Fault Detection and Diagnosis for General Stochastic Systems Using B-Spline Expansions and Nonlinear Filters

This paper presents a new fault detection and diagnosis (FDD) algorithm for general stochastic systems. Different from the classical FDD design, the distribution of system output is supposed to be measured rather than the output signal itself. The task of such an FDD algorithm design is to use the measured output probability density functions (PDFs) and the input of the system to construct a stable filter-based residual generator such that the fault can be detected and diagnosed. For this purpose, square root B-spline expansions are applied to model the output PDFs and the concerned problem is transformed into a nonlinear FDD algorithm design subjected to a nonlinear weight dynamical system. A linear matrix inequality based solution is presented such that the estimation error system is stable and the fault can be detected through a threshold. Moreover, an adaptive fault diagnosis method is also provided to estimate the size of the fault. Simulations are provided to show the efficiency of the proposed approach.     

Phase and Frequency Transfer Between Mutually Synchronized Oscillators

Accurate phase and frequency transfer between mutually synchronized oscillators is a problem of current interest. This paper addresses a system of two mutually synchronized oscillators with inherently sinusoidal phase detectors. The system is studied in the context of nonlinear phase-locked loop theory. This is accomplished by Statistically characterizing the "time" and "space and time" increments of the phase processes generated by the two oscillators. The characterization of these increment processes is obtained in the form of steady-state probability density functions (pdf's). The effects of such disturbances as noise, transmission path delays, and oscillator frequency instabilities on the system are studied through their effects on these pdf's. Gaussian approximations for these pdf's (which simplify the extraction of the effects of the disturbances on the system) are also developed. Additionally, the stability of the time intervals and time interval errors generated by the oscillators are studied in the context of cycle slipping phenomena.     

Fault detection and diagnosis in asymmetric multilevel inverter using artificial neural network

The increased component requirement to realise multilevel inverter (MLI) fallout in a higher fault prospect due to power semiconductors. In this scenario, efficient fault detection and diagnosis (FDD) strategies to detect and locate the power semiconductor faults have to be incorporated in addition to the conventional protection systems. Even though a number of FDD methods have been introduced in the symmetrical cascaded H-bridge (CHB) MLIs, very few methods address the FDD in asymmetric CHB-MLIs. In this paper, the gate-open circuit FDD strategy in asymmetric CHB-MLI is presented. Here, a single artificial neural network (ANN) is used to detect and diagnose the fault in both binary and trinary configurations of the asymmetric CHB-MLIs. In this method, features of the output voltage of the MLIs are used as to train the ANN for FDD method. The results prove the validity of the proposed method in detecting and locating the fault in both asymmetric MLI configurations. Finally, the ANN response to the input parameter variation is also analysed to access the performance of the proposed ANN-based FDD strategy.     

Synergistic use of soft computing technologies for fault detection in gas turbine engines

In this paper, we present a synergistic approach to startup fault detection and diagnosis (FDD) in gas turbine engines. The method employs statistics, signal processing, and soft computing techniques in a complementary manner to address fault detection at transient conditions. Traditional turbine engine FDD methods are based on engine data collected at steady-state conditions. However, incipient faults are difficult to diagnose using steady-state engine data; only engine faults that are fairly developed can be detected using conventional methods. Because incipient engine component faults are often manifest in the engine startup characteristics, we present a method to characterize the engine transient startup. Engine sensor data during engine startup are recorded in time series format. The sensor profiles corresponding to "good" and "bad" engine startups are sampled using the bootstrap technique. A feature vector is extracted in two steps, and signal processing is followed by the feature vector selection. In the signal processing step, principal component analysis (PCA) is applied to reduce the samples consisting of sensor profiles into a smaller set. In the feature vector selection step, a cost function is defined, and important discriminating features for fault diagnosis are distilled from the PCA output vector. The features obtained from this step are then classified using neural-network-based methods. The "leave-one-out" approach to cross validation is applied to obtain an objective evaluation of the neural network training. The proposed FDD method is evaluated using actual engine startup data, and the results are presented.     

