scholarly journals High-Speed Edge Trimming of CFRP and Online Monitoring of Performance of Router Tools Using Acoustic Emission

Materials ◽  
2016 ◽  
Vol 9 (10) ◽  
pp. 798 ◽  
Author(s):  
Rangasamy Prakash ◽  
Vijayan Krishnaraj ◽  
Redouane Zitoune ◽  
Jamal Sheikh-Ahmad
2019 ◽  
Vol 85 (6) ◽  
pp. 53-63 ◽  
Author(s):  
I. E. Vasil’ev ◽  
Yu. G. Matvienko ◽  
A. V. Pankov ◽  
A. G. Kalinin

The results of using early damage diagnostics technique (developed in the Mechanical Engineering Research Institute of the Russian Academy of Sciences (IMASH RAN) for detecting the latent damage of an aviation panel made of composite material upon bench tensile tests are presented. We have assessed the capabilities of the developed technique and software regarding damage detection at the early stage of panel loading in conditions of elastic strain of the material using brittle strain-sensitive coating and simultaneous crack detection in the coating with a high-speed video camera “Video-print” and acoustic emission system “A-Line 32D.” When revealing a subsurface defect (a notch of the middle stringer) of the aviation panel, the general concept of damage detection at the early stage of loading in conditions of elastic behavior of the material was also tested in the course of the experiment, as well as the software specially developed for cluster analysis and classification of detected location pulses along with the equipment and software for simultaneous recording of video data flows and arrays of acoustic emission (AE) data. Synchronous recording of video images and AE pulses ensured precise control of the cracking process in the brittle strain-sensitive coating (tensocoating)at all stages of the experiment, whereas the use of structural-phenomenological approach kept track of the main trends in damage accumulation at different structural levels and identify the sources of their origin when classifying recorded AE data arrays. The combined use of oxide tensocoatings and high-speed video recording synchronized with the AE control system, provide the possibility of definite determination of the subsurface defect, reveal the maximum principal strains in the area of crack formation, quantify them and identify the main sources of AE signals upon monitoring the state of the aviation panel under loading P = 90 kN, which is about 12% of the critical load.


2021 ◽  
pp. 147592172110360
Author(s):  
Dongming Hou ◽  
Hongyuan Qi ◽  
Honglin Luo ◽  
Cuiping Wang ◽  
Jiangtian Yang

A wheel set bearing is an important supporting component of a high-speed train. Its quality and performance directly determine the overall safety of the train. Therefore, monitoring a wheel set bearing’s conditions for an early fault diagnosis is vital to ensure the safe operation of high-speed trains. However, the collected signals are often contaminated by environmental noise, transmission path, and signal attenuation because of the complexity of high-speed train systems and poor operation conditions, making it difficult to extract the early fault features of the wheel set bearing accurately. Vibration monitoring is most widely used for bearing fault diagnosis, with the acoustic emission (AE) technology emerging as a powerful tool. This article reports a comparison between vibration and AE technology in terms of their applicability for diagnosing naturally degraded wheel set bearings. In addition, a novel fault diagnosis method based on the optimized maximum second-order cyclostationarity blind deconvolution (CYCBD) and chirp Z-transform (CZT) is proposed to diagnose early composite fault defects in a wheel set bearing. The optimization CYCBD is adopted to enhance the fault-induced impact response and eliminate the interference of environmental noise, transmission path, and signal attenuation. CZT is used to improve the frequency resolution and match the fault features accurately under a limited data length condition. Moreover, the efficiency of the proposed method is verified by the simulated bearing signal and the real datasets. The results show that the proposed method is effective in the detection of wheel set bearing faults compared with the minimum entropy deconvolution (MED) and maximum correlated kurtosis deconvolution (MCKD) methods. This research is also the first to compare the effectiveness of applying AE and vibration technologies to diagnose a naturally degraded high-speed train bearing, particularly close to actual line operation conditions.


2021 ◽  
Vol 2 (3) ◽  

Cold forging is a high-speed forming technique used to shape metals at near room temperature. and it allows high-rate production of high strength metal-based products in a consistent and cost-effective manner. However, cold forming processes are characterized by complex material deformation dynamics which makes product quality control difficult to achieve. There is no well defined mathematical model that governs the interactions between a cold forming process, material properties, and final product quality. The goal of this work is to provide a review for the state of research in the field of using acoustic emission (AE) technology in monitoring cold forging process. The integration of AE with machine learning (ML) algorithms to monitor the quality is also reviewed and discussed. It is realized that this promising technology didn’t receive the deserving attention for its implementation in cold forging and that more work is needed.


2018 ◽  
Vol 962 ◽  
pp. 012064
Author(s):  
S Bakhri ◽  
E Sumarno ◽  
R Himawan ◽  
T Y Akbar ◽  
M. Subekti ◽  
...  

2018 ◽  
Vol 18 (6) ◽  
pp. 243-250 ◽  
Author(s):  
Zhang Ji-wang ◽  
Zhang Lai-bin ◽  
Ding Ke-Qin ◽  
Duan Li-xiang

Abstract High-speed blades form core mechanical components in turbomachines. Research concerning online monitoring of operating states of such blades has drawn increased attention in recent years. To this end, various methods have been devised, of which, the blade tip-timing (BTT) technique is considered the most promising. However, the traditional BTT method is only suitable for constant-speed operations. But in practice, the rotational speed of turbomachine blades is constantly changing under the influence of external factors, which lead to unacceptable errors in measurement. To tackle this problem, a new BTT method based on multi-phases is proposed. A plurality of phases was arranged as evenly as possible on the rotating shaft to determine the rotation speed. Meanwhile, the corresponding virtual reference point was determined in accordance with the number of blades between consecutive phases. Based on these reference points, equations to measure displacement due to blade vibrations were deduced. Finally, mathematical modeling, numerical simulation and experimental tests were performed to verify the validity of the proposed method. Results demonstrate that the error in measurement induced when using the proposed method is less than 1.8 %, which is much lower compared to traditional methods utilized under variable-speed operation.


2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Marek Kočiško ◽  
Petr Baron ◽  
Monika Telíšková ◽  
Jozef Török ◽  
Anna Bašistová

The paper presents the results of an experimental study aimed at assessing the correlation between the measurement of dynamic parameters (vibration, high-frequency vibration, and acoustic emission) and the analysis of friction mode and the state of lubrication of the contact surfaces of two gearboxes in the turbo-generator assembly (high-speed single-body steam turbine—gearbox—generator) with the transmission power of no more than 50 MW. The analysis confirmed the assumption of a significant correlation of the monitored high-frequency vibration signal with the unsatisfactory engagement of the gear teeth. Through vibration analysis, an increased level of the tooth vibration component and vibration multiples with increased acoustic emission were identified in gearbox operation. The gear oil of one of the gearboxes examined showed a loss of additive elements in the real operation of the contact surfaces of the teeth engagement. The trend analysis confirmed the complexity of the monitored transmission operation in terms of the friction mode and the influence of the oil quality on the state of the tooth flank microgeometry.


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