Compressed Air System Research Articles

Graphene-Based Thermopneumatic Generator for On-Board Pressure Supply of Soft Robots.

Various fields, including medical and human interaction robots, gain advantages from the development of bioinspired soft actuators. Many recently developed grippers are pneumatics that require external pressure supply systems, thereby limiting the autonomy of these robots. This necessitates the development of scalable and efficient on-board pressure generation systems. While conventional air compression systems are hard to miniaturize, thermopneumatic systems that joule heat a transducer material to generate pressure present a promising alternative. However, the transducer materials of previously reported thermopneumatic systems demonstrate high heat capacities and limited surface area resulting in long response times and low operation frequencies. This study presents a thermopneumatic pressure generator using aerographene, a highly porous (>99.99%) network of interconnected graphene microtubes, as lightweight and low heat capacity transducer material. An aerographene pressurizer module (AGPM) can pressurize a reservoir of 4.2 cm3 to ∼14 kPa in 50 ms. Periodic operation of the AGPM for 10 s at 0.66 Hz can further increase the pressure in the reservoir to ∼36 kPa. It is demonstrated that multiple AGPMs can be operated parallelly or in series for improved performance. For example, three parallelly operated AGPMs can generate pressure pulses of ∼21.5 kPa. Connecting AGPMs in series increase the maximum pressure achievable by the system. It is shown that three AGPMs working in series can pressurize the reservoir to ∼200 kPa in about 2.5 min. The AGPM's minimalistic design can be easily adapted to circuit boards, making the concept a promising fit for the on-board pressure supply of soft robots.

Pathway to Decarbonization Through Industrial Energy Efficiency: Micro and Macro Perspectives from Compressed Air Usage

Energy audits directly provided the industrial sector with reduced energy costs and avoided emissions. Still, they also lead to far-reaching indirect and induced local, regional, and national benefits. This paper aims to present the techno-economic-environmental analysis to achieve decarbonization through implementing industrial energy efficiency at micro and macro levels. An integrated techno-economic-environmental methodology is developed. Case studies of micro-level carbon reduction efforts through industrial energy efficiency technologies are presented. The broader macroeconomic and environmental effects of technology on society are analyzed using data from 206 energy audits of industrial compressed air systems conducted over 13 years. The impacts show that energy-efficient improvements lead to direct cost savings for manufacturers, boost economic activity across sectors, and affect carbon dioxide emissions both short-term and long-term in the region. Given their extensive benefits, energy audits significantly influence policymaking. We devised a methodology to link micro-level energy audit data with macroeconomic and environmental analyses to quantify these cascading benefits. The economic scenario analysis shows that $228 M has been saved from direct industrial energy savings from implementing all compressed air recommendations in the studied periods and the region. In addition, the investment made through manufacturers would create 2,025 jobs and $383 M annually, cascading regional economic impacts. The environmental analysis shows that the regional manufacturers have directly avoided about 2.8 M metric tons of carbon dioxide emissions.

Design and Development of Pneumatic Sheet Metal Cutting Machine

It is important to note that in today's industrial era, sheet metal is cut and bent into a variety of shapes to obtain better surface finish and flexibility in manufacturing processes. The use of modern techniques, such as pneumatic sheet cutting machines, has greatly improved the efficiency of sheet metal cutting and bending processes. This review focuses on the reliability, performance, and design simplification of pneumatic sheet cutting machines. Additionally, it examines the energy lost in the pneumatic cylinder while it imparts force on the cutting blade. The energy efficiency of pneumatic and compressed air systems is a critical aspect in the development of sustainable production. The objective of this cross-discipline review is to provide production and life cycle engineering researchers with an update on the state of the art in energy efficiency for pneumatic production and associated compressed air infrastructure.

