Surface defects,including dents,spalls,and cracks,for rolling element bearings are the most common faults in rotating machinery.The accurate model for the time-varying excitation is the basis for the vibration mechani...Surface defects,including dents,spalls,and cracks,for rolling element bearings are the most common faults in rotating machinery.The accurate model for the time-varying excitation is the basis for the vibration mechanism analysis and fault feature extraction.However,in conventional investigations,this issue is not well and fully addressed from the perspective of theoretical analysis and physical derivation.In this study,an improved analytical model for time-varying displacement excitations(TVDEs)caused by surface defects is theoretically formulated.First and foremost,the physical mechanism for the effect of defect sizes on the physical process of rolling element-defect interaction is revealed.According to the physical interaction mechanism between the rolling element and different types of defects,the relationship between time-varying displacement pulse and defect sizes is further analytically derived.With the obtained time-varying displacement pulse,the dynamic model for the deep groove bearings considering the internal excitation caused by the surface defect is established.The nonlinear vibration responses and fault features induced by surface defects are analyzed using the proposed TVDE model.The results suggest that the presence of surface defects may result in the occurrence of the dual-impulse phenomenon,which can serve as indexes for surface-defect fault diagnosis.展开更多
Feature extraction is essential to the classification of surface defect images. The defects of hot-rolled steels distribute in different directions. Therefore, the methods of multi-scale geometric analysis （MGA） wer...Feature extraction is essential to the classification of surface defect images. The defects of hot-rolled steels distribute in different directions. Therefore, the methods of multi-scale geometric analysis （MGA） were employed to decompose the image into several directional subba^ds at several scales. Then, the statistical features of each subband were calculated to produce a high-dimensional feature vector, which was reduced to a lower-dimensional vector by graph embedding algorithms. Finally, support vector machine （SVM） was used for defect classification. The multi-scale feature extraction method was implemented via curvelet transform and kernel locality preserving projections （KLPP）. Experiment results show that the proposed method is effective for classifying the surface defects of hot-rolled steels and the total classification rate is up to 97.33%.展开更多
Considering that the surface defects of cold rolled strips are hard to be recognized by human eyes under high-speed circumstances, an automatic recognition technique was discussed. Spectrum images of defects can be go...Considering that the surface defects of cold rolled strips are hard to be recognized by human eyes under high-speed circumstances, an automatic recognition technique was discussed. Spectrum images of defects can be got by fast Fourier transform （FFF） and sum of valid pixels （SVP）, and its optimized center region, which concentrates nearly all energies, are extracted as an original feature set. Using genetic algorithm to optimize the feature set, an optimized feature set with 51 features can be achieved. Using the optimized feature set as an input vector of neural networks, the recognition effects of LVQ neural networks have been studied. Experiment results show that the new method can get a higher classification rate and can settle the automatic recognition problem of surface defects on cold rolled strips ideally.展开更多
A new surface strengthening technology, luster polish strengthening treatment, was proposed to treat the raceway surface of aeroengine bearings （9Cr18Mo） with the centrifugal strengthening machine exclusively design...A new surface strengthening technology, luster polish strengthening treatment, was proposed to treat the raceway surface of aeroengine bearings （9Cr18Mo） with the centrifugal strengthening machine exclusively designed for luster polish strengthening treatment. The experimental results showed that luster polish strengthening treatment produced a compressive residual stress layer with a depth of over 80 μm below the surface of the bearing raceway, and thus effectively removed the metamorphic layer in the raceway surface. After luster polish strengthening treatment, the average surface hardness of the aeroengine bearing raceway was increased from 61.02 HRC to 63.01 HRC, the surface roughness was reduced from 0.06 μm to 0.03 μm, and the contact fatigue life of the aeroengine bearings was improved by about 90%, with the dispersion of fatigue life being reduced remarkably. Theoretical calculation result agrees with that obtained by experiment.展开更多
Considering the influence caused by a early single pit defect on the outer raceway of the work roll bearing,a 2-DOF plate strip rolling mill vertical vibration model with a single point weak fault on the outer raceway...Considering the influence caused by a early single pit defect on the outer raceway of the work roll bearing,a 2-DOF plate strip rolling mill vertical vibration model with a single point weak fault on the outer raceway was established.With the practical parameters of the roughing mill of the 1780 hot continuous rolling mill,the vertical vibration characteristics of the rolling mill work roll with different rotating speed and different single pit defect area on the bearing outer raceway are analyzed by numerical simulation.It is found that with the change of the rotation speed of the work roll,different nonlinear vibration behaviors occurred,such as superharmonic resonance,main resonance,com-bined resonance and sub-harmonic resonance.Especially the subharmonic resonance of the work roll is more harmful than the main resonance when the work roll speed is twice the rotation speed corresponding to the first and second natural frequency of the rolling mill.This work provides a theoretical basis for further clarifying the effect caused by a early defect of the work roll bearing on the mill vibration.展开更多
