Search

Wave height is a critical consideration in the planning and execution of maritime projects. Wave height forecasting methods include numerical and machine learning (ML) techniques. The traditional process involves using numerical wave prediction models, which are very successful but are highly complex as they require adequate information on nonlinear wind–wave and wave–wave interactions, such as the wave energy-balance equation. In contrast, ML techniques can predict wave height without prior knowledge of the above-mentioned complex interactions. This research aims to predict wave height using micro-electromechanical systems (MEMS), internet of things (IoTs), and ML-based approaches. A floating buoy is developed using a MEMS inertial measurement unit and an IoT microcontroller. An experiment is conducted in which the developed buoy is subjected to different wave heights in real time. The changes in three-axis acceleration and three-axis gyroscope signals are acquired by a computer via IoT. These signals are analyzed using ML-based classification models to accurately predict wave height. The obtained validation accuracy of the ML models K-NN (K-nearest neighbor), support vector machine, and the bagged tree is 0.9906, 0.9368, and 0.9887 respectively, which indicates that MEMS and IoT can be used to accurately classify and predict wave heights in real-time.

A novel algorithm which is an ensemble of two metaphor-less algorithms is presented in this paper. The algorithm is inspired by Rao-1 and Jaya algorithms. Since the algorithm always plays around with the best and worst solutions; the algorithm is named as Best-Worst-Play (BWP) algorithm. The algorithm does not require any algorithm specific parameters, however, algorithm control parameters are required. To test the effectiveness and performance of the proposed algorithm, a number of unconstrained and constrained benchmark functions are considered. It is found that proposed algorithm has outperformed several well-established metaphor based algorithms. The proposed BWP algorithm may be used by researchers to solve the unconstrained and constrained optimization problems

In this paper, stress and eigen frequencies are analyzed through prediction of microcantilever model using design of experiment approach. The important factors affecting displacement sensitivity, stress and eigen frequencies were identified such as geometrical dimensions of microcantilever (length, breadth and thickness), modulus of elasticity of materials, applied force. Based on the selection of factors and levels, experiments were designed using L9 orthogonal array. The designed experiments were simulated with finite element method in COMSOL Multiphysics software. Further, optimum values of dimensions of microcantilever and material property are used for stress and eigen frequencies analysis. The evaluated frequencies under eigen frequency analysis revealed that designed and simulated Gallium Arsenide (GaAs) microcantilever is prone to vibrate at these frequencies, whereas stress analysis illustrates the response of structure and material properties towards reliability.

The purpose of this paper is design, virtual fabrication and simulation of microcantilever based Force sensor using Comsol Multiphysics Software version 5.3a to perform analytical analysis of MEMS/NEMS based sensor for microbotic applications.Piezoresistive MEMS Force sensor having dimension of fixed part is 1000 µm 2 with height of 50µm and movable part is 600 µm length, 500µm breadth and 20 µm height.The analysis of force sensor is observed by plotting a curve between force and voltage, Displacement and Voltage and Sensitivity. The range of force measured by this sensor is from 10N to 1µN, the simulating result shows that a very wide range of force can be measured by this single sensor. The force measurement at microscale has been very common in microbotics for micromanipulation . The simulated MEMS force sensor having resolution 0.1µN using piezoresistive sensing which is improved then the previous work. This range of force, resolution and sensitivity can be used for the application of two –fingered microgripper in microbotic system.Mathematically, dynamic frequency range for microcatilever based force sensor is calculated in range of 1.477076 KHz to 467.935969KHz, along with its different frequency harmonics for force 10N-100µN.Here, microcatilever is used for the measurement of force by using piezoresistors which are arranged in voltage divider sensing technique to obtain higher resolution, sensitivity and wide and lower range of force.

The purpose of this paper is comparative study, design and simulation of two stage, analog to digital convertor to convert the properly conditioned stepwise linearized analog output signal from a ratio metric NTC thermistor circuit. The design part consists of linearization of thermistor temperature- resistance characteristics in analog domain. A CMOS sample and hold circuit is used to bridge linearizing circuit in analog domain and the flash ADC circuit in digital domain. Ratio of the voltage is sensed rather than absolute voltage across the thermistor, as part of linearization. Further linearization is done in two stage flash ADC consisting of a reference voltage divider resistance, comparators, analog multiplexers and 8bit differential ADC. A graph is plotted between temperature and the corresponding resistance of NTC thermistor NTCLE100E10 [1], having a resistance of 10kΩ at 25°C. The graph is an exponential curve and it is linearized [2] around 50°C by drawing a curve between temperature and voltage ratio across a resistor connected in series to the thermistor. This curve is still nonlinear at extreme values of the considered range -20 °C to 100 °C. The full range is divided into four sub ranges and piecewise linearization is done simultaneously with analog to digital conversion. Analog and digital integrated circuits are generally low powered and the voltage limit is 5V. Thermistor is compatible in this range. A number of signal conditioning circuits are devised in the past. Here the linearizing steps involved in simple circuit elements and simple design. Signal conditioning of thermistor response has a number of design circuits already devised, still there is room for research to make it is small in size, low powered, high sensitivity and cost effective.

The paper deals with the application of vibration in tillage operations. Nowadays implements which can reduce draft and power consumption of tractor is the main area of concern to scientists and engineers. Vibratory tillage is one such concept in which there are many advantages over passive equipments. Thus a review based study has been made to identify the advantages that exist in active vibratory tillage equipment as compared to rigid tools.