RESUMEN
In this study, the phytoremediation efficiency of Arabidopsis halleri L. in response to mechanical injury were compared between those irrigated with magnetized water and those irrigated with normal water. Under normal irrigation treatment, wounding stress increased malondialdehyde (MDA) concentrations and hydrogen peroxide (H2O2) levels in A. halleri leaves significantly, by 46.7-86.1% and 39.4-77.4%, respectively, relative to those in the intact tissues. In addition, wounding stresses decreased the content of Cd in leaves by 26.8-52.2%, relative to the control, indicating that oxidative damage in plant tissues was induced by mechanical injury, rather than Cd accumulation. There were no significant differences in MDA and H2O2 between A. halleri irrigated with magnetized water and with normal water under wounding conditions; however, the activities of catalase (CAT), ascorbate peroxidase (APX), and superoxide dismutase (SOD) in the leaves of plants treated with magnetized water were significantly increased by 25.1-56.7%, 47.3-183.6%, and 44.2-109.4%, respectively. Notably, under the magnetic field, the phytoremediation effect of 30% wounded A. halleri nearly returned to normal levels. We find that irrigation with magnetized water is an economical pathway to improve the tolerance of A. halleri to inevitable mechanical injury and may recover its phytoremediation effect.
RESUMEN
This study uses the machine vision method to develop an on-machine turning tool insert condition monitoring system for tool condition monitoring in the cutting processes of computer numerical control (CNC) machines. The system can identify four external turning tool insert conditions, namely fracture, built-up edge (BUE), chipping, and flank wear. This study also designs a visual inspection system for the tip of an insert using the surrounding light source and fill-light, which can be mounted on the turning machine tool, to overcome the environmental effect on the captured insert image for subsequent image processing. During image capture, the intensity of the light source changes to ensure that the test insert has appropriate surface and tip features. This study implements outer profile construction, insert status region capture, insert wear region judgment, and calculation to monitor and classify insert conditions. The insert image is then trimmed according to the vertical flank, horizontal blade, and vertical blade lines. The image of the insert-wear region is captured to monitor flank or chipping wear using grayscale value histogram. The amount of wear is calculated using the wear region image as the evaluation index to judge normal wear or over-wear conditions. On-machine insert condition monitoring is tested to confirm that the proposed system can judge insert fracture, BUE, chipping, and wear. The results demonstrate that the standard deviation of the chipping and amount of wear accounts for 0.67% and 0.62%, of the average value, respectively, thus confirming the stability of system operation.