Measurements, Models, Systems and Design

531 s.

ReSCon '09, Research Student Conference: Book of Abstracts

The second SED Research Student Conference (ReSCon2009) was hosted over three days, 22-24 June 2009, in the Lecture Centre at Brunel University. The conference consisted of technical presentations, a poster session and social events. The abstracts and presentations were the result of ongoing research by postgraduate research students from the School of Engineering and Design at Brunel University. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School

DEVELOPING A BIOSENSOR WITH APPLYING KALMAN FILTER AND NEURAL NETWORK TO ANALYZE DATA FOR FUSARIUM DETECTION

Early detection of Fusarium is arduous and highly desired as the detection assists in protecting crops from the harmful potential of plant pathogens which affect the quality and quantity of agriculture products. The thesis work concentrates on searching an approach for Fusarium spore detection and developing portable, reliable and affordable Fusarium detection device. The system can also promptly and continuously sample and sense the presence of the fungus spores in the air. From the investigation of the Fusarium oxysporum Chlamydospores by ATR-FTIR spectroscopy, a distinct infrared spectrum of the Chlamydospore was collected. There are two typical infrared wavelengths can be used for Fusarium detection: 1054cm-1 (9.48µm) and 1642cm-1 (6.08µm). Infrared (IR) light is a form of electromagnetic wave which its wavelength ranges from around 0.75µm to 1000µm and it is invisible to human eyes. To be familiar with the light concepts and quantities, it is necessary to start working with the visible light which is also a form of electromagnetic wave with the wavelength range from about 0.3µm to 0.75µm. A visible spectrometer, which automatically corrects data error caused by unstable light, was built. By using the Kalman filter algorithm, Matlab simulations and training program, the appropriate coefficients to apply to the Kalman corrector were found. The experiments proved that the corrector in the visible spectrometer can reduce the data error in the spectra at the order of 10 times. From the knowledge of working with the visible spectrometer and visible light, the task of searching the detecting approach and building the device in the IR spectrum was reconsidered. The Fusarium detection device was successfully built. Among other components to build the device, there are two essential thermopiles and one infrared light source. The infrared light source emits an IR spectrum from 2µm to 22µm. The two thermopiles working on the IR wavelengths of λ1=6.09±0.06µm and λ2=9.49±0.44µm are used for Fusarium spore detection analysis. The Beer-Lambert assists in quantifying the number of spores in the sample. The group distinction coefficient supports in distinguishing the Fusarium spore from other particulates in the experiments (pollen, turmeric, and starch). Pollen was chosen as it is often present in crop fields, and the other two samples were chosen as they help to verify the work of the system. The group distinction coefficients of Fusarium (1.14±0.15), pollen (0.13±0.11), turmeric (0.79±0.07) and starch (0.94±0.07) are distinct from each other. The size of Fusarium spore is from about 10µm to 70µm. To mitigate the influence of the other particulates, such as pollens or dust which their sizes are not in the above range, a bandpass particle filter consists of a cyclone separator and a high voltage trap were designed and built. The particles with the sizes not in the interested range are eliminated by the filter. From simulations by the COMSOL Multiphysics and experiments, the particle filter proves that it works well with the assigned particle size range. The filter is useful as it helps to sample a certain size range which contains the interested bio objects. As other electronic devices, the Fusarium detection device encountered several common types of noises (thermal noise, burst noise, and background noise). These noises along with the thermopile signals are amplified by the amplifiers. These amplifiers have high gain coefficients to amplify weak signals in nV to µV in magnitude. These noises depend on the operating conditions such as power supplies or environment temperature. If the operating conditions can be monitored, the information of the conditions can be used to correct the error data. To perform the correction task, the neural network was selected. To make a NN working, it requires sufficient data to train. In this research, the training data were collected in one week to record as much as possible working conditions. In addition to the thermopile data, the training data also included the environment temperature and the 5V and 9V voltage-regulator data. Then, the trained NN was applied to fix error data. The contribution of this NN method is the use of operating conditions to fix error data. Although the errors in the data can be corrected well by the trained NN, several other problems still exist. In the samples of Fusarium, starch, pollen, and turmeric, the group-distinction coefficients of Fusarium and starch are very similar. To distinguish better the samples with similar group distinction coefficients, the existing Fusarium detection device was upgraded with a broadband thermopile. The extra thermopile was used along with λ1 and λ2 thermopiles to analyze the reflecting IR light of the samples. To pre-process the thermal noise and burst noise, an adaptive and cognitive Kalman algorithm was proposed. Burst noise is expressed in the form of outliers in the thermopile data. To detect these outliers, a mechanism of using first-order and second-order discrete differentiation of the data and correcting the burst noise and thermal noise was introduced. To study the effectiveness of this pre-processing, the pre-processed data and raw data were applied in the NN training. The main stopping parameters in the training are the number of epochs, absolute mean error, and entropy. The pre-processed data and the trained NN were used for distinguishing samples. The three-thermopile Fusarium detection device led to a use of a validation area to distinguish the samples with similar group-distinction coefficients. The results prove that the use of three thermopiles works very well. The research provides a comprehensive approach of designing system, particulate sampling, particulate filtering, signal processing, and sample distinguishing. The results from the experiments prove that the proposed approach can detect not only Fusarium but also many other different bio-objects. For further work from this research, the Fusarium detection apparatus should be tested in the crop fields infected by Fusarium spores. The outcomes of the research can be applied in other areas such as food safety and human living or hospital environment to detect not only Fusarium spores but the other pathogens, spores, and mold

