For the randomness of crane working load leading to the decrease of load spectrum prediction accuracy with time,an adaptive TSSA-HKRVM model for crane load spectrum regression prediction is proposed.The heterogeneous ...For the randomness of crane working load leading to the decrease of load spectrum prediction accuracy with time,an adaptive TSSA-HKRVM model for crane load spectrum regression prediction is proposed.The heterogeneous kernel relevance vector machine model(HKRVM)with comprehensive expression ability is established using the complementary advantages of various kernel functions.The combination strategy consisting of refraction reverse learning,golden sine,and Cauchy mutation+logistic chaotic perturbation is introduced to form a multi-strategy improved sparrow algorithm(TSSA),thus optimizing the relevant parameters of HKRVM.The adaptive updatingmechanismof the heterogeneous kernel RVMmodel under themulti-strategy improved sparrow algorithm(TSSA-HKMRVM)is defined by the sliding window design theory.Based on the sample data of the measured load spectrum,the trained adaptive TSSA-HKRVMmodel is employed to complete the prediction of the crane equivalent load spectrum.Applying this method toQD20/10 t×43m×12mgeneral bridge crane,the results show that:compared with other prediction models,although the complexity of the adaptive TSSA-HKRVMmodel is relatively high,the prediction accuracy of the load spectrum under long periods has been effectively improved,and the completeness of the load information during thewhole life cycle is relatively higher,with better applicability.展开更多
Based on the basic theory of mechanics,kinematic and dynamic analysis for a slider-crank mechanism with a balance mechanism is performed.The theoretical formula of the load spectrum for the interaction between the cra...Based on the basic theory of mechanics,kinematic and dynamic analysis for a slider-crank mechanism with a balance mechanism is performed.The theoretical formula of the load spectrum for the interaction between the crank shaft and the bearing seat of the upper beam is achieved by approximately simplifying the mechanical model of the crank shaft.The simulation for the load spectrum data of combined frame under the operating conditions of blanking or piling is performed using Matlab and the law of the load spectrum curves under these two conditions is analyzed.The simulation results show that under a no-load condition,the load spectrum curves of the interaction between the crank shaft and the bearing seat of the upper beam present a form of periodic sine wave and under the piling condition,the load spectrum curves of the interaction between the crank shaft and the bearing seat of the upper beam present a form of periodic pulse wave.The simulation results can provide a theoretical foundation for the load determination during the process of analyzing the dynamic characteristics on the combined frame of a closed high-speed press through the finite element method.展开更多
The rain-flow counting method is widely used to compile the fatigue load spectrum, The second stage counting of the rain-flow method is a troublesome process. In order to overcome this drawback, the rain-flow and reve...The rain-flow counting method is widely used to compile the fatigue load spectrum, The second stage counting of the rain-flow method is a troublesome process. In order to overcome this drawback, the rain-flow and reverse rain-flow counting method is proposed in this paper. In this counting method, the rule for counting of the rain-flow method is modified, so that the sequence of load-time need not be adjusted. This is a valid and useful method to count cycles and compile the load spectrum and it can be widely used in ocean engineering.展开更多
A filtering method of aero-engine load spectrum based on the rain flow counting is proposed in this paper.Firstly,the original load spectrum is counted through the rain flow method to get the peak and valley values.Th...A filtering method of aero-engine load spectrum based on the rain flow counting is proposed in this paper.Firstly,the original load spectrum is counted through the rain flow method to get the peak and valley values.Then,some data points in the original load spectrum are added between the peak and valley values.Finally,the filtering spectrum is obtained.The proposed method can reflect the path information of the original load spectrum.In addition,it can also eliminate the noise in the signal and improve the efficiency of signal processing,which is of practical significance for the research of aero-engine.展开更多
The rainflow counting method is a reasonable cyclecounting procedure for fatigue life calculation and simulation testing of structures.It defines cycles as closed stress /strain hysteresis loops.Application of the rai...The rainflow counting method is a reasonable cyclecounting procedure for fatigue life calculation and simulation testing of structures.It defines cycles as closed stress /strain hysteresis loops.Application of the rainflow counting method requires a data processing of the loading spectrum,which consists of the elimination of non-peak value data points,load time histories adjustment and loop extraction.In the data processing of the loading spectrum,if a stress point is neither the peak nor the valley,it will be identified and eliminated from the loading spectrum.Generally,the loading process is idealized as a single peak-valley straight line.But in actually,there are polylines or nearly straight lines between peaks and valleys which can't be ignored.Therefore,in the process of eliminating such data points,it will produce error in method itself.To reduce the error produced by the traditional method itself,a new method which can well simplify the polylines in data processing of loading spectrum is proposed in this paper.Comparing with the original approximation method,the proposed method has higher precision.展开更多
