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The purpose of this paper is to employ the acoustic wave propagation method for leakage detection in pipes. The first objective is to use acoustic finite element analysis (AFEA) method to simulate acoustic wave propagation and acoustic wave reflectometry in an intact pipe and in pipes with leaks of various sizes. This is followed by the second objective which is to validate the effectiveness and the practicability of the acoustic wave method via experimental testing. The third objective involves the decomposition and de-noising of the measured acoustic waves using stationary wavelet transform (SWT). It is shown that this approach, which is used for the first time on leakage detection in pipes, can be used to identify, locate and estimate the size of a leakage defect in a pipe.

The research work was designed inline with best practices and acceptable standards. The research methodology focusses on five basic areas: literature review; experimental measurements; simulations; data analysis and writing-up of the study with clear-cut communication of the findings. The approach used was acoustic wave propagation-based method in conjunction with SWT for leakage detection in fluid-filled pipe.

First, the simulation of acoustic wave propagation and acoustic wave reflectometry in fluid-filled pipes with and without leakage have great potential in leakage detection in pipeline systems and can detect very small leaks of 1 mm diameter. Second, the measured noise-contaminated acoustic wave propagation in a fluid-filled pipe can be successfully de-noised using the SWT method in order to clearly identify and locate leakage as little as 5 mm diameter in a pipe. Third, AFEA of a fluid-filled pipe can be achieved with the simulation of only the fluid content of the pipe and without the inclusion of the pipe in the model. This eliminates contact interaction of the solid pipe walls and the fluid, and as a consequence reduces computational time and resources. Fourth, the relationship of the ratio of the leakage diameter to the ratio of the first and second secondary wave amplitudes caused by the leakage can be represented by a second-order polynomial function. Fifth, the identification of leakage in a pipe is intuitive from mere comparison of the acoustic waveforms of an intact pipe with that of a pipe with a leakage.

The research work is a novelty and was developed from the scratch. The AFEA of acoustic wave propagation and acoustic wave reflectometry in a static fluid-filled pipe, and the SWT method have been used for the first time to detect, locate and estimate the size of a leakage in a fluid-filled pipe.

Examines pollution risks in Ibadan′s (Nigeria) water distribution system. Attributes the observed reduction in water quality to urbanization pressure, age of piping, differences in pipe materials and distance from the treatment plant. The turbidity of some of the samples indicates the entry of foreign materials into the system and thus health hazards. Suggests some measures to ameliorate the situation.

Most residential building owners often report problems associated with the plumbing systems. If identified at the early stages, plumbing-related defects can be easily repaired. However, if unnoticed for a long period of time, they could lead to major damages and incur a significant cost to repair. Despite the problems, studies investigating plumbing anomalies and their root causes in residential buildings are limited. This study aims to explore plumbing defects and their potential causes, diagnosis methods and repair techniques in residential buildings.

This research used data collected through an extensive survey of both academic and grey literature. Through the content analysis, plumbing defects and the associated causes have been identified and presented in tabular format.

The study investigated the anomalies and causes in the residential plumbing system under five key sub-systems: water supply system; sanitary plumbing system; roof drainage system; heating, ventilation, air conditioning and gas system; and swimming pool. Accordingly, some of the identified plumbing defects include leakages, corrosion, water penetration, slow drainage and cracks. Damaged pipes, faulty equipment and installations are some of the common causes of the anomalies. Visual inspection, hydrostatic pressure test, thermography, high-tech pipe cameras, infrared cameras, leak noise correlators and leak loggers are techniques used for diagnosing anomalies. Reactive, preventive, predictive and reliability-centred maintenance strategies are identified to control or prevent anomalies.

The findings of this research can be used as a useful tool or guideline for contractors, plumbers, facilities managers and building surveyors to identify and rectify plumbing system-related defects in residential buildings.

Lubricating oil leakage is a common issue in thermal power plant operation sites, requiring prompt equipment maintenance. The real-time detection of leakage occurrences could avoid disruptive consequences caused by the lack of timely maintenance. Currently, inspection operations are mostly carried out manually, resulting in time-consuming processes prone to health and safety hazards. To overcome such issues, this paper proposes a machine vision-based inspection system aimed at automating the oil leakage detection for improving the maintenance procedures.

