Optimal inspection for randomly triggered hidden deterioration processes

This paper deals with degradation processes whose onset is triggered at a random time and which stay hidden until they are discovered through inspection or when they begin to show symptoms. This is applicable in many healthcare and industrial scenarios, for example, in the modeling of breast cancer or termite infestation. In our model, we assume that symptoms appear after hitting a random critical threshold and that inspections may have a sensitivity less than one as well as a nonzero false positive rate. The expected cost of repair is derived, and the inspection rate is optimized for a cycle (which lasts from degradation-free to repaired state). This gives results for three cases: the first is for a finite observation period with no degradation recurrence, the second for infinite time horizon allowing recurrence. In the third case, we derive an upper bound for the expected cost in a given constant time period. Finally, the model is applied to determine the optimal strategy for breast cancer screening with regard to the effects of different parametrizations.     

Progress of Air Pollution Control in China and Its Challenges and Opportunities in the Ecological Civilization Era

China’s past economic growth has substantially relied on fossil fuels, causing serious air pollution issues. Decoupling economic growth and pollution has become the focus in developing ecological civilization in China. We have analyzed the three-decade progress of air pollution controls in China, highlighting a strategic transformation from emission control toward air quality management. Emission control of sulfur dioxide (SO₂) resolved the deteriorating acid rain issue in China in 2007. Since 2013, control actions on multiple precursors and sectors have targeted the reduction of the concentration of fine particulate matter (PM_2.5), marking a transition to an air-quality-oriented strategy. Increasing ozone (O₃) pollution further requires O₃ and PM_2.5 integrated control strategies with an emphasis on their complex photochemical interactions. Fundamental improvement of air quality in China, as a key indicator for the success of ecological civilization construction, demands the deep de-carbonization of China’s energy system as well as more synergistic pathways to address air pollution and global climate change simultaneously.     

Adaptive neuro-fuzzy algorithm applied to predict and control multi-phase flow rates through wellhead chokes

A Takagi-Sugeno adaptive neuro-fuzzy inference system (TSFIS) model is developed and applied to a dataset of wellhead flow-test data for the Resalat oil field located offshore southern Iran, the objective is to assist in the prediction and control of multi-phase flow rates of oil and gas through the wellhead chokes. For this purpose, 182 test data points (Appendix 1) related to the Resalat field are evaluated. In order to predict production flow rate (Q_L) expressed as stock-tank barrels per day (STB/D), this dataset includes four selected input variables: upstream pressure (Pwh); wellhead choke sizes (D64); gas to liquid ratio (GLR); and, base solids and water including some water-soluble oil emulsion (BS&W). The test data points evaluated include a wide range of oil flow rate conditions and values for the four input variables recorded. The TSFIS algorithm applied involves five data processing steps: a) pre-processing, b) fuzzification, c) rules base and adaptive neuro-fuzzy inference engine, d) defuzzification, and e) post-processing of the fuzzy model. The developed TSFIS model for the Resalat oil field database predicted oil flow rate to a high degree of accuracy (root mean square error = 247 STB/D, correlation coefficient = 0.9987), which improves substantially on the commonly used empirical algorithms used for such predictions. TSFIS can potentially be applied in wellhead choke fuzzy controllers to stabilize flow in specific wells based on real-time input data records.     

基于Stateflow电力机车变流器控制设计与实现

某出口型号交流电力机车牵引控制系统要求变流器控制逻辑具备接触器控制、牵引系统数据交互、变流器故障保护、变流器启动自检等功能。针对以上功能,基于MATLAB中的Simulink/Stateflow可视化编程工具进行牵引控制模型的搭建,遵循模块化编程理念,采用较少的程序代码编写实现复杂的逻辑控制模型,生成逻辑清晰的控制功能流程图,进行半实物仿真测试,增强控制模型的可靠性。通过该变流器产品型式试验检验,验证变流器控制逻辑的功能可以满足控制系统的需求。     

Encapsulation of MnS Nanocrystals into N,S-Co-doped Carbon as Anode Material for Full Cell Sodium-Ion Capacitors

