scholarly journals An improved analytical dynamic model for rotating blade crack: With application to crack detection indicator analysis

2021 ◽  
pp. 146134842110126
Author(s):  
Laihao Yang ◽  
Meng Ma ◽  
Shuming Wu ◽  
Xuefeng Chen ◽  
Ruqiang Yan ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Dynamic Model ◽  
Crack Detection ◽  
Failure Modes ◽  
Numerical Study ◽  
Analytical Models ◽  
Crack Model ◽  
Rotating Blade ◽  
Vibration Responses ◽  
Blade Crack

Rotating blade is one of the most important components for turbomachinery. Blade crack is one of the most common and dangerous failure modes for rotating blade. Therefore, the fault mechanism and feature extraction of blade crack are vital for the safety assurance of turbomachinery. This study is aimed at the nonlinear dynamic model of rotating blade with transverse crack and the prior feature extraction of blade crack faults based on the vibration responses. First and foremost, a high-fidelity breathing crack model (HFBCM) for rotating blade is proposed on the basis of criterion for stress states at crack section. Since HFBCM is physically deduced from the perspective of energy dissipation and the coupling between centrifugal stress and bending stress is considered, the physical interpretability and the accuracy of the crack model are enhanced comparing with conventional models. The validity of the proposed HFBCM is verified through the comparison study among HFBCM, conventional crack models, and finite element-based contact crack model (FECCM). It is suggested that HFBCM behaves best among the analytical models and matches well with FECCM. With the proposed HFBCM, the nonlinear vibration responses are investigated, and four types of blade crack detection indicators for rotating blade and their quantification method are presented. The numerical study manifests that all these indicators can well characterize the occurrence and severity of crack faults for rotating blade. It is indicated that these indicators can serve as the crack-monitoring indexes.

scholarly journals Planetary Gearbox Dynamic Modeling Considering Bearing Clearance and Sun Gear Tooth Crack

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2638
Author(s):  
Xianhua Chen ◽  
Xingkai Yang ◽  
Ming J. Zuo ◽  
Zhigang Tian
Keyword(s):  
Dynamic Model ◽  
Dynamic Modeling ◽  
Failure Modes ◽  
Gear Tooth ◽  
Working Environment ◽  
The Sun ◽  
Planetary Gearbox ◽  
Bearing Clearance ◽  
Vibration Responses ◽  
Planet Gear

Planetary gearbox systems are critical mechanical components in heavy machinery such as wind turbines. They may suffer from various failure modes, due to the harsh working environment. Dynamic modeling is a useful method to support early fault detection for enhancing reliability and reducing maintenance costs. However, reported studies have not considered the sun gear tooth crack and bearing clearance simultaneously to analyze their combined effect on vibration characteristics of planetary gearboxes. In this paper, a dynamic model is developed for planetary gearboxes considering the clearance of planet gear, sun gear, and carrier bearings, as well as sun gear tooth crack levels. Bearing forces are calculated considering bearing clearance, and the dynamic model equations are updated accordingly. The results reveal that the combination of bearing clearances can affect the vibration response with sun gear tooth crack by increasing the kurtosis. It is found that the effect of planet gear bearing clearance is very small, while the sun gear and carrier bearing clearance has clear impact on the vibration responses. These findings suggest that the incorporation of bearing clearance is important for planetary gearbox dynamic modeling.

REINFORCED CONCRETE CRACK MODEL BASED ON STIFFNESS ANALYSIS OF TENSION MEMBERS

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Angus Murray ◽  
Raymond Ian Gilbert ◽  
Arnaud Castel
Keyword(s):  
Reinforced Concrete ◽  
Numerical Study ◽  
Crack Spacing ◽  
Analytical Models ◽  
Crack Model ◽  
Primary Crack ◽  
Proposed Model ◽  
Average Crack ◽  
Service Behavior ◽  
Tension Members

The average spacing of primary cracks in a reinforced concrete (RC) member greatly influences its in-service behavior, especially with regard to stiffness and average crack width. Accurate predictions of the average crack spacing are therefore crucial for satisfying serviceability requirements in RC structures. This is particularly the case when relying on analytical models that treat cracks discretely rather than in a smeared fashion. Popular code-based models for primary crack spacing are often wildly inaccurate and may lead to poor predictions of in-service behavior. In this paper, the problem or primary crack formation is approached from a stiffness perspective. The proposed model is based on the results of several experimental tension stiffening studies in the literature, as well as a previous numerical study dealing with the effect on stiffness of non-plane deformation in the neighborhood of primary cracks. The proposed model is compared to some popular code-based models and is shown to better predict average crack spacing for a wide variety of beams, slabs, and tension members.

