Fuzzy control algorithm of cleaning parameters of street sweeper based on road garbage volume grading
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View abstract on PubMed
Summary
This summary is machine-generated.This study introduces an intelligent fuzzy control algorithm for street sweepers, optimizing cleaning settings based on road garbage volume. The system achieves significant energy savings, improving urban cleaning efficiency.
Area Of Science
- Environmental Engineering
- Robotics and Intelligent Systems
- Artificial Intelligence
Background
- Street sweepers face challenges in adapting cleaning parameters to variable road garbage levels, leading to inefficient operations and high energy use.
- Current systems lack the intelligence to dynamically adjust cleaning settings, impacting urban cleanliness and resource management.
Purpose Of The Study
- To develop and evaluate a fuzzy control algorithm for adaptive street sweeper cleaning parameter adjustment.
- To enhance the intelligence and energy efficiency of urban street cleaning operations.
Main Methods
- Utilized the YOLO (You Only Look Once) v5 deep learning model for real-time garbage detection and classification on road surfaces.
- Developed a fuzzy control model using garbage volume grading coefficients and sweeper speed to optimize disc brush and fan speeds.
- Integrated garbage coverage and weight data to calculate road garbage volume grading coefficients.
Main Results
- The proposed fuzzy control algorithm demonstrated adaptive control of street sweeper cleaning parameters.
- Achieved a 29.77% energy saving compared to conventional gear control under identical road garbage conditions.
- Successfully enhanced the operational intelligence of street sweepers through dynamic parameter adjustment.
Conclusions
- The fuzzy control algorithm effectively addresses the limitations of traditional street sweeper control systems.
- The intelligent system offers a viable solution for improving energy efficiency and cleaning performance in urban environments.
- This research paves the way for smarter, more sustainable urban maintenance technologies.
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