The approach aims at developing a novel modular-structured automatic inspection system. The image acquisition module collects digital images along a predefined inspection path using a dual-light (i.e. ultraviolet and blue light) illumination system, deploying the fluorescence of the lubricating oil while suppressing unwanted background noise. The image processing module is designed to detect the oil leakage within the digital images minimizing detection errors. A case study is reported to validate the industrial suitability of the proposed inspection system.

On-site experimental results demonstrate the capabilities to complete the automatic inspection procedures of the tested industrial equipment by achieving an oil leakage detection accuracy up to 99.13%.

The proposed inspection system can be adopted in industrial context to detect lubricant leakage ensuring the equipment and the operators safety.

The proposed inspection system adopts a computer vision approach, which deploys the combination of two separate sources of light, to boost the detection capabilities, enabling the application for a variety of particularly hard-to-inspect industrial contexts.

This paper discusses some important findings from a research project on the maintainability of wet areas of high‐rise non‐residential, buildings. The implications of six key factors of maintainability namely water‐tightness, spatial, integrity, ventilation, material and plumbing on the occurrence of 14 most common defects found in wet areas were evaluated. Problem areas evaluated include water leakage from ceiling, staining/discolouration, paint defects, cracking/spalling of concrete, cracking/debonding of tiles, fungi/algae growth, pipe leakage and corrosion. An industry wide survey was conducted and the factors including workmanship, design detailing, maintenance and material incompatibility under tropical conditions are identified and discussed.

The purpose of this paper is to predict the life of a corroding metallic structure in seawater so that uncertain and unpredictable failures of a structure, leading to accidents, can be prevented.

Pitting has been known to show a large scatter in the measurable parameters such as corrosion rate, maximum pit depth, time to perforation and so on. Scatter results from the influence on pit development on metal surface heterogeneity and from variations in the corrosive environment over time. All these facts suggest that randomness is an inherent and unavoidable characteristic of pitting corrosion over time, so that stochastic models have been developed to formulate pit depth as a function of parameters influencing the process. Since chloride penetrates the passive film of the metal surface, Cl ion distribution into the metal has been mapped by finite element method (FEM).

The maximum pit depth which decides the onset of perforation or leakage has been modeled by the following equation: d=36.31(ΔE)^0.68×(Δt)^0.35. Cl ion distribution within a pit and outside has been modeled for better understanding of pit initiation which till today is not fully understood.

Perforation and leakage of a tank, container, or pipeline occur when the depth of pitting reaches the section thickness of the material of which the metallic structures are made. The pitting corrosion is localized and occurs at any spot or site where electrochemical conditions (ΔE Equation (9)) are prone to pitting. This leads to unpredictable failures of the structures which may look polished and undamaged under naked eyes. In most metallic structures, pitting may be present at some spots, but failures occur only when the depth predicted by the model Equation (9) reaches the section thickness of the material. Thus, determining pipe to soil potential gives a guide to go for maintenance before pit depth reaches the material thickness, and thereby unpredictable failure can be prevented. Second, the map generated by FEM showing Cl distribution throws much information and light on movement of Cl ions from passive layer into the pit, which leads to its growth. This helps scientists and researchers to understand the mechanism and gives much insights on finding new methods for protection of structures.

The work will guide the engineers and researchers to prevent unpredictable failures of structures leading to accidents and human and property loss and prevent environment pollution from spilling of oil from tank and pipeline.

This is an original work based on several laboratory-generated simulated experimental data.

Proper risk management is a critical requirement for the success of every project. This is, to a large extent, due to the role risk plays in determining project outcomes. The mining sector usually is linked with high environmental, social and economic risks. Hence, the process of systematic risk management applied to a single case study of a tailings re-mining project in Ghana holds the potential for invaluable insights on risk management in the mining sector. The paper aims to discuss these issues.

Mining organization experts were asked to identify project risks, and 50 staff from the organization were invited to make subjective assessments of the probability of occurrence and consequences for each of 15 identified risks. From this assessment, a risk severity matrix was developed.

The findings show that the most severe risks for a tailings re-mining project include spillage caused by leakage from pipes; vandalism by illegal mining operators; late deliveries of mining materials; the effect of rainfall; and failure to gain project approval from the Environmental Protection Agency. Risk treatment options are suggested for these risks.

The study is limited to only the risk issues associated with tailings re-mining projects.

Practically, this study highlights for mining companies and operators, the critical risks factors that militate against successful tailings re-mining projects.

This study, essentially, reveals the threat of illegal mining operations to such an important project and hence the need for strong security to avoid such threats.

