CN109583314A - A kind of optimization method and device of concrete girder bridge safety monitoring index - Google Patents
A kind of optimization method and device of concrete girder bridge safety monitoring index Download PDFInfo
- Publication number
- CN109583314A CN109583314A CN201811291733.XA CN201811291733A CN109583314A CN 109583314 A CN109583314 A CN 109583314A CN 201811291733 A CN201811291733 A CN 201811291733A CN 109583314 A CN109583314 A CN 109583314A
- Authority
- CN
- China
- Prior art keywords
- strain
- neutral axis
- amplitude
- responsive
- safety monitoring
- 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
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
- G06F2218/04—Denoising
- G06F2218/06—Denoising by applying a scale-space analysis, e.g. using wavelet 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
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/08—Feature extraction
- G06F2218/10—Feature extraction by analysing the shape of a waveform, e.g. extracting parameters relating to peaks
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Tourism & Hospitality (AREA)
- Quality & Reliability (AREA)
- General Business, Economics & Management (AREA)
- Operations Research (AREA)
- Game Theory and Decision Science (AREA)
- Artificial Intelligence (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Signal Processing (AREA)
- General Engineering & Computer Science (AREA)
- Bridges Or Land Bridges (AREA)
Abstract
The present invention relates to a kind of optimization method and devices of concrete girder bridge safety monitoring index, wherein method includes: step S1: receiving the structural strain signal of the bridge collected, and strain signal is analyzed and reconstructed using multiresolution wavelet analysis, to eliminate environment temperature and data noise；Step S2: based on the threshold interval set up, peak value and valley composition binary array of the amplitude caused by same mobile load more than threshold interval is extracted, strain-responsive amplitude caused by single vehicle motivates is obtained；Step S3: calculating corresponding neutral axis height according to the strain-responsive amplitude at monitoring cross section different height, carry out data integration to intraday neutral axis safety index, calculates the statistical property including probability distribution as the safety monitoring index after optimization.Compared with prior art, the present invention analyzes using statistical means and assesses the statistical nature of neutral axis distribution, is particularly suited for the long term monitoring of bridge structure.
Description
Technical field
The present invention relates to structural safety monitoring fields, more particularly, to a kind of concrete girder bridge safety monitoring index
Optimization method and device.
Background technique
Beam bridge, in occupation of the principal status of public economy that can not be shaken in highway bridge.With the increase of bridge Years Of Service,
Large quantities of newly building bridges just progress into " aging " stage, and various forms of structure degradations inevitably occur.It can
See, it is very urgent for carrying out safety monitoring research of the beam bridge under operation state.By selecting reasonable, general safety
Index carries out long term monitoring, the structure degradation process of target bridge can be effectively held, to study and judge the peace of the bridge of target
Full deposit, and carry out preventive maintenance.
Neutral axis is considered as the potential safety index that can be used for bridge long term monitoring.But in engineering practice, still have one
A little problems demands solve.For example, the variation of environment temperature and the presence of data noise will lead to original strain signal at any time
Apparent drift is generated, and then causes the stability of neutral axis safety index and accuracy insufficient.Therefore, it is necessary to by the modern times
Signal processing technology eliminates the above interference, it is ensured that the excitation of treated strain signal really reflects vehicular load.Furthermore
Even if strain signal by filtering processing, is arbitrarily carried out using the strain-responsive amplitude descended at different height in the same time neutral
Axis calculating is also infeasible.Under low strain dynamic amplitude, the uncertainty and the insufficient of measurement accuracy of parameters can be significant
Weaken the safety instruction performance of neutral axis.
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide a kind of concrete girder bridges
The optimization method and device of safety monitoring index.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of optimization method of concrete girder bridge safety monitoring index, comprising:
Step S1: the structural strain signal of the bridge collected is received, and using multiresolution wavelet analysis to strain
Signal is analyzed and is reconstructed, to eliminate environment temperature and data noise；
Step S2: based on the threshold interval set up, extract peak value of the amplitude caused by same mobile load more than threshold interval and
Valley forms binary array, obtains strain-responsive amplitude caused by single vehicle motivates；
Step S3: corresponding neutral axis height is calculated according to the strain-responsive amplitude at monitoring cross section different height, to one section
Neutral axis safety index in time carries out data integration, after calculating the statistical property including probability distribution as optimization
Safety monitoring index.
