Ambient Vibration Based Damage Diagnosis Using Statistical Modal Filtering and Genetic Algorithm: A Bridge Case Study

The authors recently developed a damage identification method which combines ambient vibration measurements and a Statistical Modal Filtering approach to predict the location and degree of damage. The method was then validated experimentally via ambient vibration tests conducted on full-scale reinforced concrete laboratory specimens. The main purpose of this paper is to demonstrate the feasibility of the identification method for a real bridge. An important challenge in this case is to overcome the absence of vibration measurements for the structure in its undamaged state which corresponds ideally to the reference state of the structure. The damage identification method is, therefore, modified to adapt it to the present situation where the intact state was not subjected to measurements. An additional refinement of the method consists of using a genetic algorithm to improve the computational efficiency of the damage localization method. This is particularly suited for a real case study where the number of damage parameters becomes significant. The damage diagnosis predictions suggest that the diagnosed bridge is damaged in four elements among a total of 168 elements with degrees of damage varying from 6% to 18%

Wavelet Transform-Based Damage Identification in Bladed Disks and Rotating Blades

Blade vibration and blade clearance are effective diagnostic features for the identification of blade damage in rotating machines. Blade tip-timing (BTT) is a noncontact method that is often used to monitor the vibration and clearance of blades in a rotating machinery. Standard signal processing of BTT measurements give one blade response sample per revolution of the machine which is often insufficient for the diagnosis of damage. This paper uses the raw data signals from the sensors directly and employs a wavelet energy-based mistuning index (WEBMI) to predict the presence and locations of damage in rotating blades. The Lipschitz exponent is derived from the wavelet packet coefficients and used to estimate the severity of the damage. In this study, experiments were conducted to obtain BTT measurements on rotating blades at  rpm using three different sensors: an active eddy current sensor, a passive eddy current sensor, and an optical sensor. In addition, hammer excitation experiments were conducted for various added mass (damage) cases to compute the damage severity for a bladed disk. To simulate the damage experimentally in the bladed disk and rotating blades, masses were added to the blades to alter their dynamics and mimic the damage. The results indicate that the WEBMI can detect the presence and location of damage in rotating blades using measurements from common BTT sensors. To check the robustness of the proposed damage severity index, the experimental results were compared with numerical simulation for the bladed disk and showed good agreement

Simulating eddy current sensor outputs for blade tip timing

Blade tip timing is a contactless method used to monitor the vibration of blades in rotating machinery. Blade vibration and clearance are important diagnostic features for condition monitoring, including the detection of blade cracks. Eddy current sensors are a practical choice for blade tip timing and have been used extensively. As the data requirements from the timing measurement become more stringent and the systems become more complicated, including the use of multiple sensors, the ability to fully understand and optimize the measurement system becomes more important. This requires detailed modeling of eddy current sensors in the blade tip timing application; the current approaches often rely on experimental trials. Existing simulations for eddy current sensors have not considered the particular case of a blade rotating past the sensor. Hence, the novel aspect of this article is the development of a detailed quasi-static finite element model of the electro-magnetic field to simulate the integrated measured output of the sensor. This model is demonstrated by simulating the effect of tip clearance, blade geometry, and blade velocity on the output of the eddy current sensor. This allows an understanding of the sources of error in the blade time of arrival estimate and hence insight into the accuracy of the blade vibration measurement

Trends in popularity of some morphological traits of purebred dogs in Australia.

