Browsing by Author "Alotaibi, Ahmed"

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    Direct and Extended Piezoresistive and Piezoelectric Strain Fusion for a Wide Band PVDF/MWCNT-Based 3D Force Sensor
    (IEEE, 2021) Alotaibi, Ahmed; Anwar, Sohel; Mechanical and Energy Engineering, School of Engineering and Technology
    This paper presents a novel 3D force sensor design based on in-situ nanocomposite strain sensors. The polymer matrix of the polyvinylidene fluoride (PVDF) and multi-walled carbon nanotubes (MWCNT) conductive filler nanocomposite film have been chosen as sensing elements for the 3D force sensor. A bioinspired tree branch design was used as the 3D force sensor’s elastic structure, that was built using thin Aluminum plates and a laser cutting fabrication process. The PVDF/MWCNT films contained piezoresistive and piezoelectric characteristics, allowing for static/low and dynamic strain measurements, respectively. Two compositions with 0.1 and 2 wt.% PVDF/MWCNT sensing elements were selected for piezoelectric and piezoresistive strain measurements, respectively. These characteristic measurements were investigated under different loading frequencies in a simply supported beam experiment. The 3D force sensor was tested under dynamic excitation in the Z-direction and the X-direction. A Direct Piezoresistive/Piezoelectric fusion (DPPF) method was developed by fusing the piezoresistive and piezoelectric measurements at a given frequency that overcomes the limited frequency ranges of each of the strain sensor characteristics. The DPPF method is based on a fuzzy inference system (FIS) which is constructed and tuned using the subtractive clustering technique. Different nonlinear Hammerstein-Wiener (nlhw) models were used to estimate the actual strain from piezoresistive and piezoelectric measurements at the 3D force sensor. In addition, an Extended direct Piezoresistive/Piezoelectric fusion (EPPF) algorithm is introduced to enhance the DPPF method via performing the fusion in a range of frequencies instead of a particular one. The DPPF and EPPF methods were implemented on the 3D force sensor data, and the developed fusion algorithms were tested on the new 3D force sensor via experimental data. The simulation results show that the proposed fusion methods have been effective in achieving lower Root Mean Square Error (RMSE) in the estimated strain than those obtained from the tuned nlhw models at different operating frequencies.
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    A Fuzzy Logic Based Piezoresistive/Piezoelectric Fusion Algorithm for Carbon Nanocomposite Wide Band Strain Sensor
    (IEEE, 2021) Alotaibi, Ahmed; Anwar, Sohel; Mechanical and Energy Engineering, School of Engineering and Technology
    Polymer nanocomposites (PNC) have a great potential for in-situ strain sensing applications in both static and dynamic loading scenarios. These PNCs, having a polymer matrix of polyvinylidene fluoride (PVDF) with a conductive filler of multi-walled carbon nanotubes (MWCNT), have both piezoelectric and piezoresistive characteristics. Generally, this composite would accurately measure either low frequency dynamic strain using piezoresistive characteristic or high frequency dynamic strains using piezoelectric characteristics of the MWCNT/PVDF film sensor. This limits the frequency bands of the strain sensor to either piezoresistive or piezoelectric ranges. In this study, a novel weighted fusion technique, called piezoresistive/piezoelectric fusion (PPF), is proposed to combine both piezoresistive and piezoelectric characteristics to capture wide frequency bands of strain measurements in real time. This fuzzy logic (FL) based method combines the salient features (i.e. piezoresistive and piezoelectric) of the nanocomposite sensor via reasonably accurate models to extend the frequency range over a wider band. The FL determines the weight of each signal based on the error between the estimate and actual measurements. These weights indicate the contribution of each signal to the final fused measurement. The fuzzy inference system (FIS) was developed using both optimization and data clustering techniques. In addition, type-2 FIS was utilized to overcome the model's uncertainty limitations. The developed PPF methods were verified with experimental data at different dynamic frequencies that were obtained from existing literature. The fused measurements of the MWCNT/PVDF were found to correlate very well with the actual strain and a high degree of accuracy was achieved by the subtractive clustering PPF's FISs algorithm.