Fault detection filter design for linear discrete time-varying systems with multiplicative noise

The problem of fault detection for linear discrete timevarying systems with multiplicative noise is dealt with.By using an observer-based robust fault detection filter（FDF） as a residual generator,the design of the FDF is formulated in the framework of H ∞ filtering for a class of stochastic time-varying systems.A sufficient condition for the existence of the FDF is derived in terms of a Riccati equation.The determination of the parameter matrices of the filter is converted into a quadratic optimization problem,and an analytical solution of the parameter matrices is obtained by solving the Riccati equation.Numerical examples are given to illustrate the effectiveness of the proposed method.

H_-/H_∞ fault detection filter design for interval time-varying delays switched systems

The problem of the robust fault detection filter design for time-varying delays switched systems is considered in the framework of mixed H-/H∞. Firstly, the weighted H∞ performance index is utilized as the robustness performance, and the H- index is used as the sensitivity performance for obtaining the robust fault detection filter. Then a novel multiple Lyapunov-Krasovskii function is proposed for deriving sufficient existence conditions of the robust fault detection filter based on the average dwell time technique. By introducing slack matrix variable, the coupling between the Lyapunov matrix and system matrix is removed, and the conservatism of results is reduced. Based on the robust fault detection filter, residual is generated and evaluated for detecting faults. In addition, the results of this paper are dependent on time delays,and represented in the form of linear matrix inequalities. Finally,the simulation example verifies the effectiveness of the proposed method.

A 15-year-Long catalog of seismicity in the Eastern Tennessee Seismic Zone(ETSZ)using matched filter detection

We present a detailed catalog of 13671 earthquakes in the Eastern Tennessee Seismic Zone(ETSZ)that spans January 1,2005 to July 31,2020.We apply a matched filter detection technique on over 15 years of continuous data,resulting in arguably the most complete catalog of seismicity in the ETSZ yet.The magnitudes of newly detected events are determined by computing the amplitude ratio between the detections and templates using a principal component fit.We also compute the b-value for the new catalog and comparatively relocate a subset of newly detected events using XCORLOC and hypoDD,which shows a more defined structure at depth.We find the greatest concentration along and to the east of the New York-Alabama Lineament,as defined by the magnetic anomaly,supporting the argument that this feature likely is related to the generation of seismicity in the ETSZ.We examine seismicity in the vicinity of the Watts Bar Reservoir,which is located about 5 km from the epicenter of the M_(W) 4.4 December 12,2018 Decatur,Tennessee earthquake,and find possible evidence for reservoir modulated seismicity in this region.We also examine seismicity in the entire ETSZ to search for a correlation between shallow earthquakes and seasonal hydrologic changes.Our results show limited evidence for hydrologicallydriven shallow seismicity due to seasonal groundwater levels in the ETSZ,which contradicts previous studies hypothesizing that most intraplate earthquakes are associated with the dynamics of hydrologic cycles.

Robust fault detection filter design for a class of time-delay systems via equivalent transformation

This paper is concerned with the robust fault detection filter （RFDF） design for a class of linear time- invariant systems （LTISs） with output state time delays. Although existing results in literatures study the RFDF for time- delay systems, few is concerned with the output state time-delay systems. The basic idea of our study is to eliminate the time delays of system and transform it to a delay-free system （i.e., a linear time-invariant system without time delays） by the bicausal change of coordinates approach. Then, we design the RFDF for the delay-free LTIS, which is equivalent to the original system with time delays. We first introduce a class of systems with output state time delays, whose fault can be detected by using the RFDF design approach for delay-free systems. Then, since the RFDF design problem can be formulated as a standard H-infinity-model matching problem, it is solved by using H-infinity-optimization LMI techniques. In the last, the adaptive threshold of fault detection is chosen and an illustrative design example is used to demonstrate the validity of the design approach.

Design of parametric fault detection systems: An H-infinity optimization approach

Problems related to the design of observer-based parametric fault detection(PFD) systems are studied. The core of our study is to first describe the faults occurring in systemactuators, sensors and components in the form of additive parameter deviations, then to transformthe PFD problems into a similar additive fault setup, based on which an optimal observer-basedoptimization fault detection approach is proposed. A constructive solution optimal in the sense ofminimizing a certain performance index is developed. The main results consist of defining parametricfault detectability, formulating a PFD optimization problem and its solution. A numerical exampleto demonstrate the effectiveness of the proposed approach is provided.

Optimal fault detection for a class of discrete-time switched linear systems

This paper deals with the problem of optimal fault detection filter （FDF） design for a class of discrete-time switched linear systems under arbitrary switching. By using an observer-based FDF as a residual generator, the design of the FDF is formulated into an optimization problem through maximizing the H_/H∞ or H∞/H∞ performance index. With the aid of an operator optimization method, it is shown that a mode-dependent unified optimal solution can be derived by solving a coupled Riccati equation. A numerical example is given to show the effectiveness of the proposed method.

