With the explosion of the Web, focused web crawlers are gaining attention. Focused web crawlers aim at finding web pages related to the pre-defined topic. CINDI Robot is a focused web crawler devoted to finding computer science and software engineering academic documents. We propose a multi-level inspection scheme to discover relevant web pages. Through this multi-level inspection scheme, the text feature of the content contributes to the classification; furthermore other web characteristics, such as URL pattern, anchor text and so on, assist the decision process. The experiment result demonstrates this multilevel inspection method outperforms other traditional methods.
In this study, the classification threshold of stator slot wedge tightness is established, and a non-destructive testing technology of stator slot wedge tightness based on acoustics is proposed. Firstly, the classification threshold of slot wedge tightness is determined. Then through the compression test of corrugated plate, the corresponding corrugated plate shape variable is obtained. The mechanical classification threshold is transformed into the deformation threshold of corrugated plate. Secondly, the tightness test platform of stator slot wedge is established and the tightness test is carried out. Then, the percussion signals is preprocessed by endpoint detection method, which greatly reduces the subsequent calculation. Subsequently, the characteristic parameters of the percussion signals are extracted by time-domain and frequency-domain analysis, and the characteristic parameters are screened by F-ratio method and Pearson correlation coefficient method. Finally, the Support Vector Machine(SVM) optimized by cross validation method is used to classify the test sets to realize pattern recognition. The results show that the tightness of stator slot wedge can be accurately detected by using this research. This research realizes the intelligent identification of the tightness of the stator slot wedge of the generator set, and provides an important reference for the tightness detection of the stator slot wedge.
High-speed cutting (HSC) is frequently adopted to manufacture parts in many industries, including aerospace and automotive. To manufacture high-quality parts, adiabatic shear banding (ASB), often observed on serrated chips of various metallic materials during the HSC process, should be suppressed and studied. ASB is formed due to work hardening of metallic materials and work softening induced by adiabatic heating. The onset of ASB during the orthogonal cutting of Ti6Al4V is modeled based on the continuum mechanics, taking both work hardening and work softening into considerations. The model is validated by finite element method (FEM) and experiments. Moreover, the ASB onset process is simulated in FEM to reveal the ASB formation mechanism. The effect of the mechanical properties of Ti6Al4V on the onset of ASB is investigated based on the Johnson-Cook model. The investigation reveals the main factors that affect the onset of ASB during the HSC process. Future work includes characterizing the mechanical behavior of Ti6Al4V after the onset of ASB during a cutting process by coupling the continuum mechanics and micromechanics.
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