Accuracy of Various Algorithms for Diagnosing from a Disease by Finding Sensitivity Matrix

2009 ◽  
Author(s):  
Robert M. Hamm ◽  
Kiamars R. Golmoradi ◽  
Timothy A. Wolfe ◽  
Talia B. Magrill ◽  
Frank J. Papa
Keyword(s):  
ATZ worldwide ◽  
2021 ◽  
Vol 123 (3) ◽  
pp. 26-31
Author(s):  
Jana Büttner ◽  
Stefan Schwarz ◽  
Axel Schumacher ◽  
Thomas Bäck

2021 ◽  
pp. 147592172110219
Author(s):  
Rongrong Hou ◽  
Xiaoyou Wang ◽  
Yong Xia

The l1 regularization technique has been developed for damage detection by utilizing the sparsity feature of structural damage. However, the sensitivity matrix in the damage identification exhibits a strong correlation structure, which does not suffice the independency criteria of the l1 regularization technique. This study employs the elastic net method to solve the problem by combining the l1 and l2 regularization techniques. Moreover, the proposed method enables the grouped structural damage being identified simultaneously, whereas the l1 regularization cannot. A numerical cantilever beam and an experimental three-story frame are utilized to demonstrate the effectiveness of the proposed method. The results showed that the proposed method is able to accurately locate and quantify the single and multiple damages, even when the number of measurement data is much less than the number of elements. In particular, the present elastic net technique can detect the grouped damaged elements accurately, whilst the l1 regularization method cannot.


2016 ◽  
Vol 16 (8) ◽  
pp. 2466-2476 ◽  
Author(s):  
Jiamin Ye ◽  
Mingxu Mao ◽  
Haigang Wang ◽  
Wuqiang Yang

2012 ◽  
Vol 57 (19) ◽  
pp. 6279-6293 ◽  
Author(s):  
Moulay Ali Nassiri ◽  
Sami Hissoiny ◽  
Jean-François Carrier ◽  
Philippe Després
Keyword(s):  

Author(s):  
Jorge Saavedra ◽  
Venkat Athmanathan ◽  
Guillermo Paniagua ◽  
Terrence Meyer ◽  
Doug Straub ◽  
...  

Abstract The aerothermal characterization of film cooled geometries is traditionally performed at reduced temperature conditions, which then requires a debatable procedure to scale the convective heat transfer performance to engine conditions. This paper describes an alternative engine-scalable approach, based on Discrete Green’s Functions (DGF) to evaluate the convective heat flux along film cooled geometries. The DGF method relies on the determination of a sensitivity matrix that accounts for the convective heat transfer propagation across the different elements in the domain. To characterize a given test article, the surface is discretized in multiple elements that are independently exposed to perturbations in heat flux to retrieve the sensitivity of adjacent elements, exploiting the linearized superposition. The local heat transfer augmentation on each segment of the domain is normalized by the exposed thermal conditions and the given heat input. The resulting DGF matrix becomes independent from the thermal boundary conditions, and the heat flux measurements can be scaled to any conditions given that Reynolds number, Mach number, and temperature ratios are maintained. The procedure is applied to two different geometries, a cantilever flat plate and a film cooled flat plate with a 30 degree 0.125” cylindrical injection orifice with length-to-diameter ratio of 6. First, a numerical procedure is applied based on conjugate 3D Unsteady Reynolds Averaged Navier Stokes simulations to assess the applicability and accuracy of this approach. Finally, experiments performed on a flat plate geometry are described to validate the method and its applicability. Wall-mounted thermocouples are used to monitor the surface temperature evolution, while a 10 kHz burst-mode laser is used to generate heat flux addition on each of the discretized elements of the DGF sensitivity matrix.


Author(s):  
Jon Geist ◽  
Muhammad Yaqub Afridi ◽  
Craig D. McGray ◽  
Michael Gaitan

Cross-sensitivity matrices are used to translate the response of three-axis accelerometers into components of acceleration along the axes of a specified coordinate system. For inertial three-axis accelerometers, this coordinate system is often defined by the axes of a gimbal-based instrument that exposes the device to different acceleration inputs as the gimbal is rotated in the local gravitational field. Therefore, the cross-sensitivity matrix for a given three-axis accelerometer is not unique. Instead, it depends upon the orientation of the device when mounted on the gimbal. We define nine intrinsic parameters of three-axis accelerometers and describe how to measure them directly and how to calculate them from independently determined cross-sensitivity matrices. We propose that comparisons of the intrinsic parameters of three axis accelerometers that were calculated from independently determined cross-sensitivity matrices can be useful for comparisons of the cross-sensitivity-matrix measurement capability of different institutions because the intrinsic parameters will separate the accelerator-gimbal alignment differences among the participating institutions from the purely gimbal-related differences, such as gimbal-axis orthogonality errors, z-axis gravitational-field alignment errors, and angle-setting or angle-measurement errors.


Robotica ◽  
2010 ◽  
Vol 29 (6) ◽  
pp. 805-814 ◽  
Author(s):  
Farhad Aghili

SUMMARYThis paper investigates 3-dimensional (3D) Simultaneous Localization and Mapping (SLAM) and the corresponding observability analysis by fusing data from landmark sensors and a strap-down Inertial Measurement Unit (IMU) in an adaptive Kalman filter (KF). In addition to the vehicle's states and landmark positions, the self-tuning filter estimates the IMU calibration parameters as well as the covariance of the measurement noise. The discrete-time covariance matrix of the process noise, the state transition matrix and the observation sensitivity matrix are derived in closed form, making it suitable for real-time implementation. Examination of the observability of the 3D SLAM system leads to the the conclusion that the system remains observable, provided that at least three known landmarks, which are not placed in a straight line, are observed.


2011 ◽  
Vol 243-249 ◽  
pp. 1830-1834
Author(s):  
Ke Ke Peng

As to sensitivity analysis, based on traditional sensitive factor definition and concept of reliability vector, two kinds of sensitivity problems are putted forward in this paper. And factor sensitivity matrix is defined. As far as large and complex structures are concerned, factor sensitivity matrix of incremental form is given. Furthermore, sensitivity surface is putted forward. ANSYS PDS(ANSYS Probabilistic Design System)can solve the above two kinds of sensitivity problems efficiently. The example bridge is a CFST arch bridge with 83.6 meter-span, which operated for 10 years. The analysis result shows that the definitions enhance the maneuverability of sensitivity analysis, and ANSYS PDS is practical.


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