Evaluation of a Bespoke Antarctic Meteorite Detection System in Polar Operating Conditions

2020 ◽  
Author(s):  
Liam A Marsh ◽  
Wouter van Verre ◽  
John Wilson ◽  
Geoffrey W Evatt ◽  
Anthony J Peyton
Keyword(s):  
Detection System ◽  
Operating Conditions

Fuzzy ignition timing control for a spark ignition engine

2000 ◽  
Vol 214 (3) ◽  
pp. 297-306 ◽  
Author(s):  
W Wang ◽  
E. C. Chirwa ◽  
E Zhou ◽  
K Holmes ◽  
C Nwagboso
Keyword(s):  
Fuzzy Logic ◽  
Detection System ◽  
Open Loop ◽  
Operating Conditions ◽  
Spark Ignition Engine ◽  
Coolant Temperature ◽  
Optimum Level ◽  
Ignition Timing ◽  
Timing Control ◽  
Engine Design

It is well known that the optimum ignition timing, which gives the maximum brake torque (MBT) for a given engine design, varies with the rate of flame development and propagation in the cylinder. This depends, among other factors, on engine design and operating conditions, and on the properties of the air-fuel mixture. In modern engines the ignition timing is generally controlled by fixed open-loop schedules as functions of engine speed, load and coolant temperature. It is desairable that this ignition timing can be adjusted to the optimum level producing the best torque to obtain minimum fuel consumption and maximum available power. This paper presents an ignition timing control system based on fuzzy logic theory. A pressure sensor system ws developed for the determination of combustion parameters and ignition control on a Ford 1600cm3 four-cylinder engine fuelled with natural gas. Several tests were carried out in optimizing the pressure detection system. The results obtained provide important information compatible with intelligent control of the engine using fuzzy logic technology. Moreover, tests carried out to date using this technology show good results that fit quite well with the original engine output torque characteristics.

scholarly journals Reliability of the Determinations of Polychlorinated Contaminants (Biphenyls, Dioxins, Furans)

1996 ◽  
Vol 79 (3) ◽  
pp. 589-621 ◽  
Author(s):  
William Horwitz ◽  
Richard Albert
Keyword(s):  
Performance Studies ◽  
Detection System ◽  
Operating Conditions ◽  
Mass Spectrometers ◽  
Common Reference ◽  
Ring Compounds ◽  
Interlaboratory Variability ◽  
Dioxins And Furans ◽  
Relative Standard ◽  
Good Laboratory

Abstract Precision performance parameters from results of 34 interlaboratory performance studies of polychlorinated aromatic ring compounds (biphenyls, dioxins, and furans) (PCCs) have been recalculated by using the International Union of Pure and Applied Chemistry-1987 harmonized protocol. Most studies of 1052 test samples, 56 analytes, 19 matrixes, and 2 types of detectors (electron capture and mass spectrometers) provide among-laborato- ries relative standard deviations (RSDRs), that are considerably better than those predicted from the Horwitz equation at fractional concentrations of 10−6 down to 10−15. The explanation suggested is that supplying common reference calibration solutions, as was done in many of these studies, does not reflect realistic operating conditions. Furthermore, the ability to repeat, discuss, and reassess aberrant reported values results in underestimating the true RSDR. The commonly reported problems of preparation of standard calibrating solutions, instability of the detection system, and failure to follow quality control instructions and good laboratory practices may be important sources of interlaboratory variability in PCC determinations

Improved Leak Detection by Method Diversity

1998 ◽  
Author(s):  
Ruprecht M. J. Pichler
Keyword(s):  
Transient Flow ◽  
Detection System ◽  
Type System ◽  
Leak Detection ◽  
Operating Conditions ◽  
Detection Methods ◽  
Special Focus ◽  
Oil Pipeline ◽  
Knowledge Based ◽  
Noise Factors

Leak detection systems for liquid pipelines are installed to minimize spillage in case of a leak. Therefore reliability, sensitivity and detection time under practical operating conditions are the most important parameters of a leak detection system. Noise factors to be considered among others are unknown fluid property data, friction factor, instrument errors, transient flow, slack-line operation and SCADA update time. The opening characteristics and the size of leaks differ considerably from case to case. Each software-based leak detection method available today has its particular strength. As long as just one or two of these methods are applied to a pipeline a compromise has to be found for the key parameters of the leak detection system. The paper proposed illustrates how a combination of several different software-based leak detection methods together with observer-type system identification and a knowledge-based evaluation can improve leak detection. Special focus is given to leak detection and automated leak locating under transient flow conditions. Practical results are shown for a crude oil pipeline and a product pipeline.