An adaptive notch-filter-based frequency-difference detector andits applications

A frequency-difference detector (FDD) based on an adaptive notch filter is proposed. Frequency detectors are useful in decreasing acquisition times in phase-locked-loop and Costas-loop-based clock and carrier-recovery systems. To avoid certain drawbacks associated with signal down-conversion to baseband, the input is initially processed in the bandpass domain. In applications where limits on acquisition time demand a wide closed-loop tracking bandwidth, the output of the proposed FDD has less inherent ripple and bias when compared with a quadricorrelator, a commonly used FDD. Two applications of the proposed FDD in the demodulation of BPSK data are presented     

Fault Detection for Networked Nonlinear Systems with Time Delays and Packet Dropouts

This paper addresses the problem of fault detection (FD) for networked systems with global Lipschitz nonlinearities and incomplete measurements, including time delays and packet dropouts which are described by a more general model using Markov jump system approach. We aim to design a mode-dependent fault detection filter (FDF) such that, for all external disturbances and incomplete measurements, the error between the residual and fault is made as small as possible. The addressed FD problem is then converted into an auxiliary H _∞ filtering problem of Markov jump system with time-varying delay. By applying Lyapunov–Krasovskii approach, a sufficient condition for the existence of the FDF is derived in terms of certain linear matrix inequalities (LMIs). When these LMIs are feasible, the explicit expression of the desired FDF can also be characterized. A numerical example is exploited to show the effectiveness of the results obtained.     

Flexible UL-DL Switching Point in TDD Cellular Local?Area Wireless Networks

An advantage of time division duplex (TDD) wireless networks over frequency division duplex (FDD) is that the UL-DL switching point may be flexibly adapted to asymmetric traffic loads. This enables more efficient spectrum use, but on the other hand may lead to harmful cross-link interference between cells. As a result, the net gain (or loss) from flexible TDD depends on the traffic characteristics and network scenario. In this paper we address the problem in local area packet data networks, such as small- or femto-cell network, where high fluctuation in short term traffic loads is expected. We show through analysis and system level simulations that in such a scenario a significant gain in effective user throughput and packet delays may be achieved under low traffic loads. At high load the gain becomes smaller as packets accumulate in queues and there is both UL and DL traffic to transmit with high probability. When the UL and DL transmit powers are not balanced and switching point adaptation is applied the link direction with lower power may provide degraded performance. We show that introducing interference awareness at the scheduler provides more balanced performance and lowers the packet delays further.     

Delay-dependent fault detection for switched linear systems with time-varying delays—the average dwell time approach

In this paper, the fault detection problem is investigated for a class of discrete-time switched linear systems with time-varying delays. The main purpose is to design a fault detection filter such that, for all unknown inputs, control inputs and time delays, the estimation error between the residual and fault is minimized in an exponential way. The fault detection problem is converted into an exponential H_∞ filtering problem. By using a newly constructed Lyapunov functional and the average dwell time scheme, a novel delay-dependent sufficient condition for the solvability of this problem is established in terms of linear matrix inequalities (LMIs). A numerical example is given to demonstrate the effectiveness of the developed theoretical results.     

Fault Detection for a Class of Nonlinear Singular Systems Over Networks with Mode-Dependent Time Delays

In this paper, the fault detection problem is investigated for a class of nonlinear discrete-time singular systems over networks with mode-dependent time delays. The transmission delays are modeled as a Markov chain with partly known distribution, which takes values in a finite state space. By augmenting the original nonlinear singular system and the fault detection filter, the resulting fault detection dynamics is formulated as an \(H_{\infty }\) filtering problem of a singular Markov jump system. Regular, casual, stochastically stable of the fault detection dynamics and the prescribed \(H_{\infty }\) attenuation level are obtained by the mode-dependent Lyapunov functional approach. The desired fault detection filter is obtained in terms of a series of feasible LMIs. A numerical example is presented to show the effectiveness of the developed technique.     

