The Study of Zhuism under the Background of Ancient and Modern

In the period of the Republic of China gradually entered, After the baptism of the May Fourth Movement, The collision of Chinese and Western ideas, Western research concepts are deeply rooted in the people, Zhuism is no exception, This paper discusses the study of Zhuism science under different tendencies influenced by Western thought, including the scientific, philosophical and political perspectives, the problems that need to be discussed include the definition of science and the discussion of the relationship between Zhuism science and science; The philosophical aspect is the focus, Including the study of Zhu Zi’s study from the perspective of western new realism, metaphysics and dialectics; The study of political perspective is inevitable in the special era background of the Republic of China

Parallel experimental study of a novel super-thin thermal absorber based photovoltaic/thermal (PV/T) system against conventional photovoltaic (PV) system

Photovoltaic (PV) semiconductor degrades in performance due to temperature rise. A super thin-conductive thermal absorber is therefore developed to regulate the PV working temperature by retrofitting the existing PV panel into the photovoltaic/thermal (PV/T) panel. This article presented the parallel comparative investigation of the two different systems through both laboratory and field experiments. The laboratory evaluation consisted of one PV panel and one PV/T panel respectively while the overall field system involved 15 stand-alone PV panels and 15 retrofitted PV/T panels. The laboratory testing results demonstrated the PV/T panel could achieve the electrical efficiency of about 16.8% (relatively 5% improvement comparing with the stand-alone PV panel), and yield an extra amount of heat with thermal efficiency of nearly 65%. The field testing results indicated that the hybrid PV/T panel could enhance the electrical return of PV panels by nearly 3.5%, and increase the overall energy output by nearly 324.3%. Further opportunities and challenges were then discussed from aspects of different PV/T stakeholders to accelerate the development. It is expected that such technology could become a significant solution to yield more electricity, offset heating load freely and reduce carbon footprint in contemporary energy environment

A novel method for self-adaptive feature extraction using scaling crossover characteristics of signals and combining with LS-SVM for multi-fault diagnosis of gearbox

Vibration signals of defective gears are usually non-stationary and masked by noise. As a result, the feature extraction of gear fault data is always an intractable problem, especially for multi-fault couple system (two or more fault types simultaneously occur in mechanical systems). Recently, an interesting crossover characteristic of nonlinear data is used to diagnose the different severities of gear faults. Nonetheless, it lacks of self-adaptivity. Consequently, a novel method for self-adaptive feature extraction using scaling crossover characteristics of signals and combining with least square support vector machine (LS-SVM) for multi-fault diagnosis of gearbox is proposed. Firstly, detrended fluctuation analysis (DFA) is introduced to analyze fractal properties and multi-scaling behaviors of vibration signal from multi-fault gearbox. The scale exponents are abrupt changed with the gradual increasing of time scales, which can be observed in the scaling-law curve. Secondly, a criterion based on a Quasi-Monte Carlo algorithm is developed to uncover optimal scaling intervals of scaling-law curve. Several different scaling regions are objectively measured in each of which a single scale exponent can be estimated. Thirdly, a three-dimensional vector, containing three scale exponents which carry definite physical meaning, is used as the feature parameter to describe the underlying dynamic mechanism hidden in gearbox vibration data. Lastly, these vectors are classified by LS-SVM. Moreover, the method of statistical parameters is exploited to classify the multi-fault vibration data which have been investigated by proposed method. The results show that the proposed method is sensitive to multi-fault vibration data of gearbox with similar fault patterns and has a better performance than other methods