Yeon-Pun Chang

Bio: Yeon-Pun Chang is an academic researcher from Chung Yuan Christian University. The author has contributed to research in topics: Bearing (mechanical) & Nonlinear system. The author has an hindex of 15, co-authored 53 publications receiving 980 citations.

Size effects of SiO2 nanoparticles as oil additives on tribology of lubricant

Abstract: Purpose – The purpose of this paper is to investigate the tribological properties of liquid paraffin with SiO2 nanoparticles additive made by a sol‐gel method.Design/methodology/approach – The tribological properties of the SiO2 nanoparticles as an additive in liquid paraffin are measured using a ball‐on‐ring wear tester to determine the optimal additive concentration. The mechanism that wear and friction are reduced is studied using scanning electron microscopy (SEM), energy dispersive spectrometry (EDS), and atomic force microscope (AFM).Findings – Experimental results indicate that the sizes of the synthesized SiO2 nanoparticles are distributed uniformly and that the optimal concentrations of SiO2 nanoparticles in liquid paraffin is associated with better tribological properties than pure paraffin oil, and an anti‐wear (AW) ability that depends on the particle size.Originality/value – It is shown in the paper that by reducing friction and AW, the lubricant prepared by the methods described can prolong ...

Applications of fault diagnosis in rotating machinery by using time series analysis with neural network

Abstract: The common diagnosis method of time series analysis is an autoregressive (AR) method, which is a kind of math model that can be established by time difference and vibration amplitude. As the AR model utilized the math method for fitting the variable, the AR coefficients represent the signal features and can be used to determine fault types. This study proposed the difference values of AR coefficients, which indicated that the AR coefficients of ideal signal for normal machine are deducted from faulty machines. It is convention that the relationship between the difference values of AR coefficients and fault types as trained by using back-propagation neural network (BPNN). The new fault diagnosis method by using the difference of AR coefficients with BPNN was proposed in this study. The diagnosis results were obtained and compared with the three methods, which include the difference of AR coefficients with BPNN, the AR coefficients with BPNN and the distance of AR coefficients method for 23 samples. And the diagnosis results obtained by using the difference of AR coefficients with BPNN were superior to AR coefficients with BPNN and distance of AR coefficients methods.

A review on nanofluids: preparation, stability mechanisms, and applications

Abstract: Nanofluids, the fluid suspensions of nanomaterials, have shown many interesting properties, and the distinctive features offer unprecedented potential for many applications. This paper summarizes the recent progress on the study of nanofluids, such as the preparation methods, the evaluation methods for the stability of nanofluids, and the ways to enhance the stability for nanofluids, the stability mechanisms of nanofluids, and presents the broad range of current and future applications in various fields including energy and mechanical and biomedical fields. At last, the paper identifies the opportunities for future research.

Mechanical properties of nanoparticles: basics and applications

Abstract: The special mechanical properties of nanoparticles allow for novel applications in many fields, e.g., surface engineering, tribology and nanomanufacturing/nanofabrication. In this review, the basic physics of the relevant interfacial forces to nanoparticles and the main measuring techniques are briefly introduced first. Then, the theories and important results of the mechanical properties between nanoparticles or the nanoparticles acting on a surface, e.g., hardness, elastic modulus, adhesion and friction, as well as movement laws are surveyed. Afterwards, several of the main applications of nanoparticles as a result of their special mechanical properties, including lubricant additives, nanoparticles in nanomanufacturing and nanoparticle reinforced composite coating, are introduced. A brief summary and the future outlook are also given in the final part. (Some figures may appear in colour only in the online journal)

Modification of Graphene Platelets and their Tribological Properties as a Lubricant Additive

Abstract: Graphene platelets were chemically modified in a reflux reaction with stearic and oleic acids. Examination of the surface features of the graphene platelets before and after modification by infrared spectroscopy and ultraviolet–visible spectrophotometer revealed that the modification led to an improvement in the dispersion of graphene platelets in base oil. The tribological behavior of the lubricating oil containing modified graphene platelets (MGP) was further investigated using a four-ball machine. The results indicated that the oil containing only 0.075 wt% of MGP clearly improved the wear resistance and load-carrying capacity of the machine. Scanning electron microscopy and energy dispersive spectrometer performed to analyze the wear scar surfaces after friction confirmed that the outstanding lubrication performance of MGP could be attributed to their small size and extremely thin laminated structure, which allow the MGP to easily enter the contact area, thereby preventing the rough surfaces from coming into direct contact.