CN110414602A - A kind of prestressing force string chord member of truss damnification recognition method based on multi-modal data fusion - Google Patents

A kind of prestressing force string chord member of truss damnification recognition method based on multi-modal data fusion Download PDF

Info

Publication number
CN110414602A
CN110414602A CN201910692595.4A CN201910692595A CN110414602A CN 110414602 A CN110414602 A CN 110414602A CN 201910692595 A CN201910692595 A CN 201910692595A CN 110414602 A CN110414602 A CN 110414602A
Authority
CN
China
Prior art keywords
truss
prestressing force
chord member
modal data
string
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201910692595.4A
Other languages
Chinese (zh)
Inventor
曾滨
周臻
张庆方
许庆
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Central Research Institute of Building and Construction Co Ltd MCC Group
China Jingye Engineering Corp Ltd
Original Assignee
Central Research Institute of Building and Construction Co Ltd MCC Group
China Jingye Engineering Corp Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Central Research Institute of Building and Construction Co Ltd MCC Group, China Jingye Engineering Corp Ltd filed Critical Central Research Institute of Building and Construction Co Ltd MCC Group
Priority to CN201910692595.4A priority Critical patent/CN110414602A/en
Publication of CN110414602A publication Critical patent/CN110414602A/en
Pending legal-status Critical Current

Links

Classifications

    • E—FIXED CONSTRUCTIONS
    • E04—BUILDING
    • E04B—GENERAL BUILDING CONSTRUCTIONS; WALLS, e.g. PARTITIONS; ROOFS; FLOORS; CEILINGS; INSULATION OR OTHER PROTECTION OF BUILDINGS
    • E04B1/00—Constructions in general; Structures which are not restricted either to walls, e.g. partitions, or floors or ceilings or roofs
    • E04B1/18—Structures comprising elongated load-supporting parts, e.g. columns, girders, skeletons
    • E04B1/19—Three-dimensional framework structures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/25—Fusion techniques
    • 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
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • 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
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06395—Quality analysis or management
    • E—FIXED CONSTRUCTIONS
    • E04—BUILDING
    • E04B—GENERAL BUILDING CONSTRUCTIONS; WALLS, e.g. PARTITIONS; ROOFS; FLOORS; CEILINGS; INSULATION OR OTHER PROTECTION OF BUILDINGS
    • E04B1/00—Constructions in general; Structures which are not restricted either to walls, e.g. partitions, or floors or ceilings or roofs
    • E04B1/18—Structures comprising elongated load-supporting parts, e.g. columns, girders, skeletons
    • E04B1/19—Three-dimensional framework structures
    • E04B2001/1996—Tensile-integrity structures, i.e. structures comprising compression struts connected through flexible tension members, e.g. cables

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Strategic Management (AREA)
  • Development Economics (AREA)
  • Educational Administration (AREA)
  • Economics (AREA)
  • General Physics & Mathematics (AREA)
  • Marketing (AREA)
  • Architecture (AREA)
  • Data Mining & Analysis (AREA)
  • Game Theory and Decision Science (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • General Business, Economics & Management (AREA)
  • Electromagnetism (AREA)
  • Civil Engineering (AREA)
  • Structural Engineering (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Artificial Intelligence (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Biology (AREA)
  • Evolutionary Computation (AREA)
  • General Engineering & Computer Science (AREA)
  • Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)

Abstract

The invention discloses a kind of using monitoring modal data, based on the prestressing force string chord member of truss damnification recognition method of multi-modal data fusion, for the non-destructive tests of prestressing force string chord member of truss, including following key step: (1) analyzing the preparation stage；(2) prestressing force string chord member of truss single injury distinguishing indexes calculate；(3) prestressing force string chord member of truss fuse damaged distinguishing indexes calculate；(4) prestressing force string chord member of truss damage position is determined.This method uses the truss string structure damnification recognition method merged based on multi-modal data, multisensor by being arranged in chord node in structure obtains each rank modal data of prestressing force truss string structure, truss string structure single injury distinguishing indexes are calculated based on modal data, then it chooses D-S evidence matrix rule and merges a variety of truss string structure single injury distinguishing indexes, the fuse damaged distinguishing indexes of prestressing force truss string structure are obtained, to judge truss string structure chord member damage position.

