New initial position detection technique for three-phase brushless DC motor without position and current sensors

This paper presents a new detection technique of initial position for a three-phase brushless DC motor which does not require any current and position sensors, and thereby significantly reduces the cost. The fundamental principle of the technique is to determine the initial position of the permanent magnet by the time periods of discharge of stator windings, which are excited before discharge. As compared to previous approaches, the presented technique does not cause any rotation during detection, and it is therefore very promising for particular kinds of applications, which do not allow the motor to rotate potentially in the wrong direction during initial position detection, e.g., electrical vehicles. As compared to earlier techniques, the presented technique dramatically simplifies the detection procedures and cost. Experimental results derived from a field-programmable gate-array-based control system are presented to demonstrate the feasibility of the presented technique.     

Diverse reasoning in automated model formulation

Diverse reasoning supports a dynamic integration of various reasoning methods in a computerized system. This paper describes a control blackboard approach to simulate the control features observed in the expert's model formulation protocols. The diverse reasoning concept is incorporated so that the model formulation process is dynamically in a plan-directed, action-directed, or data-directed fashion. The diverse reasoning concept facilitates the control features simulation. By analyzing the diverse reasoning behavior in the proposed system, this paper contributes to a better understanding of and support to the modeling process for the design of intelligent decision support systems. The usefulness of the prototype system is also evaluated using an empirical experiment.     

Product family modeling for mass customization

With growing reliance on modeling in product development, it is imperative to describe product families in a cohesive way. In particular, mass customization calls for a close integration of product life cycle from customer recognition to delivery and services. This paper proposes a triple-view scheme for modeling product families. Technical challenges are discussed by comparing product family modeling with modeling single products. Individual modeling formalisms for different views are discussed. An example of product family modeling in power supply design is presented to illustrate the feasibility and potential of the proposed approach.     

Modeling and Simulation of Porous Elastoviscoplastic Material

Many materials exhibit elasto–visco–plastic behavior when subjected to loadings with certain strain rate. Examples include natural materials such as metals, clays, and soils and manmade materials such as some biomimic materials. Some voids may exist or be introduced in these materials. The effects of the voids on the material response are important in predicting the strength, reliability, and service life of structural systems containing these materials. This paper presents the results of applying a statistical micromechanical approach to describe the macroscopic behavior of elasto–visco–plastic materials containing many randomly dispersed spherical voids. Most existing micromechanics based models are only applicable to monotonic proportional loadings. The limitation is removed by integrating the material model into the framework of continuum plasticity. With the discrete integration algorithm and local return mapping algorithm, the proposed computation method is applicable to any loading and unloading histories and is ready for implementing into finite element analysis.     

Performance comparison between the training method and the numerical method of the orthogonal neural network in function approximation

The orthogonal neural network is a recently developed neural network based on the properties of orthogonal functions. It can avoid the drawbacks of traditional feedforward neural networks such as initial values of weights, number of processing elements, and slow convergence speed. Nevertheless, it needs many processing elements if a small training error is desired. Therefore, numerous data sets are required to train the orthogonal neural network. In the article, a least‐squares method is proposed to determine the exact weights by applying limited data sets. By using the Lagrange interpolation method, the desired data sets required to solve for the exact weights can be calculated. An experiment in approximating typical continuous and discrete functions is given. The Chebyshev polynomial is chosen to generate the processing elements of the orthogonal neural network. The experimental results show that the numerical method in determining the weights gives as good performance in approximation error as the known training method and the former has less convergence time. © 2004 Wiley Periodicals, Inc. Int J Int Syst 19: 1257–1275, 2004.     

Rare earth element cerium substituted Ca–Si–Mg system bioceramics: From mechanism to mechanical and degradation properties

Cerium (Ce)-substituted diopsides (CaMgSi₂O₆) with enhanced mechanical strength and bioactivity were fabricated by precipitation method, followed by annealing at 1000 °C for 4 h. The mineralogical, morphological, in vitro biomineralization, degradation, and mechanical properties were investigated in order to assess the factors and mechanisms affecting the resultant properties. The X-ray diffractometer results showed that the onset of substitutional solid solubility in 0.25 mol Ce would result in new phase formation (cerium dioxide [CeO₂], and magnesium silicate [MgSiO₃]) further causing lattice instability. With increasing Ce dopant levels to 1.00 mol, the initial CaMgSi₂O₆ phase was completely replaced by new phases. The field-emission scanning electron microscopy results indicated that the 0.25 mol Ce had the best biomineralization performance in vitro, while less hydroxyapatite precipitates were found with further increasing Ce dopant levels, suggesting the new phases led to the hindrance of precipitates. The weight loss values indicated that the high dissolution rate of ions in the matrix was observed in the pure sample, while the high readsorption rate of ions in the simulated body fluid (SBF) occurred with increasing Ce dopant levels. The pH value and the inductively coupled plasma-mass spectrometer results suggested that the release of Ca and Mg ions controlled the pH value. The mechanical strength of matrices before SBF immersion was related to the phase transformation, the elastic modulus of CeO₂ and CaMgSi₂O₆, and the release of Mg ions, while the mechanical strength of matrices after SBF immersion was dominated by the structure of matrices.     

Big label: categorizing the Web efficiently and accurately

Searching on the Web has never been an easy task. Even if semantic information is successfully inferred from a user query, how can we benefit from it? The most popular remedy today is to categorize the Web in advance. By gathering similar Web resources into a group, the search performance should increase even though search engines still have little idea about the semantics part. To categorize a set of Web resources according to meta-information associated with them, at first, one has to analyze the relationships between meta-information and Web resources. However, the result will be severely affected by the ambiguous nature of the Web. As a result, the goal of this research is to propose a new labeling method to enhance both the efficiency and accuracy of Web resources categorization.     

An experimental model of Chinese textual database

Abstract

A textual database deals with retrieval and manipulation of documents. It allows a user to search on‐line complete documents or parts of documents rather than attributes of documents. Resembling a formatted database which uses a data model as its underlying structure, a textual database has to base its development upon a document model. In this paper, a document model, called the ECHO model, is proposed. The ECHO model provides a document representation, called the ECHO structure, for expressing documents and operations on the representation that serve to express queries and manipulations on documents. It has the ability to provide multiple document structures for a document, a flexible search unit for retrieving textual information, and a subrange search on a textual database. In addition, the ECHO structure is relatively easy to maintain. An architecture of a textual database based on the ECHO model is also proposed. In order to improve the query performance, a refined character inversion method, called ARCIM, is proposed as the text‐access method of the Chinese textual database. The ARCIM can retrieve texts faster than a simple inversion method and requires less space overhead.