低挥发分煤在新型干法窑生产中的应用

对劣质煤、低挥发分煤的燃烧特性分析,工艺设备分析,提出预分解窑烧劣质煤、低挥发分煤的可能性、必要性,为我公司烧劣质煤、无烟煤打下了基础。     

Fault tolerant multiple event detection in a wireless sensor network

With an increasing acceptance of Wireless Sensor Networks (WSNs), the health of individual sensor is becoming critical in identifying important events in the region of interest. One of the key challenges in detecting event in a WSN is how to detect it accurately transmitting minimum information providing sufficient details about the event. At the same time, it is also important to devise a strategy to handle multiple events occurring simultaneously. In this paper, we propose a Polynomial-based scheme that addresses these problems of Event Region Detection (PERD) by having a aggregation tree of sensor nodes. We employ a data aggregation scheme, TREG (proposed in our earlier work) to perform function approximation of the event using a multivariate polynomial regression. Only coefficients of the polynomial (P$P$) are passed instead of aggregated data. PERD includes two components: event recognition and event report with boundary detection. This can be performed for multiple simultaneously occurring events. We also identify faulty sensor(s) using the aggregation tree. Performing further mathematical operations on the calculated P$P$ can identify the maximum (max) and minimum (min) values of the sensed attribute and their locations. Therefore, if any sensor reports a data value outside the [min, max] range, it can be identified as a faulty sensor. Since PERD is implemented over a polynomial tree on a WSN in a distributed manner, it is easily scalable and computation overhead is marginal. Results reveal that event(s) can be detected by PERD with error in detection remaining almost constant achieving a percentage error within a threshold of 10%$10\%$ with increase in communication range. Results also show that a faulty sensor can be detected with an average accuracy of 94%$94\%$ and it increases with increase in node density.     

一种WSN的非一致性数据故障检测机制

针对无线传感器网络数据传输过程中产生的非一致性问题,提出了一种基于无线传感器网络的非一致性故障检测机制IFDM（Inconsistent Failures Detection Mechanism）。IFDM通过采用节点不相交多重路径,比较数据包内容,判断故障路径,并实施故障节点的定位。仿真实验表明,IFDM能有效的检测出非一致性故障路径及故障节点,具有检测速度快、功耗低、时延小等特性。     

Regularizers for fault tolerant multilayer feedforward networks

Fault tolerance is an important issue for multilayer feedforward networks (MFNs). However, in the classical training approach for open node fault and open weight fault, we should consider many potential faulty networks. Clearly, if the number of faulty networks considered in the objective function is large, this training approach would be very time consuming. This paper derives two objective functions for attaining fault tolerant MFNs. One objective function is designed for handling open node fault while another one is designed for handling open weight fault. With the linearization technique, each of these two objective functions can be decomposed into two terms, the training error and a simple regularization term. In our approach, the objective functions are computationally simple. Hence the conventional backpropagation algorithm can be simply applied to handle these fault tolerant objective functions.     

Distributed computing on oriented anonymous hypercubes with faulty components

We give efficient algorithms for distributed computation on oriented, anonymous, asynchronous hypercubes with possible faulty components (i.e. processors and links) and deterministic processors. Initially, the processors know only the size of the network and that they are inter-connected in a hypercube topology. Faults may occur only before the start of the computation (and that despite this the hypercube remains a connected network). However, the processors do not know where these faults are located. As a measure of complexity we use the total number of bits transmitted during the execution of the algorithm and we concentrate on giving algorithms that will minimize this number of bits. The main result of this paper is an algorithm for computing Boolean functions on anonymous hypercubes with bit cost , where is the number of faulty components (i.e. links plus processors), is the number of links which are either faulty, or non-faulty but adjacent to faulty processors, and is the diameter of the hypercube with faulty components. Received: October 1992 / Accepted: April 2001     

Machine learning-based novelty detection for faulty wafer detection in semiconductor manufacturing

Since semiconductor manufacturing consists of hundreds of processes, a faulty wafer detection system, which allows for earlier detection of faulty wafers, is required. statistical process control (SPC) and virtual metrology (VM) have been used to detect faulty wafers. However, there are some limitations in that SPC requires linear, unimodal and single variable data and VM underestimates the deviations of predictors. In this paper, seven different machine learning-based novelty detection methods were employed to detect faulty wafers. The models were trained with Fault Detection and Classification (FDC) data to detect wafers having faulty metrology values. The real world semiconductor manufacturing data collected from a semiconductor fab were tested. Since the real world data have more than 150 input variables, we employed three different dimensionality reduction methods. The experimental results showed a high True Positive Rate (TPR). These results are promising enough to warrant further study.     

一种中低压配电网单相接地故障选线新原理

为了改正当前小电流接地系统单相接地故障选线装置准确率不高的缺点,作者提出了与零序电压和零序电流极性无关的新的零序电流有功分量比幅选线方法.Matlab仿真表明该方法能准确识别出故障线路.     

一起多传动变频器故障的处理过程

本文介绍一起ABB多传动变频器故障的处理过程。     

Linear-code multicast on parallel architectures

Parallel architectures involve communication with the aim of fast receiving of complete information at each node. Several architectures have been proposed to overcome the problem of high communicational and computational time complexity for transferring and receiving information. To reduce the complexity of such communication, we have implemented Linear Network Coding (LNC) in the parallel environment. For verification of our approach, we have considered some parallel architecture for implementing network coding approach and examined our results on these networks in a generic environment. We have formulated a standard approach for parallel networks, showing that by applying this approach effect of faulty nodes, information size and communication complexity exponentially decreases with code length.     

大型汽轮发电机组误并列及其监测

本文结合国内第一台大型汽轮发电机组TSA—1系统的开发,研究了误并列判据和角度分析模型并给出部分误并列监测记录。可靠地监测误并角,为运行人员判别分析并列优劣提供了依据。