[Research on the Source Identification of Mine Water Inrush Based on LIF Technology and SIMCA Algorithm]

Area of Science:

• Geochemistry
• Analytical Chemistry
• Spectroscopy

Context:

• Mine water inrush poses significant hazards, necessitating rapid source identification for effective early warning and prevention.
• Traditional chemical analysis methods for identifying water inrush sources are time-consuming, limiting their utility in emergency situations.
• Developing rapid, accurate methods is crucial for mitigating risks associated with coal mine water disasters.

Purpose:

• To introduce a novel method for rapid mine water inrush source identification.
• To leverage laser-induced fluorescence (LIF) technology and soft independent modeling of class analogy (SIMCA) for real-time water sample analysis.
• To overcome the limitations of traditional, slow chemical identification methods.

Summary:

• A method combining laser-induced fluorescence (LIF) and soft independent modeling of class analogy (SIMCA) was developed for rapid mine water inrush source identification.
• Experiments involved analyzing fluorescence spectrums of five types of water inrush samples using a 405 nm laser, followed by preprocessing and classification with SIMCA based on PCA models.
• The study achieved 100% accuracy in predicting and testing sets, demonstrating the effectiveness of LIF and SIMCA for distinguishing different water sources.

Impact:

• Enables near-instantaneous identification of mine water sources, significantly improving early warning systems for water hazards.
• Provides a fast and sensitive alternative to traditional chemical analysis, crucial for post-disaster relief operations.
• Enhances mine safety by allowing for quicker and more informed decision-making during water inrush events.