Background The morphology of dogs can provide information about their predisposition to some disorders. For example, larger breeds are predisposed to hip dysplasia and many neoplastic diseases. Therefore, longitudinal trends in popularity of dog morphology can reveal potential disease pervasiveness in the future. There have been reports on the popularity of particular breeds and behavioural traits but trends in the morphological traits of preferred breeds have not been studied. Methods This study investigated trends in the height, dog size and head shape (cephalic index) of Australian purebred dogs. One hundred eighty-one breeds derived from Australian National Kennel Council (ANKC) registration statistics from 1986 to 2013 were analysed. Weighted regression analyses were conducted to examine trends in the traits by using them as outcome variables, with year as the explanatory variable and numbers of registered dogs as weights. Linear regression investigated dog height and cephalic index (skull width/skull length), and multinomial logistic regression studied dog size. Results The total number of ANKC registration had decreased gradually from 95,792 in 1986 to 66,902 in 2013. Both weighted minimal height (p = 0.014) and weighted maximal height (p < 0.001) decreased significantly over time, and the weighted cephalic index increased significantly (p < 0.001). The odds of registration of medium and small breeds increased by 5.3 % and 4.2 %, respectively, relative to large breeds (p < 0.001) and by 12.1 % and 11.0 %, respectively, relative to giant breeds (p < 0.001) for each 5-year block of time. Conclusions Compared to taller and larger breeds, shorter and smaller breeds have become relatively popular over time. Mean cephalic index has increased, which indicates that Australians have gradually favoured breeds with shorter and wider heads (brachycephalic). These significant trends indicate that the dog morphological traits reported here may potentially influence how people select companion dogs in Australia and provide valuable predictive information on the pervasiveness of diseases in dogs. Keywords: Purebred dogs, Dog popularity, Dog height, Dog size, Cephalic index, Brachycephalic Disease, predisposition, Australia. Plain English Summary Some diseases in dogs are related to certain physical characteristics. For example, larger breeds have a higher risk of getting hip dysplasia and certain neoplastic diseases while breeds with wider and shorter heads, such as Pug and French bulldog, are more likely to experience breathing problems and dystocia. Therefore, if we know the trends in popularity of dogs of a certain morphology, we may be able to predict disease pervasiveness. The study aimed to investigate the trends in the height, dog size and head shape of Australian purebred dogs. The numbers of dogs registered within the 181 breeds in Australian National Kennel Council (ANKC) every year from 1986 to 2013 were obtained and analysed. The total number of ANKC registration had decreased from 95,792 in 1986 to 66,902 in 2013. Compared to taller and larger breeds, shorter and smaller breeds have become relatively popular over time. Also, the data suggest that Australians increasingly favour dogs with shorter and wider heads for whose welfare veterinarians often express concern [1, 2]. The results indicate that dog height, dog size and dog head shape may potentially influence how people select companion dogs in Australia and provide valuable predictive information on trends in disease prevalence, enabling the veterinary profession and industry to prepare for potential future caseloads

Dynamic stability of a nonlinear multiple-nanobeam system

We use the incremental harmonic balance (IHB) method to analyse the dynamic stability problem of a nonlinear multiple-nanobeam system (MNBS) within the framework of Eringen’s nonlocal elasticity theory. The nonlinear dynamic system under consideration includes MNBS embedded in a viscoelastic medium as clamped chain system, where every nanobeam in the system is subjected to time-dependent axial loads. By assuming the von Karman type of geometric nonlinearity, a system of m nonlinear partial differential equations of motion is derived based on the Euler–Bernoulli beam theory and D’ Alembert’s principle. All nanobeams in MNBS are considered with simply supported boundary conditions. Semi-analytical solutions for time response functions of the nonlinear MNBS are obtained by using the single-mode Galerkin discretization and IHB method, which are then validated by using the numerical integration method. Moreover, Floquet theory is employed to determine the stability of obtained periodic solutions for different configurations of the nonlinear MNBS. Using the IHB method, we obtain an incremental relationship with the frequency and amplitude of time-varying axial load, which defines stability boundaries. Numerical examples show the effects of different physical and material parameters such as the nonlocal parameter, stiffness of viscoelastic medium and number of nanobeams on Floquet multipliers, instability regions and nonlinear amplitude–frequency response curves of MNBS. The presented results can be useful as a first step in the study and design of complex micro/nanoelectromechanical systems

Global respiratory syncytial virus–related infant community deaths

Background Respiratory syncytial virus (RSV) is a leading cause of pediatric death, with >99% of mortality occurring in low- and lower middle-income countries. At least half of RSV-related deaths are estimated to occur in the community, but clinical characteristics of this group of children remain poorly characterized. Methods The RSV Global Online Mortality Database (RSV GOLD), a global registry of under-5 children who have died with RSV-related illness, describes clinical characteristics of children dying of RSV through global data sharing. RSV GOLD acts as a collaborative platform for global deaths, including community mortality studies described in this supplement. We aimed to compare the age distribution of infant deaths <6 months occurring in the community with in-hospital. Results We studied 829 RSV-related deaths <1 year of age from 38 developing countries, including 166 community deaths from 12 countries. There were 629 deaths that occurred <6 months, of which 156 (25%) occurred in the community. Among infants who died before 6 months of age, median age at death in the community (1.5 months; IQR: 0.8−3.3) was lower than in-hospital (2.4 months; IQR: 1.5−4.0; P < .0001). The proportion of neonatal deaths was higher in the community (29%, 46/156) than in-hospital (12%, 57/473, P < 0.0001). Conclusions We observed that children in the community die at a younger age. We expect that maternal vaccination or immunoprophylaxis against RSV will have a larger impact on RSV-related mortality in the community than in-hospital. This case series of RSV-related community deaths, made possible through global data sharing, allowed us to assess the potential impact of future RSV vaccines