Reliability evaluation method and system for the ventilation door cylinder based on Bayes Monte Carlo simulation

Area of Science:

• Mining Engineering
• Reliability Engineering
• Statistical Modeling

Background:

• Automatic ventilation doors are vital for mine safety and ventilation stability.
• Cylinder monitoring is often inadequate, risking operational reliability.
• Proactive maintenance is needed to prevent failures in critical mining components.

Purpose of the Study:

• To develop a Weibull life prediction method for anticipating cylinder reliability changes.
• To integrate Bayesian inference and Monte Carlo simulation for accurate life prediction.
• To establish a reliability evaluation system for mine emergency control equipment.

Main Methods:

• Applied Bayesian methodology and accelerated life testing principles to analyze cylinder life characteristics.
• Utilized Monte Carlo simulation to estimate Weibull parameters under varying operational conditions.
• Derived posterior distribution functions for Weibull parameters with unknown shape and scale.

Main Results:

• The proposed method effectively predicts cylinder life using truncated small-sample data.
• Life characteristics were shown to correlate with environmental factors like temperature.
• Demonstrated applicability in life assessment for automatic ventilation doors.

Conclusions:

• The developed Weibull prediction method overcomes limitations of conventional approaches for reliability analysis.
• A real-time reliability evaluation system for mine emergency control equipment was successfully developed.
• The findings support enhanced maintenance and management practices in mining operations.