Scalable Distributed Sensor Fault Diagnosis for Smart Buildings

The enormous energy use of the building sector and the requirements for indoor living quality that aim to improve occupants’ productivity and health, prioritize Smart Buildings as an emerging technology. The Heating, Ventilation and Air-Conditioning (HVAC) system is considered one of the most critical and essential parts in buildings since it consumes the largest amount of energy and is responsible for humans comfort. Due to the intermittent operation of HVAC systems, faults are more likely to occur, possibly increasing eventually building’s energy consumption and/or downgrading indoor living quality. The complexity and large scale nature of HVAC systems complicate the diagnosis of faults in a centralized framework. This paper presents a distributed intelligent fault diagnosis algorithm for detecting and isolating multiple sensor faults in large-scale HVAC systems. Modeling the HVAC system as a network of interconnected subsystems allows the design of a set of distributed sensor fault diagnosis agents capable of isolating multiple sensor faults by applying a combinatorial decision logic and diagnostic reasoning. The performance of the proposed method is investigated with respect to robustness, fault detectability and scalability. Simulations are used to illustrate the effectiveness of the proposed method in the presence of multiple sensor faults applied to a 83-zone HVAC system and to evaluate the sensitivity of the method with respect to sensor noise variance.      

Zero-Sequence Voltage-based Method for Determination and Classification of Unloaded Overhead Line Operating Conditions at the Moment of Energization

Overhead line energization can be performed under normal or faulty conditions. The latter indicates an occurrence of a fault along the line that exists at the moment of energization. This can lead to significant over-voltages that could endanger proper line operation. The issue gets more complex to protective devices when it comes to high-resistance faults, which impair the ability of relays to react promptly and accurately. Consequently, installation of additional detection devices becomes necessary. This paper proposes a novel method that properly detects and classifies line operating conditions at the moment of energization. The method is designed to be useful for utilities and it can be considered as a low-cost, fast, and accurate detection and classification approach, suitable for dealing with both low-resistance and high-resistance faults. Through comprehensive mathematical modeling it was found that both normal and faulty conditions during line energization are accompanied by the zero-sequence voltages of specific characteristics. The differences between zero voltage sequences are reflected in harmonic content, magnitudes of dominant frequencies, and their phase angles in regard to supply voltage. These findings are taken as the method's detection and classification criteria. The validity of the proposed model is verified by simulations and by field measurements.     

断层应力区巷道顶板支护优化设计

1208运巷在过F4断层时,巷道顶板出现破碎、下沉以及局部冒顶现象,不仅降低了巷道掘进效率,而且威胁施工安全。通过分析原巷道支护设计存在的主要问题,对原支护进行优化,提出了“注浆锚棚+纵向桁架锚索”等联合支护措施。通过实际应用效果观察发现,支护设计优化后,加强了顶板稳定性,防止了顶板冒落事故发生。     

Asynchronous adaptive output feedback sliding mode control for Takagi-Sugeno fuzzy Markovian jump systems with actuator faults

In this article, the problem of asynchronous adaptive dynamic output feedback sliding mode control (SMC) for a class of Takagi-Sugeno (T-S) fuzzy Markovian jump systems (MJSs) with actuator faults is investigated. The asynchronous dynamic output feedback control strategy is employed, as the nonsynchronization phenomenon of jump modes exists between the plant and the controller. A novel asynchronous adaptive SMC approach is proposed to solve the synthesis problem for T-S fuzzy MJSs with actuator faults. Sufficient conditions for stochastic asymptotic stability of T-S fuzzy MJSs are given. Under the designed asynchronous adaptive SMC scheme, the effects of actuator faults and external disturbance can be completely compensated and the reachability of sliding surface is ensured. Finally, an example is provided to demonstrate the effectiveness of the proposed design techniques.     

Gliding arc plasma reforming of toluene for on-board hydrogen production

Hydrogen is considered as a clean and promising fuel, and hydrogen production on-board has attracted widespread research attention. In this work, a gliding arc discharge (GAD) plasma reactor was utilized to reform toluene at room temperature and atmosphere pressure. The performance of hydrogen production through oxidative reforming with toluene as raw material under different input power, oxygen to carbon molecular ratio (O/C), residence time and argon addition was investigated. The optimal yields of H₂ and CO (48.6% and 44.3%) were obtained under the condition of the input power of 32 W, the O/C of 0.68, the residence time of 18.4 s and 10 vol% Ar addition. By analyses of spectrum lines and GC-MS, the plasma reforming mechanism of toluene was proposed. It is believed that N₂(B³Πg) and Ar* could increase the formation of reactive oxygen species (O⁺, O (¹D), O and so on), and N₂(B³Πg) could impact directly the reforming of toluene.     

