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Wiener processes have received considerable attention in degradation modeling over the last two decades. In this paper, we propose a generalized Wiener process degradation model that takes unit-to-unit variation, time-correlated structure and measurement error into considerations simultaneously. The constructed methodology subsumes a series of models studied in the literature as limiting cases. A simple method is given to determine the transformed time scale forms of the Wiener process degradation model. Then model parameters can be estimated based on a maximum likelihood estimation (MLE) method. The cumulative distribution function (CDF) and the probability distribution function (PDF) of the Wiener process with measurement errors are given based on the concept of the first hitting time (FHT). The percentiles of performance degradation (PD) and failure time distribution (FTD) are also obtained. Finally, a comprehensive simulation study is accomplished to demonstrate the necessity of incorporating measurement errors in the degradation model and the efficiency of the proposed model. Two illustrative real applications involving the degradation of carbon-film resistors and the wear of sliding metal are given. The comparative results show that the constructed approach can derive a reasonable result and an enhanced inference precision.

Aiming at the sensor subsystem of spacecraft attitude control system equipped with gyroscopes, earth sensors and sun sensors, the observer-based fault detection and fault location problems are studied to ensure the decoupling of fault diagnosis results with actuator faults. The kinematics equation of spacecraft attitude control system and the measurement model of various sensors are given. Then the sensor subsystem is regarded as a virtual system with gyroscope outputs as input and earth sensor outputs and sun sensor outputs as outputs. On this basis, observers with different functions are designed according to different axes of spacecraft attitude control system, and the diagnostic logic is proposed correspondingly. Finally, the effectiveness of the algorithm is verified by the simulation of the satellite attitude control system.

In this paper, we focus our study on analysis of fault diagnosis performance for satellite attitude control systems subject to $l_{2}$ -norm-bounded process disturbances and measurement noises, which concerns with fault detectability and fault isolability. For an observer-based fault detection (FD), a major concern is to answer if the choice of a threshold satisfies an acceptable trade-off between fault detection rate (FDR) and false alarm rate (FAR). The smaller a threshold is, the better is the FDR, but the poorer is the FAR. In addition to this, knowledge of fault isolability is useful for answering how difficult it is to isolate a fault from another one. The main contributions of this paper are the probabilistic performance evaluation of the FD system in the context of FAR and a contribution analysis-based method of fault isolation. First, an extended $H_{i}/H_{\infty }$ optimization-based FD scheme is applied to the satellite attitude control systems and a recursive algorithm is presented to the implementation of online FD. Second, regarding the uncertain statistical characteristics of the unknown inputs, randomized algorithms are developed to verify the achievable FAR for a prescribed given threshold. Especially, without knowing the $l_{2}$ -norm boundedness of the unknown inputs, a probabilistic estimation of worst case threshold is also obtained to guarantee an acceptable level of FAR. Third, a contribution analysis-based method of fault isolation is proposed for satellite attitude control systems. Finally, the effectiveness of the proposed algorithms is verified through a satellite attitude control system.

Liquid lithium has been considered as a candidate material for several components of future fusion devices. Since the containment materials are usually ferrous alloys, molecular dynamics simulations were performed to study the diffusion behavior of lithium atoms along tilt grain boundaries (GB) including Σ9{114}, Σ11{113}, Σ3{112} and Σ11{332} in α-Fe. The binding energies of a Li interstitial to the GBs were calculated. The results suggest that all the GBs have strong binding effect on the Li atom. The critical temperatures for the Li atom to diffuse were determined. The diffusion process of a Li interstitial in the GBs was systematically analyzed. It turns out that the diffusion mechanism depends on the GB structures. For Σ11{113} and GB Σ9{114}, the Li atom was trapped by the Frenkel defect around the GBs at 300 K and 400 K respectively and therefore the diffusion was slowed down rapidly. For Σ3{112}, no defects were formed around GB and the Li atom diffused into Fe bulk at 700 K and above. For Σ3{112}, the diffusion process is driven by the movement of the GB. Finally, the diffusion coefficient, as well as the activation energy, was evaluated.