This study contributes to the debate on the risk factors that affect tailings re-mining, especially, from a developing country’s point of view.

The purpose of this paper is to explore the possibilities of improving the quality of existing maintenance task of the atomizer of milk powder manufacturing unit of a dairy plant. Looking to the past business volume and expected growth, the milk powder manufacturing unit forms a noticeable sector of processing plant. The lack of quality in maintenance standards leads to reliability losses of about 20–25% with low productivity and profit. Such facts and challenges of keeping the system in ready-state motivate a definite maintenance plan to be modeled based on a live failure analysis to be executed during shutdown or scheduled period.

The deliverables are achieved by collecting the historical failure data i.e. downtime and failure frequencies; from January 2020 to July 2020 at Dudhsagar dairy, Gujarat, India. Reliability modeling is done in a view to understand the failure pattern behavior of the milk powder manufacturing unit. The atomizer is discriminated as a critical component based on these data and their functional failures, failure causes, effects and repercussions of failures with existing control and maintenance practices has been modeled based on live shop-floor study. Scores are assigned on 1 to 10 levels by analyzing attributes effects from lowest to highest concern respectively for every modes of failure through realistic brain-storming among maintenance team by incorporating some advanced attributes like maintainability, economic safety, economic cost and spares with basic criteria in this study. The maintainability criticality index (MCI) is narrated by these score values through multi-attribute decision-making (MADM) based failure analysis models like Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS).

The primary findings of this research work are to propose improvements in the quality of the maintenance plan of critical component like; atomizer of a milk powder manufacturing unit which is commonly representing critical component in a major range of industrial processes. The case study recommended four silent maintenance strategies i.e. scheduled maintenance scheduled discard, scheduled failure finding and redesign as a qualified maintenance plan for the atomizer based on MCI and rankings of its potential failure causes. The results are helpful in upgrading quality standards for the maintenance activities of a process industry of alike or of dissimilar kinds in accordance with the failure analysis.

Originality mainly consists of investigating the scope of enhancing the existing maintenance practices through actual failure analysis with the help of TOPSIS. The criteria employed in this study are probability of chances of failure, degree of detectability and degree of severity as basic criteria along with some advanced criteria like; maintainability, spare parts, economic cost, economic safety are selected based on the outcome of shop-floor study and reliability modeling. The notable past failure statistics (downtime, frequency of failures) of a milk powder manufacturing unit were recorded and these data are analyzed based on reliability to extract an explicative component i.e. atomizer.

Reliability analysis is required to identify the components or subsystems with low reliability for a given designed performance. Life cycle cost analysis helps understand the cost implications over the entire life span of a product. The purpose of this paper is to present a case study describing reliability analysis and life cycle cost optimization of a band saw cutting machine manufactured and used in India.

The data required for reliability analysis is collected from the manufacturer and users of band saw cutting machine. The parameters of failure distribution have been estimated by using ReliaSoft’s Weibull++6 software. The life cycle cost is divided into various cost elements such as acquisition cost, operation cost, failure cost, support cost and net salvage value.

The results of the analysis show that the components such as band wheel bearing, guide roller bearing, limit switch, carbide pad, hydraulic cylinder oil seal, control panel dial, control panel and solenoid valve are critical from reliability and life cycle cost analysis perspective.

With certain design changes it is found that the reliability of the system is increased by 15.85 percent while the life cycle cost is reduced by 22.09 percent. The study also shows that the reliability analysis is useful for deciding maintenance intervals.

To introduce a new, low‐cost and easy‐to‐use leak detection system to help water utilities improve their effectiveness in locating leaks. The paper also presents an overview of leakage management strategies including acoustic and other leak detection techniques.

The design approach was based on the use personal computers as a platform and enhanced signal processing algorithms. This eliminated the need for a major component of the usual hardware of leak pinpointing correlators which reduced the system's cost; made it easy to use, and improved the effectiveness of locating leaks in all types of pipes.

Effectiveness of the new leak detection system for pinpointing leaks was demonstrated using real world examples. The system has promising potential for all water utilities, including small and medium‐sized ones and utilities in developing countries.

The leak detection system presented in the paper will help all water utilities, including small and medium‐sized ones and utilities in developing countries, to save water by dramatically improving their effectiveness in locating leaks in all types of pipes.

The paper presents information about a new effective system for locating leaks in water distribution pipes. Effective leak detection tools are needed by water utilities worldwide.