The step S1 is specifically included:
Step S11: the sensor signal time-history curves of the strain gauge of each channel acquisition in the same day are obtained；
Step S12: to the strain data in each channel, the use of the small wave system of dmey is basic function, is carried out 12 levels
Wavelet decomposition；
Step S13: the low-frequency component for extracting the 12nd layer of decomposition is reconstructed into the temperature strain response in the channel, is answered with original
Varying signal subtracts temperature strain response, obtains required mobile load strain-responsive.
The step S2 is specifically included:
Step S21: threshold interval is defined；
Step S22: peak value and valley composition binary array of the amplitude caused by same mobile load more than threshold interval is extracted；
Step S22: subtracting valley using peak value and obtain the strain-responsive amplitude under the mobile load, motivates institute as the mobile load
Strain-responsive amplitude caused by corresponding vehicle motivates.
The step S3 is specifically included:
Step S31: the strain-responsive amplitude that comprehensive same section different height measures calculates neutral axis index；
Step S32: summarize intraday all neutral axis indexs monitored and carry out Frequency statistics, be depicted as frequency
Distribution histogram；
Step S33: normal curve fitting is carried out to the frequency distribution histogram, obtains its corresponding normal distribution；
Step S34: the mean value and standard deviation of the distribution are exported, and is compared with historical data, if appointing in mean value and standard deviation
One amplitude of variation is more than threshold value, assert that there are structural damages.
The threshold value is 3%.
A kind of optimization device of concrete girder bridge safety monitoring index, including processor, memory, and be stored in
The program executed in memory and by the processor, the processor are performed the steps of when executing described program
Step S1: the structural strain signal of the bridge collected is received, and using multiresolution wavelet analysis to strain
Signal is analyzed and is reconstructed, to eliminate environment temperature and data noise；
Step S2: based on the threshold interval set up, extract peak value of the amplitude caused by same mobile load more than threshold interval and
Valley forms binary array, obtains strain-responsive amplitude caused by single vehicle motivates；
Step S3: corresponding neutral axis height is calculated according to the strain-responsive amplitude at monitoring cross section different height, to one day
Interior neutral axis safety index carries out data integration, is fitted its probability distribution, and assess its statistical property.
The step S1 is specifically included:
Step S11: the sensor signal time-history curves of the strain gauge of each channel acquisition in the same day are obtained；
Step S12: to the strain data in each channel, the use of the small wave system of dmey is basic function, is carried out 12 levels
Wavelet decomposition；
Step S13: the low-frequency component for extracting the 12nd layer of decomposition is reconstructed into the temperature strain response in the channel, is answered with original
Varying signal subtracts temperature strain response, obtains required mobile load strain-responsive.
The step S2 is specifically included:
Step S21: threshold interval is defined；
Step S22: peak value and valley composition binary array of the amplitude caused by same mobile load more than threshold interval is extracted；
Step S22: subtracting valley using peak value and obtain the strain-responsive amplitude under the mobile load, motivates institute as the mobile load
Strain-responsive amplitude caused by corresponding vehicle motivates.
The step S3 is specifically included:
Step S31: the strain-responsive amplitude that comprehensive same section different height measures calculates neutral axis index；
Step S32: summarize intraday all neutral axis indexs monitored and carry out Frequency statistics, be depicted as frequency
Distribution histogram；
Step S33: normal curve fitting is carried out to the frequency distribution histogram, obtains its corresponding normal distribution；
Step S34: the mean value and standard deviation of the distribution are exported, and is compared with historical data, if appointing in mean value and standard deviation
One amplitude of variation is more than threshold value, assert that there are structural damages.
The threshold value is 3%.
Compared with prior art, the invention has the following advantages:
1) interference of environment temperature and data noise to strain signal is effectively reduced, neutral axis safety index is improved
Stability and accuracy.The statistical nature that neutral axis distribution is analyzed and assessed using statistical means, is particularly suited for bridge
The long term monitoring of structure.
2) using response peak/valley under vehicular load excitation, and the neutral axis index referred in timing window is sampled and is carried out
Data integration and statistical analysis assess the variation of its statistical property, effective and practical application direction.
Detailed description of the invention
Fig. 1 is the key step flow diagram of the method for the present invention；
Fig. 2 (a) is the schematic diagram of original strain signal；
Fig. 2 (b) is the signal of mobile load strain signal；
Fig. 3 is the pickup schematic diagram that peak-to-valley value is carried out to strain signal；
Fig. 4 is that the frequency histogram of neutral axis and normal state statistical distribution are fitted schematic diagram.
