Alireza Delavari

About a year ago, Jamshaid Mushtaq, Muhammad Najam Akbar Baig and I worked on a very common but crucial challenge in electronics design: creating a high-fidelity low-pass filter with stable gain and excellent noise suppression! The core problem we aimed to solve was designing an active low-pass filter that could significantly attenuate high-frequency components (specifically, anything at 10.5 kHz or more needed to be reduced by over 15 dB) while maintaining a positive passband gain of 20 dB, with a tight tolerance of just 3 dB deviation. Our desired passband was 700 Hz and below. Initially, we explored using a first-order filter, but our analysis quickly showed it wouldn't meet the demanding specifications. The roll-off of 20 dB per decade simply wasn't steep enough to achieve the required attenuation within the given frequency range, as it could only provide 23.52 dB of attenuation over 1.176 decades, far short of the required 35 dB (or 57 dB total from the passband to the stopband). This fundamental limitation of a first-order filter, highlighted by the asymptotic Bode magnitude plot, underscored the need for a more robust solution. So, we shifted our focus to a second-order filter design, which inherently offers a steeper 40 dB per decade slope, providing the necessary freedom to shape the gain characteristic as required. To achieve the desired positive gain while benefiting from the second-order characteristics, we opted for a cascaded approach using two first-order active low-pass filter circuits. This allowed us to leverage the simplicity of first-order stages while achieving the overall second-order performance. We carefully calculated the cut-off frequency, settling on 1400 Hz for both stages to ensure our target gain and attenuation were met at 700 Hz and 10.5 kHz, respectively. We then determined the individual gains for each cascaded stage (gain of 2 for one and 5 for the other, multiplying to our desired total of 10, equivalent to 20 dB) and subsequently selected appropriate resistor and capacitor values, using a 1µF capacitor as a starting point. The journey from problem statement to a working solution involved a lot of theoretical calculation, careful component selection, and then validating our design through simulations and practical testing. We utilized MATLAB for plotting the frequency response and transfer function analysis, which was crucial for verifying our theoretical calculations and visualizing the filter's behavior across different frequencies. This iterative process of design, simulation, and real-world validation is essential for ensuring a high-fidelity output. It's incredibly rewarding to see the theory, supported by powerful software tools, translate into a functional circuit that meets all the specified criteria!

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Real-Time Defect Detection in Extrusion 3D Printing! https://lnkd.in/g_7WK-dn In the latest work from Abdul Rahman Sani’s PhD project, we developed and demonstrated the real-time dual-camera defect monitoring system on a low-cost embedded platform for Fused Deposition Modeling (FDM)! This study enabled multi-angle detection of four common extrusion defect: stringing, spaghetti, under-extrusion, and over-extrusion; during live printing. The models were fine-tuned and optimized using Optuna for multi-objective performance (accuracy, localization, and speed), achieving over 50 FPS on Raspberry Pi 5B. Critically, this work links real-time camera inference to printer firmware, validating a closed-loop defect-response pipeline, a major step towards autonomous 3D/4D printing systems and AI-augmented additive manufacturing (AI2AM) aligned. Read more: https://lnkd.in/g_7WK-dn #3DPrinting #4DPrinting #FDM #AI2AM #RealTimeMonitoring #deakinuniversity Australian Research Council (ARC) #deakin #aiaugmented #additivemanufacturing #DefectDetection #ClosedLoopAM #SmartManufacturing #PhD 

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⚡ Optimizing Distributed Generation Placement with Python & DIgSILENT ⚡ Over the past six months, I have been working on an exciting project in collaboration with Dr. Seyed Amir Hosseini and Dr. Hamid Reza Abdolmohammadi, focusing on the optimal placement of small-scale generators for a regional electric company. We aimed to enhance power system efficiency by integrating Python, DIgSILENT, and advanced optimization techniques. 🔹 We developed a Windows-based application in Python to preprocess input data from Excel, ensuring smooth integration with DIgSILENT. 🔹 Time-series data for network loads and generation were processed and loaded into DIgSILENT, allowing us to conduct analyses based on real-world data. 🔹 We developed a new objective function to improve generator placement, using Python and DPL to implement and test it. 🔹 The optimization was carried out using a quasi-dynamic approach with the PSO algorithm, enhancing distributed generation placement strategies. This project has been a rewarding experience, merging power system engineering with software development to tackle real-world challenges in the energy sector. Image source: Salam, I. U., Yousif, M., Numan, M., Zeb, K., & Billah, M. (2023). Optimizing distributed generation placement and sizing in distribution systems: a multi-objective analysis of power losses, reliability, and operational constraints. Energies, 16(16), 5907. #PowerSystems #Optimization #Python #DIgSILENT #EnergyInnovation #ElectricityIndustry

