Construction of Fiber Standardization Demonstration Area to Be Started

The China Fiber Inspection Bureau has announced that in 2007 it will reinforce the implementation of science, technologies, and standardization, and begin a project of constructing a fiber standardization demonstration area.     

泰国Indorama增设涤纶装置

日本《海外速报》No.524报道，泰国Indorama化学公司将Nakhon path的涤纶长/短丝/切片 装置生产能力增加1倍，从100 kt/a扩大到200 kt/a，预定2001年上半年动工，2003年上 半年投产。现处拟招标阶段，使用的技术还没有决 定。该公司 计划采用股票和贷款方式筹集1亿美元的增设资金。 　　Indorama公司测算，2000年的世界聚酯需求比上年增加6.5%，今后几年内将继续增长。 (编委 王德诚 供稿)     

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Vibration Feature Abstraction and Classification of Diesel Fault

The feature of a periodic cyclic-nonstationary signal for a cyclic working machine such as a diesel engine is studied in the aspect of working procedure,force and vibration.On the basis of the study,a method of characteristic abstraction and classification is put forward for periodic cyclic-non-stationary vibration signal.The proposed method is applied to experimental data of an ISUZU C240 diesel engine.Experiment results show the effectiveness of the proposed method in classification of engine faults.     

希望的原野呼唤着“麦田守望者” 整个社会要有勇气接受新材料

以前一提到建筑材料和建筑技术时,往往没有把它与建筑创作和建筑艺术联系在一起.实际上,建筑是一种造型艺术,任何一个艺术门类都与材料有很大的关系,大家知道,绘画和雕塑采取不同的材料,会使作品的艺术风貌产生完全不同的结果.     

Outlook of PetroChina＇s Technological Development during the 11th Five-Year Plan Period

The 11th Five-Year Plan period is a critical time for PetroChina transforming to a transnational enterprise group with international competitiveness, also a turning point for the implementation of its scientific and technological strategy.[第一段]     

Realization of the 9200-MW Generation Assets

With a process of disposition obeying market rules and a result of realization at a cost of 18.7 billion Yuan which is 56% excess, the State Electricity Regulatory Commission, the organizers for realization of the 9200-MW generation assets （the so-called ＂920 Project＂） didn＇t fail to accomplish its mission and withdrew the curtain of power reform in the 11th Five-Year period with a satisfactory performance.     

Cylinder Pressure Prediction of An HCCI Engine Using Deep Learning

Engine tests are both costly and time consuming in developing a new internal combustion engine.Therefore,it is of great importance to predict engine characteristics with high accuracy using artificial intelligence.Thus,it is pos-sible to reduce engine testing costs and speed up the engine development process.Deep Learning is an effective artificial intelligence method that shows high performance in many research areas through its ability to learn high-level hidden features in data samples.The present paper describes a method to predict the cylinder pressure of a Homogeneous Charge Compression Ignition(HCCI)engine for various excess air coefficients by using Deep Neural Network,which is one of the Deep Learning methods and is based on the Artificial Neural Network(ANN).The Deep Learning results were compared with the ANN and experimental results.The results show that the difference between experimental and the Deep Neural Network(DNN)results were less than 1％.The best results were obtained by Deep Learning method.The cylinder pressure was predicted with a maximum accuracy of 97.83％ of the experimental value by using ANN.On the other hand,the accuracy value was increased up to 99.84％ using DNN.These results show that the DNN method can be used effectively to predict cylinder pressures of internal combustion engines.