Specific embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.The present embodiment is with the technology of the present invention side
Implemented premised on case, the detailed implementation method and specific operation process are given, but protection scope of the present invention is unlimited
In following embodiments.
The application discloses a kind of optimization method of beam bridge cross section neutral axis safety index, and this method combines the modern times
Signal processing technology and statistical estimation method form the scheme of optimization neutral axis safety index performance.It is strained by introducing
The multiresolution wavelet analysis of signal and peak algorithm is picked up, the interference of ambient noise and temperature change can be effectively reduced, improved
The accuracy of neutral axis index.Be used in combination statistical estimation correlation theory, obtain refer to timing window under neutral axis safety index it is close
Structure feature is characterized like probability distribution, and with its statistical property.By real bridge verification experimental verification, the neutral axis that method obtains according to this
Safety index shows stabilization during long term monitoring, has outstanding anti-interference ability, and significant increase neutral axis refers to safely
The practical value being marked in bridge long term monitoring.
Specifically, as shown in Figure 1, comprising:
Step S1: setting signal time window length=1 day, all dynamic strain data acquired in the same day are retrieved,
Integrated and pretreatment；Strain signal is decomposed using multiresolution wavelet analysis, eliminates low frequency temperature ingredient, extracts knot
Response trend of the structure under vehicular load excitation, specifically includes:
Step S11: the sensor signal time-history curves of the strain gauge of each channel acquisition in the same day are obtained, data set is carried out
At；
Step S12: to the strain data in each channel, the use of the small wave system of dmey is basic function, is carried out 12 levels
Wavelet decomposition；
Step S13: the low-frequency component for extracting the 12nd layer of decomposition is reconstructed into the temperature strain response in the channel, is answered with original
Varying signal subtracts temperature strain response, obtains required mobile load strain-responsive.
Step S2: based on the threshold interval set up, extract peak value of the amplitude caused by same mobile load more than threshold interval and
Valley forms binary array, obtains strain-responsive amplitude caused by single vehicle motivates, and define strain time history curve medium wave peak
Height or the depth of trough be its significance degree, define corresponding threshold interval, pick up wave crest, trough beyond threshold value limit
Value；According to the corresponding relationship between peak-to-valley value, peak-to-valley value caused by being motivated by same mobile load forms binary array, the two phase
Subtract to obtain strain-responsive amplitude, specifically include:
Step S21: defining threshold interval, and the significant strain as caused by vehicular load that is considered as beyond the range is rung
It answers；
Step S22: peak value and valley composition binary array of the amplitude caused by same mobile load more than threshold interval is extracted；
Step S22: subtracting valley using peak value and obtain the strain-responsive amplitude under the mobile load, motivates institute as the mobile load
Strain-responsive amplitude caused by corresponding vehicle motivates.
Step S3: corresponding neutral axis height is calculated according to the strain-responsive amplitude at monitoring cross section different height, to one section
Neutral axis safety index in time (such as in one day or in one month etc.) carries out data integration, and calculating includes probability distribution
Statistical property inside is specifically included as the safety monitoring index after optimization:
Step S31: the strain-responsive amplitude that comprehensive same section different height measures calculates neutral axis index, for example,
It is ε that top sensor, which measures strain,t, it is ε that bottom sensor, which measures strain,b, vertically distance is h to the two, then by looking for following formula to acquire
Neutral axis height yb:
Wherein: εbStrain, ε are measured for bottom sensortStrain is measured for top sensor, h is the perpendicular of two sensors
To distance.
Step S32: summarize intraday all neutral axis indexs monitored and carry out Frequency statistics, be depicted as frequency
Distribution histogram；
Step S33: normal curve fitting is carried out to the frequency distribution histogram, obtains its corresponding normal distribution, probability
Density are as follows:
Step S34: distribution X~N (μ, σ are exported2) mean μ and standard deviation sigma, and with historical data compare, if mean value
It is more than 3% with any one amplitude of variation in standard deviation, assert that there are structural damages.
Such as current statistic feature is μ1And σ1, historical statistics feature is μ0And σ0, then whenOrWhen decision structure exist damage.
