打管理基础 求科技支撑 取创新成效 全力履行精益保供核心使命

主要介绍了热电厂近几年来在技术管理方面取得的主要工作经验，以及围绕生产经营开展科技创新所取得的成绩，并且针对当前形势，进一步提出了热电厂今后一个时期科技工作的指导思想、任务目标和措施。     

悟

“悟”是一种对客观的事和物的一种感知,是对事和物获取了解、获取知效,是人们求得理解的一种启示、一种认识的过程。一般地说,“我对事和物,意在彻悟”,是指人们得到充分的悟性,特别对意、意义的悟,有的很快领会,有的要耗费时日,有的要经过一定的时间乃至终身。悟性就是理解的     

Pattern analysis of airborne dipole antenna in high-frequency region

The Uniform Geometrical Theory of Diffraction (UTD) has been successfully used in pattern analysis of airborne dipole antenna on the A-5 fighter in high-frequency region. In the analysis, several canonical problems are investigated first, then the complicated problem is calculated with compiling these canonical problems. The numerical results are compared with the experimental data, and good agreement has been seen. The effectiveness and practicality of the present analysis are thus verified.     

Feature Reduction via Generalized Uncorrelated Linear Discriminant Analysis

High-dimensional data appear in many applications of data mining, machine learning, and bioinformatics. Feature reduction is commonly applied as a preprocessing step to overcome the curse of dimensionality. Uncorrelated Linear Discriminant Analysis (ULDA) was recently proposed for feature reduction. The extracted features via ULDA were shown to be statistically uncorrelated, which is desirable for many applications. In this paper, an algorithm called ULDA/QR is proposed to simplify the previous implementation of ULDA. Then, the ULDA/GSVD algorithm is proposed, based on a novel optimization criterion, to address the singularity problem which occurs in undersampled problems, where the data dimension is larger than the sample size. The criterion used is the regularized version of the one in ULDA/QR. Surprisingly, our theoretical result shows that the solution to ULDA/GSVD is independent of the value of the regularization parameter. Experimental results on various types of data sets are reported to show the effectiveness of the proposed algorithm and to compare it with other commonly used feature reduction algorithms.     

A novel methanol-tolerant Ir-Se chalcogenide electrocatalyst for oyxgen reduction

A novel methanol-tolerant oxygen-reduction catalyst, Iridium-selenium (Ir-Se) chalcogenide, was synthesized by chemical precipitation in an organic solvent. Auger electron spectroscopy (AES) analysis confirmed that the synthesized Ir-Se chalcogenide had a chemical formula of Ir₄Se. This chalcogenide showed strong catalytic activity towards the oxygen reduction reaction (ORR) and a high methanol tolerance. It was found that most of the oxygen could be directly reduced to water through a four-electron pathway with less than 10% hydrogen peroxide (H₂O₂) being produced during the ORR. The improvement in catalytic activity of the Ir-Se chalcogenide in comparison with that of pure Ir might be attributed to the effect of a bimetallic interaction.     

担载型含稀土三组份体系在二氧化碳甲烷化反应中的催化性能

用浸渍法制备了一系列氧化锆担载的含稀土Ⅷ族金属催化剂，对其在二氧化碳甲烷化过程中的催化活性作了研究，并用漫反射紫外可见光谱，ＦＴＩＲ等手段对催化剂作了表征。结果表明，含稀土新型催化剂具有催化活性高，目标产物选择性好等优点；稀土主要以氧化物形式存在于催化剂表面，参与对氢及表面含碳物种的吸附及活化；含稀土三组份催化剂的活性与所添加稀土三价离子的４ｆ电子数有关。     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

A conditional classification recurrent RBM for improved series mid-term forecasting

In the context of human-robot and robot-robot interactions, the better cooperation can be achieved by predicting the other party’s subsequent actions based on the current action of the other party. The time duration for adjustment is not sufficient provided by short term forecasting models to robots. A longer duration can by achieved by mid-term forecasting. But the mid-term forecasting models introduce the previous errors into the follow-up forecasting and amplified gradually, eventually invalidating the forecasting. A new mid-term forecasting with error suppression based on restricted Boltzmann machine(RBM) is proposed in this paper. The proposed model can suppress the error amplification by replacing the previous inputs with their features, which are retrieved by a deep belief network(DBN). Furthermore, a new mechanism is proposed to decide whether the forecasting result is accepted or not. The model is evaluated with several datasets. The reported experiments demonstrate the superior performance of the proposed model compared to the state-of-the-art approaches.

     

混沌信号的主要测量特性分析

初步分析了混沌信号(以Logistic为例)应用于测量中的主要特性。仿真分析了Logistic信号的频谱特性、相关特性、模糊函数。说明了混沌信号在具有较高的距离速度分辨力,同时具备强抗干扰性。对比分析了混沌码和伪随机码的多普勒容限能力。初步分析Logistic信号的抗干扰特性。     

铝阳极氧化膜颜色的检验和观察法

介绍铝及铝合金阳极氧化膜颜色的概念和描写,对颜色的儿种测量方法进行了比较,重点分析观察法及其在各国标准中的异同。在此基础上,提出了GB8013中的对颜色进行观察的条件和理论根据。