M
Mallika Alapati
Researcher at VNR Vignana Jyothi Institute of Engineering and Technology
Publications - 10
Citations - 24
Mallika Alapati is an academic researcher from VNR Vignana Jyothi Institute of Engineering and Technology. The author has contributed to research in topics: Engineering & Structural health monitoring. The author has an hindex of 1, co-authored 6 publications receiving 9 citations.
Papers
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Journal ArticleDOI
Condition Assessment of Existing Concrete Building Using Non-Destructive Testing Methods for Effective Repair and Restoration-A Case Study
TL;DR: In this article, the NDT methods have greater advantage in evaluating the uniformity, homogeneity, approximate compressive strength, durability, the extent of corrosion of rebars in concrete etc.
Journal ArticleDOI
Damage detection of structural members using internet of things (IoT) paradigm
TL;DR: An integrated platform of IoT for damage detection using a Wi-Fi module, Raspberry Pi, (Piezoelectric) PZT sensors along with Digital to Analog (DAC) and Analog to Digital converters (ADC) and a mathematical model is proposed to identify and quantify the damage compared with responses of the healthy structural member.
Journal ArticleDOI
Effect of external vibrations on Electro-Mechanical impedance signatures in damage detection
TL;DR: In this article, the influence of external vibration with different excitation frequencies and amplitudes on EMI signatures of healthy and damaged beams is analyzed and presented on a cantilever aluminium flat.
Journal ArticleDOI
Numerical investigation on EMI signatures in pipes with varied damage levels
TL;DR: In this article, the root mean square deviation (RMSD) of smart pipes is computed based on the conductance signatures of the healthy and damaged pipes damage indices (Root Mean Square Deviation-RDSD) and it is concluded that greater RMSD values indicate the larger extent of the damage.
Book ChapterDOI
Study on Sensitivity of PZT Signatures for Damage Detection in RC Columns—A Numerical Study
TL;DR: In this paper, conductance signatures were extracted from the smart RC column in healthy and damaged conditions (in the form of cracks) under different frequency ranges, i.e., 0-10 kHz and 0-300 kHz, and found that there is significant change in the conductance signature by which the damage location and severity can be identified.