Characterization of the iPhone LiDAR-Based Sensing System for Vibration Measurement and Modal Analysis

Area of Science:

• Engineering
• Physics
• Computer Science

Background:

• Portable depth sensing technology, utilizing time-of-flight LiDAR, is integrated into modern mobile devices like the iPhone 13 Pro.
• LiDAR sensors offer non-contact measurement capabilities, making them attractive for various sensing applications.

Purpose of the Study:

• To characterize the performance of mobile LiDAR systems for full-field vibration measurement in modal analysis.
• To evaluate the sensor's limitations and quality concerning noise, frequency response, and operational range.
• To investigate the impact of environmental factors like phone-to-target distance and lighting conditions on measurement accuracy.

Main Methods:

• A vibrating target was used to test the LiDAR sensor against a laser displacement transducer.
• Experiments were conducted varying phone-to-target distances and lighting conditions.
• Depth map data was processed using Stochastic Subspace Identification (SSI) for modal parameter identification.

Main Results:

• The optimal phone-to-target distance was found to be between 0.30 m and 2.00 m.
• The actual LiDAR depth map sampling rate was confirmed to be 15 Hz, not the indicated 60 Hz framerate.
• Despite noise, natural frequencies were identified with an average error of 1.9% compared to the reference transducer, and mode shapes with uncertainty were obtained.

Conclusions:

• Mobile LiDAR is a viable tool for modal identification when combined with prior knowledge of the structural system.
• The 15 Hz sampling rate necessitates downsampling for accurate vibration analysis.
• The technology holds significant potential for structural health monitoring and diagnostics in accessible and challenging scenarios.