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Procedure to Evaluate the Efficiency of Flocculants for the Removal of Dispersed Particles from Plant Extracts

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Waste drilling fluid flocculation identification method based on improved YOLOv8n.

Min Wan¹, Xin Yang², Huaibang Zhang¹

¹School of Mechanical Engineering, Southwest Petroleum University, Chengdu, Sichuan 610500, China.

The Review of Scientific Instruments

|January 8, 2025

Summary

This study introduces an enhanced YOLOv8n algorithm for real-time monitoring of drilling fluid flocculation. The improved model achieves high accuracy and efficiency, making it suitable for field deployment.

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Area of Science:

* Drilling Engineering
* Artificial Intelligence
* Material Science

Background:

* Accurate identification of drilling fluid flocculation is crucial for efficient waste management.
* Existing methods face challenges in real-time field monitoring due to complexity and computational demands.

Purpose of the Study:

* To develop an optimized You Only Look Once version 8 nano-algorithm (YOLOv8n) for real-time drilling fluid flocculation detection.
* To enhance detection speed, reduce computational load, and improve accuracy under field conditions.

Main Methods:

* Utilized MobileNetV3 as the backbone network for reduced memory and improved processing speed.
* Integrated an efficient multi-scale attention mechanism within the cross-stage partial fusion module to preserve image details.
* Employed the wise intersection over union loss function to accelerate convergence and enhance bounding box accuracy.

Main Results:

* The enhanced YOLOv8n algorithm achieved an average recognition accuracy of 98.6%, a 4.8% improvement over the original model.
* Model size was reduced to 2.9 MB, and parameter count to 2.8 GFLOPS, significantly smaller than the original.
* Demonstrated effective prediction of flocculation state changes across diverse working conditions.

Conclusions:

* The proposed algorithm offers a highly deployable solution for real-time monitoring of drilling fluid flocculation.
* The optimizations ensure high accuracy and efficiency, addressing previous limitations in field applications.