Incipient Surge Detection in Large Volume Energy Systems Based On Wigner-Ville Distribution Evaluated On Vibration Signals

2021 ◽  
Author(s):  
Carlo Alberto Niccolini Marmont Du Haut Champ ◽  
Paolo Silvestri ◽  
Mario L. Ferrari ◽  
Aristide Fausto Massardo
Keyword(s):  
Research Field ◽  
Rotating Stall ◽  
Operating Conditions ◽  
Rolling Bearings ◽  
Time Frequency ◽  
Rotating Machine ◽  
Large Size ◽  
Critical Issues ◽  
Volume Energy ◽  
Transient Operations

Abstract Compressor response investigation in nearly unstable operating conditions, like rotating stall and incipient surge, is a challenging topic nowadays in the turbomachinery research field. Indeed, turbines connected with large-size volumes are affected by critical issues related to surge prevention, particularly during transient operations. Advanced signal-processing operations conducted on vibrational responses provide an insight into possible diagnostic and predictive solutions which can be derived from accelerometer measurements. Indeed, vibrational investigation is largely employed in rotating-machine diagnostics together with time-frequency analysis such as smoothed pseudo-Wigner Ville (SPWVD) time-frequency distribution (TFD) considered in this paper. It is characterized by excellent time and frequency resolutions and thus it is effectively employed in numerous applications in the condition monitoring of machinery. The aim and the innovation of this work regards SPWVD utilization to study turbomachinery behavior in detail in order to identify incipient surge conditions in the centrifugal compressor starting from operational vibrational responses measured at significant plant locations. To this aim, an experimental campaign has been conducted on a T100 microturbine connected with different volume sizes to collect significant data to be analyzed. The results show that SPWVD is able to successfully identify system evolution towards an unstable condition, by recognizing different levels and features of the particular kind of instability that is going to take place within the plant. Instability phenomena regarding rolling bearings have also been identified and their interaction with surge onset has been investigated for diagnostic purposes.

Experimental Study of a Bulb Turbine Model During Start-Up and at Speed-No-Load Conditions, Based on the Measurement of Unsteady Pressure

2020 ◽  
Vol 142 (8) ◽  
Author(s):  
Maxime Coulaud ◽  
Jean Lemay ◽  
Claire Deschenes
Keyword(s):  
Pressure Fluctuations ◽  
Pressure Sensors ◽  
Suction Side ◽  
Rotating Stall ◽  
Operating Conditions ◽  
Time Frequency ◽  
Runner Blade ◽  
Start Up ◽  
Morlet Wavelet Transform ◽  
Bulb Turbine

Abstract Experimental analysis of a bulb turbine during the start-up sequence and in speed-no-load (SNL) operating conditions was performed in a closed-loop circuit. This study focuses on pressure fluctuations across the machine. The turbine was equipped with 26 pressure sensors on one runner blade and 16 in the stationary reference frame. Strain measurements were also performed on two other runner blades. The first section of this analysis focuses on SNL operating conditions using standard Fourier data processing. The results show that three rotating flow phenomena are only present close to the runner. One of them corresponds to the interblade vortex at f/fr=4.00, whereas the two others, which have subsynchronous runner frequencies, are consistent with a possible rotating stall. These phenomena, which exist predominantly on the suction side, have a strong influence on runner blade strain. The second section of the study concentrates on a time-frequency analysis using the Morlet wavelet transform. It reveals that the two subsynchronous flow structures appear at the end of the start-up and exhibit bistable behavior. As well, each of these phenomena acts differently on the blade. These phenomena also interact with the interblade vortex.

scholarly journals Predicting Remaining Useful Life of Rolling Bearings Based on Reliable Degradation Indicator and Temporal Convolution Network with the Quantile Regression

2021 ◽  
Vol 11 (11) ◽  
pp. 4773
Author(s):  
Qiaoping Tian ◽  
Honglei Wang
Keyword(s):  
Quantile Regression ◽  
Probability Density ◽  
Degradation Process ◽  
Remaining Useful Life ◽  
Health State ◽  
Rolling Bearings ◽  
Data Set ◽  
Time Frequency ◽  
Useful Life ◽  
Degradation Indicator

