风缸自动焊控制系统的研制

简要介绍了采用ＰＬＣ 为控制核心的风缸自动焊控制系统的软件和硬件，并探讨了自动焊控制系统中的电机调速电路，该控制系统在实际生产中的应用表明：控制系统软硬件设计合理，具有较高的可靠性。

基于PLC的工业机床自动控制系统设计

由于现有工业机床自动控制系统在进行自动化生产时,由于未能有效进行机床参数控制,导致出现加工速度慢的情况,因此,基于可编程逻辑控制器(PLC),对工业机床自动控制系统进行设计。在系统硬件设计方面,根据工业机床运行要求优化电路电源,利用半闭环控制模式优化传动电路,实现PLC控制器的选取;在系统软件设计方面,采用PLC技术改变工业机床的原始参数,并利用T指令来扫描PLC产品中的机床型号,实现自动控制方式的合理选择,基于此,在TABLE中完成转换后的机床检索,由此实现工业机床的自动控制过程。通过实验对比得到结果,证明所设计的基于PLC的工业机床自动控制系统加工速度最快,具有一定的高效性。

Design and analysis of singal conditioning circuit for vibration sensor

A piezoelectric sensor charge/voltage conversion circuit is designed based on the principle that piezoelectric sensor can convert the vibration or shock acceleration into the charge proportionally.Effect of temperature characteristic of feedback capacitor on the switching circuit output is analyzed based on the acquisition and measurement system in this paper.The characteristics of different filters are analyzed,and the corresponding filter circuit is configured according to the actual sensor bandwidth.Experiments show that the circuit can effectively filter out noises among the vibration signal and obtain vibration signal accurately.

Shadow obstacle model for realistic corner-turning behavior in crowd simulation

This paper describes a novel model known as the shadow obstacle model to generate a realistic comer-tuming behavior in crowd simulation. The motivation for this model comes from the observation that people tend to choose a safer route rather than a shorter one when turning a comer. To calculate a safer route, an optimization method is proposed to generate the corner-turning rule that maximizes the viewing range for the agents. By combining psychological and physical forces together, a full crowd simulation framework is established to provide a more realistic crowd simulation. We demonstrate that our model produces a more realistic comer-turning behavior by comparison with real data obtained from the experiments. Finally, we per- form parameter analysis to show the believability of our model through a series of experiments.

Fast implementation of kernel simplex volume analysis based on modified Cholesky factorization for endmember extraction

Endmember extraction is a key step in the hyperspectral image analysis process. The kernel new simplex growing algorithm （KNSGA）, recently developed as a nonlinear alternative to the simplex growing algorithm （SGA）, has proven a promising endmember extraction technique. However, KNSGA still suffers from two issues limiting its application. First, its random initialization leads to inconsistency in final results; second, excessive computation is caused by the iterations of a simplex volume calculation. To solve the first issue, the spatial pixel purity index （SPPI） method is used in this study to extract the first endrnember, eliminating the initialization dependence. A novel approach tackles the second issue by initially using a modified Cholesky fac- torization to decompose the volume matrix into triangular matrices, in order to avoid directly computing the determinant tauto- logically in the simplex volume formula. Theoretical analysis and experiments on both simulated and real spectral data demonstrate that the proposed algorithm significantly reduces computational complexity, and runs faster than the original algorithm.

A survey of photon mapping state-of-the-art research and future challenges

Global illumination is the core part of photo-realistic rendering. The photon mapping algorithm is an effective method for computing global illumination with its obvious advantage of caustic and color bleeding rendering. It is an active research field that has been developed over the past two decades. The deficiency of precise details and efficient rendering are still the main challenges of photon mapping. This report reviews recent work and classifies it into a set of categories including radiance estimation, photon relaxation, photon tracing, progressive photon mapping, and parallel methods. The goals of our report are giving readers an overall introduction to photon mapping and motivating further research to address the limitations of existing methods.

Thermal energy harvesting circuit with maximum power point tracking control for self-powered sensor node applications

We present a simple implementation of a thermal energy harvesting circuit with the maximum power point tracking（MPPT） control for self-powered miniature-sized sensor nodes. Complex start-up circuitry and direct current to direct current（DC-DC） boost converters are not required, because the output voltage of targeted thermoelectric generator（TEG） devices is high enough to drive the load applications directly. The circuit operates in the active/asleep mode to overcome the power mismatch between TEG devices and load applications. The proposed circuit was implemented using a 0.35-μm complementary metal-oxide semiconductor（CMOS） process. Experimental results confirmed correct circuit operation and demonstrated the performance of the MPPT scheme. The circuit achieved a peak power efficiency of 95.5% and an MPPT accuracy of higher than 99%.

