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High-Fidelity Modeling of Laser Levels via Pulse-Window Software Lock-In PSD Sensing.

Shudong Zhuang¹, Jiale Sun¹, Rugao He²

¹College of Mechanical and Electrical Engineering, Hohai University, Changzhou 213251, China.

Sensors (Basel, Switzerland)

|February 27, 2026

Summary

This summary is machine-generated.

This study introduces a novel Pulse-Window Software Lock-in (PWSL) method to accurately measure dynamic parameters like natural frequency and damping ratio in self-leveling mechanisms. The approach successfully identified unmodeled friction, enhancing precision instrument design.

Keywords:

PSD sensing dynamic identification high-fidelity modeling laser level software lock-in detection

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Area of Science:

Mechanical Engineering
Vibration Analysis
Precision Instrumentation

Background:

Accurate dynamic parameters (natural frequency, damping ratio) are crucial for self-leveling mechanisms.
Traditional Finite Element Analysis (FEA) struggles with micro-friction, and contact methods cause interference.
Existing methods lack the precision needed for advanced applications.

Purpose of the Study:

To develop an integrated framework for precise identification of dynamic parameters in laser level self-leveling mechanisms.
To overcome limitations of traditional FEA and contact measurement techniques.
To enable refined design of precision pendulum instruments through accurate modeling.

Main Methods:

Integration of Pulse-Window Software Lock-in (PWSL) sensing with data-driven model updating.
Development of a non-contact Position Sensitive Detector (PSD) system.
Utilizing a custom PWSL algorithm with a 10 kHz laser carrier for high-fidelity signal extraction and noise suppression.

Main Results:

Experimental natural frequency (2.861 Hz) showed a 4.22% error compared to simulation (2.987 Hz).
Measured damping ratio (0.1435) exceeded simulation (0.1255) by 14.34%, indicating unmodeled friction.
FEA model updating with an equivalent friction coefficient reduced damping prediction error to 0.97%.

Conclusions:

The PWSL method accurately captures dynamic parameters, revealing unmodeled energy dissipation.
Data-driven model updating effectively refines FEA models by incorporating friction.
This integrated framework provides a reliable basis for designing high-performance precision instruments.