Steel Drum Leak Detection Signal Processing Based on Time-Frequency Domain (1)
Van Persie
Abstract
Steel drums are essential packaging containers in modern life, widely used in the storage, transportation, and application of various liquid and solid commodities in industries such as chemicals, petroleum, and paints. Their excellent corrosion resistance, high strength, safety, and reliability make them ideal for packaging products like food, industrial goods, and hazardous materials. Due to their widespread use, leakage has become a critical concern, especially in sectors like petrochemicals and dangerous goods. A leak not only causes economic loss but also poses serious safety risks.
Leak testing is one of the most important steps in the production and application of steel drums. Research into new leak detection methods plays a vital role in improving production efficiency and ensuring safe usage in daily life. With the rapid development of computer processing capabilities, steel drum leak detection has significantly advanced. This paper introduces a steel drum leak detection system using MATLAB’s time-frequency analysis method and GUI platform, combined with acoustic emission technology. The system can effectively analyze and detect leakage signals, demonstrating strong adaptability. Experimental results confirm the feasibility of using time-frequency analysis to extract characteristic parameters from leakage signals.
The study confirms that acoustic emission technology is a feasible method for detecting leaks in steel drums. It enhances production efficiency and improves safety in daily applications. Moreover, it opens up new possibilities for fault detection in other metal materials.
Keywords: steel drum leak detection, acoustic emission technology, time-frequency analysis, MATLAB GUI
Chapter One Introduction
1.1 Introduction
With the growth of the economy and improvements in living standards, environmental protection and sustainable development have become central topics globally. The packaging industry, closely tied to everyday life, has increasingly contributed to environmental pollution. Governments and organizations worldwide have invested significant resources to reduce the environmental impact of packaging. However, despite these efforts, the industry still faces challenges in addressing pollution and public health concerns.
Steel drums are crucial in packaging due to their durability, strength, and resistance to corrosion. They are widely used in the transport and storage of liquids and solids across multiple industries. Given their extensive use, leakage has become a major issue, particularly in sensitive areas like chemical and hazardous material handling. Leaks can lead to severe economic and safety consequences, and numerous incidents have highlighted the need for more effective detection methods. In the production and use of steel drums, leak detection is a critical process. Therefore, it is essential to address and improve this aspect.
1.2 Methods and Techniques for Leak Detection of Steel Drums
In developed countries, the detection of leaks in metal containers, including steel drums, is highly regulated and technologically advanced. As a result, manufacturers must stay updated with the latest detection technologies to ensure quality and compliance. While China's steel drum manufacturing has made progress, its leak detection technology lags behind global standards. Many companies still rely on outdated methods from the 1950s and 1960s, which are insufficient for modern demands. Leakage from steel drums has long caused environmental damage and economic losses, making it imperative to adopt advanced detection systems.
Traditional leak detection methods, such as bubble testing, involve applying soapy water or submerging drums in water to check for air bubbles. Although this method identifies small leaks and their locations, it cannot measure the leakage rate and is labor-intensive. Additionally, it leaves residues on the drum surface, requiring further cleaning before the next production stage, which can affect coating quality or cause rusting.
Some automated production lines in China now use foreign-standard leak detection systems, but they often fail to deliver expected results. Modern techniques include pressure decay, vacuum attenuation, helium gas detection, and pressure sensor-based methods. These technologies offer higher accuracy and efficiency without damaging the drum itself. However, many Chinese companies focus on production equipment rather than detection technology, leading to a gap in overall quality and safety.
To improve the steel drum industry, companies should invest in both advanced production and detection technologies. Relevant authorities and manufacturers should prioritize the adoption of foreign leak detection innovations to enhance safety and competitiveness.
1.3 Content and Significance of the Research in This Paper
1.3.1 Research Content
This paper focuses on analyzing and processing acoustic emission signals from steel drums to extract key characteristics. It explores how internal activities of leakage sources generate unique acoustic signatures. Using digital signal processing techniques, the research aims to identify and extract relevant features from leakage signals. Key aspects include:
1. Introducing the mechanism of leakage acoustic emission signals and their processing methods.
2. Applying FIR bandpass filters to effectively reduce noise in acoustic emission signals.
3. Using time-frequency domain analysis to extract RMS and ASL values in the time domain, and employing power spectrum estimation, FFT, Hilbert transform, and time-frequency distribution for frequency domain analysis.
4. Designing a leak detection system using MATLAB’s GUI to analyze acoustic emission signals.
1.3.2 Significance of the Study
Acoustic emission technology evaluates the activity of a leakage source by analyzing collected signals. The information from these signals provides critical insights into the nature of the leak. By analyzing and processing acoustic emission signals, we can extract meaningful parameters that differ from traditional methods. This makes acoustic emission a promising tool for monitoring equipment conditions and triggering alarms. However, the complexity and susceptibility to external interference limit its practical application.
This paper addresses these limitations by analyzing the time and frequency domains of acoustic emission signals and extracting key parameters. This approach helps improve the reliability and effectiveness of leak detection.
[1] Yang Wenliang. Steel Drum and Environment [J]. China Packaging News, 2001 (04): 1-5.
[2] Yang Wenliang. China's Steel Barrel Market [J]. Shanghai Packaging News, 2003 (05): 1-3.
[3] Yang Wenliang. Development of Leak Detection Technology for Metal Containers [J]. China Packaging News, 2008 (05): 1-3.
[4] Yang Wenliang. Leak Detection Technology for Metal Containers [J]. Enterprise Technology and Development, 2008 (03): 51-52.
Related Links
Steel Drum Leak Detection Signal Processing Based on Time-Frequency Domain (1)
Steel Drum Leak Detection Signal Processing Based on Time-Frequency Domain (2)
Steel Drum Leak Detection Signal Processing Based on Time-Frequency Domain (3)
Steel Drum Leak Detection Signal Processing Based on Time-Frequency Domain (4)
Steel Drum Leak Detection Signal Processing Based on Time-Frequency Domain (5)
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