Monitoring of compressed air losses in branched air flow networks of mining enterprises

Compressed air as a type of safe technological energy carrier is widely used in many industries. In economically developed countries energy costs for the production and distribution of compressed air reach 10 % of the total energy costs. The analysis of compressed air production and distribution systems in the industrial sector shows that the efficiency of the systems is at a relatively low level. This is due to the fact that insufficient attention is paid to these systems since the compressed air systems energy monitoring has certain difficulties – the presence of complex and branched air pipeline networks with unique characteristics; low sensitivity of the equipment which consumes compressed air; the complexity of auditing pneumatic equipment that is in constant operation. The article analyzes the options for reducing the cost of production and compressed air distribution. One of the promising ways to reduce the compressed air distribution cost is timely detection and elimination of leaks that occur in the external air supply network of the enterprise. The task is solved by hardware-software monitoring of compressed air pressure at key points in the network. The proposed method allows real-time detecting of emerging air leaks in the air duct network and sending commands to maintenance personnel for their timely localization. This technique was tested in the industrial conditions of ALROSA enterprises on the air pipeline network of the Mir mine of the Mirninsky Mining and Processing Plant and showed satisfactory convergence of the calculated leakage values ​​with the actual ones. The practical significance of the obtained results is that the developed method for monitoring air leaks in the air duct network is simple, it requires an uncomplicated software implementation and allows to localize leaks in a timely manner, thereby reducing unproductive energy costs at the enterprises

Analyzing Compressed Air Demand Trends to Develop a Method to Calculate Leaks in a Compressed Air Line Using Time Series Pressure Measurements

Indiana University-Purdue University Indianapolis (IUPUI)Compressed air is a powerful source of stored energy and is used in a variety of applications varying from painting to pressing, making it a versatile tool for manufacturers. Due to the high cost and energy consumption associated with producing compressed air and it’s use within industrial manufacturing, it is often referred to as a fourth utility behind electricity, natural gas, and water. This is the reason why air compressors and associated equipment are often the focus for improvements in the eyes of manufacturing plant managers. As compressed air can be used in multiple ways, the methods used to extract and transfer the energy from this source vary as well. Compressed air can flow through different types of piping, such as aluminum, Polyvinyl Chloride (PVC), rubber, etc. with varying hydraulic diameters, and through different fittings such as 90-degree elbows, T-junctions, valves, etc. which can cause one of the major concerns related to managing the energy consumption of an air compressor, and that is the waste of air through leaks. Air leaks make up a considerable portion of the energy that is wasted in a compressed air system, as they cause a multitude of problems that the compressor will have to make up for to maintain the steady operation of the pneumatic devices on the manufacturing floor that rely on compressed air for their application. When air leaks are formed within the compressed air piping network, they act as continuous consumers and cause not only the siphoning off of said compressed air, put also reduce the pressure that is needed within the pipes. The air compressors will have to work harder to compensate for the losses in the pressure and the amount of air itself, causing an overconsumption of energy and power. Overworking the air compressor also causes the internal equipment to be stretched beyond its capabilities, especially if they are already running at full loads, reducing their total lifespans considerably. In addition, if there are multiple leaks close to the pneumatic devices on the manufacturing floor, the immediate loss in pressure and air can cause the devices to operate inefficiently and thus cause a reduction in production. This will all cumulatively impact the manufacturer considerably when it comes to energy consumption and profits. There are multiple methods of air leak detection and accounting that currently exist so as to understand their impact on the compressed air systems. The methods are usually conducted when the air compressors are running but during the time when there is no, or minimal, active consumption of the air by the pneumatic devices on the manufacturing floor. This time period is usually called non-production hours and generally occur during breaks or between employee shift changes. This time is specifically chosen so that the only air consumption within the piping is that of the leaks and thus, the majority of the energy and power consumed during this time is noted to be used to feed the air leaks. The collected data is then used to extrapolate and calculate the energy and power consumed by these leaks for the rest of the year. There are, however, a few problems that arise when using such a method to understand the effects of the leaks in the system throughout the year. One of the issues is that it is assumed that the air and pressure lost through the found leaks are constant even during the production hours i.e. the hours that there is active air consumption by the pneumatic devices on the floor, which may not be the case due to the increased air flow rates and varying pressure within the line which can cause an increase in the amount of air lost through the same orifices that was initially detected. Another challenge that arises with using only the data collected during a single non-production time period is that there may be additional air leaks that may be created later on, and the energy and power lost due to the newer air leaks would remain unaccounted for. As the initial estimates will not include the additional losses, the effects of the air leaks may be underestimated by the plant managers. To combat said issues, a continuous method of air leak analyses will be required so as to monitor the air compressors’ efficiency in relation to the air leaks in real time. By studying a model that includes both the production, and non-production hours when accounting for the leaks, it was observed that there was a 50.33% increase in the energy losses, and a 82.90% increase in the demand losses that were estimated when the effects of the air leaks were observed continuously and in real time. A real time monitoring system can provide an in-depth understanding of the compressed air system and its efficiency. Managing leaks within a compressed air system can be challenging especially when the amount of energy wasted through these leaks are unaccounted for. The main goal of this research was to find a nonintrusive way to calculate the amount of air as well as energy lost due to these leaks using time series pressure measurements. Previous studies have shown a strong relationship between the pressure difference, and the use of air within pneumatic lines, this correlation along with other factors has been exploited in this research to find a novel and viable method of leak accounting to develop a Continuous Air Leak Monitoring (CALM) system