The detection and classification of real-time surface defects play an important role in automotive sheet inspection and production. In this paper, an automatic surface inspection system （ASIS） based on signal proces...The detection and classification of real-time surface defects play an important role in automotive sheet inspection and production. In this paper, an automatic surface inspection system （ASIS） based on signal processing in Baosteel NO. 4 cold-rolled plant is briefly presented. We demonstrate that the strip surface defect properties such as image, type, pitch, and position can be accurately calculated and classified by the automatic surface inspection system. In the manufacturing of the high-quality cold-rolled strips, it is necessary that the real-time surface defects can be detected and transferred by the automatic surface inspection system combined with annealing lines and recoiling lines.展开更多
The continuous descaling and cold rolling mill（ CDCM） is renow ned for its high capacity and high speed,which makes it very difficult to manually check the surface quality of steel strips. A surface-defect online de...The continuous descaling and cold rolling mill（ CDCM） is renow ned for its high capacity and high speed,which makes it very difficult to manually check the surface quality of steel strips. A surface-defect online detector and its components,which are employed in a CDCM at Baosteel,are introduced,including the electrical,imaging,processing and softw are systems. To evaluate the effectiveness of the application of this detector,and to reduce the number of false alarms,the optimal number of defect samples is determined,pre- and post-processing rules are established,and talking-voice and color-changing alarms are employed.展开更多
A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products,largely used in many industrial sectors.However,computers used in the production...A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products,largely used in many industrial sectors.However,computers used in the production line of small to medium size companies,in general,lack performance to attend real-time inspection with high processing demands.In this paper,a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed.The architecture is based on the state-of-the-art SqueezeNet approach,which was originally developed for usage with autonomous vehicles.The main features of the proposed model are:small size and low computational burden.The model is 10 to 20 times smaller when compared to other networks designed for the same task,and more than 700 times smaller than general networks.Also,the number of floating-point operations for a prediction is about 50 times lower than the ones used for similar tasks.Despite its small size,the proposed model achieved near-perfect accuracy on a public dataset of 1800 images of six types of steel rolling defects.展开更多
Researches on the processing method of ceramic bearing ball,the formation and propagation of defects in the manufacturing and the nondestructive evaluation(NDE) are summarized in this paper.The key for successful proc...Researches on the processing method of ceramic bearing ball,the formation and propagation of defects in the manufacturing and the nondestructive evaluation(NDE) are summarized in this paper.The key for successful processing of high strength ceramic balls is to avoid producing related defects.Many investigations show that the material microstructures,defects as well as mechanical processing parameters influence the final surface quality significantly.Most of NDE technologies,such as radiation,ultrasonic,dye-penetration and laser scatter,have been studied for ceramic bearing ball surface inspection around the world.So far,the difficulties to develop the perfect NDE system for ceramic bearing balls,which are caused by the defect variety and surface unfolding,have not been overcome yet.展开更多
基金This work is sponsored by the National Natural Science Foundation of China(Nos.52105117&52105118).
文摘Surface defects,including dents,spalls,and cracks,for rolling element bearings are the most common faults in rotating machinery.The accurate model for the time-varying excitation is the basis for the vibration mechanism analysis and fault feature extraction.However,in conventional investigations,this issue is not well and fully addressed from the perspective of theoretical analysis and physical derivation.In this study,an improved analytical model for time-varying displacement excitations(TVDEs)caused by surface defects is theoretically formulated.First and foremost,the physical mechanism for the effect of defect sizes on the physical process of rolling element-defect interaction is revealed.According to the physical interaction mechanism between the rolling element and different types of defects,the relationship between time-varying displacement pulse and defect sizes is further analytically derived.With the obtained time-varying displacement pulse,the dynamic model for the deep groove bearings considering the internal excitation caused by the surface defect is established.The nonlinear vibration responses and fault features induced by surface defects are analyzed using the proposed TVDE model.The results suggest that the presence of surface defects may result in the occurrence of the dual-impulse phenomenon,which can serve as indexes for surface-defect fault diagnosis.
基金supports by the Program for New Century Excellent Talents in Chinese Universities (No.NCET-08-0726)Beijing Nova Program (No. 2007B027)the Fundamental Research Funds for the Central Universities (No. FRF-TP-09-027B)
文摘Feature extraction is essential to the classification of surface defect images. The defects of hot-rolled steels distribute in different directions. Therefore, the methods of multi-scale geometric analysis （MGA） were employed to decompose the image into several directional subba^ds at several scales. Then, the statistical features of each subband were calculated to produce a high-dimensional feature vector, which was reduced to a lower-dimensional vector by graph embedding algorithms. Finally, support vector machine （SVM） was used for defect classification. The multi-scale feature extraction method was implemented via curvelet transform and kernel locality preserving projections （KLPP）. Experiment results show that the proposed method is effective for classifying the surface defects of hot-rolled steels and the total classification rate is up to 97.33%.
基金This work was financially supported by the National High Technology Research and Development Program of China (No.2003AA331080 and 2001AA339030)the Talent Science Research Foundation of Henan University of Science & Technology (No.09001121).
