Diesel engine fuel injection monitoring using acoustic measurements and independent component analysis

Air-borne acoustic based condition monitoring is a promising technique because of its intrusive nature and the rich information contained within the acoustic signals including all sources. However, the back ground noise contamination, interferences and the number of Internal Combustion Engine ICE vibro-acoustic sources preclude the extraction of condition information using this technique. Therefore, lower energy events; such as fuel injection, are buried within higher energy events and/or corrupted by background noise. This work firstly investigates diesel engine air-borne acoustic signals characteristics and the benefits of joint time-frequency domain analysis. Secondly, the air-borne acoustic signals in the vicinity of injector head were recorded using three microphones around the fuel injector (120° apart from each other) and an Independent Component Analysis (ICA) based scheme was developed to decompose these acoustic signals. The fuel injection process characteristics were thus revealed in the time-frequency domain using Wigner-Ville distribution (WVD) technique. Consequently the energy levels around the injection process period between 11 and 5 degrees before the top dead center and of frequency band 9 to 15 kHz are calculated. The developed technique was validated by simulated signals and empirical measurements at different injection pressure levels from 250 to 210 bars in steps of 10 bars. The recovered energy levels in the tested conditions were found to be affected by the injector pressure settings

Introduction of Abnormal Combustion in Hydrogen Internal Combustion Engines and the Detection Method

As a clean, environmentally friendly and renewable energy source, hydrogen as an alternative engine fuel can greatly reduce atmospheric pollution and alleviate the shortage of oil resources, and is the most promising alternative fuel for vehicles among new fuels. However, due to its fast combustion rate and wide ignition limit, hydrogen often shows abnormal combustion phenomena (such as pre-ignition, backfire and knock), when it is used in the engine, thus affecting the performance and normal use of engines. In this paper, the advantages and disadvantages of hydrogen as an alternative fuel for the engine are summarized according to the characteristics of hydrogen. On this basis, the mechanism, influence factors and harm of abnormal combustion in the hydrogen internal combustion engine are analyzed and summarized, which provides a theoretical basis for solving abnormal combustion problems. Finally, several commonly used abnormal combustion detection methods are summarized.Citation: Liu, J. (2022). Introduction of Abnormal Combustion in Hydrogen Internal Combustion Engines and the Detection Method. Trends in Renewable Energy, 8, 38-48. DOI: 10.17737/tre.2022.8.1.0013

An application of early fault detection for the crankshaft and piston of an internal combustion engine

Internal combustion engines are made of many moving components that are subjected to high inertia and combustion loads. Crankshaft bearing and piston-cylinder walls work under hydrodynamic lubrication conditions. Any failure at those bearing may cause severe damage on the engine. Acceleration measurement on the cylinder block and cylinder was effectively used for early detection of failure in hydrodynamic lubrication. Inspection of the crankshaft and piston components after the test clearly shows that metal-to-metal contact occurred during the test and real-time acceleration signal analysis can help to early detection of the problem

Application of a PCA-based fault detection and diagnosis method in a power generation system with a 2 MW natural gas engine

Based on increasing global energy demand, electric power generation from Internal Combustion Engines (ICE) has increased over the years. On this idea, the industries have adopted different methods and procedures to prevent failures in these engines, achieve an extension of the life cycle of the machines, improve their safety, and provide financial savings. For this reason, this work implements a methodology for detecting and identifying failures in a natural gas engine (JGS 612 GS-N. L), based on the integration of Principal Component Analysis (PCA) and alarm streak analysis. A method used to describe a data set in terms of new uncorrelated variables or components. The components are ordered by the amount of original variance they describe, making the technique useful for reducing the dimensionality of a data set. Technically, PCA searches for the projection according to which the data are best represented in terms of least squares, using the T2 and Q statistics. In the initial stage, a PCA-based algorithm was developed to detect abnormal process trends and identify the variables of greater impact when these anomalies arise. In the next stage, an algorithm was developed and implemented, based on the analysis of alarm streaks, to identify the system’s behavior and thus classify fluctuations into either normal operating condition drifts or system failures. The application of the proposed methodology with real operation data of the engine (JGS 612 GS-N. L) shows that the method outperforms operators in detecting and identifying faults, as it performs these tasks considerably earlier than operators