Development and Evaluation of an Optimized Energy Recovery System from Excess Heat of a Compressed Air System

The aim of this study is to build a bounded optimized energy recovery system from the compressed air system’s excess heat. It is important to concentrate on the use of products that satisfy the requirements for performance and sustainability, as well as the need for energy that will be optimized. Purposive sampling is used to select the respondents, using quantitative research, specifically both descriptive and developmental methods. The researcher utilized a decision support tool developed by Kolaitis et al., (2020) as the primary research instrument of the study. The adopted tool was slightly modified to suit the assessment needs of the developed energy utilization system. All the main criteria components are interpreted as highly sustainable. The researcher utilized log sheets to determine the performance of the study. Finally, paired t-test was used to determine whether there was a significant difference in the performance of the study. The performance of the optimized energy after the implementation of the project was statistically higher than the performance of the optimized energy before the implementation of the project. The researcher concluded that the performance of the optimized energy recovery system from excess heat of a compressed air system after the installation and operation was effective and efficient based on the ratings of respondents and descriptive measures on the log sheet. For this kind of innovation, the manufacturing company with the same equipment should adopt and sustain it for potential energy savings and protect mother nature.

Experimental study on permeability evolution of sandstone under cyclic loading

The permeability of a rock mass affects the site selection and construction of underground high-pressure gas storage for compressed-air energy storage. This study investigates the permeability evolution of sandstone under high-pressure gas during the cycle of confining and axial pressures. Nitrogen permeation tests were conducted at different inlet pressures using the steady-state method. The initial steady-state flow, seepage in the circulation, and steady-state flow after circulation were measured continuously in three stages. The effects of the loading and unloading rates and load-holding time on the seepage flow were analyzed. The results indicate that the flow rate and displacement changed with periodic changes in the axial and confining pressures during the cycle. The higher the inlet pressure, the greater was the difference between the peak and trough of the flow in the cycle, and the greater was the difference between the flow after the cycle and the initial flow. When the inlet pressure was 10 MPa, the steady-state flow rate increased from 284 ml/min to 336 ml/min (18%). When the inlet pressure was 2 MPa, the evolution range of the seepage flow in the sample was similar for different load-holding times. The loading and unloading rates had a significant influence on the flow waveform in the circulation process but little influence on the wave height. With an increase in the number of cycles, the porosity of the samples first decreased rapidly and then increased slowly. This study provides a reference for construction and operation of compressed-air energy-storage systems.

A Review of Energy Overconsumption Reduction Methods in the Utilization Stage in Compressed Air Systems

Pneumatic systems use the energy of compressed air to carry out manufacturing automation processes through the implementation of complex handling and motion tasks. However, these systems are energy intensive: it is estimated that pneumatic systems in manufacturing plants consume approximately 10% of all electricity consumed in the industrial sector. At the same time, the energy efficiency of the whole pneumatic system is observed to be 6–10%, due to the compression process, oversizing, and overconsumption. There are numerous solutions in the literature focusing on improving efficiency at the compression stage of utilization; however, for the utilization stage, there is a lack of systematization and grouping of these solutions. The following review will summarize current knowledge about the utilization stage and methods for improving oversizing and energy overconsumption. In addition, a method of exergy analysis for pneumatic systems will be presented, which is a very useful tool to assess the efficiency of these systems.

ML- and LSTM-Based Radiator Predictive Maintenance for Energy Saving in Compressed Air Systems

Air compressors are widely used in industrial fields. Compressed air systems aggregate air flows and then supply them to places of demand. These huge systems consume a significant amount of energy and generate heat internally. Machine components in compressed air systems are vulnerable to heat, and, in particular, a radiator to cool the heat of the overall air compressor is the core component. Dirty radiators increase energy consumption due to anomalous cooling. To reduce the energy consumption of air compressors, this mechanism emphasizes a machine learning-based radiator fault detection, using features such as RPM, motor power, outlet pressure, air flow, water pump power, and outlet temperature with slight true fault labels. Moreover, the proposed system adds an LSTM-based motor power prediction model to point out the initial judgment of radiator fault possibility. Via the rigorous analysis and the comparison among machine learning models, this meticulous approach improves the performance of radiator fault prediction up to 93.0%, and decreases the mean power consumption of the air compressor around 2.24%.