Reliability analysis of a two-unit parallel system with dissimilar units and general distributions

We study the reliability characteristics of a parallel system attended by a single repair facility and general failure and repair time probability distribution functions (pdf). The basic mathematical problem is the solution of a pair of simultaneous Wiener-Hopf integral equations.A formal solution procedure of the equations has been discussed in the case of unspecified characteristic functions (cf).Fairly explicit solutions are performed if at least one of the failure time pdf's has a rational cf.We compare some of the results presented in previous literature.     

Real Time Fault Diagnosis with Tests of Uncertain Quality for Multimode Systems and its Application in a Satellite Power System

Dynamic fault diagnosis must consider complex fault situations such as fault evolution, coupling, unreliable tests and so on. Previous dynamic fault diagnostic models and inference algorithms are mainly designed for the steady state systems, which are not suitable for the multimode systems. In this paper, a time varying dynamic model to solve the multimode fault diagnosis problem is proposed. Its structure and formulation are presented. Fault diagnosis based on this model is realized by means of inference calculation given the test result, which is formulated as an optimization problem. A new algorithm to solve this problem is proposed. Simulation experiments on different scenarios are carried out to validate the model and the algorithm. As an example, the case of a satellite electrical power system is studied in detail. Both the simulation result and the application result show that the method proposed in this paper can be used to solve the dynamic fault diagnosis problem for multimode systems considering the complex circumstances such as uncertain tests and system delay.     

Fault Tolerant Control for Non-Gaussian Stochastic Distribution Systems

A new fault tolerant control (FTC) problem via the output probability density functions (PDFs) for non-Gaussian stochastic distribution control systems (SDC) is investigated. The PDFs can be approximated by the radial basis functions (RBFs) of neural networks. Differently from the conventional FTC problems, the measured information is in the form of probability distributions of the system output rather than the actual output values. The control objective is to use the output PDFs to design control algorithm that can compensate the faults and attenuate the disturbances. As a result, the concerned FTC problem subject to dynamic relation between the input and output PDFs can be transformed into a nonlinear FTC problem subject to dynamic relation between the control input and the weights of the RBFs neural networks. Feasible criteria to compensate the faults and attenuate the disturbances are provided in terms of linear matrix inequality (LMI) techniques. In order to improve FTC performances, H ^∞ optimization techniques are applied to the FTC design problem to assure that the faults can be compensated and the disturbances can be attenuated. At last, an illustrated example is given to demonstrate the efficiency of the proposed algorithm, and the satisfactory results have been obtained.     

Transistor-level to gate-level comprehensive fault synthesis for n-input primitive gates

In order to have a high level of confidence in system testing, more accurate fault models are needed. An accurate fault model cannot be attained unless all faults in the transistor-level (low level) are considered. However, these transistor-level faults must be mapped onto gate-level (higher level) so that the efficiency of fault simulation, fault emulation and test pattern generation at the gate-level is not sacrificed. This paper covers the static and dynamic single physical failures at transistor-level for static CMOS primitive gates and shows their effects in the output behavior in terms of gate-level faults. A specific fault pattern is proposed and a general formula to calculate the total number of static faults is concluded from these patterns for each type of gate regardless of its number of inputs. The dynamic nature of the physical faults included in the static fault list is evaluated and their cumulative effect on the timing at the circuit output is examined. A general formula for calculating propagation delay at the output due to resistive shorts and opens is derived and a delay fault pattern with variable defect resistance is provided.     

An assessment of alternative wireless access technologies for PCSapplications

The results of studies on three important wireless access technology issues in the personal communications services (PCS) arena are described. They are signal duplexing, multiplexing on the downlink, and channel frequency assignment. Each of these issues was addressed through the comparison of two competing technologies. In the area of duplexing, frequency division duplexing (FDD) was compared to time division duplexing (TDD) with the result that FDD is preferred if appropriate spectrum is available. Multiplexing on the downlink examined time division multiplexing (TDM) versus a burst downlink (TDMA). TDM is preferred for the wide-area local-exchange environment, but in certain indoor, office applications, TDMA may prove advantageous. The two methods of frequency channel assignment investigated are quasi-state autonomous frequency assignment (QSAFA) and dynamic channel assignment (DCA). QSFA is generally preferred, although indoor, multitenent environments with low port loading may benefit from the use of DCA. These analyses assume that the system uses time-division multiple access (TDMA)     