The application method is applied to actual test, certain bridge is prestressed concrete shake out beam bridge, and across footpath group becomes 32+32
+37+32m.The 4th hole 1/4 of bridge across, 1/2 across, 3/4 be respectively set 4,6,4 dynamic strain measuring points across place, laying with
On the web of box-beam structure two sides.Original strain signal is decomposed and reconstructed using the method for Fig. 2, after obtaining signal
Manage result.And then the peak-to-valley value array generated under vehicular load excitation by the method pickoff signals of Fig. 3, and calculate neutral axis
Index.Histogram as shown in Figure 4 is drawn, being fitted and verifying its probability distribution is normal distribution, its mean value and variance are obtained,
And it is compared with historical data.By the operation of several months, it was demonstrated that the method for the present invention is reliably that data are highly stable, is avoided previous
Beam bridge monitors the common weakness and deficiency of system.
Claims (10)
1. a kind of optimization method of concrete girder bridge safety monitoring index characterized by comprising
Step S1: the structural strain signal of the bridge collected is received, and using multiresolution wavelet analysis to strain signal
It is analyzed and is reconstructed, to eliminate environment temperature and data noise；
Step S2: based on the threshold interval set up, the peak value and valley that amplitude caused by same mobile load is more than threshold interval are extracted
Binary array is formed, strain-responsive amplitude caused by single vehicle motivates is obtained；
Step S3: corresponding neutral axis height is calculated according to the strain-responsive amplitude at monitoring cross section different height, to a period of time
Interior neutral axis safety index carries out data integration, calculates the statistical property including probability distribution as the safety after optimization
Monitoring index.
2. a kind of optimization method of concrete girder bridge safety monitoring index according to claim 1, which is characterized in that institute
Step S1 is stated to specifically include:
Step S11: the sensor signal time-history curves of the strain gauge of each channel acquisition in the same day are obtained；
Step S12: to the strain data in each channel, the use of the small wave system of dmey is basic function, is carried out the small echo of 12 levels
It decomposes；
Step S13: the low-frequency component for extracting the 12nd layer of decomposition is reconstructed into the temperature strain response in the channel, with original strain signal
Temperature strain response is subtracted, required mobile load strain-responsive is obtained.
3. a kind of optimization method of concrete girder bridge safety monitoring index according to claim 2, which is characterized in that institute
Step S2 is stated to specifically include:
Step S21: threshold interval is defined；
Step S22: peak value and valley composition binary array of the amplitude caused by same mobile load more than threshold interval is extracted；
Step S22: subtracting valley using peak value and obtain the strain-responsive amplitude under the mobile load, corresponding as mobile load excitation
Strain-responsive amplitude caused by vehicle motivates.
4. a kind of optimization method of concrete girder bridge safety monitoring index according to claim 3, which is characterized in that institute
Step S3 is stated to specifically include:
Step S31: the strain-responsive amplitude that comprehensive same section different height measures calculates neutral axis index；
Step S32: summarize intraday all neutral axis indexs monitored and carry out Frequency statistics, it is straight to be depicted as frequency distribution
Fang Tu；
Step S33: normal curve fitting is carried out to the frequency distribution histogram, obtains its corresponding normal distribution；
Step S34: the mean value and standard deviation of the distribution are exported, and is compared with historical data, if any one in mean value and standard deviation
Amplitude of variation is more than threshold value, assert that there are structural damages.
5. a kind of optimization method of concrete girder bridge safety monitoring index according to claim 4, which is characterized in that institute
Stating threshold value is 3%.
6. a kind of optimization device of concrete girder bridge safety monitoring index, which is characterized in that including processor, memory, with
And the program for being stored in memory and being executed by the processor, the processor realize following step when executing described program
It is rapid:
Step S1: the structural strain signal of the bridge collected is received, and using multiresolution wavelet analysis to strain signal
It is analyzed and is reconstructed, to eliminate environment temperature and data noise；
Step S2: based on the threshold interval set up, the peak value and valley that amplitude caused by same mobile load is more than threshold interval are extracted
Binary array is formed, strain-responsive amplitude caused by single vehicle motivates is obtained；
Step S3: corresponding neutral axis height is calculated according to the strain-responsive amplitude at monitoring cross section different height, to intraday
Neutral axis safety index carries out data integration, is fitted its probability distribution, and assess its statistical property.
