The permanent magnet synchronous motor (PMSM) plays an important role in the power system of agricultural machinery. Inter-turn short circuit (ITSC) faults are among the most common failures in PMSMs, and early diagnosis of these faults is crucial for enhancing the safety and reliability of motor operation. In this article, a multi-source data-fusion algorithm based on convolutional neural networks (CNNs) has been proposed for the early fault diagnosis of ITSCs. The contributions of this paper can be summarized in three main aspects. Firstly, synchronizing data from different signals extracted by different devices presents a significant challenge. To address this, a signal synchronization method based on maximum cross-correlation is proposed to construct a synchronized dataset of current and vibration signals. Secondly, applying a traditional CNN to the data fusion of different signals is challenging. To solve this problem, a multi-stream high-level feature fusion algorithm based on a channel attention mechanism is proposed. Thirdly, to tackle the issue of hyperparameter tuning in deep learning models, a hyperparameter optimization method based on Bayesian optimization is proposed. Experiments are conducted based on the derived early-stage ITSC fault-severity indicator, validating the effectiveness of the proposed fault-diagnosis algorithm.

Comprehensive evaluation of Korla fragrant pears and optimization of plucking time during the harvest period

Non-destructive detection of the fruit firmness of Korla fragrant pear based on electrical properties

Construction method of quantitative evaluation model for the maturity of Korla fragrant pear

Apricot powder functionality after drying, grinding and sieving remains insufficiently understood. This study prepared powders from diluted Diaoganxing apricot pulp using hot-air drying (HAD), infrared drying (IRD), vacuum-pulsed drying (VPD) and vacuum freeze drying (VFD), followed by identical grinding and 60-mesh sieving. Moisture status, density, calculated porosity, particle characteristics, reconstitution, flowability, color, selected phytochemical indicators, ferric reducing antioxidant power (FRAP) and supplementary electronic-nose fingerprints were evaluated. The drying route markedly affected powder properties: moisture content and water activity ranged from 7.23 ± 0.38% to 9.85 ± 0.02% and 0.218 ± 0.002 to 0.370 ± 0.007, respectively. VFD gave the highest calculated porosity (59.09 ± 0.84%), shortest wettability time (46.05 ± 1.71 s), highest water-holding capacity (3.63 ± 0.07 g/g), smallest color difference (ΔE = 1.12 ± 0.47), and highest TPC, TCC, AAC and FRAP values. VPD showed the best handling indices, with the lowest angle of repose (28.44 ± 0.34°), Hausner ratio (1.07 ± 0.01) and Carr index (6.33 ± 0.66%). Correlation/PCA indicated treatment-level co-variation, not causality. Under the tested processing conditions, VFD may be preferable for rapid reconstitution and the measured quality indicators, whereas VPD may be more suitable for powder handling.