Accelerated degradation analysis plays an important role in assessing reliability and making maintenance schedule for highly reliable products with long lifetime. In practical engineering, degradation data, especially measured under accelerated condition, are often compounded and contaminated by measurement errors, which makes the analysis more challenging. Therefore, a Wiener process model simultaneously incorporating temporal variability, individual variation and measurement errors is proposed to analyze the accelerated degradation test (ADT). The explicit forms of the probability distribution function (PDF) and the cumulative distribution function (CDF) are derived based on the concept of first hitting time (FHT). Then, combining with the acceleration models, the maximum likelihood estimations (MLE) of the model parameters are obtained. Finally, a comprehensive simulation study involving two examples and a practical application are given to demonstrate the necessity and efficiency of the proposed model.

Degradation testing is an important technique for assessing life time information of complex systems and highly reliable products. Motivated by fatigue crack growth (FCG) data and our previous study, this paper develops a novel degradation modeling approach, in which degradation is represented by an independent increment process with linear mean and general quadratic variance functions of test time or transformed test time if necessary. Based on the constructed degradation model, closed-form expressions of failure time distribution (FTD) and its percentiles can be straightforwardly derived and calculated. A one-stage method is developed to estimate model parameters and FTD. Simulation studies are conducted to validate the proposed approach, and the results illustrate that the approach can provide reasonable estimates even for small sample size situations. Finally, the method is verified by the FCG data set given as the motivating example, and the results show that it can be considered as an effective degradation modeling approach compared with the multivariate normal model and graphic approach.

This paper studies the sensor optimization configuration which meets the fault diagnosability of affine nonlinear faulty systems. First of all, the judgment method of fault diagnosability and the relevant quantitative evaluation indexes based on the differential geometry theory are presented. Then the optimal sensor allocation model is built, and the pagerank algorithm of the web page ranking is introduced into the configuration problem. Being differ from the new intellective heuristic algorithms, the weighted pagerank algorithm shifts the focus from designing an optimal subset search algorithm of better performance out to evaluating the important degree of each measuring point, and makes use of the analytic model more efficiently rather than the direct graph method. In the end, a validation example of the point mass satellite system is presented to demonstrate the effectiveness of the proposed approach.

This paper deals with the problem of fault estimation for satellite attitude control system with typical component configuration. In order to understand sensor and actuator faults propagation in the attitude control system, we have built the overall system model firstly, which includes the attitude dynamics model, sensor measurement model, attitude determination model, controller model and the moment distribution model. The faults are then considered as unknown inputs and are estimated using a classical proportional-integral observer, more over constant or time-varying fault can be estimated. The proposed observer is derived as a solution of off-line Linear Matrix Inequality (LMI) conditions. Additionally, simulation results are presented to illustrate the efficiency of the proposed method.

This paper focuses on actuator placement joint with a state feedback controller, to minimize the H ∞ norm of the closed-loop system. The actuator placement is even subject to a class of nonlinear constraints. This actuator selection problem is first formulated to be a non-convex optimization problem. Then to overcome these non-convex constraints, several procedures are provided to convert the problem into a sequential convex optimization problem, and correspondingly an optimization algorithm is given. Thruster location selection of an earth-pointing satellite is illustrated to verify the effectiveness of the proposed algorithm.

Knowledge of achievable diagnosability performance can provide theoretical guidance for developing diagnostic algorithms and optimizing sensor placement. A data driven approach for fault diagnosability quantitative evaluation without designing any diagnosis algorithm is proposed. Fault diagnosability is converted to similarity measure of output information which is denoted by fuzzy sets under different fault states. A quantitative evaluation measure and a specific diagnosability evaluation process are given. Finally, an example is presented to demonstrate the effectiveness of the proposed methodology.

This paper investigates the actuator placement of uncertain linear systems. The designed actuator locations are subject to a class of nonlinear equality constraints, and a dynamic output feedback controller should also be derived based on measured outputs. To minimize \(H\infty \) norm of the closed-loop systems, the actuator placement problem is formulated as an uncertain non-convex optimization problem. A series of transformations are developed to convert this problem into a deterministic successive convex problem. Correspondingly, an optimization algorithm is derived based on prediction-correction procedure.

