In this research, two methods for crack detection in structures are presented and compared. The considered structure is a cantilever beam with rectangular cross section. In order to find cracks, firstly, a new technique based on wavelet analysis and finite element method (FEM) is applied. The advantage of this technique is that the crack detection process is more clear and comfortable than previous works. Then the process of crack detection is performed using FEM and combination of two types of artificial neural network (ANN) including radial basis function (RBF) and back-error propagation (BEP) neural networks. For crack identification in the proposed method, firstly, a RBF neural network is used to detect the number of cracks of structure. Then a BEP neural network is trained to detect the locations of cracks. Training of neural networks is performed using obtained data from FEM. Finally obtained results from two methods are compared with each other.
- Inderscience Publishers
- Applying artificial neural network and wavelet analysis for ...
Using Spectroscopy for Used Oil Analysis
Evaluating the wear condition of equipment is a primary requirement of conditionmonitoringprograms. Oil wetted equipment will generate wear particles throughoutits lifetime, the nature and rate of the wear varies from initial break in through to endof life seizure. The technique employed to detect wear and its severity is spectroscopy. Spectroscopy is a technique for detecting and quantifying the presence of elementsin a material. Spectroscopy utilizes the fact that each element has a unique atomicstructure. When...
Micro-plastics and the Specac Diamond Compression Cell
The Environmental Audit Committee has called for a global ban on microbeads, minuscule plastic balls used by the cosmetic and cleaning industries for their abrasive properties (exfoliating face-wash, shower gel, toothpaste, etc). According to BBC News, a single shower using a micro-bead product can release up to 100,000 micro-beads into the ocean. These can become ingested by fish, worms, birds and other organisms, causing physical/biological harm or even death and disrupting the marine ecosystem. Every...
Steam Turbine Rotor Transient Thermo-Structural Analysis and Lifetime Prediction
Market requirements for faster and more frequent power unit start-up events result in a much faster deterioration of equipment, and a shorter equipment lifespan. Significant heat exchange occurs between steam and turbine rotors during the start-up process and even more intensive heat exchange takes place during the condensation phase in cold start-up mode, which leads to further thermal stresses and lifetime reduction. Therefore, the accuracy of lifetime prediction is strongly affected and dependent on the...
Satellite analysis to identify changes and drivers of CyanoHABs dynamics in Lake Taihu
A long-term satellite-based analysis was performed to assess the impact of environmental factors on cyanobacterial harmful blooms (CyanoHABs) dynamics in a typical shallow lake, Lake Taihu. A sub-pixel approach (algae pixel-growing algorithm) was used with 13 years of MOderate-resolution Imaging Spectroradiometer (MODIS) data to evaluate changes in bloom extension, initiation date, duration, and occurrence frequency before and after a massive bloom event (2007). Results indicated that the conditions after this...
Geochemical classification of groundwater using multivariate statistical analysis in Latvia
Multivariate statistical methods – principal component analysis (PCA) and hierarchical cluster analysis (HCA) – are applied to identify geochemically distinct groundwater groups in the territory of Latvia. The main processes observed to be responsible for groundwater chemical composition are carbonate and gypsum dissolution, fresh and saltwater mixing and ion exchange. On the basis of major ion concentrations, eight clusters (C1–C8) are identified. C6 is interpreted as recharge water not in equilibrium with most...