Plate Wall Offset Measurement for U-Shaped Groove Workpieces Based on Multi-Line-Structured Light Vision Sensors.

To address the challenge of measuring the plate wall offset at the U-shaped groove positions after assembling large cylindrical shell arc segments, this paper proposes a measurement method based on multi-line-structured light vision sensors. The sensor is designed and calibrated to collect U-shaped groove workpiece images containing multiple laser stripes. The central points of the laser stripes are extracted and matched to their corresponding light plane equations to obtain local point cloud data of the measured positions.

Quantitative predictions of protein and total flavonoids content in Tartary and common buckwheat using near-infrared spectroscopy and chemometrics.

A rapid method was developed for determining the total flavonoid and protein content in Tartary buckwheat by employing near-infrared spectroscopy (NIRS) and various machine learning algorithms, including partial least squares regression (PLSR), support vector regression (SVR), and backpropagation neural network (BPNN). The RAW-SPA-CV-SVR model exhibited superior predictive accuracy for both Tartary and common buckwheat, with a high coefficient of determination (Rp = 0.9811) and a root mean squared error of prediction (RMSEP = 0.