Sodium-ion capacitors(SICs)have received increasing interest for grid stationary energy storage application due to their affordability,high power,and energy densities.The major challenge for SICs is to overcome the kinetics imbalance between faradaic anode and nonfaradaic cathode.To boost the Na+reaction kinetics,the present work demonstrated a high-rate MnS-based anode by embedding the MnS nanocrystals into the N,S-co-doped carbon matrix(MnS@NSC).Benefiting from the fast pseudocapacitive Na+storage behavior,the resulting composite exhibits extraordinary rate capability(205.6 mAh g−1 at 10 A g−1)and outstanding cycling stability without notable degradation after 2000 cycles.A prototype SIC was demonstrated using MnS@NSC anode and N-doped porous carbon(NC)cathode;the obtained hybrid SIC device can display a high energy density of 139.8 Wh kg−1 and high power density of 11,500 W kg−1,as well as excellent cyclability with 84.5%capacitance retention after 3000 cycles.The superior electrochemical performance is contributed to downsizing of MnS and encapsulation of conductive N,S-co-doped carbon matrix,which not only promote the Na+and electrons transport,but also buffer the volume variations and maintain the structure integrity during Na+insertion/extraction,enabling its comparable fast reaction kinetics and cyclability with NC cathode.     

环形供热管网水力工况设计方法研究

为提高环形供热管网水力工况运行稳定性,提出了基于模糊PID控制的环形供热管网水力工况控制方法。构建环形供热管网水力工况控制的约束参量模型,在此基础上采用回归模型逼近方法构建其测试指标集,结合自适应融合反馈跟踪方法进行环形供热管网水力工况信息的融合处理,并从中提取分布特征量;采用模糊PID控制方法调节提取结果的输出稳定性,实现环形供热管网水力工况优化设计和自适应控制。仿真结果表明,采用该方法进行环形供热管网水力工况控制的稳定性较好,自适应控制能力较强,实现了环形供热管网水力工况优化调节。     

斗轮取料机液压控制系统的故障分析及改进

针对臂式斗轮取料机运行中抖动现象,进行了故障分析和排除,并对其液压原理和元件选型进行了优化及改进,为相关液压系统的故障分析和设计选型提供参考。     

两级伸缩式液压缸与四柱两级滑轨的故障分析与排除

本文通过对两级伸缩式液压缸与四柱滑轨结合使用中所出现问题及处理过程的阐述,提出了在液压系统设计与制造中,准确的原理仅仅是基础,其上还有许许多多的细枝末节需要仔细修剪,比如污染、噪声、温度、泄漏以及与机械的协调等等。     

富水软岩巷道稳定性控制技术研究

富水条件下软岩巷道容易出现大变形及围岩强度大幅度降低等情况,对矿井的生产安全造成极大威胁。为探索富水软岩巷道稳定性控制技术,结合新上海一号煤矿113082工作面运输巷工程实例,采用理论分析方法研究了地下水对巷道围岩及支护结构的影响,提出围岩稳定性控制对策,并对控制方案进行数值模拟验证。针对富水软岩巷道,首先采取导、疏结合的控水措施,减小对原有围岩强度的影响,降低对支护结构的损害;其次采用全断面、多手段联合加固的支护措施,控制围岩变形。工程实际及数值模拟结果表明,对于富水软岩巷道采取以上技术措施,能够有效保证巷道的稳定性。     

Actuator fault tolerant control using adaptive RBFNN fuzzy sliding mode controller for coaxial octorotor UAV

In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial octorotor helicopter control is proposed in presence of actuator faults. Radial Base Function Neural Network (RBFNN), Fuzzy Logic Control approach (FLC) and Sliding Mode Control (SMC) technique are used to design a controller, named Fault Tolerant Control (FTC), for each subsystem of the octorotor helicopter. The proposed FTC scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller, and guaranteeing the stability and the robustness of the system. The simulation results show that the proposed FTC can greatly alleviate the chattering effect, good tracking in presence of actuator faults.