Determination of Surface Roughness in Wire and Arc Additive Manufacturing Based on Laser Vision Sensing

Wire and arc additive manufacturing(WAAM) shows a great promise for fabricating fully dense metal parts by means of melting materials in layers using a welding heat source. However, due to a large layer height produced in WAAM, an unsatisfactory surface roughness of parts processed by this technology has been a key issue. A methodology based on laser vision sensing is proposed to quantitatively calculate the surface roughness of parts deposited by WAAM.Calibrations for a camera and a laser plane of the optical system are presented. The reconstruction precision of the laser vision system is verified by a standard workpiece. Additionally, this determination approach is utilized to calculate the surface roughness of a multi-layer single-pass thin-walled part. The results indicate that the optical measurement approach based on the laser vision sensing is a simple and effective way to characterize the surface roughness of parts deposited by WAAM. The maximum absolute error is less than 0.15 mm. The proposed research provides the foundation for surface roughness optimization with different process parameters.

Surface roughness measurement and analysis of mechanical parts based on digital holography

We measure the surface roughness of the mechanical parts based on digital holography. A digital off- axis hologram recording setup for reflective samples is built. Firstly, the height reconstruction error 2.3% of the setup is calibrated by using the quartz step height standard （VLSI- SHS-880QC）. Then, the standard scribed-line model and the grinding roughness specimen are selected as the test samples and their surface roughness are 0.095 6 jam and 0.025 3 jam, with errors 6.3%, 0.9%, respectively. The results are in good agreement with the given roughness parameters. At last, we also analyze the window effect of the filter on the roughness measurement value based on digital holography. In conclu- sion, the paper demonstrated effectively that the digital holography could provide the surface feature for the rough- ness measurement with high accuracy.

Description of shape characteristics through Fourier and wavelet analysis

In this paper, Fourier and Wavelet transformation were adopted to analyze shape char- acteristics, with twelve simple shapes and two types of second phases from real microstructure mor- phology. According to the results of Fast Fourier transformation （FFT）, the Fourier descriptors can be used to characterize the shape from the aspects of the first eight Normalization amplitudes, the number of the largest amplitudes to inverse reconstruction, similarity of shapes and profile roughness. And the Diepenbroek Roughness was rewritten by Normalization amplitudes of FFT results. Moreover, Sum Square of Relative Errors （SSRE） of Wavelet transformation （WT） signal sequence, including approximation signals and detail signals, was introduced to evaluate the simi- larity and relative orientation among shapes. As a complement to FFT results, the WT results can retain more detailed information of shapes including their orientations. Besides, the geometric sig- natures of the second phases were extracted by image processing and then were analyzed by means of FFT and WT.

Approximation operators based on vague relations and roughness measures of vague sets

Rough set theory and vague set theory are powerful tools for managing uncertain, incomplete and imprecise information. This paper extends the rough vague set model based on equivalence relations and the rough fuzzy set model based on fuzzy relations to vague sets. We mainly focus on the lower and upper approxima- tion operators of vague sets based on vague relations, and investigate the basic properties of approximation opera- tors on vague sets. Specially, we give some essential characterizations of the lower and upper approximation operators generated by reflexive, symmetric, and transi- tive vague relations. Finally, we structure a parameterized roughness measure of vague sets and similarity measure methods between two rough vague sets, and obtain some properties of the roughness measure and similarity measures. We also give some valuable counterexamples and point out some false properties of the roughness measure in the paper of Wang et al.

RESISTANCE OF FLOW OVER ROUGH BED

In this paper, the flow resistance in a flume with rough bed was studied, and the criteria of 2-dimensional flow were obtained. The effects of bed roughness on Manning coefficient n and Chezy coefficient C were also discussed, and the experimental results indicate that n and C can be taken as constants for small-scale roughness case.