Framework for a space shuttle main engine health monitoring system

A framework developed for a health management system (HMS) which is directed at improving the safety of operation of the Space Shuttle Main Engine (SSME) is summarized. An emphasis was placed on near term technology through requirements to use existing SSME instrumentation and to demonstrate the HMS during SSME ground tests within five years. The HMS framework was developed through an analysis of SSME failure modes, fault detection algorithms, sensor technologies, and hardware architectures. A key feature of the HMS framework design is that a clear path from the ground test system to a flight HMS was maintained. Fault detection techniques based on time series, nonlinear regression, and clustering algorithms were developed and demonstrated on data from SSME ground test failures. The fault detection algorithms exhibited 100 percent detection of faults, had an extremely low false alarm rate, and were robust to sensor loss. These algorithms were incorporated into a hierarchical decision making strategy for overall assessment of SSME health. A preliminary design for a hardware architecture capable of supporting real time operation of the HMS functions was developed. Utilizing modular, commercial off-the-shelf components produced a reliable low cost design with the flexibility to incorporate advances in algorithm and sensor technology as they become available

A Realistic Simulation Testbed of A Turbocharged Spark-Ignited Engine System: A Platform for the Evaluation of Fault Diagnosis Algorithms and Strategies

Research on fault diagnosis on highly nonlinear dynamic systems such as the engine of a vehicle have garnered huge interest in recent years, especially with the automotive industry heading towards self-driving technologies. This article presents a novel opensource simulation testbed of a turbocharged spark ignited (TCSI) petrol engine system for testing and evaluation of residuals generation and fault diagnosis methods. Designed and developed using Matlab/Simulink, the user interacts with the testbed using a GUI interface, where the engine can be realistically simulated using industrial-standard driving cycles such as the Worldwide harmonized Light vehicles Test Procedures (WLTP), the New European Driving Cycle (NEDC), the Extra-Urban Driving Cycle (EUDC), and EPA Federal Test Procedure (FTP-75). The engine is modeled using the mean value engine model (MVEM) and is controlled using a proportional-integral (PI)-based boost controller. The GUI interface also allows the user to induce one of the 11 faults of interest, so that their effects on the performance of the engine are better understood. This minimizes the risk of causing permanent damages to the engine and shortening its lifespan, should the tests be conducted onto the actual physical system. This simulation testbed will serve 16 as an excellent platform where researchers can generate critical data to develop and compare current and future research methods for fault diagnosis of automotive engine systems.Comment: 64 pages, 23 figures, To appear in IEEE Control System

Langley aerospace test highlights, 1985

The role of the Langley Research Center is to perform basic and applied research necessary for the advancement of aeronautics and space flight, to generate new and advanced concepts for the accomplishment of related national goals, and to provide research advice, technological support, and assistance to other NASA installations, other government agencies, and industry. Significant tests which were performed during calendar year 1985 in Langley test facilities, are highlighted. Both the broad range of the research and technology activities at the Langley Research Center and the contributions of this work toward maintaining United States leadership in aeronautics and space research, are illustrated. Other highlights of Langley research and technology for 1985 are described in Research and Technology-1985 Annual Report of the Langley Research Center

Actuator Fault Diagnosis with Application to a Diesel Engine Testbed

This work addresses the issues of actuator fault detection and isolation for diesel engines. We are particularly interested in faults affecting the exhaust gas recirculation (EGR) and the variable geometry turbocharger (VGT) actuator valves. A bank of observer-based residuals is designed using a nonlinear mean value model of diesel engines. Each residual on the proposed scheme is based on a nonlinear unknown input observer and designed to be insensitive to only one fault. By using this scheme, each actuator fault can be easily isolated since only one residual goes to zero while the others do not. A decision algorithm based on multi-CUSUM is used. The performances of the proposed approach are shown through a real application to a Caterpillar 3126b engine