The water-lubricated thrust bearings of the marine rim-driven thruster(RDT)are usually composed of polymer composites,which are prone to serious wear under harsh working conditions.Ultrasonic is an excellent non-destr...The water-lubricated thrust bearings of the marine rim-driven thruster(RDT)are usually composed of polymer composites,which are prone to serious wear under harsh working conditions.Ultrasonic is an excellent non-destructive monitoring technology,but polymer materials are characterized by viscoelasticity,heterogeneity,and large acoustic attenuation,making it challenging to extract ultrasonic echo signals.Therefore,this paper proposes a wear monitoring method based on the amplitude spectrum of the ultrasonic reflection coefficient.The effects of bearing parameters,objective function,and algorithm parameters on the identification results are simulated and analyzed.Taking the correlation coefficient and root mean square error as the matching parameters,the thickness,sound velocity,density,and attenuation factor of the bearing are inversed simultaneously by utilizing the differential evolution algorithm(DEA),and the wear measurement system is constructed.In order to verify the identification accuracy of this method,an accelerated wear test under heavy load was executed on a multi-functional vertical water lubrication test rig with poly-ether-etherketone(PEEK)fixed pad and stainless-steel thrust collar as the object.The thickness of pad was measured using the high-precision spiral micrometer and ultrasonic testing system,respectively.Ultimately,the results demonstrate that the thickness identification error of this method is approximately 1%,and in-situ monitoring ability will be realized in the future,which is of great significance to the life prediction of bearings.展开更多
Cotton defoliation and post-harvest destruction are important cultural practices for cotton production.Cotton root rot is a serious and destructive disease that affects cotton yield and lint quality.This paper present...Cotton defoliation and post-harvest destruction are important cultural practices for cotton production.Cotton root rot is a serious and destructive disease that affects cotton yield and lint quality.This paper presents an overview and summary of the methodologies and results on the use of remote sensing technology for evaluating cotton defoliation and regrowth control methods and for assessing cotton root rot infection based on published studies.Ground reflectance spectra and airborne multispectral and hyperspectral imagery were used in these studies.Ground reflectance spectra effectively separated different levels of defoliation and airborne multispectral imagery permitted both visual and quantitative differentiations among defoliation treatments.Both ground reflectance and airborne imagery were able to differentiate cotton regrowth among different herbicide treatments for cotton stalk destruction.Airborne multispectral and hyperspectral imagery accurately identified root rot-infected areas within cotton fields.Results from these studies indicate that remote sensing can be a useful tool for evaluating the effectiveness of cotton defoliation and regrowth control strategies and for detecting and mapping root rot damage in cotton fields.Compared with traditional visual observations and ground measurements,remote sensing techniques have the potential for effective and accurate assessments of various cotton production operations and pest conditions.展开更多
基金supported by the National Key R&D Program of China(No.2018YFE0197600)European Union’s Horizon 2020 Research and Innovation Programme RISE under Grant Agreement No.823759(REMESH)the National Natural Science Foundation of China(No.52071244).
文摘The water-lubricated thrust bearings of the marine rim-driven thruster(RDT)are usually composed of polymer composites,which are prone to serious wear under harsh working conditions.Ultrasonic is an excellent non-destructive monitoring technology,but polymer materials are characterized by viscoelasticity,heterogeneity,and large acoustic attenuation,making it challenging to extract ultrasonic echo signals.Therefore,this paper proposes a wear monitoring method based on the amplitude spectrum of the ultrasonic reflection coefficient.The effects of bearing parameters,objective function,and algorithm parameters on the identification results are simulated and analyzed.Taking the correlation coefficient and root mean square error as the matching parameters,the thickness,sound velocity,density,and attenuation factor of the bearing are inversed simultaneously by utilizing the differential evolution algorithm(DEA),and the wear measurement system is constructed.In order to verify the identification accuracy of this method,an accelerated wear test under heavy load was executed on a multi-functional vertical water lubrication test rig with poly-ether-etherketone(PEEK)fixed pad and stainless-steel thrust collar as the object.The thickness of pad was measured using the high-precision spiral micrometer and ultrasonic testing system,respectively.Ultimately,the results demonstrate that the thickness identification error of this method is approximately 1%,and in-situ monitoring ability will be realized in the future,which is of great significance to the life prediction of bearings.
文摘Cotton defoliation and post-harvest destruction are important cultural practices for cotton production.Cotton root rot is a serious and destructive disease that affects cotton yield and lint quality.This paper presents an overview and summary of the methodologies and results on the use of remote sensing technology for evaluating cotton defoliation and regrowth control methods and for assessing cotton root rot infection based on published studies.Ground reflectance spectra and airborne multispectral and hyperspectral imagery were used in these studies.Ground reflectance spectra effectively separated different levels of defoliation and airborne multispectral imagery permitted both visual and quantitative differentiations among defoliation treatments.Both ground reflectance and airborne imagery were able to differentiate cotton regrowth among different herbicide treatments for cotton stalk destruction.Airborne multispectral and hyperspectral imagery accurately identified root rot-infected areas within cotton fields.Results from these studies indicate that remote sensing can be a useful tool for evaluating the effectiveness of cotton defoliation and regrowth control strategies and for detecting and mapping root rot damage in cotton fields.Compared with traditional visual observations and ground measurements,remote sensing techniques have the potential for effective and accurate assessments of various cotton production operations and pest conditions.
