Cylinders diagnosis system of a 1 MW internal combustion engine through vibrational signal processing using DWT technique

In the present study an innovative diagnostic system of the combustion process, developed especially for cogenerative reciprocating engines, is introduced. This work is part of a more wide research activity, dedicated to the development of diagnostic systems for energy plants. This system is based on the evaluation of the energy content of the vibration signal directly acquired on the cylinders head through the Discrete Wavelet Transform technique and the Parseval’s theorem. The system development and its test took place alongside a consistent maintenance work that has allowed to distinguish between different engine operative functioning, and, in particular, between good and bad conditions of the combustion chambers. Then, starting from the obtained results, a diagnostic system has been developed, basing on the acquired vibration signals and the operative engine load, in order to formulate for each cylinder a judgment about the quality of the combustion process.     

Modeling of a 1 MW cogenerative internal combustion engine for diagnostic scopes

This paper contributes to the development of a thermo-dynamic model of the 1 MW cogenerative internal combustion engine (I.C.E.), including also an artificial neural network simulator of the electronic control module. Such a study is part of a more wide research activity, concerning the development of a diagnosis and monitoring system specifically for power plants. In particular, the engine model was realized to simulate the engine functioning also in the case of malfunctions and failures occurrence, taking in consideration the compensation effect operated by the regulation system.     

Design of the measurements validation procedure and the expert system architecture for a cogeneration internal combustion engine

A research activity has been initiated to study the development of a diagnostic methodology, for the optimization of energy efficiency and the maximization of the operational time in those conditions, based on artificial intelligence (AI) techniques such as artificial neural network (ANN) and fuzzy logic.The diagnostic procedure, developed specifically for the cogeneration plant located at the Engineering Department of the University of Perugia, must be characterized by a modular architecture to obtain a flexible architecture applicable to different systems. The first part of the study deals with the identifying the principal modules and the corresponding variables necessary to evaluate the module “health state”.Also the consequent upgrade of the monitoring system is described in this paper. Moreover it describes the structure proposed for the diagnostic procedure, consisting of a procedure for measurement validation and a fuzzy logic-based inference system. The first reveals the presence of abnormal conditions and localizes their source distinguishing between system failure and instrumentation malfunctions. The second provides an evaluation of module health state and the classification of the failures which have possibly occurred. The procedure was implemented in C++.     

Artificial intelligence for the modeling and control of combustion processes: a review

Artificial intelligence (AI) systems are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing, and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. AI systems comprise areas like, expert systems, artificial neural networks, genetic algorithms, fuzzy logic and various hybrid systems, which combine two or more techniques. The major objective of this paper is to illustrate how AI techniques might play an important role in modeling and prediction of the performance and control of combustion process. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in the different disciplines of combustion engineering. The various applications of AI are presented in a thematic rather than a chronological or any other order. Problems presented include two main areas: combustion systems and internal combustion (IC) engines. Combustion systems include boilers, furnaces and incinerators modeling and emissions prediction, whereas, IC engines include diesel and spark ignition engines and gas engines modeling and control. Results presented in this paper, are testimony to the potential of AI as a design tool in many areas of combustion engineering.     

基于BP神经网络的GD-1高压共轨系统的建模研究

基于GD-1高压共轨燃油喷射系统,运用BP神经网络理论对GD-1系统高压油泵及共轨管进行建模,在Matlab平台上利用实际测得的数据对所建的神经模型进行训练,利用Simulink工具将训练好的高压油泵及共轨管模型与GD-1控制策略连接在一起进行闭环仿真,仿真结果表明设计的神经网络能很好地模拟共轨管内实际油压变化.     

