Analysis Of Laser Speckle Patterns Research Articles

Detection of intralayer alignment in multicomponent lipids by dynamic speckle pattern analysis.

Multicomponent mixtures of bilayer lipids, thanks to the coexistence of liquid-crystalline phases in their structures, may be used in the development of functional membranes. In such membranes interlayer ordering distributes across membrane lamellae, resulting in long-range alignment of phase-separated domains. In this paper, we explore the dynamics of this phenomenon by laser speckle pattern analysis. We show that cholesterol content decreases the activity, and the rate of the domains size development is related to the change of physical roughness of the multicomponent lipid mixture. Our results are in agreement with the previous experimental reports. However, our experimental procedure is an easy-to-implement and effective methodology.

On-Machine Surface Texture Measuring System Using Laser Speckle Pattern Analysis

Functional surfaces are expected technologies in various industries. However, the efficient generation of microscale surface structures is difficult because the process relies on precision surface texture assessments, which require long measuring times. An on-machine measuring system may solve this issue. In this study, a new on-machine surface texture measuring system based on laser speckle pattern analysis is proposed. The proposed system efficiently assesses various qualities of the surface texture, such as surface roughness, undulation of microscale surface structures, and anisotropy, from a laser speckle pattern obtained from the precision-machined surface. For precise measurements, disturbances caused by the machining system itself and the environment must be avoided. The laser speckle detection unit in the proposed system is supported by non-contact active vibration-isolation units, which reduce the transmission of ground vibrations. From the experimental results, the system indicated high repeatability in measurements and robustness against disturbances.

Multi-dimensional Assessment of Precision Machined Surface Texture Based on Laser Speckle Pattern Analysis

Surface texture of precision machined surfaces plays an important role in providing various functions to product surfaces. This paper presents a surface texture assessment method based on a laser speckle pattern analysis. Considered as simple light scattering phenomenon, laser speckle intensity can represent surface roughness. On the other hand, considered as diffraction phenomenon, the period of anisotropic pattern on a laser speckle is estimated to be inversely proportional to the period of micro structure. The proposed method evaluates multiple properties of surface texture from a laser speckle pattern, such as roughness, period, and degree of similarity in periodic micro surface structures. By investigating experimentally the relation between surface texture and laser speckle pattern of machined surfaces, several characteristic parameters of laser speckle, such as the mean intensity, the autocorrelation length of intensity distribution, and the degree of similarity between adjacent speckle patterns are proposed for evaluating surface texture properties. In addition, the anisotropy of micro surface structure is assessed by using the proposed parameters of laser speckle pattern.

Multi-dimensional assessment of nano/micro scale surface texture using laser speckle pattern analysis

Abstract Nano/micro scale surface structure on precision machined parts dominates the various product functions such as friction, wear resistance, corrosion, fatigue, and wetting. This paper presents a multi-dimensional surface texture assessment using laser speckle pattern analysis. From the observation result of laser speckle in precision machined surface, the probability density distribution of light intensity on laser speckle changes with the surface roughness. In addition, the autocorrelation function of speckle intensity distribution changes with the periodicity of micro surface structure. By analyzing the relation between surface texture and laser speckle pattern, characteristic parameters of laser speckle reflecting surface texture properties are identified; i.e. the mean light intensity, the deviation of the probability density distribution of light intensity, the autocorrelation length of intensity distribution, and the degree of dissimilarity between adjacent speckle patterns. The proposed parameters can evaluate the roughness, the period, and the degree of dissimilarity in periodic micro surface structure. Furthermore, the surface texture distribution and the anisotropy of micro surface structure can be assessed by detecting the variation of the proposed parameters. In consequence, the proposed method can quantitatively assess the nano/micro scale surface texture.

Resolving transitions in the mesoscale domain configuration in VO2 using laser speckle pattern analysis.

The configuration and evolution of coexisting mesoscopic domains with contrasting material properties are critical in creating novel functionality through emergent physical properties. However, current approaches that map the domain structure involve either spatially resolved but protracted scanning probe experiments without real time information on the domain evolution, or time resolved spectroscopic experiments lacking domain-scale spatial resolution. We demonstrate an elegant experimental technique that bridges these local and global methods, giving access to mesoscale information on domain formation and evolution at time scales orders of magnitude faster than current spatially resolved approaches. Our straightforward analysis of laser speckle patterns across the first order phase transition of VO2 can be generalized to other systems with large scale phase separation and has potential as a powerful method with both spatial and temporal resolution to study phase separation in complex materials.

Surface texture assessment of ultra-precision machined parts based on laser speckle pattern analysis

Abstract Surface texture plays an important role in overall product specification, because the surface quality of the product is dominated by the nano-scale surface texture. This paper presents a surface texture assessment method for evaluating roughness and periodicity of surface structure with a laser speckle pattern analysis. By investigating the relation between surface texture and laser speckle pattern, characteristic parameters for describing a laser speckle pattern are proposed. The proposed characteristic parameters can evaluate the surface texture in entire observed area and in limited area in any given direction. Furthermore, the surface texture can be qualitatively assessed with a radar chart of the proposed laser speckle characteristic parameters.

Precision Measurement Using Template Matching for Laser Speckle Patterns from Different Materials

The accuracy of precision measurement is an essential requirement for precision positioning. This paper presents a new precision measurement method by combining the uniqueness analysis of laser speckle patterns (LSPs) and the template matching algorithm. In this paper, an invariant speckle capturing device and template matching criteria are developed. Experimental results have shown that LSPs can demonstrate different unique and invariant properties even though they are captured from the same material but different samples. Also, accurate direction and displacement information of moving LSPs can be obtained in real-time. Therefore, this merit can provide the potential of speckle pattern analysis for applications of precision positioning in the future.