Hybrid Kalman Filter Approach for Aircraft Engine In-Flight Diagnostics: Sensor Fault Detection Case

2006 ◽  
Author(s):  
Takahisa Kobayashi ◽  
Donald L. Simon
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
Linear Models ◽  
Detection System ◽  
Piecewise Linear ◽  
Diagnostic System ◽  
Aircraft Engine ◽  
Operating Conditions ◽  
Sensor Fault ◽  
Sensor Fault Detection

In this paper, a diagnostic system based on a uniquely structured Kalman filter is developed for its application to inflight fault detection of aircraft engine sensors. The Kalman filter is a hybrid of a nonlinear on-board engine model (OBEM) and piecewise linear models. The utilization of the nonlinear OBEM allows the reference health baseline of the diagnostic system to be updated, through a relatively simple process, to the health condition of degraded engines. Through this health baseline update, the diagnostic effectiveness of the in-flight sensor fault detection system is maintained as the health of the engine degrades over time. The performance of the sensor fault detection system is evaluated in a simulation environment at several operating conditions during the cruise phase of flight.

Corona Detection System on Insulators via Acoustic Emissions

2012 ◽  
Vol 260-261 ◽  
pp. 379-384
Author(s):  
Marco Antônio Martins Rennó ◽  
Erik Leandro Bonaldi ◽  
Levy Ely Lacerda Oliveira ◽  
Jonas Guedes Borges Silva ◽  
Germano Lambert-Torres
Keyword(s):  
Climate Change ◽  
Quality Of Service ◽  
Transmission Lines ◽  
Detection System ◽  
Low Cost ◽  
Acoustic Emissions ◽  
Computer Programs ◽  
Operating Conditions ◽  
Operational Capacity

This paper presents a computational package and equipment with the purpose to detect corona problems of insulators in transmission lines. Low-cost equipment detects presence of corona, via acoustic emissions and stores them in a memory. These data are processed by computer programs. The applicability of this equipment is immediate for any transmission company, because the perfect understanding of the operational capacity of its lines in various operating conditions and climate change allows for a safer operation with improvement of quality of service provided.

Formulation and Analysis of the Probability of Detection and False Detection for Subsea Leak Detection Systems

2014 ◽  
Author(s):  
Alireda Aljaroudi ◽  
Faisal Khan ◽  
Ayhan Akinturk ◽  
Mahmoud Haddara ◽  
Premkumar Thodi
Keyword(s):  
Oil And Gas ◽  
Detection System ◽  
Oil And Gas Industry ◽  
Leak Detection ◽  
Probability Of Detection ◽  
Operating Conditions ◽  
False Detection ◽  
Potential Threat ◽  
Probability Of False Alarm ◽  
Detection Systems

Insuring the integrity of subsea process component is one of the primary business objectives for oil and gas industry. One of the systems used to insure reliability of a pipeline, is the Leak Detection System (LDS). Different leak detection systems use different technologies for detecting and locating leaks that could result from pipelines. One technology in particular that is gaining wide acceptance by the industry is the optical leak detection systems. This technology has great potential for subsea pipelines applications. It is the most suited for underwater applications due to the ease of installation and reliable sensing capabilities. Having pipelines underwater in the deep sea present a greater challenge and a potential threat to the environment and operation. Thus, there is a need to have a reliable and effective system to provide the assurances that the monitored subsea pipeline is safe and functioning as per operating conditions. Two important performance parameters that are of concern to operators are the probability of detection and probability of false alarm. This article presents a probabilistic formulation of the probability of detection and probability of false detection for fiber optic LDS based systems.

scholarly journals A Fault Detection System for The Yaw Control of A HAWT Based on Neural Networking

2021 ◽  
Vol 85 (1) ◽  
pp. 135-142
Author(s):  
Ahmed R. El-Mallawany ◽  
Sameh Shaaban ◽  
Aida Abdel Hafiz
Keyword(s):  
Fault Detection ◽  
Wind Turbine ◽  
Detection System ◽  
Operating Conditions ◽  
Horizontal Axis Wind Turbine ◽  
Yaw Control ◽  
Detection Approach ◽  
Simulation Results ◽  
Early Fault Detection ◽  
The Time Domain

The objective of the yaw control system in a horizontal axis wind turbine (HAWT) is to follow the wind direction with a minimum error. In this paper, a data driven fault detection approach of a HAWT is applied. Three simulation programs were utilized in order to model a 1.5 MW HAWT. These programs are Fatigue, Aerodynamics, Structures, and Turbulence(FAST), TurbSim, and MATLAB. The approach is implemented under normal operating scenarios while considering different wind velocities. Different kinds of faults were applied to the system for a nacelle-yaw angle error ranging from -10° to +20°. The simulation results of the Tower Top Deflection (TTD) in the time domain were transferred into frequency domain by Fast Fourier Transform (FFT). The output variables were used in order to build a Neural Networking, which will monitor the performance of the wind turbine. The built Neural Networking will also provide an early fault detection to avoid the operating conditions that lead to sudden turbine breakdown. The present work provides initial results that are useful for remote condition monitoring and assessment of a 1.5MW HAWT. The simulation results indicate that the implemented Neural Networking can achieve improvement of the wind turbine operation and maintenance level.