文摘Considering that the surface defects of cold rolled strips are hard to be recognized by human eyes under high-speed circumstances, an automatic recognition technique was discussed. Spectrum images of defects can be got by fast Fourier transform （FFF） and sum of valid pixels （SVP）, and its optimized center region, which concentrates nearly all energies, are extracted as an original feature set. Using genetic algorithm to optimize the feature set, an optimized feature set with 51 features can be achieved. Using the optimized feature set as an input vector of neural networks, the recognition effects of LVQ neural networks have been studied. Experiment results show that the new method can get a higher classification rate and can settle the automatic recognition problem of surface defects on cold rolled strips ideally.
基金The National Key Project of China duringthe 10th Five-Year Plan Period (NoMKPT-01-004(ZD))
文摘A new surface strengthening technology, luster polish strengthening treatment, was proposed to treat the raceway surface of aeroengine bearings （9Cr18Mo） with the centrifugal strengthening machine exclusively designed for luster polish strengthening treatment. The experimental results showed that luster polish strengthening treatment produced a compressive residual stress layer with a depth of over 80 μm below the surface of the bearing raceway, and thus effectively removed the metamorphic layer in the raceway surface. After luster polish strengthening treatment, the average surface hardness of the aeroengine bearing raceway was increased from 61.02 HRC to 63.01 HRC, the surface roughness was reduced from 0.06 μm to 0.03 μm, and the contact fatigue life of the aeroengine bearings was improved by about 90%, with the dispersion of fatigue life being reduced remarkably. Theoretical calculation result agrees with that obtained by experiment.
基金This research is supported by Natural Science Foundation of China(Grant no.51405068)Natural Science Foundation of Hebei Province of China(Grant no.E2019203146)Natural Science Foundation of Hebei Province of China(Grant no.E2014501006).
文摘Considering the influence caused by a early single pit defect on the outer raceway of the work roll bearing,a 2-DOF plate strip rolling mill vertical vibration model with a single point weak fault on the outer raceway was established.With the practical parameters of the roughing mill of the 1780 hot continuous rolling mill,the vertical vibration characteristics of the rolling mill work roll with different rotating speed and different single pit defect area on the bearing outer raceway are analyzed by numerical simulation.It is found that with the change of the rotation speed of the work roll,different nonlinear vibration behaviors occurred,such as superharmonic resonance,main resonance,com-bined resonance and sub-harmonic resonance.Especially the subharmonic resonance of the work roll is more harmful than the main resonance when the work roll speed is twice the rotation speed corresponding to the first and second natural frequency of the rolling mill.This work provides a theoretical basis for further clarifying the effect caused by a early defect of the work roll bearing on the mill vibration.
文摘The detection and classification of real-time surface defects play an important role in automotive sheet inspection and production. In this paper, an automatic surface inspection system （ASIS） based on signal processing in Baosteel NO. 4 cold-rolled plant is briefly presented. We demonstrate that the strip surface defect properties such as image, type, pitch, and position can be accurately calculated and classified by the automatic surface inspection system. In the manufacturing of the high-quality cold-rolled strips, it is necessary that the real-time surface defects can be detected and transferred by the automatic surface inspection system combined with annealing lines and recoiling lines.
文摘The continuous descaling and cold rolling mill（ CDCM） is renow ned for its high capacity and high speed,which makes it very difficult to manually check the surface quality of steel strips. A surface-defect online detector and its components,which are employed in a CDCM at Baosteel,are introduced,including the electrical,imaging,processing and softw are systems. To evaluate the effectiveness of the application of this detector,and to reduce the number of false alarms,the optimal number of defect samples is determined,pre- and post-processing rules are established,and talking-voice and color-changing alarms are employed.
文摘A proper detection and classification of defects in steel sheets in real time have become a requirement for manufacturing these products,largely used in many industrial sectors.However,computers used in the production line of small to medium size companies,in general,lack performance to attend real-time inspection with high processing demands.In this paper,a smart deep convolutional neural network for using in real-time surface inspection of steel rolling sheets is proposed.The architecture is based on the state-of-the-art SqueezeNet approach,which was originally developed for usage with autonomous vehicles.The main features of the proposed model are:small size and low computational burden.The model is 10 to 20 times smaller when compared to other networks designed for the same task,and more than 700 times smaller than general networks.Also,the number of floating-point operations for a prediction is about 50 times lower than the ones used for similar tasks.Despite its small size,the proposed model achieved near-perfect accuracy on a public dataset of 1800 images of six types of steel rolling defects.
基金the National Nature Science Foundation of China (50275031)
文摘Researches on the processing method of ceramic bearing ball,the formation and propagation of defects in the manufacturing and the nondestructive evaluation(NDE) are summarized in this paper.The key for successful processing of high strength ceramic balls is to avoid producing related defects.Many investigations show that the material microstructures,defects as well as mechanical processing parameters influence the final surface quality significantly.Most of NDE technologies,such as radiation,ultrasonic,dye-penetration and laser scatter,have been studied for ceramic bearing ball surface inspection around the world.So far,the difficulties to develop the perfect NDE system for ceramic bearing balls,which are caused by the defect variety and surface unfolding,have not been overcome yet.