7. a kind of optimization method of concrete girder bridge safety monitoring index according to claim 6, which is characterized in that institute
Step S1 is stated to specifically include:
Step S11: the sensor signal time-history curves of the strain gauge of each channel acquisition in the same day are obtained；
Step S12: to the strain data in each channel, the use of the small wave system of dmey is basic function, is carried out the small echo of 12 levels
It decomposes；
Step S13: the low-frequency component for extracting the 12nd layer of decomposition is reconstructed into the temperature strain response in the channel, with original strain signal
Temperature strain response is subtracted, required mobile load strain-responsive is obtained.
8. a kind of optimization method of concrete girder bridge safety monitoring index according to claim 7, which is characterized in that institute
Step S2 is stated to specifically include:
Step S21: threshold interval is defined；
Step S22: peak value and valley composition binary array of the amplitude caused by same mobile load more than threshold interval is extracted；
Step S22: subtracting valley using peak value and obtain the strain-responsive amplitude under the mobile load, corresponding as mobile load excitation
Strain-responsive amplitude caused by vehicle motivates.
9. a kind of optimization method of concrete girder bridge safety monitoring index according to claim 8, which is characterized in that institute
Step S3 is stated to specifically include:
Step S31: the strain-responsive amplitude that comprehensive same section different height measures calculates neutral axis index；
Step S32: summarize intraday all neutral axis indexs monitored and carry out Frequency statistics, it is straight to be depicted as frequency distribution
Fang Tu；
Step S33: normal curve fitting is carried out to the frequency distribution histogram, obtains its corresponding normal distribution；
Step S34: the mean value and standard deviation of the distribution are exported, and is compared with historical data, if any one in mean value and standard deviation
Amplitude of variation is more than threshold value, assert that there are structural damages.
10. a kind of optimization method of concrete girder bridge safety monitoring index according to claim 9, which is characterized in that
The threshold value is 3%.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811291733.XA CN109583314A (en) | 2018-10-31 | 2018-10-31 | A kind of optimization method and device of concrete girder bridge safety monitoring index |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811291733.XA CN109583314A (en) | 2018-10-31 | 2018-10-31 | A kind of optimization method and device of concrete girder bridge safety monitoring index |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109583314A true CN109583314A (en) | 2019-04-05 |
Family
ID=65921114
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811291733.XA Pending CN109583314A (en) | 2018-10-31 | 2018-10-31 | A kind of optimization method and device of concrete girder bridge safety monitoring index |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109583314A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111238748A (en) * | 2020-01-17 | 2020-06-05 | 上海城建城市运营(集团)有限公司 | Movable rapid monitoring system for box girder bridge |
| CN112945195A (en) * | 2021-01-26 | 2021-06-11 | 北京讯腾智慧科技股份有限公司 | Method and device for measuring gradient of track bridge during passing of train |
| CN113155063A (en) * | 2021-01-26 | 2021-07-23 | 北京讯腾智慧科技股份有限公司 | Method and device for determining track bridge deformation data during train passing through bridge |
| CN113961882A (en) * | 2021-11-18 | 2022-01-21 | 郑州大学 | Damage detection method considering influence of vertical temperature difference of concrete girder on performance of neutral shaft |
| CN116842348A (en) * | 2023-08-31 | 2023-10-03 | 安徽省云鹏工程项目管理有限公司 | Bridge health monitoring system based on artificial intelligence |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120209538A1 (en) * | 2011-02-10 | 2012-08-16 | Caicedo Juan M | Determination of the Remaining Life of a Structural System Based on Acoustic Emission Signals |
| CN104881567A (en) * | 2015-04-24 | 2015-09-02 | 浙江工业大学 | Statistical model based bridge health monitoring data wavelet denoising method |
| CN108399277A (en) * | 2018-01-24 | 2018-08-14 | 华南理工大学 | A kind of bridge damnification recognition method based on temperature with strain relevance |
-
2018
- 2018-10-31 CN CN201811291733.XA patent/CN109583314A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120209538A1 (en) * | 2011-02-10 | 2012-08-16 | Caicedo Juan M | Determination of the Remaining Life of a Structural System Based on Acoustic Emission Signals |
