AE signal extraction under the strong noise
According to the technology of using acoustic emission signal to extrapolate the acoustic emission source, the multiple signal classification algorithm based on far-field uniform linear array model had been researched in this paper. Combined with the property of AE monitoring, we present that the far-field multiple signal classification algorithm can be applied to estimate the position of the AE signal source. We can basically find the position of the AE signal source by making this algorithm adaptation with roadway shape and workface in the coal mine AE signal detection. The simulation results show that the proposed algorithm could effectively estimate the position of the AE signal source.
Signal Extraction over Noise
Through the technology of using acoustic emission signal to extrapolate the AE source; this paper describes the basic theory of the near-field uniform linear array model and the Multiple Signal Classification algorithms. Combined with the property of AE monitoring, we present this algorithm can be applied to the spatial position estimation of AE source. The simulation result proves that the MUSIC algorithm based on the near-field uniform linear array will be effectively used in the estimation of AE source.
Assessment of fractures in endodontically treated teeth restored with and without root canal posts using high-resolution cone beam computed tomography
Background Root fractures are a diagnostic challenge for dentists in endodontic treatment. This study aimed to determine the relationship between the characteristics of tooth fractures and the presence of root canal posts in endodontically treated teeth using high-resolution cone beam computed tomography (CBCT). Material and Methods Fifty high-resolution CBCT scans of endodontically treated teeth with a diagnosis of fracture were obtained, of which 30 were from women and 20 were from men. These scans were acquired with three Veraviewepocs 3D units and one 3D Accuitomo 170 unit, with a 40 × 40-mm field of view and 125 μm voxel size. The variables assessed included the type of fracture, extent of fracture, type of retention, post length, cause of endodontic failure, location of the lesion, and time required to detect the fracture (difficulty score). For data analysis, the chi-squared test, Student’s t-test, and multiple linear regression (α <0.05) were used. Results No association was found between the type of fracture and type of retention or between the type of fracture and its extent (P>0.05). On the other hand, the type of fracture significantly influenced the time required for its detection. Additionally, the most difficult plane for detecting the fracture and the difficulty score were associated, with statistically significant results. Conclusions The type of fracture in endodontically treated teeth was not associated with the type of post used for restoration. All of the CBCT systems used to detect tooth fracture showed the same efficiency. Key words:Cone-Beam CT, Tooth Fracture, Root Canal Post.