Sediment load estimation is generally required for study and development of water resources system. In this regard, artificial neural network (ANN) is the most widely used modeling tool especially in data-constraint r...Sediment load estimation is generally required for study and development of water resources system. In this regard, artificial neural network (ANN) is the most widely used modeling tool especially in data-constraint regions. This research attempts to combine SSA (singular spectrum analysis) with ANN, hereafter called SSA-ANN model, with expectation to improve the accuracy of sediment load predicted by the existing ANN approach. Two different catchments located in the Lower Mekong Basin (LMB) were selected for the study and the model performance was measured by several statistical indices. In comparing with ANN, the proposed SSA-ANN model shows its better performance repeatedly in both catchments. In validation stage, SSA-ANN is superior for larger Nash-Sutcliffe Efficiency about 24% in Ban Nong Kiang catchment and 7% in Nam Mae Pun Luang catchment. Other statistical measures of SSA-ANN are better than those of ANN as well. This improvement reveals the importance of SSA which filters noise containing in the raw time series and transforms the original input data to be near normal distribution which is favorable to model simulation. This coupled model is also recommended for the prediction of other water resources variables because extra input data are not required. Only additional computation, time series decomposition, is needed. The proposed technique could be potentially used to minimize the costly operation of sediment measurement in the LMB which is relatively rich in hydrometeorological records.展开更多
A new, more actual approach for omitting small loads in a loading history was pres-ented according to crack closure, and load interactive effects which are large on damage of com-ponents were studied. Intrinsic period...A new, more actual approach for omitting small loads in a loading history was pres-ented according to crack closure, and load interactive effects which are large on damage of com-ponents were studied. Intrinsic periodic spectrum block representing a damage element of a loadhistory, a new concept, was put out. It has been proven by theoretic analysis and tests that themodes of constructing fatigue loading spectrum have little effect on damage of components,which will change the incomplete knowledges on constructing fatigue spectrum ago.展开更多
基金sponsored by the National Natural Science Foundation of China(52105269).
文摘For the randomness of crane working load leading to the decrease of load spectrum prediction accuracy with time,an adaptive TSSA-HKRVM model for crane load spectrum regression prediction is proposed.The heterogeneous kernel relevance vector machine model(HKRVM)with comprehensive expression ability is established using the complementary advantages of various kernel functions.The combination strategy consisting of refraction reverse learning,golden sine,and Cauchy mutation+logistic chaotic perturbation is introduced to form a multi-strategy improved sparrow algorithm(TSSA),thus optimizing the relevant parameters of HKRVM.The adaptive updatingmechanismof the heterogeneous kernel RVMmodel under themulti-strategy improved sparrow algorithm(TSSA-HKMRVM)is defined by the sliding window design theory.Based on the sample data of the measured load spectrum,the trained adaptive TSSA-HKRVMmodel is employed to complete the prediction of the crane equivalent load spectrum.Applying this method toQD20/10 t×43m×12mgeneral bridge crane,the results show that:compared with other prediction models,although the complexity of the adaptive TSSA-HKRVMmodel is relatively high,the prediction accuracy of the load spectrum under long periods has been effectively improved,and the completeness of the load information during thewhole life cycle is relatively higher,with better applicability.
基金The Key Technologies R& D Program of Jiangsu Province(No. BE2006036)Transformation Program of Science and Technology Achievements of Jiangsu Province (No. BA2008030)
文摘Based on the basic theory of mechanics,kinematic and dynamic analysis for a slider-crank mechanism with a balance mechanism is performed.The theoretical formula of the load spectrum for the interaction between the crank shaft and the bearing seat of the upper beam is achieved by approximately simplifying the mechanical model of the crank shaft.The simulation for the load spectrum data of combined frame under the operating conditions of blanking or piling is performed using Matlab and the law of the load spectrum curves under these two conditions is analyzed.The simulation results show that under a no-load condition,the load spectrum curves of the interaction between the crank shaft and the bearing seat of the upper beam present a form of periodic sine wave and under the piling condition,the load spectrum curves of the interaction between the crank shaft and the bearing seat of the upper beam present a form of periodic pulse wave.The simulation results can provide a theoretical foundation for the load determination during the process of analyzing the dynamic characteristics on the combined frame of a closed high-speed press through the finite element method.
