The Dihedral Angle and Intersection Processes of a Conjugate Strike-Slip Fault System in the Tarim Basin, NW China

Recent studies, focused on dihedral angles and intersection processes, have increased understandings of conjugate fault mechanisms. We present new 3-D seismic data and microstructural core analysis in a case study of a large conjugate strike-slip fault system from the intracratonic Tarim Basin, NW China. Within our study area, ＂X＂ type NE and NW trending faults occur within Cambrian- Ordovician carbonates. The dihedral angles of these conjugate faults have narrow ranges, 19~ to 62~ in the Cambrian and 26~ to 51~ in the Ordovician, and their modes are 42~ and 44~ respectively. These data are significantly different from the ~60~ predicted by the Coulomb fracture criterion. It is concluded that： （1） The dihedral angles of the conjugate faults were not controlled by confining pressure, which was low and associated with shallow burial; （2） As dihedral angles were not controlled by pressure they can be used to determine the shortening direction during faulting; （3） Sequential slip may have played an important role in forming conjugate fault intersections; （4） The conjugate fault system of the Tarim basin initiated as rhombic joints; these subsequently developed into sequentially active ＂X＂ type conjugate faults; followed by preferential development of the NW-trending faults; then reactivation of the NE trending faults. This intact rhombic conjugate fault system presents new insights into mechanisms of dihedral angle development, with particular relevance to intracratonic basins.

A New Growth Model of Fault Attributes in a Strike-Slip Fault System in the Tarim Basin

Fault attributes generally display a consistent power–law-scaling relationship.Based on new 3 D seismic data,however,we found some exceptional fault attribute relationships of lengths(L)–throw(T)(vertical component of displacement),overlap zone length(Lo)–width(Wo)from a strike-slip fault system of the Ordovician carbonates in the Tarim Basin.The L–T relationship shows two linear segments with breakup at^40 km in fault length.This presents an exceptional throw increase in the second stage,which is attributed to a localization of vertical displacement and deformation in overlapping zones other than the different fault scales in a mature fault zone.The Lo–Wo relationship in the overlapping zones shows multiply stepped-shape patterns,suggesting multiple fault differential growth and periodic increase in fault size.Therefore,we propose a new alternative growth model of fault attributes in strike-slip fault zones,in which the overlapping zones accumulated localized displacement and deformation in the intracratonic strike-slip fault zone.

Effects of Surface Etch Hole Fault on the Velocity Field in Microchannel Reactors

Microchannel reactors are commonly used in micro-chemical technology. The performance of microreactors is greatly affected by the velocity field in the microchannel. The flow field is disturbed by the cylindrical etch holes caused by air dust on the microchannel surface during its processing procedure. In this approach, a two-dimensional computational fluid dynamics （CFD） model is put forward to study the effect of etch holes on flow field. The influenced area of single or two concave etch holes is studied for the case of laminar flow. The hole diameter, the Reynolds number and the distance between the center of holes are found to have influences on the flow field. Numerical results indicate that the effects of etch hole on the flow field should be evaluated and the way of choosing the economic class of cleanroom for microreactor manufacture is presented.

Diagnosis of process faults and sensor faults in a class of nonlinear uncertain systems

This paper presents a fault diagnosis method for process faults and sensor faults in a class of nonlinear uncertain systems.The fault detection and isolation architecture consists of a fault detection estimator and a bank of adaptive isolation estimators,each corresponding to a particular fault type.Adaptive thresholds for fault detection and isolation are presented.Fault detectability conditions characterizing the class of process faults and sensor faults that are detectable by the presented method are derived.A simulation example of robotic arm is used to illustrate the effectiveness of the fault diagnosis method.