Shape design and numerical analysis on a 1 MW tidal current turbine for the south-western coast of Korea

The study concentrates on the shape design and numerical analysis of a 1 MW horizontal axis tidal current turbine (HATCT), which can be applied near the southwest regions of Korea. On the basis of actual tidal current conditions of south-western region of Korea, configuration design of 1 MW class turbine rotor blade is carried out by blade element momentum theory (BEMT). The hydrodynamic performance including the lift and drag forces, is conducted with the variation of the angle of attack using an open source code of X-Foil. The optimized blade geometry is used for Computational Fluid Dynamics (CFD) analysis with hexahedral numerical grids. This study focuses on developing a new hydrofoil and designing a blade with relatively shorter chord length in contrast to a typical TCT blade. Therefore, after a thorough study of two common hydrofoils, (S814 and DU-91-W2-250, which show good performance for rough conditions), a new hydrofoil, MNU26, is developed. The new hydrofoil has a 26% thickness that can be applied throughout the blade length, giving good structural strength. Power coefficient, pressure and velocity distributions are investigated according to Tip Speed Ratio by CFD analysis. As cavitation analysis is also an important part of the study, it is investigated for all the three hydrofoils. Due to the shorter chord length of the new turbine blade in contrast to a typical TCT blade design, a Fluid Structure Interaction (FSI) analysis is also done. Concrete conclusions have been made after comparing the three hydrofoils, considering their performance, efficiency, occurrence of cavitation and structural feasibility.     

一种基于单谐次角振动信号的内燃机工作状态监测新方法

分析了内燃机轴承低阶扭振振型特性;提出了单谐次准等差振幅模型。当内燃机轴系满足此条件时,提出一种利用曲轴低谐次扭振信号幅值监测内燃机工作状态的新方法。并以某机车柴油发电机组轴系为对象进行了应用研究,验证了本方法的实用性和诊断准确性。新方法不需要其他结构参数,简便易行,而且准确度高,适用广泛,有较强的工程实用价值。     

Research on the inducing factors and characteristics of knock combustion in a DI hydrogen internal combustion engine in the process of improving performance and thermal efficiency

Hydrogen energy is gaining greater attention because of the energy crisis and CO2 emissions, and knock combustion has become the main obstacle to improving thermal efficiency and power performance of hydrogen engines, which is an important method of hydrogen energy application. In this paper, the knock characteristic parameters and the factors affecting knock tendency of a 2.0 L DI hydrogen engine are investigated experimentally. The results reveal the variation in knock intensity is not linear with the retarding of SOI, which is related to the cylinder mixture distribution. Furthermore, methods such as increasing injection pressures can be useful in reducing the knock intensity. Equivalence ratio has a greater impact on knock compared with other parameters. The conclusions can be used in the further exploration of the knock combustion mechanism in DI hydrogen engines.     

Influence of the equivalence ratio on the knock and performance of a hydrogen direct injection internal combustion engine under different compression ratios

Hydrogen has become an ideal alternative fuel for internal combustion engines. However, with an increase in the equivalence ratio and compression ratio, knock combustion is more likely to occur, which limits its engineering application. In this study, the effects of the equivalence ratio on the knock under different compression ratios were studied through numerical simulation. The signal energy ratio (SER) were used to evaluate the knock onset (KO). The knock intensity (KI) and engine performance were compared and analyzed under different equivalence ratios and compression ratios. The results revealed that a high compression ratio can significantly amplify the effect of the equivalence ratio on combustion and knock. Under the compression ratio of 17.5, KI increases more quickly, with the constant equivalence ratio rise and is more sensitive to ignition timing with equivalence ratio increasing. For the compression ratio of 11, the ignition timing limited by knock is about 4°CA earlier than that of compression ratio of 17.5, and the engine performance is more stable in the low-knock zone. However, when KI exceeds 1 MPa, the power and ITE decreases 20.6% and 20.9% respectively.     

A process simulation model for a 2 ton h−1 incinerator (a combined bed combustion and furnace heat transfer model)

A process simulation model was constructed for a 2 ton h⁻¹ incinerator. The simulation model was designed to provide system performance parameters according to various operating conditions. In accommodating the wide variation of quality and composition of input wastes, the plant operating parameters such as amount of excess air, preheated air temperature, waste feed rate and primary air distribution over the stoker, etc. must be carefully controlled. The proposed model calculates operating variables of each submodule, by employing steady-state thermal and material balance equations. Combustion of waste bed, and its radiative heat transfer in the combusion chamber are considered. The calculated results of the combustion chamber performance are evaluated, in terms of temperature, locations and width of the flame band, and mean residence time in the secondary combustion chamber. These results are compared with a limited set of field test measurements for verification of the model. © 1998 John Wiley & Sons, Ltd.     

