Acoustic emission true RMS signals used to indicate wear of a high speed ceramic insert

1989 ◽  
Vol 20 ◽  
pp. 79-91
Author(s):  
Chang-Fei Yang ◽  
J.Richard Houghton
Keyword(s):  
Acoustic Emission ◽  
High Speed ◽  
Ceramic Insert

APPLICATION OF THE EARLY DAMAGE DIAGNOSTICS TECHNIQUE TO EXAMINATION OF THE AVIATION PANEL

2019 ◽  
Vol 85 (6) ◽  
pp. 53-63 ◽  
Author(s):  
I. E. Vasil’ev ◽  
Yu. G. Matvienko ◽  
A. V. Pankov ◽  
A. G. Kalinin
Keyword(s):  
Acoustic Emission ◽  
Damage Detection ◽  
High Speed ◽  
Early Stage ◽  
Video Data ◽  
High Speed Video ◽  
Damage Diagnostics ◽  
Subsurface Defect ◽  
Sensitive Coating ◽  
Early Damage

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.

Comparative study on the use of acoustic emission and vibration analyses for the bearing fault diagnosis of high-speed trains

2021 ◽  
pp. 147592172110360
Author(s):  
Dongming Hou ◽  
Hongyuan Qi ◽  
Honglin Luo ◽  
Cuiping Wang ◽  
Jiangtian Yang
Keyword(s):  
Acoustic Emission ◽  
Fault Diagnosis ◽  
High Speed ◽  
High Speed Train ◽  
Signal Attenuation ◽  
Transmission Path ◽  
Bearing Fault Diagnosis ◽  
Operation Conditions ◽  
Fault Features ◽  
High Speed Trains

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.

Machine Learning Acoustic Emission Based Monitoring of Cold Forging for Smart Manufacturing: A Review

2021 ◽  
Vol 2 (3) ◽  
Keyword(s):  
Machine Learning ◽  
Acoustic Emission ◽  
Product Quality ◽  
High Speed ◽  
High Rate ◽  
Cold Forging ◽  
Smart Manufacturing ◽  
Forming Process ◽  
Cold Forming ◽  
Effective Manner

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.

scholarly journals Research into Correlation between the Lubrication Mode of Contact Surfaces and Dynamic Parameters of Turbo-Generator Transmissions

2019 ◽  
Vol 2019 ◽  
pp. 1-10
Author(s):  
Marek Kočiško ◽  
Petr Baron ◽  
Monika Telíšková ◽  
Jozef Török ◽  
Anna Bašistová
Keyword(s):  
Acoustic Emission ◽  
High Frequency ◽  
High Speed ◽  
Oil Quality ◽  
The State ◽  
Dynamic Parameters ◽  
High Frequency Vibration ◽  
Turbo Generator ◽  
Friction Mode ◽  
Contact Surfaces

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.

scholarly journals Experimental Investigation of the Diagnosis of Angular Contact Ball Bearings Using Acoustic Emission Method and Empirical Mode Decomposition

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Ramtin Tabatabaei ◽  
Aref Aasi ◽  
Seyed Mohammad Jafari ◽  
Enrico Ciulli
Keyword(s):  
Acoustic Emission ◽  
Empirical Mode Decomposition ◽  
High Speed ◽  
Early Stage ◽  
Signal To Noise Ratio ◽  
Operating Conditions ◽  
Outer Race ◽  
Mode Decomposition ◽  
Speed Performance ◽  
Envelope Spectrum

Early detection of angular contact bearings, one of the important subsets of rolling element bearings (REBs), is critical for applications of high accuracy and high speed performance. In this study, acoustic emission (AE) method was applied to an experimental case with defects on angular contact bearing. AE signals were collected by AE sensors in different operating conditions. Signal to noise ratio (SNR) was calculated by kurtosis to entropy ratio (KER), then acquired signals were denoised by empirical mode decomposition (EMD) method, and optimal intrinsic mode function (IMF) was selected by the proposed method. Finally, envelope spectrum was applied to the denoised signals, and frequencies of defects were obtained in different rotating speeds, loadings, and defect sizes. For the first time, a small defect with width of 0.3 mm and loading of 475 N was detected in early stage of 0.04 KHz. Moreover, a comparison between theoretical and extracted defect frequencies suggested that our method successfully detected localized defects in both inner and outer race. Our results show promise in detecting small size defects in REBs.

scholarly journals Failure Mechanism of Rock Bridge Based on Acoustic Emission Technique

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Guoqing Chen ◽  
Yan Zhang ◽  
Runqiu Huang ◽  
Fan Guo ◽  
Guofeng Zhang
Keyword(s):  
Acoustic Emission ◽  
Failure Mechanism ◽  
High Speed ◽  
Large Scale ◽  
Small Scale ◽  
Failure Behavior ◽  
Long Distance ◽  
Rock Bridge ◽  
Rocky Slope ◽  
Landslide Model

Acoustic emission (AE) technique is widely used in various fields as a reliable nondestructive examination technology. Two experimental tests were carried out in a rock mechanics laboratory, which include (1) small scale direct shear tests of rock bridge with different lengths and (2) large scale landslide model with locked section. The relationship of AE event count and record time was analyzed during the tests. The AE source location technology and comparative analysis with its actual failure model were done. It can be found that whether it is small scale test or large scale landslide model test, AE technique accurately located the AE source point, which reflected the failure generation and expansion of internal cracks in rock samples. Large scale landslide model with locked section test showed that rock bridge in rocky slope has typical brittle failure behavior. The two tests based on AE technique well revealed the rock failure mechanism in rocky slope and clarified the cause of high speed and long distance sliding of rocky slope.

Optical-Fiber Sensors for the Detection of Acoustic Emission

MRS Bulletin ◽  
2002 ◽  
Vol 27 (5) ◽  
pp. 396-399 ◽  
Author(s):  
William B. Spillman ◽  
Richard O. Claus
Keyword(s):  
Signal Processing ◽  
Acoustic Emission ◽  
Optical Fiber ◽  
Material Properties ◽  
High Speed ◽  
Optical Fiber Sensors ◽  
Piezoelectric Transducers ◽  
Fiber Sensors ◽  
Critical Materials ◽  
Signal Processing Methods

AbstractAcoustic emission (AE) is used as a means to anticipate the mechanical failure of critical materials and structures by detecting the release of energy caused by material rearrangement at the microlevel. Optical-fiber sensors have potential advantages over conventional tuned piezoelectric transducers and signal-processing methods for the detection of such types of ultrasonic acoustic wave events. A number of fiber Bragg grating techniques are presented, which in particular offer the potential to provide the high-speed signal processing and ability to multiplex numbers of AE sensors necessary to detect, quantify, and locate AE sources and thereby determine material properties and damage.

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