基金The project was financially supported by the National Natural Science Foundation of China (Grant No. 50078010)
文摘The rain-flow counting method is widely used to compile the fatigue load spectrum, The second stage counting of the rain-flow method is a troublesome process. In order to overcome this drawback, the rain-flow and reverse rain-flow counting method is proposed in this paper. In this counting method, the rule for counting of the rain-flow method is modified, so that the sequence of load-time need not be adjusted. This is a valid and useful method to count cycles and compile the load spectrum and it can be widely used in ocean engineering.
基金This work was supported by the National Basic Research Program of China,National Nature Science Foundation of China(No.51675266)the Foundation Research Funds for the Center in NUAA(Nos.NJ20160038,NS2017011)Foundation of Graduate Innovation Center in NUAA(No.kfjj20170220)。
文摘A filtering method of aero-engine load spectrum based on the rain flow counting is proposed in this paper.Firstly,the original load spectrum is counted through the rain flow method to get the peak and valley values.Then,some data points in the original load spectrum are added between the peak and valley values.Finally,the filtering spectrum is obtained.The proposed method can reflect the path information of the original load spectrum.In addition,it can also eliminate the noise in the signal and improve the efficiency of signal processing,which is of practical significance for the research of aero-engine.
基金National Natural Science Foundation of China(No.11272082)
文摘The rainflow counting method is a reasonable cyclecounting procedure for fatigue life calculation and simulation testing of structures.It defines cycles as closed stress /strain hysteresis loops.Application of the rainflow counting method requires a data processing of the loading spectrum,which consists of the elimination of non-peak value data points,load time histories adjustment and loop extraction.In the data processing of the loading spectrum,if a stress point is neither the peak nor the valley,it will be identified and eliminated from the loading spectrum.Generally,the loading process is idealized as a single peak-valley straight line.But in actually,there are polylines or nearly straight lines between peaks and valleys which can't be ignored.Therefore,in the process of eliminating such data points,it will produce error in method itself.To reduce the error produced by the traditional method itself,a new method which can well simplify the polylines in data processing of loading spectrum is proposed in this paper.Comparing with the original approximation method,the proposed method has higher precision.
文摘Sediment load estimation is generally required for study and development of water resources system. In this regard, artificial neural network (ANN) is the most widely used modeling tool especially in data-constraint regions. This research attempts to combine SSA (singular spectrum analysis) with ANN, hereafter called SSA-ANN model, with expectation to improve the accuracy of sediment load predicted by the existing ANN approach. Two different catchments located in the Lower Mekong Basin (LMB) were selected for the study and the model performance was measured by several statistical indices. In comparing with ANN, the proposed SSA-ANN model shows its better performance repeatedly in both catchments. In validation stage, SSA-ANN is superior for larger Nash-Sutcliffe Efficiency about 24% in Ban Nong Kiang catchment and 7% in Nam Mae Pun Luang catchment. Other statistical measures of SSA-ANN are better than those of ANN as well. This improvement reveals the importance of SSA which filters noise containing in the raw time series and transforms the original input data to be near normal distribution which is favorable to model simulation. This coupled model is also recommended for the prediction of other water resources variables because extra input data are not required. Only additional computation, time series decomposition, is needed. The proposed technique could be potentially used to minimize the costly operation of sediment measurement in the LMB which is relatively rich in hydrometeorological records.
文摘A new, more actual approach for omitting small loads in a loading history was pres-ented according to crack closure, and load interactive effects which are large on damage of com-ponents were studied. Intrinsic periodic spectrum block representing a damage element of a loadhistory, a new concept, was put out. It has been proven by theoretic analysis and tests that themodes of constructing fatigue loading spectrum have little effect on damage of components,which will change the incomplete knowledges on constructing fatigue spectrum ago.