Description

A kind of prestressing force string chord member of truss non-destructive tests based on multi-modal data fusion Method
Technical field
The invention belongs to the chord member non-destructive tests field of prestressing force truss string structure, it is related to a kind of based on actual monitoring data The prestressing force truss string structure damnification recognition method of multi-modal data fusion.
Background technique
Prestressing force truss string structure is one be composed of top rigid truss and lower flexible drag-line by center stayrod Kind self equilibrium systems have many advantages, such as that reasonable stress, bearing capacity are high, moulding is slim and graceful, span is big, sport at home and abroad Shop, Waiting Lounge, show room, high-speed rail station etc. become one be most widely used at present greatly across Successful utilization in steel roofing Kind form across prestressed steel structure greatly.
The general scale of truss string structure is big, service phase limit for length, and local environment complex, the load effect being subject to has random Property, the potentially danger damaged is larger, and damages and be difficult to the naked eye differentiate, therefore often will damaged member be obtained Less than timely processing and reinforce.Damage can persistently have an impact the normal use of structure in this case, or even cause and connect It is continuous to collapse, generate biggish Socie-economic loss.Once occurred both at home and abroad a lot of serious across steel worm-gearing or ceiling greatly destroy or Therefore total Collapse accident studies non-destructive tests of the truss string structure in the operation phase and has important practical significance.
Damnification recognition method based on modal data can effectively identify structural damage, and domestic and foreign scholars have carried out deeply A variety of effective damage criterions are studied and proposed, and obtain more application in bridge structure and more, high-level structure.However with Conventional roof structure is compared, there are the different types rod piece such as drag-line, strut and truss in truss string structure, rod piece wide variety, Force-mechanism is more complicated, and there are notable differences for non-destructive tests and conventional bridge type structure or multi-rise building structure.Inventor Pre-stage test and theory analysis research also show traditional signatures for damage detection applied to there are a degree of in truss string structure Erroneous judgement behavior, accuracy of identification are restricted.
Demand for truss string structure chord member health monitoring and the single injury index recognition effect based on modal data are not Data-Fusion theory is introduced the non-destructive tests of truss string structure by good problem, the present invention, and the mode obtained for multisensor is supervised Measured data carries out a variety of single injury distinguishing indexes data fusions using D-S evidence matrix rule, improves prestressing force truss string structure Non-destructive tests precision, and the application for being damage identification technique in truss string structure Practical Project provides theory- method-technology branch Support.
Data-Fusion theory is introduced into prestressing force truss string structure non-destructive tests by the present invention, solves prestressing force truss string structure With the low problem of single injury index accuracy of identification, the non-destructive tests precision of structure is improved from following several respects:
(1) present invention is analyzing the preparation stage, a certain during obtaining prestressing force truss string structure nondestructive state and use Each rank modal data of state, provides data basis for Damage Assessment Method, ensure that non-destructive tests can be gone on smoothly.
(2) present invention has initially set up the base suitable for truss string structure chord member when carrying out the calculating of single injury distinguishing indexes Quasi- signatures for damage detection system, improves the accuracy of identification of chord member single injury distinguishing indexes, provides for data fusion good Preliminary identification basis.
(3) present invention selects D-S evidence matrix theory quasi- as fusion when carrying out the calculating of fuse damaged distinguishing indexes Then, D-S evidence matrix it is theoretical its be in the nature Decision-level fusion method, have that the traffic is small, real-time is good, transmission bandwidth is low, anti- The advantages that interference performance is strong and fault-tolerance is high, and it is suitable for the fusion of no priori knowledge, therefore be suitable for the damage inspection of structure It surveys.Its recognition result for capableing of concentrated expression single injury index, can be improved the accuracy of non-destructive tests.
(4) present invention combines " single injury distinguishing indexes " with " D-S evidence matrix Data-Fusion theory ", combines more Kind of single index non-destructive tests judge damage position as a result, the accuracy of non-destructive tests can be improved effectively, with a high credibility, Robustness is good.
