Static and Dynamic Inclinometers for Industrial Applications
Learn how to create innovative solutions with high accuracy industrial-grade MEMS motion sensors
This webinar was broadcast on Thursday, August 5th, 2021
In this 1-hour webinar we will explore the implementation of inclination-sensing solutions using a highly accurate 2-axis, low-power industrial inclinometer and a high-performance 6-axis inertial module, in conjunction with available motion software libraries.
Applications include Industry 4.0, from robotics and earth-moving machinery to 5G antennas and solar panel pointing applications, and Smart City scenarios such as structural health monitoring in bridges and tunnels.
In this discussion, the IIS2ICLX with the MotionTL2 library will be used as a static inclinometer, which enables the highest accuracy in systems where the equipment being monitored is stationary or moving very slowly. The ISM330DHCX 6-axis iNEMO® inertial module features a 3D accelerometer and 3D gyroscope and uses a smart algorithm in MotionDI to combine signals from these sensors to eliminate the effects of rapid motion, vibration, or shock on the equipment, making it ideal for dynamic inclinometer applications.
Both sensors are equipped with machine learning capabilities and can implement algorithms in the sensor ASIC, alleviating the workload on the main MCU and enabling the lowest possible power consumption.
You will learn:
- How to select the right sensor for your application
- The principal parameters affecting accuracy
- ST tools for rapid development and evaluation
- About the Machine Learning Core (MLC) feature
|Jay Esfandyari |
Jay has more than 20 years of industry experience in semiconductor technology, integrated circuit fabrication processes, MEMS & sensors design and development, sensor networking, product marketing, business development and product strategy. Jay holds a master's degree and a Ph.D. in Electrical Engineering from the University of Technology of Vienna, Austria. He has more than 75 publications and conference contributions. Jay is currently the Product Marketing Manager at STMicroelectronics, located in Dallas, Texas.
|Tom Bocchino |
Tom is a Product Marketing Engineer at STMicroelectronics with broad experience in IoT platforms for the industrial, consumer and automotive industries. He joined ST after a decade as a development engineer at IBM in Boca Raton and Austin, Texas. Tom’s experience as a former designer and system engineer helps to bridge the gap between conceptual ideas and purposeful silicon based products. Most recently he has been supporting the wave of new customers and applications for ST sensors, enabled by MEMS technology.
|Chris Kim |
Chris is an Application Engineer for the MEMS & Sensors Application Support Team based in Schaumburg, IL. He is focused on providing support for sensor solutions in industrial applications. Chris received his B.S. in Electrical Engineering at the University of Illinois at Urbana-Champaign and is currently pursuing an M.S. in Computer Science degree at Georgia Institute of Technology with specialization in Machine Learning.