基于切换原理的非均匀采样系统输出反馈控制

在非均匀采样系统中,存在着刷新时间间隔不确定和时变的情况,这给系统控制器的设计造成了很大困难.针对此问题,本文将刷新时间间隔看作时延变量,将不同时延的系统动态变化过程转化为不同子系统的动态变化过程,从而将时延的变化转化为不同子模型之间的切换,最终将非均匀采样系统描述为一类具有有限个子系统的离散时间切换系统.利用输出反馈控制方法,基于平均驻留时间条件,使输出反馈闭环非均匀采样系统指数稳定.最后,通过一个非均匀采样系统仿真实例证明了提出方法的有效性.     

A min, + system theory for constrained traffic regulation and dynamic service guarantees

By extending the system theory under the (min, +) algebra to the time-varying setting, we solve the problem of constrained traffic regulation and develop a calculus for dynamic service guarantees. For a constrained traffic-regulation problem with maximum tolerable delay d and maximum buffer size q, the optimal regulator that generates the output traffic conforming to a subadditive envelope f and minimizes the number of discarded packets is a concatenation of the g-clipper with g(t) = min[f(t+ d), f (t)+q] and the maximal f-regulator. The g-clipper is a bufferless device, which optimally drops packets as necessary in order that its output be conformant to an envelope g. The maximal f-regulator is a buffered device that delays packets as necessary in order that its output be conformant to an envelope f. The maximal f-regulator is a linear time-invariant filter with impulse response f, under the (min, +) algebra. To provide dynamic service guarantees in a network, we develop the concept of a dynamic server as a basic network element. Dynamic servers can be joined by concatenation, "filter bank summation," and feedback to form a composite dynamic server. We also show that dynamic service guarantees for multiple input streams sharing a work-conserving link can be achieved by a dynamic service curve earliest deadline scheduling algorithm, if an appropriate admission control is enforced.     

Fault Tolerant Tracking Control Scheme for UAV Using Dynamic Surface Control Technique

In this paper, a novel fault tolerant control (FTC) approach is proposed for a hypersonic unmanned aerial vehicle (UAV) attitude dynamical system with actuator loss-of-effectiveness (LOE) fault. Firstly, the nonlinear attitude dynamics of hypersonic UAV is given, which represents the dynamic characteristics of UAV in ascent/reentry phases. Then a fault detection scheme is presented by designing a nonlinear fault detection observer (FDO) for the faulty attitude dynamical system of UAV. Moreover, the fault tolerant control scheme is proposed on the basis of the dynamic surface control technique, which guarantees the asymptotic output tracking and ultimate uniform boundedness of the closed-loop dynamical systems of UAV in the actuator LOE faulty case. Finally, simulation results are given to illustrate the effectiveness of the developed FTC scheme.     

TOAD中半导体光放大器的动态增益响应及光脉冲研究

讨论了太赫兹光非对称解复用器中半导体放大器（ＳＯＡ）对具有不同能量和脉宽的控制脉冲的动态增益响应，研究了不同的逆时针信号脉冲和控制脉冲时延的民政部下通过ＳＯＡ后的地针信号脉冲的功率和相位变化。     

TOAD中半导体光放大器的动态增益响应及光脉冲传输特性研究

讨论了太赫兹光非对称解复用器中半导体光放大器 (SOA)对具有不同能量和脉宽的控制脉冲的动态增益响应 ,研究了不同的逆时针信号脉冲和控制脉冲时延的情况下通过 SOA后的逆时针信号脉冲的功率和相位变化。     

多传感器故障检测与隔离的残差产生器设计方法研究

为了解决多传感器故障检测与隔离这一难题,建立了包含卡死、增益时变和偏差时变等三种典型传感器故障的数学模型.借助输出方程,将待检测的传感器故障转换到系统状态方程中进行处理.设计出既能检测出故障,又能将各个故障进行有效隔离的残差产生器,同时还要给出设计残差产生器过程中未知参数的求解方法.用算例对上述设计结果的有效性进行计算...