(5) the single injury recognition methods involved in the present invention arrived and Damage Identification Method of Data Fusion can be according to There are research and theoretical formula to realize efficient solution in each programming software, this method is easy to operate, it can be readily appreciated that having saved people Power cost has preferable practicability.
(6) the prestressing force truss string structure damnification recognition method of the invention based on multi-modal data fusion is applied to reality Among truss string structure chord member health monitoring, damage can be found and repaired in time, and structure can be made to be in comparatively safe shape State, to realize that the design of large scale structure life cycle management and maintenance provide a kind of effective means.
Summary of the invention
Prestressing force truss string structure damnification recognition method based on multi-modal data fusion of the invention, concrete scheme are as follows:
A kind of prestressing force string chord member of truss damnification recognition method based on multi-modal data fusion, which is characterized in that know Other method in turn includes the following steps:
S1: each rank mode number during acquisition prestressing force truss string structure nondestructive state and normal use under a certain detecting state According to, and mass normalisation modal data is converted by acquired each rank modal data, to construct the prestressing force string Truss non-destructive tests modal data；
S2: the prestressing force string chord member of truss single injury distinguishing indexes are calculated；
S3: the prestressing force string chord member of truss fuse damaged distinguishing indexes are calculated；
S4: judge prestressing force string chord member of truss damage position, i.e., be confirmed as fuse damaged index probability value maximum It is that damage position occurs for the prestressing force string chord member of truss.
Further, step S1 further include:
S11: it obtains each component level under the prestressing force truss string structure nondestructive state and moves normalization modal data；
S12: each component level during obtaining the prestressing force truss string structure use under a certain detecting state moves normalization mode Data；
S13: obtained each component level is moved into normalization modal data and is converted into mass normalisation modal data；
Further, it is preferably preceding 3 rank that each component level described in step S13, which moves normalization modal data,.
Further, step S2 further include:
S21: based on known single injury distinguishing indexes to the non-destructive tests effect of the prestressing force string chord member of truss, really Surely it is suitble to the fiducial lesions distinguishing indexes system of the prestressing force string chord member of truss, and therefrom chooses the knowledge of at least two single injuries Non-destructive tests of the other index for truss string structure chord member are analyzed；
S22: the characteristics of according to selected single injury distinguishing indexes, the modal data calculated for its is chosen, is chosen extremely Few first-order modal data form new truss string structure chord member modal data group；
S23: the identification of truss string structure chord member single injury is calculated separately based on the new truss string structure chord member modal data group Index.
Further, step S3 further include:
S31: probability assignment is carried out to each recognition result of prestressing force string chord member of truss single injury distinguishing indexes；
S32: using the recognition result of D-S evidence matrix rule fusion single injury index, prestressing force truss string structure string is obtained The fuse damaged distinguishing indexes of bar.
Detailed description of the invention
Fig. 1 is the flow chart of one embodiment in the present invention.
Specific embodiment
Technical solution of the present invention is described in further detail with reference to the accompanying drawing:
As shown in Figure 1, the prestressing force truss string structure damnification recognition method of the invention based on multi-modal data fusion, including Following steps:
(1) analysis prepares
(1a) obtains each rank modal data under prestressing force truss string structure nondestructive state.Injury stage does not occur in structure, Under prestressing force truss string structure nondestructive state, with TST3000 dynamic signalling analysis system acquisition sensor actual measureed value of acceleration Signal, and model analysis is carried out to acceleration signal with TSTMP model analysis software, obtain its each rank under nondestructive state Modal data(displacement normalization mode), as reference data, to be used for subsequent structural The non-destructive tests of period.
Each rank modal data during (1b) acquisition prestressing force truss string structure use under a certain detecting state.Prestressing force string Under truss nondestructive state, with TST3000 dynamic signalling analysis system acquisition sensor actual measureed value of acceleration signal, and use TSTMP model analysis software carries out model analysis to acceleration signal, obtains a certain detection during the use of prestressing force truss string structure Each rank modal data under state(displacement normalization mode).