Quantum-dot cellular automata based reversible low power parity generator and parity checker design for nanocommunication

Quantum-dot cellular automata （QCA） is an emerging area of research in reversible computing. It can be used to design nanoscale circuits. In nanocommunication, the detection and correction of errors in a received message is a major factor. Besides, device density and power dissipation are the key issues in the nanocommunication architecture. For the first time, QCA-based designs of the reversible low-power odd parity generator and odd parity checker using the Feynman gate have been achieved in this study. Using the proposed parity generator and parity checker circuit, a nanocommunication architecture is pro- posed. The detection of errors in the received message during transmission is also explored. The proposed QCA Feynman gate outshines the existing ones in terms of area, cell count, and delay. The quantum costs of the proposed conventional reversible circuits and their QCA layouts are calculated and compared, which establishes that the proposed QCA circuits have very low quantum cost compared to conventional designs. The energy dissipation by the layouts is estimated, which ensures the possibility ofQCA nano-device serving as an alternative platform for the implementation of reversible circuits. The stability of the proposed circuits under thermal randomness is analyzed, showing the operational efficiency of the circuits. The simulation results of the proposed design are tested with theoretical values, showing the accuracy of the circuits. The proposed circuits can be used to design more complex low-power nanoscale lossless cation architecture such as nano-transmitters and nano-receivers

Local uncorrelated local discriminant embedding for face recognition

The feature extraction algorithm plays an important role in face recognition. However, the extracted features also have overlapping discriminant information. A property of the statistical uncorrelated criterion is that it eliminates the redundancy among the extracted discriminant features, while many algorithms generally ignore this property. In this paper, we introduce a novel feature extraction method called local uncorrelated local discriminant embedding(LULDE). The proposed approach can be seen as an extension of a local discriminant embedding(LDE)framework in three ways. First, a new local statistical uncorrelated criterion is proposed, which effectively captures the local information of interclass and intraclass. Second, we reconstruct the affinity matrices of an intrinsic graph and a penalty graph, which are mentioned in LDE to enhance the discriminant property. Finally, it overcomes the small-sample-size problem without using principal component analysis to preprocess the original data, which avoids losing some discriminant information. Experimental results on Yale, ORL, Extended Yale B, and FERET databases demonstrate that LULDE outperforms LDE and other representative uncorrelated feature extraction methods.

Design and simulation of a standing wave oscillator based PLL

A standing wave oscillator(SWO) is a perfect clock source which can be used to produce a high frequency clock signal with a low skew and high reliability. However, it is difficult to tune the SWO in a wide range of frequencies. We introduce a frequency tunable SWO which uses an inversion mode metal-oxide-semiconductor(IMOS) field-effect transistor as a varactor, and give the simulation results of the frequency tuning range and power dissipation. Based on the frequency tunable SWO, a new phase locked loop(PLL) architecture is presented. This PLL can be used not only as a clock source, but also as a clock distribution network to provide high quality clock signals. The PLL achieves an approximately 50% frequency tuning range when designed in Global Foundry 65 nm 1P9 M complementary metal-oxide-semiconductor(CMOS) technology, and can be used directly in a high performance multi-core microprocessor.

A consensus model for group decision making under interval type-2 fuzzy environment

We propose a new consensus model for group decision making(GDM) problems, using an interval type-2 fuzzy environment. In our model, experts are asked to express their preferences using linguistic terms characterized by interval type-2 fuzzy sets(IT2 FSs), because these can provide decision makers with greater freedom to express the vagueness in real-life situations. Consensus and proximity measures based on the arithmetic operations of IT2 FSs are used simultaneously to guide the decision-making process. The majority of previous studies have taken into account only the importance of the experts in the aggregation process, which may give unreasonable results. Thus, we propose a new feedback mechanism that generates different advice strategies for experts according to their levels of importance. In general, experts with a lower level of importance require a larger number of suggestions to change their initial preferences. Finally, we investigate a numerical example and execute comparable models and ours, to demonstrate the performance of our proposed model. The results indicate that the proposed model provides greater insight into the GDM process.