Adaptive Signal Decomposition Methods for Vibration Signals of Rotating Machinery

Vibration‐based condition monitoring and fault diagnosis are becoming more common in the industry to increase machine availability and reliability. Considerable research efforts have recently been directed towards the development of adaptive signal processing methods for fault diagnosis. Two adaptive signal decomposition methods, i.e. the empirical mode decomposition (EMD) and the local mean decomposition (LMD), are widely used. This chapter is intended to summarize the recent developments mostly based on the authors’ works. It aims to provide a valuable reference for readers on the processing and analysis of vibration signals collected from rotating machinery

Novel CMOS RFIC Layout Generation with Concurrent Device Placement and Fixed-Length Microstrip Routing

With advancing process technologies and booming IoT markets, millimeter-wave CMOS RFICs have been widely developed in re- cent years. Since the performance of CMOS RFICs is very sensi- tive to the precision of the layout, precise placement of devices and precisely matched microstrip lengths to given values have been a labor-intensive and time-consuming task, and thus become a major bottleneck for time to market. This paper introduces a progressive integer-linear-programming-based method to gener- ate high-quality RFIC layouts satisfying very stringent routing requirements of microstrip lines, including spacing/non-crossing rules, precise length, and bend number minimization, within a given layout area. The resulting RFIC layouts excel in both per- formance and area with much fewer bends compared with the simulation-tuning based manual layout, while the layout gener- ation time is significantly reduced from weeks to half an hour.Comment: ACM/IEEE Design Automation Conference (DAC), 201

Progress Towards Determining the Density Dependence of the Nuclear Symmetry Energy Using Heavy-Ion Reactions

The latest development in determining the density dependence of the nuclear symmetry energy using heavy-ion collisions is reviewed. Within the IBUU04 version of an isospin- and momentum-dependent transport model using a modified Gogny effective interaction, recent experimental data from NSCL/MSU on isospin diffusion are found to be consistent with a nuclear symmetry energy of $E_{sym}(\rho)\approx 31.6(\rho /\rho_{0})^{1.05}$ at subnormal densities. Predictions on several observables sensitive to the density dependence of the symmetry energy at supranormal densities accessible at GSI and the planned Rare Isotope Accelerator (RIA) are also made.Comment: 10 pages. Talk given at the 21st Winter Workshop on Nuclear Dynamics, Breckenridge, Colorado, USA, Feb. 5-12, 2005. To appear in Heavy-Ion Physics (2005

High performance absorption algorithms for terminological reasoning in description logics

When reasoning with description logic (DL) knowledge bases (KBs) which contain a large number of axioms, performance is the key concern in real applications. To improve the performance, axiom absorption has been a central research issue in DL KBs. Well-known algorithms for axiom absorption, however, still heavily depend on the order and the format of the axioms occurring in the target KB. In addition, in many cases, there exist some restrictions in these algorithms which prevent axioms from being absorbed. Both the characteristics and the design of absorption algorithms for optimal reasoning are still open problems. In this thesis, we first seek to improve our theoretical understanding about the axiom absorption techniques including some related techniques such as simplification and normalization. Then we propose a criterion for the "best" absorption against experimental experience. Based on this criterion, we develop some new algorithms to absorb axioms in a KB to ameliorate the reasoning performance. The experimental tests we conducted are mostly based on synthetic benchmarks derived from common cases will occur in real KBs. The experimental evaluation demonstrates a significant runtime improvement