Temperature fault-tolerant control system of CSTR with coil and jacket heat exchanger based on dual control and fault diagnosis

For the characteristics of the continuous stirred-tank reactor(CSTR) with coil and jacket cooling system,a CSTR temperature dual control solution based on the analysis of the CSTR exothermic reaction control characteristic was proposed for an organic material polymerization production.The control solution has passive fault-tolerant ability for the jacket cooling water cutting off fault and active fault-tolerant potential for the coil cooling water cutting off fault,and it has good control ability,high saving energy and reducing consumption performance.Fault detection and diagnosis and fault-tolerant control strategy are designed for the coil cooling fault to achieve the active fault-tolerant control function.The CSTR temperature dual control,process fault detection and diagnosis and active fault-tolerant control were full integrated into the CSTR temperature fault-tolerant control system,which achieve fault tolerance control of CSTR temperature for any severe malfunction of jacket cooling or coil cooling cutting off,and the security for CSTR exothermic reaction is improved.Finally,the effectiveness of this system was validated by semi-physical simulation experiment.

Research on fault detection method for heat pump air conditioning system under cold weather

Building energy consumption accounts for nearly 40% of global energy consumption, HVAC （Heating, Ventilating, and Air Conditioning） systems are the major building energy consumers, and as one type of HVAC systems, the heat pump air conditioning system, which is more energy-efficient compared to the traditional air conditioning system, is being more widely used to save energy. However, in northern China, extreme climatic conditions increase the cooling and heating load of the heat pump air conditioning system and accelerate the aging of the equipment, and the sensor may detect drifted parameters owing to climate change. This non-linear drifted parameter increases the false alarm rate of the fault detection and the need for unnecessary troubleshooting. In order to overcome the impact of the device aging and the drifted parameter, a Kalman filter and SPC （statistical process control） fault detection method are introduced in this paper. In this method, the model parameter and its standard variance can he estimated by Kalman filter based on the gray model and the real-time data of the air conditioning system. Further, by using SPC to construct the dynamic control limits, false alarm rate is reduced. And this paper mainly focuses on the cold machine failure in the component failure and its soft fault detection. This approach has been tested on a simulation model of the ＂Sino-German Energy Conservation Demonstration Center＂ building heat pump air-conditioning system in Shenyang, China, and the results show that the Kalman filter and SPC fault detection method is simple and highly efficient with a low false alarm rate, and it can deal with the difficulties caused by the extreme environment and the non-linear influence of the parameters, and what＇s more, it provides a good foundation for dynamic fault diagnosis and fault prediction analysis.

An aligned mixture probabilistic principal component analysis for fault detection of multimode chemical processes

A novel approach named aligned mixture probabilistic principal component analysis(AMPPCA) is proposed in this study for fault detection of multimode chemical processes. In order to exploit within-mode correlations,the AMPPCA algorithm first estimates a statistical description for each operating mode by applying mixture probabilistic principal component analysis(MPPCA). As a comparison, the combined MPPCA is employed where monitoring results are softly integrated according to posterior probabilities of the test sample in each local model. For exploiting the cross-mode correlations, which may be useful but are inadvertently neglected due to separately held monitoring approaches, a global monitoring model is constructed by aligning all local models together. In this way, both within-mode and cross-mode correlations are preserved in this integrated space. Finally, the utility and feasibility of AMPPCA are demonstrated through a non-isothermal continuous stirred tank reactor and the TE benchmark process.

Overview of the Importance of Intelligent Approaches on Machinery Faults Diagnosis and Prediction Based on Prognostic and Health Management/Condition-Based Maintenance

Condition monitoring is increasingly used to anticipate and detect failures of industrial machines.Failures of machines can cause high maintenance or replacement costs.If neglected,it may result in catastrophic accidents leading to production shrinkage.The potential failure would negatively affect the profitability of the company,including production shut down,cost of spare parts,cost of labor,damage of reputation,risk of injury to people and the environment.In recent years,condition-based maintenance( CBM) and prognostic and health management( PHM) are developed and formed a strong connection among science,engineering,computer,reliability,communication,management,etc.Computerized maintenance management systems( CMMS) store a lot of data regarding the fault diagnosis and life prediction of the machinery equipment.It's too necessary to uncover useful knowledge from the huge amount of data.It's vital to find the ways to obtain useful and concise information from these data.This information can be of great influence in the decision making of managers.This article is a review of intelligent approaches in machinery faults diagnosis and prediction based on PHM and CBM.