Leak Detection and Localization in Pressurized Space Structures Using Bayesian Inference: Theory and Practice

Impact from micrometeoroids and orbital debris (MMOD) can cause severe damage to space vehicles. The crew habitat can begin to leak precious oxygen, critical systems can be punctured causing fatal failures, and an accumulation of impacts by MMOD can decrease the lifetime of any and all devices in space. Due to these and other potential dangers, MMODs have been considered the third largest threat to spacecraft after launch and re-entry. Many satellites and other spacecraft face this very problem inherent in all space travel on a daily basis, but often times they can be repaired. A major hurdle is to first be able to identify the presence of a leak. Many times an impact and subsequent leak is not discovered until it has caused a problem. A complete system is needed to detect and localize the impact to improve longevity of the habitat or other pressurized space structures. In this work, a system for detection and localization of air leaks using air-borne acoustic waves is proposed. The system uses microelectromechanical systems (MEMS) microphone sensors to detect and record high frequency noise in an environment, angle of arrival (AOA) calculations to estimate possible leak locations, and a Bayesian tree-search filter to detect and more accurately localize a leak. This work includes proof of concept, simulations, and physical prototypes as steps to creation of a complete system. Data from deployed flight test using said prototypes are analyzed. Modeling the effects of environmental reflections on the accuracy of localization is also studied

Failure detection techniques on the demand side of smart and sustainable compressed air systems : a systematic review

The industrial sector is a crucial economic pillar, seeing annual increases in the production output. In the last few years, a greater emphasis has been placed on the efficient and sustainable use of resources within industry. The use of compressed air in this field is hence gaining interest. These systems have numerous benefits, such as relative low investment costs and reliability; however, they suffer from low-energy efficiency and are highly susceptible to faults. Conventional detection systems, such as ultrasonic leak detection, can be used to identify faults. However, these methods are time consuming, meaning that leakages are often left unattended, contributing to additional energy wastage. Studies published in this area often focus on the supply side rather than the demand side of pneumatic systems. This paper offers a novel review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology of fault detection methods on the demand side of compressed air systems, leading towards a comprehensive understanding of smart and sustainable pneumatic systems. Fifty-three studies were classified and reviewed under the following three areas: (a) demand parameters which help in identifying fault sources; (b) approaches taken to analyse the parametric data; and (c) the role of Artificial Intelligence (AI) in pneumatic fault monitoring systems. This review shows that fault detection on the demand side has received greater importance in the last five years and that data analysis is crucial for AI to be implemented correctly. Nevertheless, it is clear that further research in this sector is essential, in order to investigate more complex systems. It is envisaged that this study can promote the adoption of such systems, contributing to an energy-efficient and cost-effective industry.peer-reviewe