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<strong>Strain Sensor’s Network for Low-Velocity Impact Location Estimation on Carbon Reinforced Fiber Plastic Structures: Part-II</strong>

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Title Statement <strong>Strain Sensor’s Network for Low-Velocity Impact Location Estimation on Carbon Reinforced Fiber Plastic Structures: Part-II</strong>
 
Added Entry - Uncontrolled Name Datta, Amitabha ; CSIR-National Aerospace Laboratories
M J, Augustin ; CSIR-National Aerospace Laboratories
Gupta, Nitesh ; CSIR-National Aerospace Laboratories
SR, Viswamurthy ; CSIR-National Aerospace Laboratories
Gaddikeri, Kotresh M; CSIR-National Aerospace Laboratories
Sundaram, Ramesh ; CSIR-National Aerospace Laboratories
Aeronautics Research and Development Board (AR&DB), New Delhi
 
Uncontrolled Index Term Impact location estimation; Fiber bragg grating; Resistance strain gauges; Structural health monitoring
 
Summary, etc. <p class="Abstract">Identification of low velocity impact (LVI) location in composite aircraft structures is seamless need for safe, reliable operation and maintenance of aerospace industry. To locate the LVI’s an optimized sensor network has designed using the strain response from fiber Bragg grating (FBG) &amp; resistance strain gauge (RSG) sensor bonded to the composite structure. Strain scan (SS) algorithm has been developed to locate such events reported as Part-I. In this work, we have developed a novel algorithm based on weighted energy (WE) of the sensor response. The LVI’s has been carried out on composite structures &amp; the locations of LVI’s have estimated using SS, WE &amp; previously developed machine learning base support vector machine (SVM) algorithms. The WE and SS algorithms are based on proximity of events (closer to the sensor, higher the response), whereas LS-SVR is a data-driven approach. Further, we have compared the performance of the developed algorithms and algorithms cited in the literature using the performance index (PI), a measure of estimation efficiency as a function of the number of sensors, dimension/area of the structure, error &amp; number of test cases. It is established that WE algorithm shown suprema performance over the other algorithm with 34 mm mean Euclidian distance error &amp; PI value of 5.5.</p>
 
Publication, Distribution, Etc. Indian Journal of Pure & Applied Physics (IJPAP)
2021-10-11 15:42:53
 
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http://op.niscair.res.in/index.php/IJPAP/article/view/44990
 
Data Source Entry Indian Journal of Pure & Applied Physics (IJPAP); ##issue.vol## 59, ##issue.no## 10 (2021): Indian Journal of Pure & Applied Physics
 
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