Effect of seeding on hydrogen and carbon particle production in a 10 MW solar thermal reactor for methane decomposition

Solar methane decomposition reactors are a novel technology for the production of carbon neutral hydrogen; however, the impact of this technology depends greatly on the ability to co-produce carbon black particles of commercial grade in order to offset the cost of hydrogen production and, therefore, the control of the reactor is very important. To this end, the seeding of indirect heating concept reactors using the product particles themselves could be used to control heat transfer inside the reactor. In this work, a previously developed one-dimensional reactor – particle population model was used to simulate the effect of seeding on the hydrogen and carbon particle production rates in the absorber tubes of a 10 MW indirect heating concept solar reactor. It was found that seed particle feed rates less than 10% of the methane-contained carbon feed rate allowed the hydrogen and fresh particle production rates to be doubled while keeping the rate of carbon growth on the tube walls constant. It was also found that similar seed fee rates could be used to maintain the hydrogen and particle production rates constant, given variations in the absorber tube wall temperature within a 100 °C range, for example due to cloud passage. Furthermore, it was found that the size characteristics of the freshly produced particles were not affected at these seed feed rates. Thus, seeding could be an effective means for increasing and controlling the hydrogen and carbon particle production rates in industrial scale indirect heating concept solar methane decomposition reactors, while also reducing carbon growth on the walls of the absorber tubes.     

Impact of HHO gas enrichment and high purity biodiesel on the performance of a 315 cc diesel engine

Biodiesel and oxyhydrogen (HHO) gas have shown promising results in improving engine performance and emissions. In this work, the effects of HHO gas and 5% biodiesel blends (B5) and their combined use in a 315 cc diesel engine have been analyzed. Biodiesel is produced by base catalyzed transesterification and cleaned by emulsification. Its calculated cetane index (CCI) was 61.4. HHO gas is produced from electrolysis of concentrated potassium hydroxide solution. The use of 5% biodiesel blend resulted in a significant rise of 9.4% in the brake thermal efficiency (BTE) and a maximum reduction of 8.19% in the brake specific fuel consumption (BSFC). HHO enrichment of diesel and biodiesel at 2.81 L/min through the intake manifold improved the torque and power by an average of over 3%. HHO addition also improved the BTE of diesel by a maximum of 3.67%. The combination of high CCI biodiesel fuel and HHO creates a mixture that has shortened the ignition delay (ID) to the point that adverse effects were observed due to the premature combustion as shown by the average decrease in the BTE of 2.97% compared to B5. Thus, B5, on its own, is found to be the optimum fuel under these conditions.     

Analysis of technology improvement opportunities for a 1.5 MW wind turbine using a hybrid stochastic approach in life cycle assessment

This paper presents an analysis of potential technological advancements for a 1.5 MW wind turbine using a hybrid stochastic method to improve uncertainty estimates of embodied energy and embodied carbon. The analysis is specifically aimed at these two quantities due to the fact that LCA based design decision making is of utmost importance at the concept design stage. In the presented case studies, better results for the baseline turbine were observed compared to turbines with the proposed technological advancements. Embodied carbon and embodied energy results for the baseline turbine show that there is about 85% probability that the turbine manufacturers may have lost the chance to reduce carbon emissions, and 50% probability that they may have lost the chance to reduce the primary energy consumed during its manufacture. The paper also highlights that the adopted methodology can be used to support design decision making and hence is more feasible for LCA studies.     

A maximum power tracking algorithm based on Impp = f(Pmax) function for matching passive and active loads to a photovoltaic generator

In this paper, a method that forces a photovoltaic generator (PVG) to operate at its maximum power point under variable load and insolation conditions is developed. The method is based on closed loop current control, in which the reference current is determined from the fitted function of I_mpp versus P_max, points of a particular PVG. A simplified computer model of the PVG is given and computer simulations for demonstrating the effectiveness of the proposed algorithm are presented. The method has also been applied using a PC with IO interface card in the laboratory. From the results of the simulations and experimental studies, it is concluded that the proposed approach can be used as a robust and fast acting maximum power point tracker.