Design and fabrication of a soft wearable robot using a novel pleated fabric pneumatic artificial muscle (pfPAM) to assist walking

Defects in walking can substantially impact individuals' quality of life. Utilizing wearable robots is one of the known methods to improve this daily activity for individuals with disabilities or limited mobility. In recent years, one of the challenges confronting researchers has been improving these devices' comfort and efficacy. This research aims to provide a lower-limb exosuit that aids in walking while being more comfortable and efficient than previous models in some certain respects. One factor that reduces the usability of these active wearables is the heavy and rigid structure of the force interaction mechanism and their inflexible actuators. This study's wearable robot benefits from a new Pneumatic Artificial Muscle (PAM) and a skeletal-free force mechanism, which, due to their innovative design and garment-like structure, when combined with a sensor network, weigh only 536 g. Also, the compressed air system is designed so that the user can quickly wear or remove it. The developed exosuit considerably improves the wearer's walking ability while remaining lightweight and comfortable. This claim has been checked and validated through numerous tests. The final results reveal that the user's posterior thigh muscles had an activity reduction of 7.4% in each complete gate cycle and 22.7% at peak time when using the exosuit compared with walking without the exosuit. Additionally, compared with the state where the exosuit was worn but inactive, the reduction was 16.2% overall and 63.9% at peak time. The motion cycle analysis also indicated that the system caused the user to take longer and more frequent steps than when walking without the exosuit. One of the reasons that has caused the performance of wearable robots to drop significantly as they become softer is the weakness of their actuators. In pursuit of this study's primary objective, a functional PAM was devised, which may have some of the most suitable features for such wearable robots. A contraction of up to 40%, a force-to-weight ratio of one thousand (with a weight of 44 g), a fabric-based structure for use alongside the body, low-cost production, contractibility at low pressures, and high controllability compared to its peer actuators are some of the soft contractile actuator features developed in this research.

Collaborative Optimization of Phononic Crystal Pipe Based on Revolving Helmholtz Resonators for Air Compressor System in FCEVs

Collaborative Optimization of Phononic Crystal Pipe Based on Revolving Helmholtz Resonators for Air Compressor System in FCEVs

Using numerical simulation to analyze the strength properties of the developed demountable body of a trolley

One of the safest types of public transport is the metro, which is actively developing in many countries. Despite a number of advantages, the construction of metro tunnels is a rather labor-intensive process, which involves complex technical equipment in the form of tunnel boring complexes. Tunnel boring complexes include locomotives that perform the functions of hauling away rock using trolley with removable body. Trolley differs from their usual characteristics - in weight, dimensions, as well as the component composition of individual systems, in particular the compressed-air braking system. The article is devoted to the analysis of the parameters of the stress-strain state of one of the main load-bearing elements of a trolley- the casing. As a result of the analysis, design loading cases were selected, the most loaded parts of the body were determined, recommendations were formed for choosing the optimal material thickness of various elements and increasing the load-bearing capacity of the body.

COMPARATIVE ANALYSIS OF PRESSURE AND FLOW CHARACTERISTICS IN BASIC AND MODIFIED AIR COMPRESSOR PIPELINE USING COMPUTATIONAL FLUID DYNAMICS IN POWER PLANT TANJUNG ENIM 3X10 MW