Dynamic Characteristic Analysis of Rotating Blade with Transverse Crack - Part I: Modeling, Modification and Validation

2020 ◽  
pp. 1-36
Author(s):  
Laihao Yang ◽  
Zheshuai Yang ◽  
Zhu Mao ◽  
Shuming Wu ◽  
Xuefeng Chen ◽  
...  
Keyword(s):  
Prediction Accuracy ◽  
Transverse Crack ◽  
Coupling Effect ◽  
Analytical Models ◽  
Crack Model ◽  
Breathing Crack ◽  
Characteristic Analysis ◽  
Model Modification ◽  
Rotating Blade ◽  
Vibration Prediction

Abstract This study aims at the systematical improvement and comparative analysis of analytical crack models for the rotating blade. Part I of this study focuses on analytical modeling, model modification, and model validation of transverse crack for rotating blade. The most widely-applied analytical crack models for rotating blade are reviewed and compared, and then their limitations are discussed. It is indicated that the conventional analytical crack models suffer from low physical interpretability and vibration prediction accuracy. By considering these limitations of conventional analytical crack models, model modification is performed to enhance the physical meaning and improve the accuracy. First, the stress-based breathing crack model (SBCM) is modified by direct calculation of the breathing function based on the theory of linear elastic fracture mechanics and resetting the correction factor of centrifugal-stiffening stiffness. Second, the vibration-based breathing crack models (VBCMs), including linear breathing crack model and cosine breathing crack model, are modified by introducing the coupling effect between bending stress and centrifugal stress based on the stress state at the blade crack section. The additional bending moment induced by the blade part outside the crack section is considered in all analytical models. The modified crack models' validity is verified by comparing vibration responses obtained by the modified crack models, the finite element contact crack model, and the conventional crack models. The comparative results suggest that the modified models promote the physical interpretability and improve the vibration prediction accuracy of analytical crack models.

INFLUENCE OF FLOW SWIRLING ON COMBUSTION OF ALUMINUM POWDER AEROSUSPENSION IN A CHAMBER WITH EXTENSION

2020 ◽  
Author(s):  
A. Yu. Krainov ◽  
◽  
K. M. Moiseeva ◽  
V. A. Poryazov ◽  
◽  
...  
Keyword(s):  
Dynamic Model ◽  
Aluminum Powder ◽  
Swirling Flow ◽  
Numerical Study ◽  
Mathematical Formulation ◽  
Expansion Chamber ◽  
Flow Swirling ◽  
Air Suspension

A numerical study of combustion of the aluminum-air suspension in the swirling flow in the expansion chamber has been performed. The physical and mathematical formulation of the problem is based on the dynamic model of the multiphase reacting media.

scholarly journals Numerical study of the centrifugal contra rotating blade system

2021 ◽  
Vol 1741 ◽  
pp. 012008
Author(s):  
A A Kulikov ◽  
A V Ratushnyi ◽  
I A Kovaliov ◽  
A S Mandryka ◽  
A S Ignatiev
Keyword(s):  
Numerical Study ◽  
Rotating Blade ◽  
Blade System

Geometry optimization of a planar double wishbone suspension based on whole-range nonlinear dynamic model

2021 ◽  
pp. 095440702110262
Author(s):  
Zhihua Niu ◽  
Sun Jin ◽  
Rongrong Wang ◽  
Yansong Zhang
Keyword(s):  
Dynamic Model ◽  
Geometry Optimization ◽  
Analytical Models ◽  
Small Displacement ◽  
Nonlinear Dynamic Model ◽  
Computational Accuracy ◽  
Suspension Systems ◽  
Geometry Design ◽  
Dynamic Performances ◽  
Suspension Geometry

Dynamic analysis is an essential task in the geometry design of suspension systems. Whereas the dynamic simulation based on numerical software like Adams is quite slowly and the existing analytical models of the nonlinear suspension geometry are mostly based on small displacement hypothesis, this paper aims to propose a whole-range dynamic model with high computational efficiency for planar double wishbone suspensions and further achieve the fast optimal design of suspension geometry. Selection of the new generalized coordinate and explicit solutions of the basic four-bar mechanism dramatically reduce the complexity of suspension geometry representation and provide analytical solutions for all of the time varying dimensions. By this means, the running speed and computational accuracy of the new model are guaranteed simultaneously. Furthermore, an original Matlab/Simulink implementation is given to maintain the geometric nonlinearity in the solving process of dynamic differential equations. After verifying its accuracy with an ADAMS prototype, the presented whole-range model is used in the vast-parameter optimization of suspension geometry. Since both kinematic and dynamic performances are evaluated in the objective function, the optimization is qualified to give a comprehensive suggestion to the design of suspension geometry.

Blade Crack Detection using Blade Tip Timing

2021 ◽  
pp. 1-1
Author(s):  
Shuming Wu ◽  
Zengkun Wang ◽  
Haoqi Li ◽  
Zhibo Yang ◽  
Shaohua Tian ◽  
...  
Keyword(s):  
Crack Detection ◽  
Blade Tip ◽  
Blade Crack

scholarly journals Concrete Crack Detection Based on Well-Known Feature Extractor Model and the YOLO_v2 Network

2021 ◽  
Vol 11 (2) ◽  
pp. 813
Author(s):  
Shuai Teng ◽  
Zongchao Liu ◽  
Gongfa Chen ◽  
Li Cheng
Keyword(s):  
Feature Extraction ◽  
Crack Detection ◽  
Computational Cost ◽  
Concrete Structures ◽  
Detection Algorithm ◽  
Computational Time ◽  
Image Size ◽  
Important Indicator ◽  
Feature Extractor ◽  
Model Training