Design/cost tradeoff studies. Appendix A. Supporting analyses and tradeoffs, book 2. Earth Observatory Satellite system definition study (EOS)

Attitude reference systems for use with the Earth Observatory Satellite (EOS) are described. The systems considered are fixed and gimbaled star trackers, star mappers, and digital sun sensors. Covariance analyses were performed to determine performance for the most promising candidate in low altitude and synchronous orbits. The performance of attitude estimators that employ gyroscopes which are periodically updated by a star sensor is established by a single axis covariance analysis. The other systems considered are: (1) the propulsion system design, (2) electric power and electrical integration, (3) thermal control, (4) ground data processing, and (5) the test plan and cost reduction aspects of observatory integration and test

Resilient Microgrids Using a State Controller

Wind energy technology is fast becoming a major component of renewable energy deployment in electric grids. This technology however, has a major challenge of low machine inertia that could impact the frequency stability of the system when deployed in microgrids. The frequency response rate to abrupt load changes becomes an issue when many wind turbines are connected in a microgrid. This dissertation investigates the impact of this low machine inertia on the nominal frequency and voltage of a microgrid. The impact of varying wind conditions on the electrical power output is also studied. The system is modelled in MATLAB/Simulink using a DFIG wind turbine rated at 1.5 MVA. This thesis studies control strategies to bring the system to a stability irrespective of the wind speeds, load conditions or perturbations. This work further focuses on how the state controller is used to improve the power system reliability, availability and resilience during extreme events such as hurricanes, earthquakes and wildfires

Application of advanced on-board processing concepts to future satellite communications systems

An initial definition of on-board processing requirements for an advanced satellite communications system to service domestic markets in the 1990's is presented. An exemplar system architecture with both RF on-board switching and demodulation/remodulation baseband processing was used to identify important issues related to system implementation, cost, and technology development

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

Time-dependent spectrum analysis of high power gyrotrons

In this work, a novel measurement system for the analysis of the gyrotron RF output spectrum was developed. It enables unprecedented time dependent measurements within a large bandwidth, dynamic range and unambiguous RF indication in the entire D-Band (110-170 GHz). Special attention was given to the investigation of parasitic RF oscillations, and the analysis of the interplay of thermal cavity expansion and ionization-based space charge neutralization at the start of long RF pulses

Bibliography of Lewis Research Center technical publications announced in 1985

This compilation of abstracts describes and indexes the technical reporting that resulted from the scientific and engineering work performed and managed by the Lewis Research Center in 1985. All the publications were announced in the 1985 issues of STAR (Scientific and Technical Aerospace Reports) and/or IAA (International Aerospace Abstracts). Included are research reports, journal articles, conference presentations, patents and patent applications, and theses

Advanced Modeling, Control, and Optimization Methods in Power Hybrid Systems - 2021

The climate changes that are becoming visible today are a challenge for the global research community. In this context, renewable energy sources, fuel cell systems and other energy generating sources must be optimally combined and connected to the grid system using advanced energy transaction methods. As this reprint presents the latest solutions in the implementation of fuel cell and renewable energy in mobile and stationary applications such as hybrid and microgrid power systems based on the Energy Internet, blockchain technology and smart contracts, we hope that they will be of interest to readers working in the related fields mentioned above