Li H.,China Aerospace Polytechnology Establishment
Guangxue Xuebao/Acta Optica Sinica | Year: 2011
Carbon fiber reinforced polymer (CFRP) is widely used for making leaf joint and cartridge receiver with the development of material science and structural mechanics. The main kind of flaw is delamination, but this type of flaw can not be tested easily by using tradition method. In order to promoting the product quality, pulse theography is developing and becoming perfect. But the test sensitivity of pulse theography can not be definited exactly, in order to solve this problem, pulse thergraphy method is used for testing artifical parts with different delamination flaws. Pulse theography method can find and locate the delamination flaw in CFRP, can measure the size and depth of the flaw. When the percentage of wide and depth is lower than 3, the test sensitivity is lower than 10%, and the sensitivity is becoming low as the size become small and the depth become deep.
Li H.,China Aerospace Polytechnology Establishment
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2015
Composite material connected by glue has gained popularity as a replacement for conventional materials and structures to reduce weight and improve strength in the aerospace industry, with the development of material science and structural mechanics. However, the adhesive bonding process is more susceptible to quality variations during manufacturing than traditional joining methods. The integrality, strength and rigidity of product would be broken by disbonding. Infrared thermography is one of several non-destructive testing techniques which can be used for defect detection in aircraft materials. Pulsed infrared thermography has been widely used in aerospace and mechanical manufacture industry because it can offer noncontact, quickly and visual examinations of disbonding defects. However the parameter choosing method is difficult to decide. Investigate the choosing technical parameters for pulse thermograpghy is more important to ensure the product quality and testing efficiency. In this paper, two kinds of defects which are of various size, shape and location below the test surface are planted in the honeycomb structure, they are all tested by pulsed thermography. This paper presents a study of single factor experimental research on damage sample in simulation was carried out. The impact of the power of light source, detection distance, and the wave band of thermography camera on detecting effect is studied. The select principle of technique is made, the principle supplied basis for selection of detecting parameters in real part testing. © SPIE. Downloading of the abstract is permitted for personal use only 2015.
Niu G.,China Aerospace Polytechnology Establishment |
Yang B.-S.,Pukyong National University
Expert Systems with Applications | Year: 2010
This paper proposes an intelligent condition monitoring and prognostics system in condition-based maintenance architecture based on data-fusion strategy. Firstly, vibration signals are collected and trend features are extracted. Then features are normalized and sent into neural network for feature-level fusion. Next, data de-noising is conducted containing smoothing and wavelet decomposition to reduce the fluctuation and pick out trend information. The processed information is used for autonomic health degradation monitoring and data-driven prognostics. When the degradation curve crosses through the specified threshold of alarm, prognostics module is triggered and time-series prediction is performed using multi-nonlinear regression models. Furthermore, the predicted point estimate and interval estimate are fused, respectively. Finally, remaining useful life of operating machine, with its uncertainty interval, are assessed. The proposed system is evaluated by an experiment of health degradation monitoring and prognostics for a methane compressor. The experiment results show that the enhanced maintenance performances can be obtained, which make it suitable for advanced industry maintenance. © 2010 Elsevier Ltd. All rights reserved.
Xuegang L.,China Aerospace Polytechnology Establishment
Procedia Engineering | Year: 2015
At present, customers demand more complex and reliable products to be developed with shorter timeand more cost effectiveness. In the product development process, the traditional approach to reliability specification has been based on unrealistic reliability prediction by usingstandards, such as Mil-Hdbk-217 in the specific case of electronics equipment. In China at the product development stage, the reliability prediction is based on GJB 299.Often, the prediction methodology used assumes an exponential failure rate, meaning that random failures and faults are inevitable. And the reliability prediction method based on GJB 299 is not relevant to product design parameters. There need a new reliability prediction method to address the challenges that we face during the product developmentprocess. In this paper, we firstanalyses the component reliability of the product by reliabilitysimulation based on physics failure theory. Then inputting the results of components reliabilitysimulation and components degradation information to the functional model, we discuss the product reliability by reliability functional simulation. It is shown that we can accurately predict the reliability in the product development process by the proposed method. © 2015 The Authors.
Tang B.,Chongqing University |
Jiang Y.,Chongqing University |
Zhang X.,China Aerospace Polytechnology Establishment
Jixie Gongcheng Xuebao/Journal of Mechanical Engineering | Year: 2010
Due to the influence caused by random noises and local strong disturbances embedded in signal on empirical mode decomposition (EMD) results, a novel integrated singular value decomposition-morphology filter method is proposed to overcome this shortcoming. And combining with EMD, a feature extraction method is presented. Firstly, reconstruct the original vibration signal in phase space and decompose the attractor track matrix by singular value decomposition (SVD), and then select a reasonable order for noise reduction according to the singular curve. Secondly, filter the de-noised signal by morphology filter. Finally, decompose it by EMD to extract the intrinsic mode functions (IMF) for fault feature extraction. Experimental results and industrial measurement analysi show that this method can extract fault characteristics of rolling bearing effectively, reduce decomposition levels and boundary effect of EMD, and imporve the timeliness and precision thereof. © 2010 Journal of Mechanical Engineering.