| CN104881567A (en) * | 2015-04-24 | 2015-09-02 | 浙江工业大学 | Statistical model based bridge health monitoring data wavelet denoising method |
| CN108399277A (en) * | 2018-01-24 | 2018-08-14 | 华南理工大学 | A kind of bridge damnification recognition method based on temperature with strain relevance |
Non-Patent Citations (1)
| Title |
|---|
| D H SIGURDARDOTTIR 等: "Neutral axis as damage sensitive feature", 《SMART MATERIALS AND STRUCTURES》 * |
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111238748A (en) * | 2020-01-17 | 2020-06-05 | 上海城建城市运营(集团)有限公司 | Movable rapid monitoring system for box girder bridge |
| CN111238748B (en) * | 2020-01-17 | 2021-09-03 | 上海城建城市运营(集团)有限公司 | Movable rapid monitoring system for box girder bridge |
| CN112945195A (en) * | 2021-01-26 | 2021-06-11 | 北京讯腾智慧科技股份有限公司 | Method and device for measuring gradient of track bridge during passing of train |
| CN113155063A (en) * | 2021-01-26 | 2021-07-23 | 北京讯腾智慧科技股份有限公司 | Method and device for determining track bridge deformation data during train passing through bridge |
| CN113961882A (en) * | 2021-11-18 | 2022-01-21 | 郑州大学 | Damage detection method considering influence of vertical temperature difference of concrete girder on performance of neutral shaft |
| CN113961882B (en) * | 2021-11-18 | 2024-02-23 | 郑州大学 | Damage detection method considering influence of vertical temperature difference of concrete girder on neutral axis performance |
| CN116842348A (en) * | 2023-08-31 | 2023-10-03 | 安徽省云鹏工程项目管理有限公司 | Bridge health monitoring system based on artificial intelligence |
| CN116842348B (en) * | 2023-08-31 | 2023-12-01 | 安徽省云鹏工程项目管理有限公司 | Bridge health monitoring system based on artificial intelligence |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109583314A (en) | A kind of optimization method and device of concrete girder bridge safety monitoring index | |
| Sivakumar et al. | Singapore rainfall behavior: chaotic? | |
| CN109655298B (en) | Fault real-time early warning method and device for large-span metal roof | |
| CN108956767B (en) | Reinforced concrete corrosion fatigue damage evaluation method based on frequency-information entropy | |
| CN107885927B (en) | Railway bridge operation state early warning method | |
| CN109506615B (en) | Long term monitoring methods based on beam bridge cross section neutral axis safety index | |
| Kothyari et al. | An investigation of changes in rainfall and temperature regimes of the Ganga Basin in India | |
| CN110954071A (en) | Probability statistical analysis method for wave parameters | |
| CN108108568B (en) | Method for eliminating low-frequency sampling indexes affecting online safety monitoring of bridge structure due to temperature | |
| CN104931040A (en) | Installation and debugging method of Beidou generation-II navigation system electric iron tower deformation monitoring device based on machine learning | |
| CN113175987A (en) | Bridge dynamic characteristic abnormity early warning method considering environment temperature variation | |
| CN114997249A (en) | Monitoring method and system for bridge expansion joint device | |
| Isioma et al. | Non-parametric Mann–Kendall test statistics for rainfall trend analysis in some selected states within the coastal region of Nigeria | |
| CN113514833B (en) | Sea surface arbitrary point wave direction inversion method based on sea wave image | |
| González et al. | Temperature measurement assisted modal tracking of an instrumented building | |
| CN113592308A (en) | Monitoring data alarm threshold extraction method based on normal model | |
| Carrara et al. | Deep learning for structural health monitoring: An application to heritage structures | |
| CN112991285A (en) | Asphalt concrete pavement engineering construction quality monitoring real-time dynamic regulation and control method based on feature recognition | |
| CN112070783A (en) | Wind deflection detection method and device for insulator string of power transmission line | |
| Chelani et al. | Nonlinear analysis and prediction of coarse particulate matter concentration in ambient air | |
| Qu et al. | Outlier Detection and Forecasting for Bridge Health Monitoring Based on Time Series Intervention Analysis. | |
| DE112022002147T5 (en) | MAPPING USING OPTICAL FIBERS | |
| CN109711075B (en) | Steel girder bridge life and reliability analysis method based on sudden load nonlinear theory | |
| CN103854658B (en) | Steel plate corrosion Research on Denoising in Acoustic Emission Signals based on Short Time Fractal Numbers enhancing method | |
| Sun et al. | Modeling and prediction of Great Salt Lake elevation time series based on ARFIMA |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190405 |