An integrated design of fault diagnosis and reconfiguration method is studied for actuator failures of satellite control system. First, the effectiveness factor and the controller gain are taken as a whole to design the combined control law, which is obtained by placing the closed-loop system poles according to the theory of regional pole assignment. And this paper uses perturbation linearization method to solve the generating bilinear matrix inequalities(BMI). Then the effectiveness factor is obtained with a two-stage Kalman filter and thus the control law can be solved. Finally, the effectiveness of the provided method is illustrated by a simulation.

Driven by the satellite's features such as closed-loop, limited storage space and computing capacity constraint, a fault detection scheme based on the coprime factorization and Youla parameterization is proposed for the on-orbit satellite attitude control system. Based on the SISO dynamic of the satellite in pitch direction and the MIMO one in roll/yaw direction, the residuals equal to y(k)–y(k) is generated by a simple computation using the plant input and control error signals without running the state observer in parallel, therefore the computing expense is reduced to a certain extent, and the related theorems are provided synchronously. Simulation results are presented to show the performance of the proposed fault detection algorithm.

The fault diagnosability analysis for a given model, before developing a diagnosis algorithm, can be used to answer questions like “can the faultfibe detected by observed states?” and “can it separate faultfifrom faultfjby observed states?” If not, we should redesign the sensor placement. This paper deals with the problem of the evaluation of detectability and separability for the diagnosability analysis of affine nonlinear system. First, we used differential geometry theory to analyze the nonlinear system and proposed new detectability criterion and separability criterion. Second, the related matrix between the faults and outputs of the system and the fault separable matrix are designed for quantitative fault diagnosability calculation and fault separability calculation, respectively. Finally, we illustrate our approach to exemplify how to analyze diagnosability by a certain nonlinear system example, and the experiment results indicate the effectiveness of the fault evaluation methods.

We will concentrate on the modeling and analysis of a class of nonstationary time series, called correlation coefficient stationary series, which commonly exists in practical engineering. First, the concept and scope of correlation coefficient stationary series are discussed to get a better understanding. Second, a theorem is proposed to determine standard deviation function for correlation coefficient stationary series. Third, we propose a moving multiple-point average method to determine the function forms for mean and standard deviation, which can help to improve the analysis precision, especially in the context of limited sample size. Fourth, the conditional likelihood approach is utilized to estimate the model parameters. In addition, we discuss the correlation coefficient stationarity test method, which can contribute to the verification of modeling validity. Monte Carlo simulation study illustrates the authentication of the theorem and the validity of the established method. Empirical study shows that the approach can satisfactorily explain the nonstationary behavior of many practical data sets, including stock returns, maximum power load, China money supply, and foreign currency exchange rate. The effectiveness of these processes is addressed by forecasting performance.

It has become an effective way to introduce reconfigurability design in design phase for improving the ability of spacecraft autonomous control since the precondition of fault processing is that the spacecraft is reconfigurable. In this paper, the reconfigurability analysis method is specially considered for the reconfigurability in design phase. Firstly, some basic definitions related to spacecraft reconfigurability are listed. On the basis of observability and controllability, the reconfigurability criterion is given out. Then, the function tree is built for the research of reconfigurability modeling. Next, the steps of reconfigurability modeling and analysis method based on minimal cut set and minimal path set are presented. After that, the indexes of fault reconfigurable degree and system reconfigurable rate for evaluating the reconfigurability are defined, and the method for analyzing the week links of a system is given out also. Finally, the above analysis method is applied to a spacecraft attitude measuring system. The method in this paper can achieve the quantitative evaluated result of reconfigurability and the weak links of a system, which are conducive for theoretical research for reconfigurability design in design phase of spacecraft.

Screening and nurturing algae with high productivity, high lipid content and strong stress resistance are very important in algae industry. In order to increase the lipid content, the Nitzschia sp. was irradiated with a 3 MeV C 2+ beam. The sample pretreatment method was optimized to obtain the best mutagenic condition and the survival ratio curve. The positive mutants with a significant improvement in lipid content were screened and their C 2+ mutagenic effects were analyzed by comparing the greasiness and growth characteristics with the wild type algae. Results showed that when the Nitzschia sp. was cultivated in nutritious medium containing 10% glycerol solution, and dried on the filter for 5 min after centrifugation, the realization of the microalgae heavy ion mutagenesis could be done. The survival ratio curve caused by C 2+ irradiation was proved to be “saddle-shaped”. A positive mutant was screened among 20 survivals after irradiation, the average lipid content of the mutation increased by 9.8% than the wild type after 4 generations. But the growth rate of the screened mutation didn’t change after the heavy ion implantation compared to the wild type algae.

