Application of phased array ultrasonic technology for nondestructive testing of railway wheels
A scheme is proposed to realize nondestructive testing (NDT) of railway wheels based on phased array ultrasonic testing technology in order to ensure the safe operation and high-speed of railway transport, and achieve accurate determine the defects of railway wheels. A phased array ultrasonic NDT system for wheels was designed. The system includes four main parts: system management software, probe moving and scanning parts, ultrasonic signal acquisition and imaging. A testing scheme for wheels was designed aiming at the configuration of railroad wheels and the distribution of defects in them. The wheels safety testing experiments were carried out on model wheels with artificial defects. Results of experiments demonstrate that the testing methods are more accurate in examining the depth and the location of defects in the wheels, and this system can obtain the defects status of wheels with higher sensitivity, higher facilitation and less affection by environmental factors.
Ultrasonic Phased Array Industrial Imaging with Sub-Nyquist Sampling Rate
this paper uses a new type of FRI (Finite Rate of Innovation) sampling pattern based Sub-Nyquist sampling model breaked through Shannon theorem that it can get accurate signal reconstruction based on signal information rate, which requires the sampling frequency lower than two times the max signal frequency. We apply the new model in the ultrasonic phased array industrial imaging. In the experiment, ultrasonic phased array realized dynamic focusing and the high speed scan by ultrasonic array transducer of various array time delays to get flexible controllable synthesis beam composed signals that received by 32 phased array elements . The results indicate that in the model it greatly reduces the signal sampling frequency and improves the signal-to-noise ratio, frequency resolution at the same of the beam focusing and steering flexible.
A natural language discourse model to explain linear programming models and solutions
Abstract This paper presents a natural language (i.e., English) discourse model to explain a linear programming model and, possibly, its computed solution (which need not be optimal). Drawing from earlier syntactic translations, a semantic model is presented, based on economic input-output relations commonly found in large-scale linear programs. These are then shown how to form rule-driven explanations, which comprises a fundamental component of an intelligent mathematical programming system.