Latest Trends in Pig Detection System

2021 ◽  
Author(s):  
Jagannath Mondal ◽  
Devarajan Umakanth ◽  
Raju Paul ◽  
Faris Ragheb Kamal
Keyword(s):  
Detection System ◽  
Operating Conditions ◽  
Process Safety ◽  
Human Intervention ◽  
End User ◽  
Start Up ◽  
Water Pipeline ◽  
Integrity Assurance ◽  
Oil Gas ◽  
Safe Operating

Abstract Pig detector plays an important role in the Commissioning and handover of Pipelines project. This paper addresses the latest trends in Pig Detectors. In addition, this paper covers the commissioning challenges and mitigations in major Offshore Brownfield Project involving new pipelines with 80 nos of Pig Detectors and accessories. Pipelines represent a considerable investment on behalf of the End User and can often prove strategic to countries and governments. Pipelines are generally accepted as being the most efficient method of transporting fluids across distances. Pipelines transport various kinds of fluids viz. oil, gas, multiphase, water. Pipeline pigging is an important operation for enhancing reliability and durability of pipeline, adopted worldwide. It has a major impact on the operational and technical integrity of a pipeline. Pigging Operation is high-risk activity in-terms of process safety. The Pigging can be safely initiated only when safe operating conditions are maintained at both ends of pipeline. Pigging involves human intervention and thus increasing personnel risk. Pipeline pigging operations is performed during pre-commissioning, start-up, normal operations and integrity assurance.

Hybrid Kalman Filter Approach for Aircraft Engine In-Flight Diagnostics: Sensor Fault Detection Case

2006 ◽  
Vol 129 (3) ◽  
pp. 746-754 ◽  
Author(s):  
Takahisa Kobayashi ◽  
Donald L. Simon
Keyword(s):  
Kalman Filter ◽  
Fault Detection ◽  
Linear Models ◽  
Detection System ◽  
Piecewise Linear ◽  
Diagnostic System ◽  
Aircraft Engine ◽  
Operating Conditions ◽  
Sensor Fault ◽  
Sensor Fault Detection

In this paper, a diagnostic system based on a uniquely structured Kalman filter is developed for its application to in-flight fault detection of aircraft engine sensors. The Kalman filter is a hybrid of a nonlinear on-board engine model (OBEM) and piecewise linear models. The utilization of the nonlinear OBEM allows the reference health baseline of the diagnostic system to be updated, through a relatively simple process, to the health condition of degraded engines. Through this health baseline update, the diagnostic effectiveness of the in-flight sensor fault detection system is maintained as the health of the engine degrades over time. The performance of the sensor fault detection system is evaluated in a simulation environment at several operating conditions during the cruise phase of flight.

A manganese porphyrin-based sensor for flow-injection potentiometric determination of thiocyanate

2010 ◽  
Vol 14 (02) ◽  
pp. 158-165 ◽  
Author(s):  
Saeed S. Beheshti ◽  
Fatemeh Sohbat ◽  
Mohammad K. Amini
Keyword(s):  
Flow Injection ◽  
Detection System ◽  
Operating Conditions ◽  
Potentiometric Determination ◽  
Membrane Composition ◽  
Manganese Porphyrin ◽  
Batch Mode ◽  
Nernstian Slope ◽  
Electrode Membrane

Metalloporphyrin-based ion-selective electrodes for flow-injection potentiometric determination of thiocyanate are described. The detection system is based on a coated glassy carbon electrode membrane sensor incorporating 5,10,15,20-tetraphenyl-21H,23H-porphine manganese(III) chloride as the active ingredient. The influences of the membrane composition, pH, and the effects of flow-injection parameters on the response of the system were investigated. At the optimized flow-injection potentiometric conditions, the sensor exhibited a Nernstian slope of -58.0 mV per decade of thiocyanate activity over the range 4.2 × 10-7–7.6 × 10-2M , where 50 μL of each sample solution was injected into the carrier solution. The detection limit of thiocyanate in the FIP mode was 4.2 × 10-7M . The selectivity of the flow-injection potentiometric system with respect to several common inorganic and organic anions was superior to that of the batch mode using the same sensor and similar operating conditions. The sensor was applied to the determination of thiocyanate in urine samples.

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