Study on Mechanical and Frost Resistance Properties of Slag and Macadam Stabilized with Cement and Fly Ash

China is a large country in terms of coal production and consumption. The fly ash and slag produced by thermal power plants pose a great threat to the environment. To reduce the adverse effects of fly ash and slag on the environment, a mixture of slag and macadam stabilized with cement and fly ash was prepared as pavement base material. Compaction tests, unconfined compressive strength tests, splitting strength tests, frost resistance tests, and ultrasonic tests were performed on the mixture. The results show that with an increase in slag replacement rate, the unconfined compressive strength and splitting strength decreased. However, the adverse influence of the slag replacement rate on unconfined compressive strength and splitting strength of specimens gradually weakened with increasing curing time. The frost resistance of the mixture first increased and then decreased with an increase in the slag replacement rate. When cement content was 5% and the slag replacement rate was 50%, the frost resistance of the mixture was the best. Regression analysis of the ultrasonic test showed that the ultrasonic test can effectively characterize the strength of the mixture and the internal damage degree under freeze–thaw cycles. In conclusion, the slag replacement rate of the mixture is recommended to be ~50%, which has preferable mechanical and frost resistance performance.

Phased Array Ultrasonic Test Signal Enhancement and Classification Using Empirical Wavelet Transform And Deep Convolution Neural Network

In the recent past, Non-Destructive Testing (NDT) has become a most popular technology due to its efficiency and accuracy without destroying the object and maintains its original structure and gathering while examining external and internal welding defects. Generally, the NDT environment is harmful which is distinguished by huge volatile fields of electromagnetic, elevated radiation emission instability and elevated heat. Therefore, a suitable NDT approach could be recognized and practiced. In this paper, a novel algorithm is proposed based on Phased array ultrasonic test (PAUT) for NDT in order to attain the proper test attributes. In the proposed methodology, carbon steel welding section is synthetically produced with various defects and tested using PAUT method. The signals acquired from PAUT device is found with noise interference. The Adaptive Least Mean Square (ALMS) filter is proposed to filter PAUT signal in order to eliminate random noise and Gaussian noise. The ALMS filter is the combination of low pass filter (LPF), high pass filter (HPF) and band pass filter (BPF). The time domain PAUT signal is converted into frequency domain signal in order to extract more number of features by applying Empirical Wavelet Transform (EWT) algorithm. In the frequency domain signal, 1st order and 2nd order features extraction techniques are applied to extract various features for further classification. The Deep Learning methodology is proposed for classification PAUT signals. Based on the PAUT signal features, the Deep Convolution Neural Network (DCNN) is applied for further classification. The DCNN will classify the welding signal is whether it is defective or non-defective. The Confusion Matrix (CM) is used for estimation of measurement of performance of classification as calculating accuracy, sensitivity and specificity. The experiments prove that out proposed methodology for PAUT testing for welding defect classification is obtained more accurately and efficiently across existing methodologies by providing numerical and graphical results.

Computer Aided Design of Ultrasonic Test by Numerical Simulation

Ultrasonic tests of dissimilar metal welds require extremely sophisticated technology. The complexity of the test is caused by the grain orientation and difficult accessibility of the weld and it is therefore necessary to redound the examinations by simulation. This study details some application possibilities of CIVA software and presents an example of the evaluation of the procedure used for the given test method with probability of detection curves.

Utilization of the Ultrasonic Diagnostic Method in Rail Status on a Defined Railway Section

In the article we deal with the issue of non-destructive diagnostics of a specified part on the railway, namely the rail. The chapters are devoted to the non-destructive defectoscopic method, or more precisely an ultrasonic test, which is performed by DIO 562 device and it also includes data processing from the measurement. The article briefly describes location and character of defects on the rails and actual process of measurement. The measurement was performed on a standard length of 10 km, with the use of a device capable of copying shape of the rails during the ultrasonic examination. The evaluation of the measurement was processed in specialized software DIO 2000 on the PC. Based on this evaluation, three manual inspections were implemented to determine the character of defects. The conclusion of this article is a precise determination of character and origin of these selected defects, and suggestion for their removal or replacement according to the valid regulations.