Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.     

厦门港口与产业集群互动发展研究

港口经济是厦门城市经济的重要组成部分,厦门港口与产业集群互动对于区域经济发展有着重要意义.文章分析了厦门主要港区、产业群及临港产业的发展现状,以灰色系统理论为基础从定量的角度分析了厦门港口与产业群互动发展关联状况.根据定性定量分析的结果,提出了促进厦门港口与产业集群互动发展的对策.     

基于改进准则法的复合壳阻尼结构拓扑减振动力学优化

针对复合壳阻尼结构的拓扑减振优化问题，以约束阻尼层的有限单元为设计变量，采用体积比、模态频率和振型为优化约束条件，构建以多模态权重系数的结构模态损耗因子数值关系为优化目标函数的拓扑减振优化模型。为了拓展优化目标灵敏度具有不局限于某一变密度法插值模型的形式，推导了数值表达式的一般函数式。动力学优化中优化目标灵敏度正、负数集共存，使得非凸性的目标函数设计变量出现负值或优化函数寻优于局部极值点。为此，推导出复合壳阻尼结构的全域灵敏度改进优化准则法迭代格，以确保每次迭代域均为全域设计变量集。结合有限单元法编程实现了复合壳阻尼结构改进准则法，并对复合壳结构进行拓扑减振优化分析。结果表明：在敷设体积减为全覆盖的50%时，复合壳结构的模态损耗因子增减偏差为10%，具有提升减振的轻量化设计目的；各阶目标函数和拓扑构型所需的迭代次数少，中间密度区域较小，多阶优于单阶模态优化函数，易于获得全域寻优的有效减振。     

Ionospheric F2-Layer critical frequency retrieved from COSMIC radio occultation: A statistical comparison with measurements from a meridional ionosonde chain over Southeast Asia

In this paper, we compared the F2-Layer critical frequency (foF2) derived from FORMOSAT-3/COSMIC radio occultation (RO) and ionosondes at Chiang Mai, Chumphon and Kototabang during the years 2008–2015 to evaluate the performance of COSMIC RO over Southeast Asia region. The results show that the time development of foF2 values derived from COSMIC RO generally agrees well with those from ionosonde measurements. However, the differences between the foF2 derived from COSMIC RO and that derived from ionosonde observations display latitudinal dependence. COSMIC RO tends to underestimate foF2 at Chiang Mai and Kototabang, which is near to the north EIA crest and the south one, respectively, while a little overestimate foF2 at Chumphon, which is close to the geomagnetic equator. COSMIC RO agrees best with ionosonde at Chumphon and worst at Chiang Mai. At each ionosonde station, the quality of COSMIC RO data degrades with the increase of solar activity. In addition, at the station Chiang Mai and Kototabang, COSMIC RO performs better in summer than in equinox and winter. Furthermore, the differences in foF2 derived from COSMIC RO and that from ionosonde measurements vary with local time, i.e., the differences in foF2 are generally smaller at night and larger in noontime when equatorial ionization anomaly (EIA) is well developed.     

黄渤海晴空像元下雾霾识别的机器学习算法

为实时有效地识别和监测雾霾，选取2013年10月4日与10月5日的两景MODIS遥感图像，利用不同类型像元的光谱差异，基于神经网络模型，建立海上雾霾的遥感识别机器学习算法。经检验表明，在晴空条件下，机器学习算法反演精度相对较高，已超过98%，利用算法可以实现对中国近海上空雾霾的监测。     

基于PDM的辅助工序设计

在统一的PDM数据管理平台、一致的制造工艺数据表示方式下,企业在制造工艺过程定义中存在制造工艺过程定义的协同等问题,而建立准确的数据模型是保证各子系统间信息顺畅传递的关键所在,本文就辅助工序设计方案及流程设计做了详细介绍。     

Grinding temperature and energy ratio coefficient in MQL grinding of high-temperature nickel-base alloy by using different vegetable oils as base oil

Vegetable oil can be used as a base oil in minimal quantity of lubrication(MQL). This study compared the performances of MQL grinding by using castor oil, soybean oil, rapeseed oil, corn oil, sunflower oil, peanut oil, and palm oil as base oils. A K-P36 numerical-control precision surface grinder was used to perform plain grinding on a workpiece material with a high-temperature nickel base alloy. A YDM–III 99 three-dimensional dynamometer was used to measure grinding force,and a clip-type thermocouple was used to determine grinding temperature. The grinding force, grinding temperature, and energy ratio coefficient of MQL grinding were compared among the seven vegetable oil types. Results revealed that(1) castor oil-based MQL grinding yields the lowest grinding force but exhibits the highest grinding temperature and energy ratio coefficient;(2) palm oil-based MQL grinding generates the second lowest grinding force but shows the lowest grinding temperature and energy ratio coefficient;(3) MQL grinding based on the five other vegetable oils produces similar grinding forces, grinding temperatures, and energy ratio coefficients, with values ranging between those of castor oil and palm oil;(4) viscosity significantly influences grinding force and grinding temperature to a greater extent than fatty acid varieties and contents in vegetable oils;(5) although more viscous vegetable oil exhibits greater lubrication and significantly lower grinding force than less viscous vegetable oil, high viscosity reduces the heat exchange capability of vegetable oil and thus yields a high grinding temperature;(6) saturated fatty acid is a more efficient lubricant than unsaturated fatty acid; and(7) a short carbon chain transfers heat more effectively than a long carbon chain. Palm oil is the optimum base oil of MQL grinding, and this base oil yields 26.98 N tangential grinding force,87.10 N normal grinding force, 119.6 °C grinding temperature, and 42.7% energy ratio coefficient.