High precision and multi information prediction results of bearing remaining useful life (RUL) can effectively describe the uncertainty of bearing health state and operation state. Aiming at the problem of feature efficient extraction and RUL prediction during rolling bearings operation degradation process, through data reduction and key features mining analysis, a new feature vector based on time-frequency domain joint feature is found to describe the bearings degradation process more comprehensively. In order to keep the effective information without increasing the scale of neural network, a joint feature compression calculation method based on redefined degradation indicator (DI) was proposed to determine the input data set. By combining the temporal convolution network with the quantile regression (TCNQR) algorithm, the probability density forecasting at any time is achieved based on kernel density estimation (KDE) for the conditional distribution of predicted values. The experimental results show that the proposed method can obtain the point prediction results with smaller errors. Compared with the existing quantile regression of long short-term memory network(LSTMQR), the proposed method can construct more accurate prediction interval and probability density curve, which can effectively quantify the uncertainty of bearing running state.

Vibration Analysis of Gears with Fatigue Crack in Tooth Root

2006 ◽  
Vol 324-325 ◽  
pp. 835-838
Author(s):  
Aleš Belšak ◽  
Jože Flašker
Keyword(s):  
Fatigue Crack ◽  
Laboratory Test ◽  
Signal Analysis ◽  
Vibration Analysis ◽  
Operating Conditions ◽  
Test Plant ◽  
Tooth Root ◽  
Unit Operation ◽  
Time Frequency ◽  
Non Stationary Signal

A crack in the tooth root, which often leads to failure in gear unit operation, is the most undesirable damage caused to gear units. This article deals with fault analyses of gear units with real damages. Numerical simulations of real operating conditions have been used in relation to the formation of those damages. A laboratory test plant has been used and a possible damage can be identified by monitoring vibrations. The influences of defects of a single-stage gear unit upon the vibrations they produce are presented. Signal analysis has been performed also in concern to a non-stationary signal, using the Time Frequency Analysis tools. Typical spectrograms, which are the result of reactions to damages, are a very reliable indication of the presence of damages.

scholarly journals Tracking and Visualizing Signs of Degradation for Early Failure Prediction of Rolling Bearings

2021 ◽  
Vol 33 (3) ◽  
pp. 629-642
Author(s):  
Sana Talmoudi ◽  
Tetsuya Kanada ◽  
Yasuhisa Hirata ◽  
◽  
Keyword(s):  
Real Time ◽  
Training Data ◽  
High Dimensional ◽  
Time Data ◽  
Early Failure ◽  
Rolling Bearings ◽  
Full Spectrum ◽  
Time Frequency ◽  
Vibration Data ◽  
Visualization Technology

Predictive maintenance, which means detection of failure ahead of time, is one of the pillars of Industry 4.0. An effective method for this technique is to track early signs of degradation before failure occurs. This paper presents an innovative failure predictive scheme for machines. The proposed scheme combines the use of the full spectrum of vibration data from the machines and a data visualization technology. This scheme requires no training data and can be started quickly after installation. First, we proposed to use the full spectrum (as high-dimensional data vectors) with no cropping and no complex feature extraction and to visualize the data behavior by mapping the high-dimensional vectors into a two-dimensional (2D) map. This ensures simplicity of the process and less possibility of overlooking important information as well as provide a human-friendly and human-understandable output. Second, we developed a real-time data tracker that can predict failure at an appropriate time with sufficient allowance for maintenance by plotting real-time frequency spectrum data of the target machine on a 2D map created from normal data. Finally, we verified our proposal using vibration data of bearings from real-world test-to-failure measurements obtained from the IMS dataset.