Each rank non-destructive tests modal data Φ during (1c) building structure use under a certain detecting state.Utilizing calculating It is mass normalisation mode that modal data used is required when signatures for damage detection, it is therefore desirable to be converted to quality to actual measurement mode Normalize mode.Formula is as follows:
WhereinMode is normalized for the displacement of the i-th rank, [M] is the quality of structure.
Prestressing force truss string structure non-destructive tests modal data Φ is obtained, wherein ΦiIndicate prestressing force truss string structure lossless The i-th rank mass normalisation modal data under state and a certain state of validity period.
Φ=[Φ1,Φ2,...,Φi,...,Φn]
Φi=[Φiu,Φid]
(2) prestressing force string chord member of truss single injury distinguishing indexes calculate, specific steps are as follows:
(2a) analyzes the single injury distinguishing indexes based on modal data to the non-destructive tests effect of prestressing force string chord member of truss Fruit, determines the benchmark mode signatures for damage detection system of suitable prestressing force string chord member of truss, therefrom chooses two kinds or more and damages The non-destructive tests for hurting distinguishing indexes for truss string structure chord member are analyzed.
(2b) be directed to each single injury distinguishing indexes of chord member, from each rank non-destructive tests modal data Φ of prestressing force truss string structure= [Φ1,Φ2,…,Φn] in, it chooses a few rank modal datas and forms new mode array S1、S2…SNFor each chord member single injury The calculating of distinguishing indexes.
(2c) is based on modal data S1Obtain chord member single injury distinguishing indexes D1, it is based on modal data S2Obtain chord member partial loss Hurt distinguishing indexes D2, according to said method until calculating chord member single injury distinguishing indexes DN, and analyze each single injury distinguishing indexes knot Fruit tentatively judges whether prestressing force truss string structure damages.
(3) prestressing force string chord member of truss fuse damaged distinguishing indexes calculate it is characterized in that first to prestressing force string purlin Each recognition result of frame chord member single injury distinguishing indexes carries out probability assignment, followed by D-S evidence matrix ruled synthesis partial loss The recognition result for hurting index obtains the fuse damaged distinguishing indexes of prestressing force string chord member of truss.
The basic principle of D-S evidence matrix are as follows: carried out independently based on multi-sensor data with a variety of signatures for damage detection Identification, and carry out probability assignment respectively to the judging result of each signatures for damage detection and determine Basic probability assignment function, then transport It is merged with D-S evidence matrix composition rule, obtains recognition result to the end.
If θ is prestressing force truss string structure non-destructive tests frame, ei(i=1,2 ... n) indicate truss string structure i-th cell damage Wound, then:
θ={ e1,e2,...,en}
The power set of prestressing force truss string structure non-destructive tests frame is 2θ, indicate the collection of prestressing force truss string structure damage regime It closes:
In formula:Indicate that prestressing force truss string structure is in nondestructive state；eiIndicate prestressing force truss string structure individual unit hair Raw damage, i.e. single injury；ei∪ej…∪ekIndicate that the multiple units of prestressing force truss string structure damage simultaneously, i.e. poly-injury.
Basic probability assignment process on identification framework can be expressed as one 2θThe function of → [0,1], i.e., it is substantially general Rate partition function mass function, is abbreviated as m, meets:
In formula: A is a certain damage regime of prestressing force truss string structure, and m (A) is the Basic probability assignment function of A.
If m1,m2,…mnIt indicates n probability distribution function on same identification framework, is synthesized with D-S evidence matrix Rule carries out operation, is expressed as follows:
Wherein,
(3a)mi(Aj) indicate the damage probability of prestressing force truss string structure jth unit that the i-th single injury distinguishing indexes obtain, DijIndicate the D of truss string structure jth unitiSignatures for damage detection value.In conjunction with the single injury distinguishing indexes that (2c) is obtained, according to the following formula The Basic probability assignment function of each chord member signatures for damage detection of truss string structure is calculated, and probability assignment is carried out to it.
...
(3b) merges the Basic probability assignment function of each chord member single index according to D-S evidence matrix rule, obtains prestressing force Truss string structure fuse damaged distinguishing indexes, i.e. the damage probability value of structure each unit.Two kinds of single injury distinguishing indexes fusion methods It is shown below, wherein A indicates a certain damage regime of truss string structure.
A variety of single injury distinguishing indexes fusion methods are shown below.
(4) damage position is determined.The prestressing force truss string structure fuse damaged distinguishing indexes judgement being calculated according to (3b) The chord member of STRUCTURE DAMAGE LOCATION, i.e. fusion index damage probability value maximum damages.

