Theoretical error formation and evaluation of acoustic source localization for cluster-based techniques.

In this paper, the formation of theoretical error is presented to investigate the acoustic source localization (ASL) error that can be expected from traditional L-shaped, cross-shaped, square-shaped, and modified square-shaped sensor cluster arrangements. The response surface model based on the optimal Latin hypercube design is developed to theoretically study the effects of sensor placement parameters on the error evaluation index of root mean squared relative error (RMSRE) for the four techniques. The ASL results from the four techniques with the optimal placement parameters are analyzed theoretically. The relevant experiments are conducted for verifying the above theoretical research. The results show that the theoretical error, formed by the difference between the true and the predicted wave propagation directions is related to arrangement of sensors. The results also show that the sensor spacing and the cluster spacing are the two parameters that affect the ASL error most. Between these two parameters the sensor spacing has the stronger influence. The RMSRE increases with an increasing sensor spacing and a decreasing cluster spacing. Meanwhile, the interaction effect of placement parameters should be also emphasized, especially that between the sensor spacing and the cluster spacing for the L-shaped sensor cluster-based technique. Among the four cluster-based techniques, the newly modified square-shaped sensor cluster-based technique shows the smallest RMSRE and not the largest number of sensors. This research on error generation and analysis will provide guidance for the optimal sensor arrangements in cluster-based techniques.

Theoretical model and digital extraction of subsurface damage in ground fused silica.

Based on the fracture mechanics and grinding kinematics, a theoretical model is developed to determine various subsurface damage (SSD) parameters and roughness Rz of the ground brittle material with consideration of the material removal mode and spring back. Based on the image processing, a digital method is proposed to extract various SSD parameters from the cross-section micrograph of the ground sample. To verify the model and method, many fused silica samples are ground under different processing parameters, and their SSD depth and roughness Rz are measured. The research results show the average SSD depth (SSDa) can be expressed as SSDa = χ1Rz4/3 + χ2Rz (χ1 and χ2 are coefficients). The SSDa is closer to half of the maximum SSD depth (SSDm) as the wheel speed decreases or the grinding depth, feed speed, or abrasive diameter increases. The SSD length or density basically increases linearly with the increase of the SSDm. The digital method is reliable with a largest relative error of 6.65% in SSD depth, extraction speed of about 1.63s per micrograph, and good robustness to the micrograph size and small-scale residue interference. The research will contribute to the evaluation of SSDs and the optimization of the grinding process of fused silica.

Microcrack localization using nonlinear Lamb waves and cross-shaped sensor clusters.

Using the nonlinear interaction effect between ultrasonic Lamb waves and microcracks to detect and locate microcracks has the advantages of fast detection speed and high sensitivity. In this paper, a method for microcrack localization based on cross-shaped sensor clusters in a plate is proposed by combining nonlinear ultrasonic Lamb wave technology and time difference of arrival (TDOA) technology. The antisymmetric (A0) mode at low frequency is chosen as the primary Lamb wave to simplify the complication of the dispersion and multi-mode properties of Lamb waves. The selected mode pair (A0-s0) weakens the influence of the cumulative growth effect of higher harmonics induced by the inherent material nonlinearity on the microcrack characteristic signals. Pulse inversion technique and cross correlation function are used to extract the TDOAs of the nonlinear characteristic signals including microcrack information. The cross-shaped sensor clusters approach proposed for the first time can achieve reliable and fast microcrack localization without being affected by the duration of the excitation signal, and a priori knowledge of group velocities of primary wave modes or generated harmonics. Experimental and numerical results validate the proposed method in isotropic and anisotropic plates. This paper provides a new idea for nonlinear ultrasonic nondestructive evaluation and structural health monitoring of microcracks in plates.

Experimental Research on Rapid Localization of Acoustic Source in a Cylindrical Shell Structure without Knowledge of the Velocity Profile.