Vibration of Large flexible appendage seriously reduces the stability and accuracy of satellite attitude control, which can be solved by adjusting controller via on-orbit system identification method. This paper focuses on large flexible close mode satellite antenna, and Observer/Kalman filter identification (OKID) method is put into practice to solve the problem of system identification. Mode parameters and displacement responses under impulse and white noise excitations are extracted by finite element method (FEM), and then the concept of singular entropy is introduced to reduce observation noise and determine system order. Markov parameters are computed from displacement response and mode order, which is adopted in minimal realization of state space based on eigensystem realization algorithm (ERA). Comparing with the results of FEM in numerical simulation, OKID method is much more accurate and efficient for large flexible close mode satellite antenna on-orbit system identification.

The satellite power system is an important piece of the satellite system; targeting on the problems of complex fault mechanisms and uncertainty between fault type and fault symptoms, the method of Bayesian network fault diagnosis in the satellite power system has been raised. In the learning process of Bayesian network structure, this algorithm adopts statistical strategy for the rule library provided by many experts, extracts causal relationship from expert knowledge base, fills in the causal relationship table, thereby sets up the fault diagnosis hierarchical structure model in the satellite power system based on Bayesian network. Simulation shows that the Bayesian network fault diagnosis model is effectively solving the uncertainties in fault diagnosis.

Background: Physical loading changes bone microstructure and may influence quantitative ultrasound (QUS) parameters. This in vitro study aims at evaluates the effect of physical loading on bone QUS measurement. Objective: Ten fresh bovine bone specimens were studied. Specimens were scanned by a micro-CT and the density and structure parameters of specimens were calculated. The QUS measurement was performed when specimens subjected to loading, which changed from 0N to 1000N with the step of 100N. Statistical analysis performed to evaluate the difference between nBUA measured with and without loading, and the relationship between nBUA and the parameters measured by micro-CT. Results: While the loading exerted on bone higher than 200N, the measured nBUA significantly higher than nBUA measured without loading. Accompany with the increasing of loading, which exerted on bone, the values of nBUA also increased. A new parameter, the slope of the linearity fitted curve of nBUA values measured under different loading condition, was introduced to evaluate BMD. The correlation coefficient between the slope and BMD is -0.869 (P=0.001). Conclusions: Physical loading substantially influences bone QUS measurement. QUS measurement performed under loading condition may be a new ultrasound method for osteoporosis diagnosis.

Ultrasound contrast agents (UCA) microbubbles have been well recognized as a potential noninvasive tool for blood pressure measurement. The effect of ambient pressure on UCA subharmonic optimal driving frequency (SODF), at which the subharmonic scattering signals were maximal, was investigated experimentally. For groups of microbubbles with 80.1%±1.6% in the diameter range of 1μm-2μm, the shift of the SODF (SSODF) was 0.6MHz between overpressures of 4mmHg and 100mmHg, which was approximately twice of the corresponding shift of the resonance frequency. The SSODF may be as a novel and sensitive index of the local blood pressure estimation based on UCA microbubbles.

Background Physical loading leads to a deformation of bone microstructure and may influence quantitative ultrasound (QUS) parameters. This study aims at evaluating the effect of physical loading on bone QUS measurement, and further, on the potential of diagnosing osteoporosis using QUS method under physical loading condition. Methods 16 healthy young females (control group) and 45 postmenopausal women (divided into 3 groups according to the years since menopause (YSM)) were studied. QUS parameters were measured at calcaneus under self-weight loading (standing) and no loading (sitting) conditions. Weight-normalized QUS parameter (QUS parameter measured under loading condition divided by the weight of the subject) was proposed to evaluate the influence of loading. T-test, One-Way analysis of variance (one way ANOVA) and receiver operating characteristic (ROC) analysis were applied for analysis. Results In QUS parameters, mainly normalized broadband ultrasound attenuation (nBUA), measured with loading significantly differed from those measured without loading (p Conclusions Physical loading substantially influenced bone QUS measurement (mainly nBUA). Weight-normalized QUS parameters can discriminate menopause more effectively. By considering the high relationship between menopause and osteoporosis, an inference was drawn that adding physical loading during measurement may be a probable way to improve the QUS based osteoporosis diagnosis.

