Improving Actuator Wearing Using Noise Filtering

Area of Science:

• Industrial Automation and Control Systems
• Mechanical Engineering and Tribology

Background:

• Actuator wear significantly contributes to industrial control system operational costs.
• Minimizing actuator movement is preferred by maintenance teams to reduce wear, but this can compromise control performance.
• Control engineers aim for active actuator operation to enhance disturbance rejection and trajectory following.

Purpose of the Study:

• To evaluate and quantify the impact of noise filtering on industrial control loop performance.
• To assess the effect of noise filtering strategies on actuator operational wear, specifically valve travel.
• To provide recommendations for control engineers on balancing control performance and actuator longevity through noise filtering parameter selection.

Main Methods:

• Analysis of industrial control system blockware within Distributed Control Systems (DCS) and Programmable Logic Controllers (PLC).
• Experimental evaluation and measurement of control loop performance metrics.
• Quantification of actuator (valve) travel as a proxy for operational wear.
• Correlation analysis between noise filtering time constant, loop performance indicators, and valve travel.

Main Results:

• Noise filtering has a measurable impact on both control loop performance and actuator wear.
• Specific filtering time constants can be identified to optimize the trade-off between control effectiveness and actuator longevity.
• The study establishes quantifiable relationships between filtering parameters, loop performance, and valve travel.

Conclusions:

• Properly designed sensor noise filtering is crucial for enhancing control loop performance while mitigating actuator wear.
• Control engineers can leverage these findings to select optimal noise filtering settings, leading to reduced operational costs and improved system reliability.
• The research provides practical guidance for implementing effective control strategies in industrial settings with limited algorithmic functionality.