Acoustic source localization in a large pressure vessel or a storage tank-type cylindrical structure is important in preventing structural failure. However, this can be challenging, especially for cylindrical pressure vessels and tanks that are made of anisotropic materials. The large area of the cylindrical structure often requires a substantial number of sensors to locate the acoustic source. This paper first applies conventional acoustic source localization techniques developed for the isotropic, flat plate-type structures to cylindrical structures. The experimental results show that the conventional acoustic source localization technique is not very accurate for source localization on cylindrical container surfaces. Then, the L-shaped sensor cluster technique is applied to the cylindrical surface of the pressure vessel, and the experimental results prove the applicability of using this technique. Finally, the arbitrary triangle-shaped sensor clusters are attached to the surface of the cylindrical structure to locate the acoustic source. The experimental results show that the two acoustic source localization techniques using sensor clusters can be used to monitor the location of acoustic sources on the surface of anisotropic cylindrical vessels, using a small number of sensors. The arbitrarily triangle-shaped sensors can be arbitrarily placed in a cluster on the surface of the cylindrical vessel. The results presented in this paper provide a theoretical and experimental basis for the surface acoustic source localization method for a cylindrical pressure vessel and lay a theoretical foundation for its application.

Shoulder Damage Model and Its Application for Single Point Diamond Machining of ZnSe Crystal.

The damaging of ZnSe crystal has a significant impact on its service performance and life. Based on the specific cutting energies for brittle and ductile mode machining, a model is proposed to evaluate the damage depth in the shoulder region of ZnSe crystal during single point diamond machining. The model considers the brittle-ductile transition and spring back of ZnSe crystal. To verify the model, the elastic modulus, hardness, spring back, and friction coefficient of ZnSe crystal are measured by nanoindentation and nanoscratch tests, and its critical undeformed chip thickness is obtained by spiral scratching. Meanwhile, orthogonal cutting experiments are conducted to obtain the different shoulder regions and cutting surfaces. The shoulder damage depth is analyzed, indicating that the effect of the feed on the damage depth at a high cutting depth is stronger than that at a low one. The model is verified to be effective with an average relative error of less than 7%. Then, the model is used to calculate the critical processing parameters and achieve a smooth ZnSe surface with a roughness Sa = 1.0 nm. The model is also extended to efficiently predict the bound of the subsurface damage depth of a cutting surface. The research would be useful for the evaluation of surface and subsurface damages during the ultra-precision machining of ZnSe crystal.

Acoustic source localization in heterogeneous media.

Acoustic source localization (ASL) or predicting the location of the acoustic source in a structure by analyzing the recorded signals at the receivers is of considerable interest for various applications. Recent research advances on this topic have been limited to homogeneous media. This paper presents a solution for acoustic source localization in a heterogeneous medium without knowing the properties of different materials constituting the heterogeneous structure. In this paper new developments for acoustic source localization in an anisotropic plate is first reviewed briefly. Then an ASL technique is presented for localizing acoustic source in heterogeneous layered structures when the layer properties are not known. The proposed technique is verified experimentally and numerically. The experimental results were generated with a specimen having one interface while numerical results were generated for both two-layered medium with one interface and three-layered medium with two interfaces.

Acoustic source localization in anisotropic plates with "Z" shaped sensor clusters.

A new sensor cluster orientation is proposed to localize an acoustic source in a plate from the time difference of arrival (TDOA) with the help of only four to eight sensors. This technique requires neither a priori knowledge of the plate material properties nor a dense array of sensors to localize the acoustic source in isotropic as well as anisotropic plates. It is achieved by placing four sensors in a cluster in the shape of letter "Z" over a small region of the plate and a second Z-shaped cluster at another location of the plate. Experimental results show that it is possible to accurately localize the acoustic source with this new configuration. It reduces the number of sensors required for acoustic source localization in an anisotropic plate. Although one cluster in principle is capable of localizing the acoustic source in absence of any experimental error for accurate source localization in presence of experimental error two such Z-shaped clusters are needed. In the currently available technique three L-shaped clusters having a total of 9 sensors are needed to achieve the same level of confidence in the acoustic source localization. Thus, the proposed new technique reduces the number of sensors by 1 (from 9 to 8) for confidently and accurately predicting the acoustic source.