Reduced-Order Modelling of Rotating Stall

2020 ◽  
Author(s):  
Dominik Schlüter ◽  
Robert P. Grewe ◽  
Fabian Wartzek ◽  
Alexander Liefke ◽  
Jan Werner ◽  
...  
Keyword(s):  
Single Cell ◽  
Mass Flow Rate ◽  
Mass Flow ◽  
Flow Rate ◽  
Rotational Speed ◽  
Stability Limit ◽  
Rotating Stall ◽  
Operating Conditions ◽  
Transonic Compressor ◽  
Experimental Findings

Abstract Rotating stall is a non-axisymmetric disturbance in axial compressors arising at operating conditions beyond the stability limit of a stage. Although well-known, its driving mechanisms determining the number of stall cells and their rotational speed are still marginally understood. Numerical studies applying full-wheel 3D unsteady RANS calculations require weeks per operating point. This paper quantifies the capability of a more feasible quasi-2D approach to reproduce 3D rotating stall and related sensitivities. The first part of the paper deals with the validation of a numerical baseline the simplified model is compared to in detail. Therefore, 3D computations of a state-of-the-art transonic compressor are conducted. At steady conditions the single-passage RANS CFD matches the experimental results within an error of 1% in total pressure ratio and mass flow rate. At stalled conditions, the full-wheel URANS computation shows the same spiketype disturbance as the experiment. However, the CFD underpredicts the stalling point by approximately 7% in mass flow rate. In deep stall, the computational model correctly forecasts a single-cell rotating stall. The stall cell differs by approximately 21% in rotational speed and 18% in circumferential size from the experimental findings. As the 3D model reflects the compressor behaviour sufficiently accurate, it is considered valid for physical investigations. In the second part of the paper, the validated baseline is reduced in radial direction to a quasi-2D domain only resembling the compressor tip area. Four model variations regarding span-wise location and extent are numerically investigated. As the most promising model matches the 3D flow conditions in the rotor tip region, it correctly yields a single-cell rotating stall. The cell differs by only 7% in circumferential size from the 3D results. Due to the impeded radial migration in the quasi-2D slice, however, the cell exhibits an increased axial extent. It is assumed, that the axial expansion into the adjacent rows causes the difference in cell speed by approximately 24%. Further validation of the reduced model against experimental findings reveals, that it correctly reflects the sensitivity of circumferential cell size to flow coefficient and individual cell speed to compressor shaft speed. As the approach reduced the wall clock time by 92%, it can be used to increase the physical understanding of rotating stall at much lower costs.

scholarly journals A Novel Hierarchical Algorithm for Bearing Fault Diagnosis Based on Stacked LSTM

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Lu Yu ◽  
Jianling Qu ◽  
Feng Gao ◽  
Yanping Tian
Keyword(s):  
Fault Diagnosis ◽  
Short Term Memory ◽  
Operating Conditions ◽  
Support Vector ◽  
Rolling Bearings ◽  
Hierarchical Algorithm ◽  
Bearing Fault Diagnosis ◽  
Rotary Machinery ◽  
Proposed Model ◽  
Series Of Experiments

Faced with severe operating conditions, rolling bearings tend to be one of the most vulnerable components in mechanical systems. Due to the requirements of economic efficiency and reliability, effective fault diagnosis methods for rolling bearings have long been a hot research topic of rotary machinery fields. However, traditional methods such as support vector machine (SVM) and backpropagation neural network (BP-NN) which are composed of shallow structures trap into a dilemma when further improving their accuracies. Aiming to overcome shortcomings of shallow structures, a novel hierarchical algorithm based on stacked LSTM (long short-term memory) is proposed in this text. Without any preprocessing operation or manual feature extraction, the proposed method constructs a framework of end-to-end fault diagnosis system for rolling bearings. Beneficial from the memorize-forget mechanism of LSTM, features inherent in raw temporal signals are extracted hierarchically and automatically by stacking LSTM. A series of experiments demonstrate that the proposed model can not only achieve up to 99% accuracy but also outperform some state-of-the-art intelligent fault diagnosis methods.

scholarly journals Impact of Number of Operators and Distance to Branch Piles on Woodchipper Operation

Forests ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 598 ◽  
Author(s):  
Łukasz Warguła ◽  
Mateusz Kukla ◽  
Piotr Krawiec ◽  
Bartosz Wieczorek
Keyword(s):  
Low Power ◽  
Adaptive Systems ◽  
Operating Time ◽  
Operating Mode ◽  
Operating Conditions ◽  
Operating Condition ◽  
Time Frequency ◽  
Drive Speed ◽  
Type Machine ◽  
Volume Output