Claims (5)

1. a kind of prestressing force string chord member of truss damnification recognition method based on multi-modal data fusion, which is characterized in that described Recognition methods in turn includes the following steps:
S1: each rank modal data during acquisition prestressing force truss string structure nondestructive state and normal use under a certain detecting state, And mass normalisation modal data is converted by acquired each rank modal data, to construct the prestressing force truss string structure Non-destructive tests modal data；
S2: the prestressing force string chord member of truss single injury distinguishing indexes are calculated；
S3: the prestressing force string chord member of truss fuse damaged distinguishing indexes are calculated；
S4: judge prestressing force string chord member of truss damage position, i.e., be confirmed as being institute by fuse damaged index probability value maximum It states prestressing force string chord member of truss and damage position occurs.
2. a kind of prestressing force string chord member of truss non-destructive tests side based on multi-modal data fusion according to claim 1 Method, which is characterized in that step S1 further include:
S11: it obtains each component level under the prestressing force truss string structure nondestructive state and moves normalization modal data；
S12: each component level during obtaining the prestressing force truss string structure use under a certain detecting state moves normalization modal data；
S13: obtained each component level is moved into normalization modal data and is converted into mass normalisation modal data.
3. a kind of prestressing force string chord member of truss non-destructive tests side based on multi-modal data fusion according to claim 2 Method, which is characterized in that it is preferably preceding 3 rank that each component level described in step S13, which moves normalization modal data,.
4. a kind of prestressing force string chord member of truss non-destructive tests side based on multi-modal data fusion according to claim 1 Method, which is characterized in that step S2 further include:
S21: it based on known single injury distinguishing indexes to the non-destructive tests effect of the prestressing force string chord member of truss, determines suitable The fiducial lesions distinguishing indexes system of the prestressing force string chord member of truss is closed, and therefrom chooses the identification of at least two single injuries and refers to Non-destructive tests of the mark for truss string structure chord member are analyzed；
S22: the characteristics of according to selected single injury distinguishing indexes, the modal data calculated for its is chosen, chooses at least one Rank modal data forms new truss string structure chord member modal data group；
S23: truss string structure chord member single injury distinguishing indexes are calculated separately based on the new truss string structure chord member modal data group.
5. a kind of prestressing force string chord member of truss non-destructive tests side based on multi-modal data fusion according to claim 1 Method, which is characterized in that step S3 further include:
S31: probability assignment is carried out to each recognition result of prestressing force string chord member of truss single injury distinguishing indexes；
S32: using the recognition result of D-S evidence matrix rule fusion single injury index, prestressing force string chord member of truss is obtained Fuse damaged distinguishing indexes.
CN201910692595.4A 2019-07-30 2019-07-30 A kind of prestressing force string chord member of truss damnification recognition method based on multi-modal data fusion Pending CN110414602A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910692595.4A CN110414602A (en) 2019-07-30 2019-07-30 A kind of prestressing force string chord member of truss damnification recognition method based on multi-modal data fusion

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910692595.4A CN110414602A (en) 2019-07-30 2019-07-30 A kind of prestressing force string chord member of truss damnification recognition method based on multi-modal data fusion

Publications (1)

Publication Number Publication Date
CN110414602A true CN110414602A (en) 2019-11-05

Family

ID=68364010

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910692595.4A Pending CN110414602A (en) 2019-07-30 2019-07-30 A kind of prestressing force string chord member of truss damnification recognition method based on multi-modal data fusion

Country Status (1)

Country Link
CN (1) CN110414602A (en)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111625934A (en) * 2020-04-30 2020-09-04 中国地质大学（武汉） Multi-mode identification method for annealing heating process based on D-S evidence theory

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102323382A (en) * 2011-07-20 2012-01-18 暨南大学 Multiple index lamination and fusion visualization method for detecting structural damages
CN104318097A (en) * 2014-10-20 2015-01-28 陈振富 Information fusion technology based damage diagnosis method
CN106897543A (en) * 2017-04-25 2017-06-27 湘潭大学 The girder construction damnification recognition method of On Modal Flexibility Curvature matrix norm
CN107092934A (en) * 2017-04-25 2017-08-25 淮阴师范学院 A kind of large scale structure damnification recognition method based on three-level data fusion
CN107957319A (en) * 2017-11-17 2018-04-24 湘潭大学 The simply supported beam Crack Damage recognition methods of uniform load face curvature
CN108226399A (en) * 2018-01-23 2018-06-29 中冶建筑研究总院有限公司 A kind of beam-string structure damage combined recognising method based on modal parameter
CN110031085A (en) * 2019-04-19 2019-07-19 大连理工大学 A kind of Damage Assessment Method sensor and Structural Damage Identification based on favour stone full-bridge principle

