MLSI-RT: memorize LOS range measurements identified residual test location algorithm and performance analysis

The dominant error source of mobile terminal location in wireless sensor networks （WSNs） is the non-line-of-sight （NLOS） propagation error. Among the algorithms proposed to mitigate the influence of NLOS propagation error, residual test （RT） is an efficient one, however with high computational complexity （CC）. An improved algorithm that memorizes the light of sight （LOS） range measurements （RMs） identified memorize LOS range measurements identified residual test （MLSI-RT） is presented in this paper to address this problem. The MLSI-RT is based on the assumption that when all RMs are from LOS propagations, the normalized residual follows the central Chi-Square distribution while for NLOS cases it is non-central. This study can reduce the CC by more than 90%.

Nondestructive Testing and Characterization of Residual Stress Field Using an Ultrasonic Method

To address the difficulty in testing and calibrating the stress gradient in the depth direction of mechanical components, a new technology of nondestructive testing and characterization of the residual stress gradient field by ultrasonic method is proposed based on acoustoelasticity theory. By carrying out theoretical analysis, the sensitivity coefficients of different types of ultrasonic are obtained by taking the low carbon steel（12%C） as a research object. By fixing the interval distance between sending and receiving transducers, the mathematical expressions of the change of stress and the variation of time are established. To design one sending-one receiving and oblique incidence ultrasonic detection probes, according to Snell law, the critically refracted longitudinal wave（LCR wave） is excited at a certain depth of the fixed distance of the tested components. Then, the relationship between the depth of LCR wave detection and the center frequency of the probe in Q235 steel is obtained through experimental study. To detect the stress gradient in the depth direction, a stress gradient LCR wave detection model is established, through which the stress gradient formula is derived by the relationship between center frequency and detecting depth. A C-shaped stress specimen of Q235 steel is designed to conduct stress loading tests, and the stress is measured with the five group probes at different center frequencies. The accuracy of ultrasonic testing is verified by X-ray stress analyzer. The stress value of each specific depth is calculated using the stress gradient formula. Accordingly, the ultrasonic characterization of residual stress field is realized. Characterization results show that the stress gradient distribution is consistent with the simulation in ANSYS. The new technology can be widely applied in the detection of the residual stress gradient field caused by mechanical processing, such as welding and shot peening.

Practical integrated navigation fault detection algorithm based on sequential hypothesis testing

In detecting system fault algorithms,the false alarm rate and undectect rate generated by residual Chi-square test can affect the stability of filters.The paper proposes a fault detection algorithm based on sequential residual Chi-square test and applies to fault detection of an integrated navigation system.The simulation result shows that the algorithm can accurately detect the fault information of global positioning system（GPS）,eliminate the influence of false alarm and missed detection on filter,and enhance fault tolerance of integrated navigation systems.

A computational model of the human glucose-insulin regulatory system

Objective：A computational model of insulin secretion and glucose metabolism for assisting the diagnosis of diabetes mellitus in clinical research is introduced.The proposed method for the estimation of parameters for a system of ordinary differential equations（ODEs）that represent the time course of plasma glucose and insulin concentrations during glucose tolerance test（GTT）in physiological studies is presented.The aim of this study was to explore how to interpret those laboratory glucose and insulin data as well as enhance the Ackerman mathematical model.Methods：Parameters estimation for a system of ODEs was performed by minimizing the sum of squared residuals（SSR）function,which quantifies the difference between theoretical model predictions and GTT＇s experimental observations.Our proposed perturbation search and multiple-shooting methods were applied during the estimating process.Results：Based on the Ackerman＇s published data,we estimated the key parameters by applying R-based iterative computer programs.As a result,the theoretically simulated curves perfectly matched the experimental data points.Our model showed that the estimated parameters,computed frequency and period values,were proven a good indicator of diabetes.Conclusion：The present paper introduces a computational algorithm to biomedical problems,particularly to endocrinology and metabolism fields,which involves two coupled differential equations with four parameters describing the glucose-insulin regulatory system that Ackerman proposed earlier.The enhanced approach may provide clinicians in endocrinology and metabolism field insight into the transition nature of human metabolic mechanism from normal to impaired glucose tolerance.

Inner Attitude Integration Algorithm Based on Fault Detection for Strapdown Inertial Attitude and Heading Reference System

This article proposes a new inner attitude integration algorithm to improve attitude accuracy of the strapdown inertial attitude and heading reference system （SIAHRS） , which, by means of a Kalman filter, integrates the calculated attitude from the accelerometers in inertial measuring unit （IMU） , called damping attitudes, with those from the conventional IMU. As vehicle＇ s acceleration could produce damping attitude errors, the horizontal outputs from accelerometers are firstly used to judge the vehicle＇ s motion so as to determine whether the damping attitudes could be reasonably applied. This article also analyzes the limitation of this approach. Furthermore, it suggests a residual chi-square test to judge the validity of damping attitude measurement in real time, and accordingly puts forward proper information fusion strategy. Finally,the effectiveness of the proposed algorithm is proved through the experiments on a real system in dynamic and static states.