflection deformation curvature is done into normalized, its vectorial difference average value is taken as Curvature varying coefficient, curvature is defined
Variation coefficient is Δ s, and its computing formula is as follows：
In formula, Δ s is the n Curvature varying coefficient of measuring point, siAnd si0The respectively measured value and benchmark of the i-th wet environment curvature
Value, n is measuring point quantity.
5. the linear appraisal procedure of a kind of bridge main beam based on real time data processing technology according to claim 1, it is special
Levy and be：Also include calculating health status scoring step, data are scored based on score by rules and weight table, its specific step
It is rapid as follows：
61) it is F to define health status scoring；
62) calculate and define health status scoring F, its formula is as follows：
Wherein, F is the total score value of linear assessment, and full marks are 100 points, and S (△ a) is Change in Mean coefficient score value, waFor average becomes
Change coefficient weights, S (△ b) is variance variation coefficient score value, wbIt is variance variation coefficient weight, S (△ c) becomes for maximum variance
Change coefficient score value, wcIt is maximum variance variation coefficient weight,It is smooth-going property coefficient score value, wpIt is smooth-going property coefficient
Weight, S (△ s) is Curvature varying coefficient score value, wsIt is Curvature varying coefficient weights.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107634864A (en) * | 2017-10-27 | 2018-01-26 | 合肥城市云数据中心股份有限公司 | A kind of high-frequency data Real-time Collection transmission method for network of highways level bridge |
| CN108133070A (en) * | 2017-09-19 | 2018-06-08 | 广州市建筑科学研究院有限公司 | A kind of appraisal procedure and system of the bridge health situation based on radial basis function neural network |
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