Domenico Capriglione

Bio: Domenico Capriglione is an academic researcher from University of Cassino. The author has contributed to research in topics: Measurement uncertainty & Cognitive radio. The author has an hindex of 19, co-authored 156 publications receiving 1277 citations. Previous affiliations of Domenico Capriglione include University of Salerno.

On-line sensor fault detection, isolation, and accommodation in automotive engines

Abstract: This paper describes the hybrid solution, based on artificial neural networks (ANNs), and the production rule adopted in the realization of an instrument fault detection, isolation, and accommodation scheme for automotive applications. Details on ANN architectures and training are given together with diagnostic and dynamic performance of the scheme.

On-line sensor fault detection, isolation, and accommodation in automotive engines

Abstract: The paper describes the hybrid solution, based on Artificial Neural Networks, ANNs, and production rule adopted in the realization of an Instrument Fault Detection, Isolation, and Accommodation scheme for automotive applications. Details on the ANN architectures and training are given together with diagnostic and dynamic performance of the scheme.

Online Fault Detection of Rear Stroke Suspension Sensor in Motorcycle

Abstract: This paper describes the implementation and experimental verification of an instrument fault detection (IFD) scheme for stroke sensors. In the scheme, a nonlinear autoregressive with exogenous inputs (NARX) neural network works as a soft sensor for the generation of residuals, while a rule-based decision maker provides the fault detection and classification. The scheme was thought to be implemented in the firmware of central units for the control of semiactive suspension systems for motorbikes. Execution times compatible with the real-time application constraints are reached through straightforward programing rules and suitable code optimization. These times were obtained with machine parameter values (such as clock frequency and absorbed current) far below the upper limit of the range, thanks to the adoption of a programing methodology specially designed for the real-time implementation of diagnostic schemes on general-purpose microcontrollers (MCUs). The diagnostic performance of the scheme was verified through an experimental campaign, carried out on a motorcycle featured with electronic controlled semiactive suspensions. Promptness and reliability in detecting the most common faults of the rear stroke sensor resulted fully compatible with actual applications’ expected values.

Experimental Analysis of Filtering Algorithms for IMU-Based Applications Under Vibrations

Abstract: The use of microelectro-mechanical systems (MEMS)-based inertial measurement units (IMUs) is widespread in many applications concerning monitoring, diagnostic, and/or controlling in navigation and transportation systems, as well as in low-cost applications for automotive and aeronautical fields. The data provided by the set of sensors typically present in IMUs, as accelerometers, gyroscopes, and magnetometers, are often used also for feeding suitable filtering and positioning algorithms able to correct the attitude and path of the vehicle on which they are installed or to provide the analytical redundancy needed for online diagnosis. Nevertheless, on one hand, the performance of low-cost MEMS-based IMUs is certified only under a small set of nominal operating conditions, and on the other hand, the filtering algorithms are often designed and verified under canonical additive noises. In this framework, this article proposes a test plan and a test setup for analyzing and characterizing the performance of filtering algorithms for positioning based on data coming from low-cost IMUs and able to verify systematically the operation of such algorithms under real scenarios. Two kinds of very popular filtering algorithms have been considered, namely, the complementary filter and the attitude and heading reference systems (AHRS) Kalman filter, which belong to two opposite approaches. The experimental results prove how the typical vibrations present in real scenarios can significantly affect the performance of such algorithms.

Analytical redundancy for sensor fault isolation and accommodation in public transportation vehicles

Abstract: The paper discusses an instrument fault detection, isolation, and accommodation procedure for public transportation vehicles. After a brief introduction to the topic, the rule set implementing the procedure with reference to the kinds of sensors usually installed on public transportation vehicles is widely discussed. Particular attention is paid to the description of the rules aimed at allowing the vehicle to continue working regularly even after a sensor fault develops. Finally, both the estimated diagnostic and dynamic performances in the off-line processing of the data acquired in several drive tests are then analyzed and commented upon.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

Abstract: From the Publisher: The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Software testing

Abstract: Software testing is any activity aimed at evaluating an attribute or capability of a program or system and determining that it meets its required results. Although crucial to software quality and widely deployed by programmers and testers, software testing still remains an art, due to limited understanding of the principles of software. The difficulty in software testing stems from the complexity of software: we can not completely test a program with moderate complexity. Testing is more than just debugging. The purpose of testing can be quality assurance, verification and validation, or reliability estimation. Testing can be used as a generic metric as well. Correctness testing and reliability testing are two major areas of testing. Software testing is a trade-off between budget, time and quality.

Camera as the instrument: the rising trend of vision based measurement

Abstract: Due to continuing and rapid advances of both hardware and software technologies in camera and computing systems, we continue to have access to cheaper, faster, higher quality, and smaller cameras and computing units. As a result, vision based methods consisting of image processing and computational intelligence can be implemented more easily and affordably than ever using a camera and its associated operations units. Among their various applications, such systems are also being used more and more by researchers and practitioners as generic instruments to measure and monitor physical phenomena. In this article, we take a look at this rising trend and how cameras and vision are being used for instrumentation and measurement, and we also cast a glance at the metrological gauntlet thrown down by vision-based instruments.