An Investigation into the Application of Acceleration Responses’ Trendline for Bridge Damage Detection Using Quadratic Regression
It has been proven that structural damage can be successfully identified using trendlines of structural acceleration responses. In previous numerical and experimental studies, the Savitzky–Golay filter and moving average filter were adjusted to determine suitable trendlines and locate structural dam...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-01-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/2/410 |
| _version_ | 1797339390720081920 |
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| author | Hadi Kordestani Chunwei Zhang Ali Arab |
| author_facet | Hadi Kordestani Chunwei Zhang Ali Arab |
| author_sort | Hadi Kordestani |
| collection | DOAJ |
| description | It has been proven that structural damage can be successfully identified using trendlines of structural acceleration responses. In previous numerical and experimental studies, the Savitzky–Golay filter and moving average filter were adjusted to determine suitable trendlines and locate structural damage in a simply supported bridge. In this study, the quadratic regression technique was studied and employed to calculate the trendlines of the bridge acceleration responses. The normalized energies of the resulting trendlines were then used as a damage index to identify the location and severity of the structural bridge damage. An ABAQUS model of a 25 m simply supported bridge under a truckload with different velocities was used to verify the accuracy of the proposed method. The structural damage was numerically modeled as cracks at the bottom of the bridge, so the stiffness at the damage positions was decreased accordingly. Four different velocities from 1 m/s to 8 m/s were used. The proposed method can identify structural damage in noisy environments without monitoring the dynamic modal parameters. Moreover, the accuracy of the newly proposed trendline-based method was increased compared to the previous method. For velocities up to 4 m/s, the damage in all single- and multiple-damage scenarios was successfully identified. For the velocity of 8 m/s, the damage in some scenarios was not located accurately. Additionally, it should be noted that the proposed method can be categorized as an online, quick, and baseline-free structural damage-detection method. |
| first_indexed | 2024-03-08T09:47:33Z |
| format | Article |
| id | doaj.art-1b58625642624e1d98b4cc0bb2c6a1fc |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-08T09:47:33Z |
| publishDate | 2024-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1b58625642624e1d98b4cc0bb2c6a1fc2024-01-29T14:14:22ZengMDPI AGSensors1424-82202024-01-0124241010.3390/s24020410An Investigation into the Application of Acceleration Responses’ Trendline for Bridge Damage Detection Using Quadratic RegressionHadi Kordestani0Chunwei Zhang1Ali Arab2School of Civil Engineering, Shandong Jianzhu University, Jinan 250101, ChinaMultidisciplinary Center for Infrastructure Engineering, Shenyang University of Technology, Shenyang 110870, ChinaMultidisciplinary Center for Infrastructure Engineering, Shenyang University of Technology, Shenyang 110870, ChinaIt has been proven that structural damage can be successfully identified using trendlines of structural acceleration responses. In previous numerical and experimental studies, the Savitzky–Golay filter and moving average filter were adjusted to determine suitable trendlines and locate structural damage in a simply supported bridge. In this study, the quadratic regression technique was studied and employed to calculate the trendlines of the bridge acceleration responses. The normalized energies of the resulting trendlines were then used as a damage index to identify the location and severity of the structural bridge damage. An ABAQUS model of a 25 m simply supported bridge under a truckload with different velocities was used to verify the accuracy of the proposed method. The structural damage was numerically modeled as cracks at the bottom of the bridge, so the stiffness at the damage positions was decreased accordingly. Four different velocities from 1 m/s to 8 m/s were used. The proposed method can identify structural damage in noisy environments without monitoring the dynamic modal parameters. Moreover, the accuracy of the newly proposed trendline-based method was increased compared to the previous method. For velocities up to 4 m/s, the damage in all single- and multiple-damage scenarios was successfully identified. For the velocity of 8 m/s, the damage in some scenarios was not located accurately. Additionally, it should be noted that the proposed method can be categorized as an online, quick, and baseline-free structural damage-detection method.https://www.mdpi.com/1424-8220/24/2/410quadratic regressiontrendlinedamage detectionbridgeacceleration responsetruckload |
| spellingShingle | Hadi Kordestani Chunwei Zhang Ali Arab An Investigation into the Application of Acceleration Responses’ Trendline for Bridge Damage Detection Using Quadratic Regression Sensors quadratic regression trendline damage detection bridge acceleration response truckload |
| title | An Investigation into the Application of Acceleration Responses’ Trendline for Bridge Damage Detection Using Quadratic Regression |
| title_full | An Investigation into the Application of Acceleration Responses’ Trendline for Bridge Damage Detection Using Quadratic Regression |
| title_fullStr | An Investigation into the Application of Acceleration Responses’ Trendline for Bridge Damage Detection Using Quadratic Regression |
| title_full_unstemmed | An Investigation into the Application of Acceleration Responses’ Trendline for Bridge Damage Detection Using Quadratic Regression |
| title_short | An Investigation into the Application of Acceleration Responses’ Trendline for Bridge Damage Detection Using Quadratic Regression |
| title_sort | investigation into the application of acceleration responses trendline for bridge damage detection using quadratic regression |
| topic | quadratic regression trendline damage detection bridge acceleration response truckload |
| url | https://www.mdpi.com/1424-8220/24/2/410 |
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