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Nonlinear guided waves mixing technology gains an ascending attention in nondestructive testing field as its capability to resist measuring device nonlinearity. However, recent studies in this topic mainly focus on theoretical analysis. In this article, Lamb waves counter-propagating mixing is explored using a numerical simulation method. Two fundamental Lamb modes(S0 at 1.13 and S0 at 1.82MHz) are selected based on the internal resonance criteria. The mixing wave mode is S1 at 2.95 MHz. A local microdefect is simulated by employing hyperelastic material properties in some regions. Results show that there is a positive correlation of nonlinear acoustic parameter and material degradation level in mixing zone and there is no correlation between nonlinear acoustic parameter and material degradation in fundamental waves propagating routine, which indicate that mixing signal is sensitive to local material defects.

In this work, a probabilistic imaging algorithm based on ellipse method was carried out to locate a fatigue crack using nonlinear S0 mode Lamb waves, which was modeled by Three-dimensional (3D) Finite Element (FE) Simulation. A fatigue crack was modeled as a through-thickness seam, and Short-time Fourier transform (STFT) was performed on the time-domain signals from FE model to extract temporal features. A damage index (DI) was built using a probabilistic imaging algorithm (PIA) after forming an ellipse-like locus. The ultimate image result showed that the location of the fatigue crack was identified and distinguished from the hole. In a conclusion, the proposed imaging algorithm would be a feasible and effective approach to locate fatigue crack by nonlinear S0 mode Lamb waves.

Nonlinear Lamb wave has been widely acknowledged as an efficient Nondestructive Testing (NDT) for detection early stage of fatigue damage. The previous studies focused on the evaluation of fatigue damage using the particular mode pairs, such as S1-S2 mode pair. Recently, Nonlinear S0 Lamb mode with low-frequency was considered for its unique features of less dispersion and easy to be generated, and was indicated may as sensitive to fatigue damage as other mode pairs reported before. However, few researches were performed on experimental measurement. In this work, the S0 mode is demonstrated as an alternative for fatigue damage detection.

P92 martensitic ferritic steels are an attractive material for critical components in power industries due to the excellent creep property. However, these steels are usually susceptible to creep strength degradation during a long service period under the elevated temperature and pressure. Creep damage evaluation is of concern to quantitatively assess the remaining lifespan of the critical components. Nonlinear Lamb waves may offer an efficient method of evaluating these damages for its significant sensitivity to microstructrual evolution. The present research focuses on the evaluation of creep damage in P92 martensitic ferritic steel using nonlinear Lamb waves.

In order to investigate the relationship between nonlinear ultrasonic signals and microstructure changes of plastically deformed materials. In this work, three sets of pure Cu were annealed for one hour at 350 °C 650 °C, 750 °C (isochronously annealed), respectively, to produce grains with different sizes inside Cu. These heat treated samples were underwent interrupted uni-axial tensile tests to get different plastic strains. Ultrasonic measurements were carried out to introduce controlled levels of plastic strain to determine the nonlinear response of longitudinal wave. Finally, the micro-structure evolution observed by transmission electron microscopy (TEM) and electron back scatter diffraction (EBSD) was analyzed to understand its contribution to the acoustic nonlinearity in the plastically damaged Cu.

With the development of modern noise reduction technology, the noise levels of the surface ship and underwater submarine are lower, making the target signal weaker and weaker. When knowing target distance and sonar system parameters, in order to acquire target signal noise level, and not lose the effective information of target signals, this paper introduces a method of estimating target signal intensity of sound source. Its characteristic is adopting diode detection and level ascension circuit. After the processing of MCU (MSP430F5438), target signal intensity is got. The designed receiver has advantages of simple structure, reliable performance, good realtime performance and low power-consumption. Test results of the entire prototype system in anechoic tank show that the maximum error of received source level is not more than 1 dB when the emission source level is between 100dB and 180dB. The designed receiver can meet the designing requirements of modern underwater receiver.

The tactical missile autopilot design process is detailed from a backstepping control perspective. Wherein, two autopilot topologies are proposed, i.e. the angle of attack (AOA) autopilot and acceleration autopilot. A set of new parameters is presented to simplify the expression of AOA control law and show that the positive real requirement on control parameters during step by step design has an unfavorable effect on closed loop system performance. An acceleration autopilot as a tracking problem is then set up and developed. Two control gains, i.e. k 1 and k 2 , are determined on the basis of step and sine command tracking. The results show that k 1 affects mainly system steady state error, and k 2 affects mainly response speed. Moreover, k 1 is bounded and its upper bound has less relevance with k 2 . The nonlinear acceleration autopilot based on a backstepping approach exhibits excellent tracking performance and robustness. In spite of good performance, the application of nonlinear autopilot is limited owing to a lack of physical meaning and complex engineering implementation.

For structural and machine components in service at high temperature and pressure, such as those used in power generating and petrochemical plants, as well as aero-engines and metallurgical machineries, creep life assessment is a major concern because of safety and economic reasons. In this paper, a new model for creep life prediction is proposed based on energy processes. The work of making the material failure of applied loads is used to describe the creep processes respectively. By mathematical technique, the expression of the model is, where is Larson-Miller constant, and is also material constant at certain condition. This function Moreover, owing to its simple expression, it is very easy to use this model to predict the creep life. To check the validity of the new model proposed in this paper, the 250000h creep rupture strength estimates for 2.25Cr1.0Mo steel under stress control at 743~793K have been performed. The results are in a good agreement with the experimental data.

The architecture of the multiplicative type-II fuzzy cellular neural networks (FCNN) with CMOS image sensor is implemented, which is with local connectivity advantageous suitable implemented for VLSI. Base on the proposed FCNN structure which is included the neuron, Min/Max, analog multiplier, pixel and CDS circuit, S/H Circuit, transfer and control circuits. The system has capability to operate the various morphological operations for binary and gray-level image, such as Dilation and Erosion. The simulation results show that the FCNN can operated the specific functions depend on the selected template is successfully verified by the TSMC 0.35 mum 2P4M CMOS technology. There have a great potential in the VLSI implementation of neural network systems for binary and gray-level patterns in image-processing applications.

In the symbol recognition stage of online handwritten math expression recognition, the one-pass dynamic programming algorithm can produce high-quality symbol graphs in addition of the best recognized hypotheses. In this paper, we exploit the rich hypotheses embedded in a symbol graph to discriminatively train the exponential weights of different model likelihoods and the insertion penalty. The training is investigated in two different criteria: maximum mutual information (MMI) and minimum symbol error (MSE). After discriminative training, trigram-based graph rescoring is performed in a post-processing stage. Experimental results finally show a 97% symbol accuracy on a test set of 2,574 written expressions with 43,300 symbols, a significant improvement of symbol accuracy obtained.