Non-Contact Local and Global Damage Detection with Integrated Ultrasonic Transducers

Peer reviewed: YesNRC publication: Ye

Engine Oil Condition Monitoring Using High Temperature Integrated Ultrasonic Transducers

The present work contains two parts. In the first part, high temperature integrated ultrasonic transducers (IUTs) made of thick piezoelectric composite films, were coated directly onto lubricant oil supply and sump lines of a modified CF700 turbojet engine. These piezoelectric films were fabricated using a sol-gel spray technology. By operating these IUTs in transmission mode, the amplitude and velocity of transmitted ultrasonic waves across the flow channel of the lubricant oil in supply and sump lines were measured during engine operation. Results have shown that the amplitude of the ultrasonic waves is sensitive to the presence of air bubbles in the oil and that the ultrasound velocity is linearly dependent on oil temperature. In the second part of the work, the sensitivity of ultrasound to engine lubricant oil degradation was investigated by using an ultrasonically equipped and thermally-controlled laboratory testing cell and lubricant oils of different grades. The results have shown that at a given temperature, ultrasound velocity decreases with a decrease in oil viscosity. Based on the results obtained in both parts of the study, ultrasound velocity measurement is proposed for monitoring oil degradation and transient oil temperature variation, whereas ultrasound amplitude measurement is proposed for monitoring air bubble content

NDT of bonded composite patches on aluminum beams using integrated ultrasonic transducers

Peer reviewed: YesNRC publication: Ye

In-situ ice and structure thickness monitoring using integrated and flexible ultrasonic transducers

Peer reviewed: YesNRC publication: Ye

Structural health monitoring of composites using integrated and flexible piezoelectric ultrasonic transducers

Peer reviewed: YesNRC publication: Ye

Pozzolanicity of the industrial wastes, glass and ceramic wools

As fibras cerâmicas se caracterizam por ser um material leve, com alto grau de pureza, baixo armazenamento de calor, baixa condutividade térmica, resistência a choque térmico e alta resistência à corrosão em altas temperaturas. Essas características levam a uma grande procura das indústrias mínero-metalúrgicas e de outros setores para revestimentos de distribuidores, muflas, fornos de aquecimentos, entre outros. Após utilização no processo, por perderem sua capacidade de isolamento, os resíduos gerados precisam de destinação. Esse trabalho enfoca, especificamente, resíduos de lã cerâmica e lã de vidro. Pelo fato de a composição das fibras cerâmicas ser rica em sílica e alumina, efetuou-se uma investigação acerca da atividade pozolânica das mesmas com a cal e o cimento, especificamente CPV ARI, CPII E32 e CPIII 32RS, para avaliação da perspectiva de reciclagem em possível incorporação no concreto

Fiber Optic Sensors for Structural Health Monitoring of Air Platforms

Aircraft operators are faced with increasing requirements to extend the service life of air platforms beyond their designed life cycles, resulting in heavy maintenance and inspection burdens as well as economic pressure. Structural health monitoring (SHM) based on advanced sensor technology is potentially a cost-effective approach to meet operational requirements, and to reduce maintenance costs. Fiber optic sensor technology is being developed to provide existing and future aircrafts with SHM capability due to its unique superior characteristics. This review paper covers the aerospace SHM requirements and an overview of the fiber optic sensor technologies. In particular, fiber Bragg grating (FBG) sensor technology is evaluated as the most promising tool for load monitoring and damage detection, the two critical SHM aspects of air platforms. At last, recommendations on the implementation and integration of FBG sensors into an SHM system are provided

Validation of strain gauges for structural health monitoring with bayesian belief networks

The application of structural health monitoring (SHM) often employs multiple sensors to monitor the state of health and usage of the structures. The fault of any sensor may lead to an inaccurate or even incorrect inference with the collected sensor data, which will accordingly create a negative impact on higher-level decisions for maintenance and services. Thus, sensor validation becomes a critical process to the performance of the whole SHM system. This paper presents the use of Bayesian belief network to validate the reading of strain gauges on an aluminum plate for loading monitoring. The Bayesian belief network is constructed with the training data. The factors investigated in this paper, which may affect the validation process, include sensor configuration, sensor redundancy, and sensor data range for the discretization. The feasibility of using a Bayesian belief network for SHM sensor validation is demonstrated with the experimental results.Peer reviewed: YesNRC publication: Ye