Electrical Engineering Colloquium 

Speaker: Prof. Nadav Levanon

Title: Non-coherent pulse compression for RADAR and LIDAR

Abstract 

Pulse compression is a major tool in radar, found in almost any modern coherent radar. Adaptation to non-coherent systems was described some 15 years ago. It turned out to be useful in direct detection laser radars (LIDAR) and non-radar applications. Appropriate emitted signals and mismatched processing on receive, and the resulted excellent performances, will be described.

Light refreshments will be served before the lecture

This colloquium is not counted toward seminar credit.

ההרצאה לא מזכה בקרדיט שמיעת סמינרים.

School of Mechanical Engineering Seminar
Monday April 17.4.2023 at 14:00

Wolfson Building of Mechanical Engineering, Room 206

Microelectromechanical (MEMS) Quartz Resonators fabricated by Laser Induced Chemical Etching

Neta Melech

M.Sc. student under the supervision of Prof. Slava Krylov and Dr. Marina Sirota (IAI).

Microelectromechanical systems (MEMS) resonators are indispensable components in numerous  engineering applications, serving as timing or signal processing devices in electronic circuits or implemented in resonant sensors.  While most of these devices are traditionally fabricated from silicon,  use of quartz in high end  MEMS sensors is promising due to the unique advantageous features of crystalline quartz, mainly its piezoelectricity, excellent mechanical properties and high frequency thermal stability. Historically first, larger scale and not integrated, resonators were and still are fabricated from crystalline quartz. However,  conventional quartz processing methods such as traditional machining or wet etching combined with photolithography prevent further downscaling on the devices and their integrability, limit design flexibility and achievable geometric complexity. Moreover, these methods are less suitable for prototyping at the early development stages. Recent advances in laser technologies and specifically of the Femtosecond Laser Induced Chemical Etching (FLICE) open new interesting possibilities for quartz processing.

In the present work we explore a feasibility to implement the FLICE technology for fabrication of fully functional crystalline quartz MEMS resonators.  We studied experimentally and numerically, by means of the finite elements models, the influence of the devices geometry, electrodes routing, clamping and operational conditions on the resonators performance. The devices of several configurations, which included single beams and double ended tuning forks with lengths between 3 mm and up to 5mm and widths of up to 90 μm, were successfully fabricated.  First, Cr/Au layers serving as a hard mask were sputtered on both sides of the 100 µm thick Z-cut quartz wafer and patterned using laser. Laser processing of the exposed quartz regions was then used to accelerate the selective wet etching of the substrate. Since the essentially mask less process does not involve lithography, the fabrication cycle is short it is especially suited for fast prototyping. The devices vibrations were excited in air and vacuum using piezoelectric actuation and a custom built setup, the responses were registered be means of laser Doppler vibrometry.  Fundamental resonance frequencies within the range between 70 kHz and up to 90 kHz and amplitudes up to 0.5 mm were consistent with the model predictions. Quality factors up to Q  ≈ 700 were detected.

Join Zoom Meeting

https://tau-ac-il.zoom.us/j/86497933118

School of Mechanical Engineering Seminar
Monday April 17.4.2023 at 14:00

Wolfson Building of Mechanical Engineering, Room 206

Xylella Diseases detection in orchards grown under nets using UAV-based images

Yasmin Mazor

 Msc student

Tel Aviv University, Institute of Agricultural Engineering, ARO

Supervisors: Dr. Victor Alchanati, Dr.Avishai Sintov

Almond trees are infected by the bacterium Xylella fastidious and the pathogen is vectored by xylem-

feeding sharpshooters and spittlebugs. Currently, no effective management techniques prevent trees

from becoming infected. The Xylella bacterium is introduced into the tip tubes of the tree by a tip-

sucking insect. As a result, there is a disruption in the fluid passage, and eventually, the tree dies. The

almond leaf scorch disease (ALS) was first identified in Israel In 2016 in the almond groves in the north

of the country. The bacterium poses a significant threat to almonds and other crops in Israel, such as

vines, olives, deciduous trees, and citrus fruits. Symptomatic trees that did not die in the previous

season will grow asymptomatic leaves in the following season, but with entering the summer months

the symptoms of the disease will reappear.

Remote sensing is a type of geospatial technology that samples emitted and reflected

electromagnetic (EM) radiation from the Earth’s terrestrial, atmospheric, and aquatic ecosystems

aiming to detect and monitor the area component without any physical contact. The data is collected

by aircraft-based and satellite-based sensor technologies, either passive or active Passive sensors,

which are the sensors that are used in this research, respond to external stimuli, gathering radiation

that is reflected or emitted by an object or the surrounding space. Popular examples of passive

remote sensors include charge-coupled devices, film photography, radiometers, and infrared. Active

sensors use internal stimuli to collect data, emitting energy to scan objects and areas at which point a

sensor measures the energy reflected from the target.

The importance of using remote sensing can be manifested when collecting data from dangerous or

inaccessible areas, with growing relevance in modern society.

Another advantage is that collecting data with remote sensing tools provides fast and repetitive

coverage of extremely large areas for everyday applications.

Front-line remote sensing tools, coupled with artificial intelligence (AI) technologies, have a significant

role in crop monitoring and disease surveillance. Crop-type classification is an example of using

remote sensing to provide precise, timely, and cost-effective information at different spatial,

temporal, and spectral resolutions.

Today, expert agronomists detect the XF disease by scouting. Each orchard is large, e.g, Sde

Nehemiah Almond orchard is about 16 ha.

As a result of the large area it is very hard for the scout to reach optimal detection of the infected

trees, he can even miss infected trees and as a result, the Xylella pathogen will spread widely in the

orchards. The long-term goal of this research is to develop a system that detects and locates infected

trees in an orchard and directs the scout to that trees without any need to search each tree whether

it is infected or not.

The objective of this work was to develop machine learning and classification algorithms that detect

and locate almond trees infected by Xyllela, using images acquired by a UAV.

Join Zoom Meeting

https://tau-ac-il.zoom.us/j/86497933118

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