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Day 36 :EMIR (Electromigration and IR Drop) Good morning, Linkedin Family!!! EMIR refers to the analysis and mitigation of Electromigration (EM) and IR Drop in integrated circuit (IC) design. Importance of EMIR 1. *Reliability*: EMIR analysis ensures IC reliability by identifying potential failure points. 2. *Performance*: EMIR analysis helps optimize power delivery and reduce voltage drops. 3. *Yield*: EMIR analysis improves manufacturing yield by reducing defects. Electromigration (EM) 1. *Definition*: EM is the movement of metal atoms in interconnects due to high current density. 2. *Impact*: EM can cause wire degradation, increased resistance, and eventual failure. IR Drop 1. *Definition*: IR Drop is the voltage drop across the power grid due to resistance. 2. *Impact*: IR Drop can cause performance degradation, timing issues, and functional failures. Let's Connect! Sharing insights on EMIR and IC design reliability. #EMIR #Electromigration #IRDrop #ICDesign #Reliability #Performance

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🚀 Student Innovation in Action! We are proud to share a recent student-led project from the Robotic Research Laboratory at Shahid Chamran University of Ahvaz – the Mobile Intelligent Solar Power Robot! 🌱🔋 This innovative robot is designed to intelligently track sunlight and operate autonomously using solar energy, combining sustainability with mobility. It’s a great step toward smart, eco-friendly robotic systems. The demonstration showcases the robot in action, highlighting its solar-tracking capability and mobile intelligence. A true testament to the creativity and technical skill of our students. This work continues to push the boundaries of what’s possible in robotics and renewable energy! #Robotics #SolarEnergy #Innovation #ShahidChamranUniversity #StudentProject #IntelligentSystems #STEM #CleanTech #Demo

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My vision for the Department of Mechatronics Engineering at the Federal University of Technology Owerri (FUTO) is to establish it as a world-class center for high-impact research, particularly in Unmanned Aerial Vehicles (UAVs), advanced robotics, and Additive Manufacturing. To achieve this, we are strategically developing specialized laboratory environments from our existing three facilities, creating focused hubs for innovation. A testament to our team's capability is the recent success in our robotics lab, supported by Scuttle Robotics (Texas). When a key component (Raspberry Pi) on a donated mobile robot required re-integration, our staff and students collaboratively engineered a solution, successfully restoring its functionality. This experience underscores the value of our partnership with Scuttle Robotics, which has significantly boosted motivation and practical engagement within the department. In our drone laboratory, we are advancing rapidly. Having mastered assembly, our focus has shifted to sophisticated research employing machine learning and machine vision for complex tasks like image recognition, specifically targeting subsurface mineral exploration. We are now actively seeking funding and partnerships to further expand our research capabilities in advanced image recognition and surveillance applications, aiming to position this lab at the forefront of UAV technology.

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At our UR place at #Collaborate, visitors could play the UR Gesture game which I had the opportunity to create with UR AI Accelerator ! 🙌🏼 🤖 It was a lot of fun. The task was to take a pack of mints, but you had to control the arm using gestures! ✋🏼 Left hand open - you are in translation mode. ✊🏼 Left hand closed - you are in rotation mode. 👆🏼 👉🏼 Right hand to indicate directions. 🤚🏼 ✋🏼 Both hands open - gripper will open ✊🏼 ✊🏼 Both hands closed - gripper will close Sounds simple, right? 😉 So now let's have some other approach. This application may seem to have nothing to do with industry, but that was the premise for this event. Is that completely true ? ✅ 60 fps image capturing with 1920x1080 resolution from both cameras (gesture and the POV one) ✅ Real time image processing for gesture camera - apply a hand landmarks to every frame and get the coordinates for each of them - 21 landmarks for one hand = 42 landmarks for both --> getting coordinates of 42 points on every frame in real time ✅ Gesture recognition based on math calculated from 42 points and their coordinates on every frame in real time ✅ Control the robot motion with frequency of 200Hz to get the smooth movement and fast reaction for gesture change Everything works in real time and is synchronized with each other—yet everything runs smoothly and does not cause any abnormal movements. Can you already see the industrial part of this application? I'm curious! 😊 If you haven't had the opportunity to play yet, it will definitely appear somewhere in the future! 

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Excited to share that our latest research has been published in Early Access by IEEE Robotics and Automation Letters (RA-L), one of the top journals in robotics. Title: Autonomous Drone-Ground Robot Alignment Through Ground Robot Visual Servo Control With Drone Detection and Tilt Correction This work addresses the critical challenge of retrieving ground robots from hazardous environments using drones. Precise alignment is key—but GPS drift, wind, and terrain irregularities make it difficult. We developed a visual servoing method combining YOLOv8-based drone detection and tilt correction to ensure accurate alignment. Field experiments confirmed the system's effectiveness with a maximum alignment error of just 20.3 cm—below the safety threshold. Proud to contribute to advancing autonomous systems and field robotics. Grateful for the support from everyone involved. Read the paper (Early Access): https://lnkd.in/gAZJsKNR #IEEE #RALetters #Robotics #Drones #VisualServoing #ComputerVision #YOLOv8 #AutonomousSystems #FieldRobotics #ResearchInnovation

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