Source rupture process of the 2015 Gorkha, Nepal Mw7.9 earthquake and its tectonic implications

On 25 April, 2015, an Mw7.9 earthquake occurred in Nepal, which caused great economic loss and casualties. However, almost no surface ruptures were observed. Therefore, in order to interpret the phenomenon, we study the rupture process of the earthquake to seek answers. Inversion of teleseismic body-wave data is applied to estimate the rupture process of the 2015 Nepal earthquake. To obtain stable solutions, smoothing and non-negative constraints are introduced. 48 teleseismic stations with good coverage are chosen. Finite fault model is established with length and width of 195 km and 150 km, and we set the initial seismic source parameters referring to CMT solutions. Inversion results indicate that the focal mechanism of this earthquake is a thrust fault type, and the strike, dip and rake angle are in accordance with CMT results. The seismic moment is 0.9195 ×10^（21）Nm（Mw7.9）, and source duration is about 70s. The rupture nucleated near the hypocenter and then propagated along the dip direction to the southeast, and the maximum slip amounts to 5.2 m. Uncertainties on the amount of slip retrieved by different inversion methods still exist, the overall characteristics are inconsistent. The lack of shallow slip during the 2015 Gorkha earthquake implies future seismic hazard and this region should be paid more attention to.

A novel multimode process monitoring method integrating LCGMM with modified LFDA

Complex processes often work with multiple operation regions, it is critical to develop effective monitoring approaches to ensure the safety of chemical processes. In this work, a discriminant local consistency Gaussian mixture model(DLCGMM) for multimode process monitoring is proposed for multimode process monitoring by integrating LCGMM with modified local Fisher discriminant analysis(MLFDA). Different from Fisher discriminant analysis(FDA) that aims to discover the global optimal discriminant directions, MLFDA is capable of uncovering multimodality and local structure of the data by exploiting the posterior probabilities of observations within clusters calculated from the results of LCGMM. This may enable MLFDA to capture more meaningful discriminant information hidden in the high-dimensional multimode observations comparing to FDA. Contrary to most existing multimode process monitoring approaches, DLCGMM performs LCGMM and MFLDA iteratively, and the optimal subspaces with multi-Gaussianity and the optimal discriminant projection vectors are simultaneously achieved in the framework of supervised and unsupervised learning. Furthermore, monitoring statistics are established on each cluster that represents a specific operation condition and two global Bayesian inference-based fault monitoring indexes are established by combining with all the monitoring results of all clusters. The efficiency and effectiveness of the proposed method are evaluated through UCI datasets, a simulated multimode model and the Tennessee Eastman benchmark process.

A Fault Sample Simulation Approach for Virtual Testability Demonstration Test

Virtual testability demonstration test has many advantages,such as low cost,high efficiency,low risk and few restrictions.It brings new requirements to the fault sample generation.A fault sample simulation approach for virtual testability demonstration test based on stochastic process theory is proposed.First,the similarities and differences of fault sample generation between physical testability demonstration test and virtual testability demonstration test are discussed.Second,it is pointed out that the fault occurrence process subject to perfect repair is renewal process.Third,the interarrival time distribution function of the next fault event is given.Steps and flowcharts of fault sample generation are introduced.The number of faults and their occurrence time are obtained by statistical simulation.Finally,experiments are carried out on a stable tracking platform.Because a variety of types of life distributions and maintenance modes are considered and some assumptions are removed,the sample size and structure of fault sample simulation results are more similar to the actual results and more reasonable.The proposed method can effectively guide the fault injection in virtual testability demonstration test.

Landmarks in the application of electrical tomography in particle science and technology

Selected milestones in the development and use of electrical tomography in powder conveying, slurry processing and multi-phase flow are highlighted. The ability to map concentration in opaque mixtures under process-realistic conditions was a major innovation for the method and has had far reaching implications. Subsequent developments have enabled velocity information to be abstracted resulting in the ability to measure component flux and motion.