Air compressor plays a crucial role by converting electrical energy into kinetic energy in the form of compressed air. This study specifically concentrates on assessing the performance of two compressors that operate alternately, with one compressor in standby mode. Unfortunately, compressor unit #1 faced issues with its drying system, rendering it unable to function within the current pipe network. In order to rectify this, proposed modifications to the pipeline network are introduced and scrutinized. To analyze these modifications, Computational Fluid Dynamics (CFD) is employed to evaluate and compare pressure and flow characteristics in both the existing and modified pipe configurations. The CFD analysis utilizes computer engineering software, with SolidWorks serving as the primary modeling and simulation tool. The assumption is made that the Reynolds number corresponds to laminar flow, factoring in pipe diameter and compressor volume rate.The resulting CFD data offers valuable insights into pressure and velocity distributions within the existing and modified pipeline networks. During the pressure simulation, surface pressure and output on both standard and modified pipes exhibit relatively similar pressure values at 7 bar. However, in the air velocity simulation, surfaces of standard and modified pipes maintain a consistent range of 0 – 5 mm/s. Notably, from the pipe output side, air velocity in standard and modified pipes displays distinct speed contours. Standard pipes show the highest speed between 0.25 – 0.38 mm/s, whereas modified pipes exhibit the highest speed within the range of 0.15 – 0.2 mm/s. This study aims to provide a comprehensive evaluation of the proposed modifications, seeking to enhance understanding of the fluid dynamics within air compressor systems. The outcomes of this research have the potential to contribute significantly to optimizing the performance and efficiency of these systems, thereby offering benefits across various industrial applications.

Desiccant-assisted multistage air compression systems: Performance improvement and humidity control

Novel desiccant-assisted systems have been evaluated for reducing the work required in multistage air compression processes. While traditional inter-cooling is generally achieved by placing heat exchangers between compression stages, the systems herein proposed are based on harvesting heat rejection to drive a desiccant cooling system. This cooling effect is then used to cool the air between the compression stages below ambient temperature, and also to pre-cool the air prior admission to the first stage, allowing for a reduction of the compression work. In addition, desiccant dehumidification is also used to control the humidity of the air in the compression system. A model based on steady-state heat and mass transfer balances across all components is presented and computationally implemented for a two-stage compression system. Numerical results are analyzed in terms of a performance factor, showing that some configurations can achieve a reduction in compression work almost 60% greater than that achieved with conventional inter-cooling systems. A final test-case was also presented, based on inlet conditions extracted from weather data of Rio de Janeiro, Brazil, demonstrating that the proposed compression schemes could be used as a viable option for reducing compression work in multi-stage systems. The use of a waste-heat-driven desiccant-assisted system for reducing compression work and controlling humidity, is an important addition to applications of desiccant cooling.

Different energy storage techniques: recent advancements, applications, limitations, and efficient utilization of sustainable energy

In order to fulfill consumer demand, energy storage may provide flexible electricity generation and delivery. By 2030, the amount of energy storage needed will quadruple what it is today, necessitating the use of very specialized equipment and systems. Energy storage is a technology that stores energy for use in power generation, heating, and cooling applications at a later time using various methods and storage mediums. Through the storage of excess energy and subsequent usage when needed, energy storage technologies can assist in maintaining a balance between generation and demand. Energy storage technologies are anticipated to play a significant role in electricity generation in future grids, working in conjunction with distributed generation resources. The use of renewable energy sources, including solar, wind, marine, geothermal, and biomass, is expanding quickly across the globe. The primary methods of storing energy include hydro, mechanical, electrochemical, and magnetic systems. Thermal energy storage, electric energy storage, pumped hydroelectric storage, biological energy storage, compressed air system, super electrical magnetic energy storage, and photonic energy conversion systems are the main topics of this study, which also examines various energy storage materials and their methodologies. In the present work, the concepts of various energy storage techniques and the computation of storage capacities are discussed. Energy storage materials are essential for the utilization of renewable energy sources and play a major part in the economical, clean, and adaptable usage of energy. As a result, a broad variety of materials are used in energy storage, and they have been the focus of intense research and development as well as industrialization. This review article discusses the recent developments in energy storage techniques such as thermal, mechanical, electrical, biological, and chemical energy storage in terms of their utilization. The focus of the study has an emphasis on the solar-energy storage system, which is future of the energy technology. It has been found that with the current storage technology, the efficiency of the various solar collectors was found to be increased by 37% compared with conventional solar thermal collectors. This work will guide the researchers in making their decisions while considering the qualities, benefits, restrictions, costs, and environmental factors. As a result, the findings of this review study may be very beneficial to many different energy sector stakeholders.