This paper compares the crack detection performance (in terms of precision and computational cost) of the YOLO_v2 using 11 feature extractors, which provides a base for realizing fast and accurate crack detection on concrete structures. Cracks on concrete structures are an important indicator for assessing their durability and safety, and real-time crack detection is an essential task in structural maintenance. The object detection algorithm, especially the YOLO series network, has significant potential in crack detection, while the feature extractor is the most important component of the YOLO_v2. Hence, this paper employs 11 well-known CNN models as the feature extractor of the YOLO_v2 for crack detection. The results confirm that a different feature extractor model of the YOLO_v2 network leads to a different detection result, among which the AP value is 0.89, 0, and 0 for ‘resnet18’, ‘alexnet’, and ‘vgg16’, respectively meanwhile, the ‘googlenet’ (AP = 0.84) and ‘mobilenetv2’ (AP = 0.87) also demonstrate comparable AP values. In terms of computing speed, the ‘alexnet’ takes the least computational time, the ‘squeezenet’ and ‘resnet18’ are ranked second and third respectively; therefore, the ‘resnet18’ is the best feature extractor model in terms of precision and computational cost. Additionally, through the parametric study (influence on detection results of the training epoch, feature extraction layer, and testing image size), the associated parameters indeed have an impact on the detection results. It is demonstrated that: excellent crack detection results can be achieved by the YOLO_v2 detector, in which an appropriate feature extractor model, training epoch, feature extraction layer, and testing image size play an important role.

scholarly journals Design and analysis of concrete-filled tubular flange girders under combined loading

2021 ◽  
pp. 136943322110015
Author(s):  
Rana Al-Dujele ◽  
Katherine Ann Cashell
Keyword(s):  
Finite Element ◽  
Axial Force ◽  
Failure Modes ◽  
Numerical Study ◽  
Combined Loading ◽  
Torsional Stiffness ◽  
Fe Model ◽  
Combined Effects ◽  
Element Analysis ◽  
Hollow Section

This paper is concerned with the behaviour of concrete-filled tubular flange girders (CFTFGs) under the combination of bending and tensile axial force. CFTFG is a relatively new structural solution comprising a steel beam in which the compression flange plate is replaced with a concrete-filled hollow section to create an efficient and effective load-carrying solution. These members have very high torsional stiffness and lateral torsional buckling strength in comparison with conventional steel I-girders of similar depth, width and steel weight and are there-fore capable of carrying very heavy loads over long spans. Current design codes do not explicitly include guidance for the design of these members, which are asymmetric in nature under the combined effects of tension and bending. The current paper presents a numerical study into the behaviour of CFTFGs under the combined effects of positive bending and axial tension. The study includes different loading combinations and the associated failure modes are identified and discussed. To facilitate this study, a finite element (FE) model is developed using the ABAQUS software which is capable of capturing both the geometric and material nonlinearities of the behaviour. Based on the results of finite element analysis, the moment–axial force interaction relationship is presented and a simplified equation is proposed for the design of CFTFGs under combined bending and tensile axial force.

Vibration-Based Early Crack Diagnosis With Machine Learning for Spur Gears

2020 ◽  
Author(s):  
Fatih Karpat ◽  
Ahmet Emir Dirik ◽  
Onur Can Kalay ◽  
Oğuz Doğan ◽  
Burak Korcuklu
Keyword(s):  
Machine Learning ◽  
Fault Diagnosis ◽  
High Speed ◽  
Crack Detection ◽  
Power Transmission ◽  
Calculated Data ◽  
Design Parameters ◽  
Tooth Stiffness ◽  
Vibration Responses ◽  
Root Crack

Abstract Gear mechanisms are one of the most significant components of the power transmission systems. Due to increasing emphasis on the high-speed, longer working life, high torques, etc. cracks may be observed on the gear surface. Recently, Machine Learning (ML) algorithms have started to be used frequently in fault diagnosis with developing technology. The aim of this study is to determine the gear root crack and its degree with vibration-based diagnostics approach using ML algorithms. To perform early crack detection, the single tooth stiffness and the mesh stiffness calculated via ANSYS for both healthy and faulty (25-50-75-100%) teeth. The calculated data transferred to the 6-DOF dynamic model of a one-stage gearbox, and vibration responses was collected. The data gathered for healthy and faulty cases were evaluated for the feature extraction with five statistical indicators. Besides, white Gaussian noise was added to the data obtained from the 6-DOF model, and it was aimed at early fault diagnosis and condition monitoring with ML algorithms. In this study, the gear root crack and its degree analyzed for both healthy and four different crack sizes (25%-50%-75%-100%) for the gear crack detection. Thereby, a method was presented for early fault diagnosis without the need for a big experimental dataset. The proposed vibration-based approach can eliminate the high test rig construction costs and can potentially be used for the evaluation of different working conditions and gear design parameters. Therefore, catastrophic failures can be prevented, and maintenance costs can be optimized by early crack detection.

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