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102323382A (en) * 2011-07-20 2012-01-18 暨南大学 Multiple index lamination and fusion visualization method for detecting structural damages
CN104318097A (en) * 2014-10-20 2015-01-28 陈振富 Information fusion technology based damage diagnosis method
CN106897543A (en) * 2017-04-25 2017-06-27 湘潭大学 The girder construction damnification recognition method of On Modal Flexibility Curvature matrix norm
CN107092934A (en) * 2017-04-25 2017-08-25 淮阴师范学院 A kind of large scale structure damnification recognition method based on three-level data fusion
CN107957319A (en) * 2017-11-17 2018-04-24 湘潭大学 The simply supported beam Crack Damage recognition methods of uniform load face curvature
CN108226399A (en) * 2018-01-23 2018-06-29 中冶建筑研究总院有限公司 A kind of beam-string structure damage combined recognising method based on modal parameter
CN110031085A (en) * 2019-04-19 2019-07-19 大连理工大学 A kind of Damage Assessment Method sensor and Structural Damage Identification based on favour stone full-bridge principle

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
YUEQUAN BAO等: ""Dempster-Shafer evidence theory approach to structural damage detection"", 《STRUCTURAL HEALTH MONITORING》 *
赵军: ""张弦梁结构基于模态参数的损伤识别方法与试验研究"", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111625934A (en) * 2020-04-30 2020-09-04 中国地质大学（武汉） Multi-mode identification method for annealing heating process based on D-S evidence theory
CN111625934B (en) * 2020-04-30 2023-05-26 中国地质大学（武汉） Multimode identification method for annealing heating process based on D-S evidence theory

Similar Documents

Publication Publication Date Title
CN105241660B (en) High-speed rail large bridge performance test methods based on health monitoring data
CN106556498B (en) Damage Identification Methods for Bridge Structures and system
CN108226399B (en) A kind of beam-string structure damage combined recognising method based on modal parameter
CN107687924B (en) A kind of safe early warning method and system of bridge
CN102330645A (en) Health monitoring system and method for wind generator system structure
CN108280294B (en) A kind of cable arch structure damage combined recognising method based on modal parameter
CN102043019A (en) Method for identifying damages of frame structure
CN110704911B (en) Bridge damage cross positioning method based on cluster structure similarity
CN105956216A (en) Finite element model correction method for large-span steel bridge based on uniform temperature response monitoring value
CN103076394A (en) Safety evaluation method for ocean platform based on integration of vibration identification frequencies and vibration mode
CN107543581A (en) Multi-functional substation framework health monitoring and damnification recognition method
CN104880217A (en) Fault sensor information reconstruction method based on measured value association degree
CN111563530A (en) Intelligent bridge disease inspection method and system
CN105488352B (en) Concrete-bridge rigidity Reliability assessment method based on Long-term Deflection Monitoring Data
CN110414602A (en) A kind of prestressing force string chord member of truss damnification recognition method based on multi-modal data fusion
Luo et al. Data missing mechanism and missing data real-time processing methods in the construction monitoring of steel structures
CN110298143A (en) A kind of prestressing force truss string structure damnification recognition method based on two stages data fusion
CN111395144B (en) Method for monitoring and judging health state of large-span continuous rigid frame bridge
CN110472368A (en) Simply supported beam damage recognition methods based on shearing and inclination effect line curvature
CN103911958B (en) The damage reason location system of suspension bridge and arch bridge suspender periodic detection and method thereof
CN111310273A (en) Full-bridge structure safety state monitoring method and system based on multi-source data
CN111261239B (en) Composite material structure damage identification method based on damage mechanics
CN103164627B (en) Based on the random structure damnification recognition method of genetic algorithm and static force measurement data
Huo et al. Cable-stayed bridge sensor optimization based on modal information incremental matrix of the covariance matrix
Yang et al. Comprehensive performance evaluation of large span metal roof based on AHP-FCE

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
RJ01 Rejection of invention patent application after publication

Application publication date: 20191105

RJ01 Rejection of invention patent application after publication