Integrating extended reality in industrial maintenance: a game-based framework for compressed air system training

In industrial environments, maintenance technologies developed under Industry 5.0 are important to ensure trouble-free production and reduce downtime. Compressed Air Systems (CASs) are an integral part of industrial production processes and require competent and correct maintenance. Maintenance personnel should be equipped with continuous and up-to-date training and their knowledge should be tested. There is a significant gap in the field of interactive educational games to improve the technical skills of the care staff, especially in the field of CAS. This research proposes a theoretical framework for a game based on Extended Reality (XR) technologies adapted for CAS maintenance training. The game leverages the trio of Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR) to provide immersive and interactive learning encounters aimed at improving technical proficiency, problem-solving skills, and safety awareness among maintenance workers. The aim is to take advantage of the rewards of game-oriented learning, such as enhanced user engagement and knowledge absorption, to increase the effectiveness of training. In this context, the CAS game framework was created with three frameworks: education, game, and CAS. The study concludes by highlighting the potential benefits, research areas, and technologies that underpin the proposed structure.

Implementation of an intelligence-based framework for anomaly detection on the demand-side of sustainable compressed air systems

The implementation of intelligent techniques produces good results in automating fault finding and predicting future outcomes. These approaches have been on the increase in the past years, especially so to detect faults within Compressed Air Systems (CASs). With the use of intelligent techniques, one could minimise the manual and time-consuming aspect of CAS maintenance, improve the environmental impact of the system, while minimising downtime. This paper proposes a general framework for the implementation of intelligent analysis techniques within a real-world system. Such an approach has been implemented on the demand-side of a CAS. In literature, no open datasets are available for use by artificial intelligence models. Hence, as part of this research, a fault generating and monitoring system has been connected to an existing production machine in a manufacturing site to collect the required data. Two classification machine learning methods were implemented and compared across a number of performance metrics. Both the general framework, and its implementation, provide a stepping stone in integrating smart systems with real-time intelligent data analytics for the demand-side of a CAS. These systems would provide a sustainable CAS operation through the effective detection of anomalies and their timely repair.

Intelligent optimisation in smart and sustainable compressed air systems: Towards support for decision-making under faulty conditions

The monitoring of complex industrial systems through the implementation of smart approaches provides unique opportunities, such as the characterisation of their real-time performance. Within this scope, there exists the need to support decision-making during maintenance processes, due to the presence of a multitude of faults in real-world systems and the difficulty of identifying the appropriate mitigating solutions. The proposed solution uses intelligent optimisation techniques to identify the ideal control solution within these complex systems when faults arise. This paper presents a framework based on an intelligent optimisation approach, which provides a workflow process for the support of decision-making during faulty situations. It is adapted and implemented to the demand-side of a Compressed Air System (CAS), thus providing a holistic approach in automating fault mitigation during real-time system operation. In implementing this framework, multiple intelligent optimisation techniques such as the Genetic Algorithm and the Particle Swarm Optimisation algorithms were adopted and implemented. Both algorithms were successful in providing the ideal control solution under fault conditions. For a typical production case study, the proposed optimisation approach results in a reduction of 40% in its air consumption, which directly improves its environmental performance and energy costs. This result demonstrates that this approach contributes a suitable control strategy for CAS when experiencing a pneumatic fault, which has a direct positive effect on the operational energy performance and costs.

Energy efficient compressed air filtration: An experimental study on the effect of filters selection and configuration on pressure drop

Over the past decades, the industrial sector has been trying to improve the use of resources and the environmental impact they create. Significant work has been done in compressed air systems. However, there is still much room for improvement. The focus of this study is on a new approach to energy efficient compressed air filtration. This approach involves the installation of different filter configurations that enable a lower pressure drop, instead of the conventionally selected filter. The goal is to reduce the pressure drop, while maintaining the same level of air quality. Pressure drop and compressed air quality are taken as key performance indicators that assess the efficiency and sustainability of compressed air system. It has been experimentally proven that compressed air quality classes remain the same for filters with the same grade of filtration, regardless of the number, type, and way of their installation. However, there is a small difference in the case of particulate and coalescing filters. This environmentally friendlier approach provides a win-win situation. The pressure drop is reduced, costs are also reduced, the system operates continuously and more reliably, and the process is more sustainable.