Osteoporosis is a worldwide health problem with enormous social and economic impact. Quantitative ultrasound (QUS) method provides comprehensive information on bone mass, microstructure and mechanical properties of the bone. And the cheap, safe and portable ultrasound equipment is more suitable for public health monitoring. QUS measurement was normally performed on bone specimens without mechanical loading. But human bones are subjected to loading during routine daily activities, and physical loading leads to the changes of bone microstructure and mechanical properties. We hypothesized that bone QUS parameters measured under loading condition differ from those measured without loading because the microstructure of bone was changed when loading subjected to bone. Furthermore, when loading was subjected on bone, the loading-lead microstructure change of osteoporosis bone may larger than that of health bone. By considering the high relationship between bone microstructure and QUS parameters, the QUS parameters of osteoporosis bone may changed larger than that of health bone. So osteoporosis may be detected more effectively by the combination of QUS method and mechanical loading.

The purpose of this study was to explore the triphasic mechanical properties of osteoarthritic cartilage with different pathological grades. First, samples of cartilage from rabbits with different stages of osteoarthritis (OA) were graded. Following this, the cartilage was strained by a swelling experiment, and changes were measured using a high-frequency ultrasound system. The result, together with fixed charge density and water volume fraction of cartilage samples, was used to estimate the uniaxial modulus of the cartilage tissue, based on a triphasic model. For the control cartilage samples, the uniaxial elastic modulus on the cartilage surface was lower than those in the middle and deep layers. With an increase in the OA grade, the uniaxial elastic modulus of the surface, middle and deep layers decreased. A significant difference was found in the surface elastic modulus of different OA grades (P

Gyroscope plays an important role in navigational systems and its drift has a direct influence on the precision. However, the gyroscope random drift series in practice are not traditional stationary time series for their time-varying means and variances, and large error cannot be avoided by traditional processing method. It is found that the statistical property of most gyroscope random drift series can meet the requirements defined by correlation coefficient stationary series. The analysis method of gyroscope drift series based on correlation coefficient stationary series model is established in this paper. The correlation coefficient stationarity testing method for gyroscope random drift series is discussed firstly. And then the modeling method process is presented. The proposed modeling procedure can efficiently improve the compensating accuracy of gyroscope random drift, because the presented method satisfactorily explains the nonstationary behavior of the gyroscope random drift series commonly existing in practice.

This paper present a low-cost wearable ultrasound bladder volume measurement and alarm system based on ARM9 and DSP. The system used a new volume computing method to estimate bladder volume based on the ultrasound echo obtained by only one phased-array ultrasonic transducer. The main signal processing task of ultrasound echo are performed using a DSP chip. The estimated value of bladder volume was transmitted to an alarm system based on Zigbee radio link. The system can be used for continuous monitoring of bladder volume and nursing on unconsciousness elders, handicapped with spinal cord injury, other urological patients, and children with nocturnal enuresis through setting alarm threshold.

Ultrasound contrast agents (UCA) micro-bubbles have been well recognized as a potential noninvasive tool for blood pressure estimation. However, previous UCA indices, e.g., the shift of the resonance frequency, echo amplitude and the disappearance time, suffered from problems of low resolution, nonlinearity in the relationship with blood pressure, and only variations of the local pressure but the absolute values etc. In this paper, the effect of ambient pressure on UCA sub-harmonic optimal driving frequency (SODF) was investigated, at which the sub-harmonic scattering signals were the maximum. By applying transmit frequencies between 3MHz and 8MHz and the acoustic pressure of 300kPa, the acoustic attenuation and scattering of micro-bubbles were measured at overpressures of 4mmHg, 50mmHg and 100mmHg, comparable with the healthy human blood pressure. For groups of micro-bubbles with 80% in the diameter range of 1-2 micrometers, the shift of the SODF (SSODF) was 0.6MHz between over-pressures of 4mmHg and 100...