Sul rinforzo di elementi in C.A.: confronto tra varie normative

Il documento pre-normativo italiano sul rinforzo di strutture in c.a. mediante l’uso di materiale fibrorinforzato. 1.1 INTRODUZIONE La situazione unica dell’Italia per quanto riguarda la conservazione delle costruzioni esistenti, è il risultato della combinazione di due aspetti, come primo, il medio-alto rischio sismico di una gran parte di territorio, come testimoniato dalla zonizzazione sismica recente, e come secondo aspetto, l'estrema complessità di un ambiente edilizio che non ha confronto nel mondo. Le tipologie della costruzione in Italia si distinguono a quelle stimate come patrimonio storico, che in alcuni casi risalgono a circa 2000 anni fa, a quelle che sono state costruite in ultimi cinque secoli, durante e dopo il Rinascimento, che sono considerate come patrimonio culturale ed architettonico dell' Italia (e del mondo!), infine a quelle fatte in tempi recenti, considerevolmente durante e dopo il boom economico del l960 ed ora visti come antiquate. Le due prime categorie in gran parte sono composte dalle edilizie di muratura, mentre agli ultimi principalmente appartengono le costruzioni di cemento armato.

Power consumption analysis for self-diagnosis of Wireless Sensor Nodes

Wireless sensor networks can transform our buildings in smart environments, improving comfort, energy efficiency and safety. Today however, wireless sensor networks are not considered reliable enough for being deployed on large scale. In this thesis, we study the main failure causes for wireless sensor networks, the existing solutions to improve reliability and investigate the possibility to implement self-diagnosis through power consumption measurements on the sensor nodes. Especially, we focus our interest on faults that generate in-range errors: those are wrong readings but belong to the range of the sensor and can therefore be missed by external observers. Using a wireless sensor network deployed in the R\&D building of NXP at the High Tech Campus of Eindhoven, we performed a power consumption characterization of the Wireless Autonomous Sensor (WAS), and studied through some experiments the effect that faults have in the power consumption of the sensor.

Fault diagnosis of an automotive suspension system

With the development of the embedded application and driving assistance systems, it becomes relevant to develop parallel mechanisms in order to check and to diagnose these new systems. In this thesis we focus our research on one of this type of parallel mechanisms and analytical redundancy for fault diagnosis of an automotive suspension system. We have considered a quarter model car passive suspension model and used a parameter estimation, ARX model, method to detect the fault happening in the damper and spring of system. Moreover, afterward we have deployed a neural network classifier to isolate the faults and identifies where the fault is happening. Then in this regard, the safety measurements and redundancies can take into the effect to prevent failure in the system. It is shown that The ARX estimator could quickly detect the fault online using the vertical acceleration and displacement sensor data which are common sensors in nowadays vehicles. Hence, the clear divergence is the ARX response make it easy to deploy a threshold to give alarm to the intelligent system of vehicle and the neural classifier can quickly show the place of fault occurrence.