Pneumatic Fault Monitoring and Control for Sustainable Compressed Air Systems

Sustainable development in the industrial sector has been widely explored in recent years, to achieve a carbon-neutral industry. Compressed air systems are widely used in the industrial sector. Numerous energy-saving improvements have been studied within this scope, as leaks make these systems inefficient. Nevertheless, it has yet to be seen how different optimisation techniques can be utilised to mitigate fault effects. This study shows how fault monitoring was performed on a multi-actuator system, using different time domain indicators including, mean and standard deviation. This was followed by exploring the system behaviour when pressure and flowrate control strategies were executed to minimize fault impacts. Fault monitoring, using the indicator data, was successful. For instance, as a 1 mm leak was induced and the consumption increased by 34%, the standard deviation in pressure drop reduced by 6% and the mean actuation time decreased by 13%. Though the mean in pressure drop was useful for fault monitoring other pressure indicators, including standard deviation, provided additional monitoring capabilities. During this monitoring exercise, it was also found that improved sensor accuracy resulted in less reading variations, obtaining more conclusive results and identifying faults of smaller sizes. As faults were accurately identified and characterised, it was then possible to mitigate their effects via pressure and flowrate adjustments. Results proved promising, as both contributed to air consumption decreases of 16% and 11%, respectively. Although such modifications decreased the production rate by 2-5%, the previously mentioned savings outweighed this decrease. This work highlights the need for development of fault monitoring and control systems which maintain the productivity and energy performance of pneumatic systems.

Autonomous Fault Monitoring for Efficient Multi-Actuator Compressed Air Systems:Data Analytics of Demand-Oriented Parameters

Industry 4.0 has given rise to an increased use of system data and analytics. Autonomous fault detection in pneumatic systems has also been increasingly explored in the last decade, with one of the main objectives being to reduce the energy consumption and resulting carbon footprint of such systems. Nevertheless, pneumatic fault monitoring systems tend to mainly focus on the supply-side, neglecting the demand-side. Studies covering pneumatic fault monitoring on the demand-side, perform research on simple systems, typically investigating the effects on a single actuator or a very small system. This study aimed at tackling this issue, with tests performed on an industrial multi-actuator pick-and-place setup, logging data (i.e. cycle time, flow rate and system pressure) concurrently at two locations within the system. Furthermore, different sized leaks were introduced at three distinct locations, while monitoring their impacts on the system. It was found that with the use of the average, standard deviation and impulse factor of the cycle time and the other two parameters, it was possible to identify the presence of faults on a relatively large system. For instance, the retraction time for one of the actuators reduced by 26% as one of the faults was induced. With modern industrial setups already logging the cycle time and system pressure along the demand-side, this study shows that by using existing equipment, one can develop a reliable fault monitoring system. Such information makes it possible to determine additional fault characteristics, mainly the fault's severity, type and location, thus paving the way towards smart and energy efficient compressed air systems.

Fault Condition Indicators along the Demand Side of a Sustainable Compressed Air System

Compressed air is a vital form of energy storage and transfer in the manufacturing industry. Pneumatic system efficiency is typically low due to faults such as leakages and pressure drops which are often left unattended due to the downtime required to maintain them. The goal of this study was to identify parameters which can be used to computationally detect the presence of faults in a pneumatic pick-and-place system within an industrial automation setup. Leakages and pressure drops were systematically induced at three locations along the demand side of the system. Pneumatic data was collected from two separate locations simultaneously, and this work presents the systematic approach utilised to investigate the impacts of each fault. Indicators, namely the mean, standard deviation and impulse factor for pressure and flow rate data were identified as being able to identify the presence of faults together with their severity, type and location. This study concludes that by solely using pressure data, all three fault characteristics could be identified. These indicators can form part of data monitoring within smart machines, allowing for autonomous analyses.