Branch chipping machines with low-power engines are distinguished with an intermittent operation due to a periodical supply of branches. A conventional drive speed control of these machines is not adapted to adjust the operating mode depending on frequency of material supply for shredding. This article discusses the issues related to the assessment of the application of adaptive systems similar in design to start–stop systems used in vehicles, as necessary in the driving of this type machine. During testing, an impact of a distance between a branch pile from the woodchipper, a number of operators on frequency of drive unit operating condition changes, and the mass and volume output (productivity) were considered. A percentage ratio of the active and passive (idle) operation in selected conditions of use was also determined. A low-power 9.5 kW engine-powered cylindrical-type woodchipper was used for testing. Material chopped in the chipper was freshly cut branches of oaks (Quercus L. Sp. Pl. 994. 1753) with a diameter in the largest cross-section ca. 80 mm and moisture content ca. 25%. Piles of branches were located at three different distances from the chipper, i.e., 3 m, 9 m and 15 m. Branches to the chipper were fed by one or two operators. It was demonstrated that the idle run time in tested conditions with one operator could be from 43% to 71% of the entire operating time. Frequency of operating condition changes when only one operator worked and fluctuated from ca. 6 to 2 times per minute. Increasing the number of operators from one to two had a slight impact on the frequency of operating condition changes (by ca. 7%) at the shortest distance from the chipper (3 m). However, at larger distances, the additional operator may increase the frequency of operating condition changes of the chipper by 77% for 9 m distance and 85% for 15 m distance. The mass and volumetric output of the cylindrical chipper in the most advantageous case is equal to 0.66 t/h and 3.5 m3/h, respectively. The increase of the branch pile distance from the chipper causes a drop in mass output by 32%, and volumetric output by 33.5%. The results of the tests confirmed the necessity for the development of low-power chipping machines designed for clearing operations rather than industrial production of biomass. A direction for development could be systems that adapt driving units to operating conditions, depending on a demand for the chipping process.

scholarly journals Improvement of Intake Structures in a Two-Way Pumping Station with Experimental Analysis

2020 ◽  
Vol 10 (19) ◽  
pp. 6842
Author(s):  
Yanjun Li ◽  
Rong Lu ◽  
Huiyan Zhang ◽  
Fanjie Deng ◽  
Jianping Yuan
Keyword(s):  
Frequency Domain ◽  
Great Influence ◽  
Operating Conditions ◽  
Stable Operation ◽  
Pressure Pulsations ◽  
Pump Unit ◽  
Measuring Point ◽  
Time Frequency ◽  
Pumping Station ◽  
Bell Mouth

Pumping stations are important regulation facilities in a water distribution system. Intake structures can generally have a great influence on the operational state of the pumping station. To analyze the effects of the bell mouth height of the two-way intake on the performance characteristics and the pressure pulsations of a two-way pumping station, the laboratory-sized model pump units with three different intakes were experimentally investigated. To facilitate parameterized control, ellipse and straight lines were used to construct the profile of the bell mouth. The frequency domain and time-frequency domain of the pressure pulsations on the wall of intakes were analyzed by the Welch’s power spectral density estimate and the continuous wavelet transform (CWT) methods, respectively. The results showed that the bell mouth height (H) has significant influences on the uniformity of the impeller inflow and the operation stability of the pump unit. When H = 204 mm, the data fluctuated greatly throughout the test process and the performance curves are slightly lower than the other two schemes. As the bell mouth height gradually decreases, the average pressure difference of each measuring point began to decrease, more homogeneous velocity distribution of impeller inflow can be ensured. The amplitude of blade passing frequency is obvious in the spectrum. While when (H) is more than 164 mm, the main frequency of pressure pulsations at three points fluctuates with the rotation of the impeller. When H decreases to 142 mm, pressure pulsations will be independent of the operating conditions and positions which contributes to the long-term stable operation of the pump unit.

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