MA/PA: Development and Optimization of Magnet-Based Whisker Sensors for Surface Structure Identification

Project Description:

This project aims to conduct a Comprehensive Study of Whisker-Based Sensor Development. The goal is to design, analyze, and fabricate a novel whisker-based sensor utilizing magnet-based detection technology for surface structure identification applications. The sensor will be developed using a combination of flexible and Magnetostrictive materials to achieve both flexibility and sensing capabilities. The project will involve designing and constructing a performance test measurement apparatus to evaluate various parameters such as frequency response, response speed, linearity, hysteresis, resolution, repeatability, durability/drift, and measurement range. Optimization efforts will focus on enhancing the sensor's frequency response and directional sensitivity to mitigate environmental noise. Furthermore, simulation techniques will be employed to optimize the whisker's geometry using finite element analysis (FEM) to enhance sensitivity levels. In the second phase of the project, a sensor array configuration will be explored, including circular and rotational arrangements, to improve precision and depth perception in surface structure detection.

In the third phase of the project, we propose integrating machine learning techniques to enhance the surface structure identification capabilities of the whisker-based sensor array. This phase aims to develop algorithms that can efficiently analyze sensor data to detect and classify patterns on surfaces. After completing the project, we aim to utilize this type of sensor for robotic applications such as grass detection, underwater robot localization, and wind turbine blade inspection.

Tasks and Duties:

o   Design and fabrication of magnet-based whisker sensors

·       Consider two approaches with bending and deflection strategy

·       Consider the material elasticity, diameter, and type (ABS, nylon, acrylic, Carbon fiber, and also Magnetostrictive materials like Terfenol-D, Galfenol, and Metglas).

·       Consider the shape of the whisker (wire, cantilever, with, length, thickness)

o   Development of the performance test measurement apparatus

·       Assessment of frequency response, response speed (delay), linearity, hysteresis, resolution, repeatability, and measurement range.

·       Assess the effect of environmental conditions/noise on the sensor e.g. wind/unsmooth surface)

o   Optimization of sensor performance

·       Directional sensitivity for windy noisy environment

·       Optimization using FEM (Frequency, geometrical parameters such as length, with, thickness, …)

o   Exploration of sensor array configurations

·       Design a circular and rotational arrangement, to improve precision and depth perception in surface structure detection.

·       Consider different strategies in the design of the array for working on unsmooth surfaces for detecting scratches/ roughness/texture

o   Applying Machine learning algorithm for pattern detection

·       Detecting the length, angle, deep of the scratch

·       Detecting the texture of the surface

·       Reconstruct an image from the scanned surface

Requirements:

o   Background in sensor technology, and materials science.

o   Proficiency in CAD software for test apparatus fabrication

o   Familiar with simulation tools for finite element analysis.

o   Interest in performance characterization and signal processing.

o   Background in machine learning algorithms for pattern detection purposes

o   Proficiency in coding (e.g. MATLAB)

o   Strong analytical and problem-solving skills

o   Effective communication skills for documenting and presenting research findings.

Contact Person: Dr. Mohammad Sadeghi (mohammad.sadeghi@tuhh.de)

Desired starting date: As Soon As possible