Stacking behavior of the close-packed Ta-atom planes and its effects on formation of “hybrid grains” in TaC0.66-0.7 ceramics

In previous works, it was found hard to synthesize “phase pure” ζ-Ta₄C_3-z at relatively low temperatures even by prolonged heating, though ζ-Ta₄C_3-z was believed stable till decomposition at ~2130°C. When the samples were subjected to TEM, vast richness of locally disordered structures in close relation with stacking of the close-pacted Ta-atom planes was observed. Although kinetic factors including diffusion of C atoms/vacancies and re-stacking of the Ta-atom planes explain the densely disordered structures, the richness of local disorders is a scenario that shows cohabitant of the cubic, rhombohedral, and hexagonal structures in a single grain, i.e. formation of a “hybrid grain” consisted of the three symmetries, indicating a transitional or intermediate stage before complete formation of the final phase of rhombohedral ζ-Ta₄C_3-z. This time tantalum carbide ceramics TaC_x with C:Ta atomic ratios x = 0.66 and 0.7 were prepared by reaction hot pressing of TaC and Ta powder mixtures. 5–30 mol% Cu/Ag additives and heat treatments were used to reproduce “hybrid grains” to facilitate further TEM and HRTEM observations on the disordered hybrid grains to argue for the transitional/intermediate stage. The cohabitant cubic, rhombohedral, and hexagonal structures in single grains may also help explain the difficulty in identification of the various phases by XRD in the transitional/intermediate stage of ζ-Ta₄C_3-z reaction. Microstructural evolution and fracture toughness of the composites were also investigated.     

A new interval diagnosis method: Application to the spacecraft rendezvous phase of the Mars sample return mission

This paper presents a new optimized interval principal component analysis applied to detect and isolate actuators faults of an autonomous spacecraft involved in the rendezvous phase of the Mars sample return mission. Based on the exploitation of various arithmetic and interval analysis properties, the new interval model is built by solving the interval eigenpairs problem via a resolution of a parametric linear programming problem. The detection and isolation phases are performed by extending the classic methods to interval-valued data. The proposed method is applied to detect and isolate actuators faults that can occur on the spacecraft's thrusters. Based on data provided by a “high fidelity” industrial simulator developed by Thales Alenia Space, the obtained results proved the effectiveness of the proposed interval fault diagnosis method on detecting and isolating thrusters' faults.     

浅谈煤矿数据的分析与应用

当今社会科技发展快、信息流通量大,人们之间的交流越来越密切,大数据这个高科技时代的产物也应运而生。煤炭作为工业发展的重要组成部分,其发展关系着整个工业的发展。如今,许多现代大型煤矿已能将井下设备信息上传到地面,在地面就可直观的看到设备当前运行的情况,从而更可靠的进行安全生产。通过结合实例将上传的设备信息数据进行整理和分析,从而预测设备的运行状况,提出建设性建议。同时对加强煤矿安全生产、促进煤炭行业现代化建设、提高煤矿的经济效益和社会效益具有重要的意义。     

Fault estimation and accommodation for networked control systems with nonuniform sampling periods

This paper deals with the problem of fault estimation and accommodation for a class of networked control systems with nonuniform uncertain sampling periods. Firstly, the reason why the adaptive fault diagnosis observer cannot be applied to networked control systems is analyzed. Based on this analysis, a novel robust fault estimation observer is constructed to estimate both continuous‐time fault and system states by using nonuniformly discrete‐time sampled outputs. Furthermore, using the obtained states and fault information, a nonuniformly sampled‐data fault tolerant control law is designed to preserve the stability of the closed‐loop system. The proposed scheme can not only guarantee the impact of continuous‐time uncertainties and discrete‐time sampled estimation errors on the faulty system to satisfy a H _∞ performance index but also repress the negative effect of the unknown intersample behavior of continuous‐time fault by use of an inequality technique. Finally, simulation results are included to demonstrate the feasibility of the proposed method. Copyright © 2014 John Wiley & Sons, Ltd.