Behaviour of Flush End-Plate Connection for Perforated Section

De’nan, Fatimah; Naaim, Nurfarhah; Leong, Lai Chun

doi:10.26480/gwk.01.2017.11.20

Cited by 4 publications

(2 citation statements)

References 13 publications

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“…Therefore, based on the above research status, an early fault model is built based on the evolution principle of the short-circuit fault of the transmission line and combined with the fault characteristics of the early fault [16]. In addition, the various states of the ship transmission line are simulated and analysed combined with the early fault module, the original short circuit module and the load module [17,18].…”

Section: State Of the Artmentioning

confidence: 99%

Simulation Model and State Analysis of Ship Transmission Line

Xu²,

2018

Polish Maritime Research

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In order to discuss the simulation model of the ship transmission line and the state of the transmission line, an early fault model is built according to the evolution principle of the short circuit fault of the transmission line and combining with the fault characteristics of the early fault. A small distributed ship transmission line system is built in MATLAB/ Simulink. Then, combined with the constructed fault module, the original short circuit module, and the load module, the various states (normal state, early fault state, severe early fault state, short circuit state) of the ship transmission line are stimulated, and the features of voltage signal in each state is analysed. It is concluded that, due to the normal operation of the ship transmission line system, the variation characteristics of the flow signal and voltage signal caused by the sudden load mutation, that is, the sudden load and the sudden increase load, are very similar to the changes caused by the early fault. Therefore, in order to find a more accurate early fault detection method, the state is divided into normal state, sudden load state, sudden increase and sudden decrease load state.

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Section: State Of the Artmentioning

confidence: 99%

Simulation Model and State Analysis of Ship Transmission Line

Xu²,

2018

Polish Maritime Research

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“…Over the years, many scholars have proposed some new ideas and methods for accurate mineral grade assessment, many of which are based on chemical or physical test equipment to obtain the data for ingredient grade analysis (Kameshwara, Rao, & Narayana, 2014;De'nan, Naaim, & Leong, 2017). Therefore, the accuracy of the data used for ore composition analysis is critical to the ore grade analysis.…”

Section: Introductionmentioning

confidence: 99%

Online Outlier Detection for Time-varying Time Series on Improved ARHMM in Geological Mineral Grade Analysis Process

Zhao¹,

Zhoub²,

Su³

et al. 2017

Earth sci. res. j.

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Given the difficulty of accurate online detection for massive data collecting real-timely in a strong noise environment during the complex geological mineral grade analysis process, an order self-learning ARHMM (Autoregressive Hidden Markov Model) algorithm is proposed to carry out online outlier detection in the geological mineral grade analysis process. The algorithm utilizes AR model to fit the time series obtained from "Online x -ray Fluorescent Mineral Analyzer" and makes use of HMM as a basic detection tool, which can avoid the deficiency of presetting the threshold in traditional detection methods. The structure of traditional BDT (Brockwell-Dahlhaus-Trindade) algorithm is improved to be a double iterative structure in which iterative calculation from both time and order is applied respectively to update parameters of ARHMM online. With the purpose of reducing the influence of outlier on parameter update of ARHMM, the strategies of detection-before-update and detection-based-update are adopted, which also improve the robustness of the algorithm. Subsequent simulation by model data and practical application verify the accuracy, robustness, and property of online detection of the algorithm. According to the result, it is obvious that new algorithm proposed in this paper is more suitable for outlier detection of mineral grade analysis data in geology and mineral processing. Existe gran dificultad para la detección en tiempo real para series de datos masivos con altos niveles de ruido de valores atípicos. Se propone un algoritmo de autoaprendizaje ARHMM (Modelo autoregresivo oculto de Markov) para llevar a cabo la detección de dichos valores atípicos en el proceso de análisis del grado mineral geológico. El algoritmo usa un modelo AR para ajustar la serie de tiempo obtenida del "analizador de fluorescencia de rayos X" y hace uso del HMM como una herramienta básica de detección, la cual puede evitar la deficiencia de predeterminar el umbral en métodos tradicionales de detección. Para actualizar los parámetros del ARHMM en tiempo real, la estructura del algoritmo BDT (Brockwell-Dahlhaus-Trindade) tradicional se mejora para ser una doble estructura iterativa en la que se aplica el cálculo iterativo en tiempo y en orden respectivamente. Con el propósito de reducir la influencia de valores atípicos (o extremos) en la actualización del parámetro de ARHMM, se adoptan las estrategias de detección-antes-que-actualización y la detección-basada-en-actualización, lo que también aumenta la robustez del algoritmo. La subsiguiente simulación por modelos de datos y aplicación práctica comprueba la precisión, fortaleza y capacidad de la detección en línea del algoritmo. De acuerdo con el resultado, es evidente que el nuevo algoritmo propuesto en este artículo es más apropiado para la detección de datos de valores atipicos para el análisis del grado mineral en geología y el procesamiento mineral. ABSTRACT RESUMEN IntroductionMineral composition analysis is a key factor in determining whether or not to carry out mining. Over t...

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Metal doped manganese oxide octahedral molecular sieve catalysts for degradation of diclofenac in the presence of peroxymonosulfate

Shi

Deng

2018

Arabian Journal of Chemistry

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Behaviour of Flush End-Plate Connection for Perforated Section

Cited by 4 publications

References 13 publications

Simulation Model and State Analysis of Ship Transmission Line

Simulation Model and State Analysis of Ship Transmission Line

Online Outlier Detection for Time-varying Time Series on Improved ARHMM in Geological Mineral Grade Analysis Process

Metal doped manganese oxide octahedral molecular sieve catalysts for degradation of diclofenac in the presence of peroxymonosulfate

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