Application of subband adaptive filtering techniques to ultrasonic detection in multilayers

The ultrasonic testing for the defects of complete disbond in multi-layered structure with lower acoustic impedance beneath a high acoustic impedance overburden is one of the difficult problems in ultrasonic nondestructive testing field. A model of a multi-layered steel-rubber composite plate is depicted. Because the acoustic impedance of the steel differs far from that of the couplant water and the rubber, the energy of the signal reflected from the debonded rubber layers is very weak. More over, the flaw echoes are masked by the strong echoes reverberated in the steel plate. It's nearly impossible to identify the debonding echoes directly. The subband adaptive filtering method is discussed in the paper, where the subband decomposition is performed by mutual wavelet packets decomposition on the criterion of maximizing the cross-correlation between the signals. The simulations on both synthetic and real signals are presented. The echoes from the delaminated flaw at the depth of 5 mm in the rubber from the calculated signal, and echoes from the flaw at the depth of 3 mm from the real signal are extracted successfully.

Improved Flight Conflict Detection Algorithm Based on Gauss-Hermite Particle Filter

In order to improve the accuracy of free flight conflict detection and reduce the false alarm rate, an improved flight conflict detection algorithm is proposed based on Gauss-Hermite particle filter（GHPF）. The algorithm improves the traditional flight conflict detection method in two aspects：（i） New observation data are integrated into system state transition probability, and Gauss-Hermite Filter（GHF） is used for generating the importance density function.（ii） GHPF is used for flight trajectory prediction and flight conflict probability calculation. The experimental results show that the accuracy of conflict detection and tracing with GHPF is better than that with standard particle filter. The detected conflict probability is more precise with GHPF, and GHPF is suitable for early free flight conflict detection.

考虑温度影响的砷化镓光子晶体压力传感器的设计与研究

提出了一种由双通道滤波器构成的砷化镓光子晶体压力传感器,利用波导与腔耦合实现窄带滤波,双通道分别实现压力探测和温度探测的功能。以室温25℃、0压力的情况作为参考,在温度为-25~45℃、压力为0~2GPa的范围内,根据滤波器的滤波波长分别与温度和压力之间的线性变化关系,探测温度和压力。同时还分析并比较了极端温度情况下滤波波长的变化,确定温度变化对压力测量造成的影响,在较恶劣的情况下温度变化不可忽略。分析得出未考虑温度响应的压力灵敏度约为16.6nm/GPa,消除温度响应后压力灵敏度约为15.9nm/GPa,品质因子高达5696。

An Improved Filter of Progressive TIN Densification for LiD AR Point Cloud Data

Based on the classic filter of progressive triangulated irregular network（TIN） densification, an improved filter is proposed in this paper. In this method, we divide ground points into grids with certain size and select the lowest points in the grids to reconstruct TIN in the process of iteration. Compared with the classic filter of progressive TIN densification（PTD）, the improved method can filter out attached objects, avoid the interference of low objects and obtain relatively smooth bare-earth. In addition, this proposed filter can reduce memory requirements and be more efficient in processing huge data volume. The experimental results show that the filtering accuracy and efficiency of this method is higher than that of the PTD method.

Novel DTD and VAD assisted voice detection algorithm for VoIP systems

Echo cancellation plays an important role in current Internet protocol（IP） based voice interactive systems. Voice state detection is an essential part in echo cancellation. It mainly comprises two parts： double talk detection（DTD） and voice activity detection（VAD）. DTD is used to detect doubletalk and prevent filter divergence in the presence of near-end speech, and VAD is used to determine the near-end voice activity and output silence indicator when near-end is silent. However, DTD straightforwardly proceeded may mistakenly declare double talk under double silent condition, coefficients update under the far-end silence condition may lead to filter divergence, and current VAD algorithms may misjudge the residual echo from the near end to be far-end voice. Therefore, a voice detection algorithm combining DTD and far-end VAD is proposed. DTD is implemented when VAD declares far-end speech, filtering and coefficients update will be halted when VAD declares far-end silence, and the far-end VAD adopted is multi-feature VAD based on short-time energy and correlation. The new algorithm can improve the accuracy of DTD, prevent filter divergence, and exclude the circumstance that far-end signal only contains residual echo from near end. Actual test results show that the voice state decision of the new algorithm is accurate, and the performance of echo cancellation is improved.

A Fault-tolerance Estimating Method for Ionosphere Corrections in Satellite Navigation System

Aiming to the reliable estimates of the ionosphere differential corrections for the satellite navigation system in the presence of the ionosphere anomaly, a fault-tolerance estimating method, which is based on the distributed Kalman filtering, is proposed. The method utilizes the parallel sub-filters for estimating the ionosphere differential corrections. Meanwhile, an infinite norm （IN） method is proposed for the detection of the ionosphere irregularity in the filter processing. Once the anomaly is detected, the sub-filter contaminated by the anomaly measurements will be excluded to ensure the reliability of the estimates. The simulation is conducted to validate the method and the results indicate that the anomaly can be found timely due to the novel fault detection method based on the infinite norm. Because of the parallel sub-filter architecture, the measurements are classified by the spatial distribution so that the ionosphere anomaly can be positioned and excluded more easily. Thus, the method can provide the robust and accurate ionosphere differential corrections.