Waveform Prediction of Blade Tip‐Timing Sensor Based on Kriging Model and Static Calibration Data

Zhang, Liang; Wang, Qidi; Li, Xin

doi:10.1155/2023/9632212

Cited by 2 publications

(1 citation statement)

References 22 publications

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“…Chu Shupo [6] explored the effect of the volute structure on the performance of the fish pump, studied the characteristics of the pump's internal flow field, and analyzed the effect of the control law of the vacuum outlet form on its performance. Ding Ziyang [7] and Zhang Liang [8] analyzed the pressure and velocity distribution inside the fish as well as the trajectory of the trace in the pump. Numerous scholars have also conducted extensive research on the analysis of the hydrodynamic characteristics of structures.…”

Section: Introductionmentioning

confidence: 99%

Hydrodynamic Characteristic Analysis and NSGA-II Optimization of a Vacuum Fish Pump

Hong

Zhu

Zhang

et al. 2023

JMSE

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The fish pump is an important piece of power equipment for aquaculture, especially for deep-sea engineering vessels and cage culture. Fish pump research focuses on reducing fish body damage, improving survival rates, and increasing fish lifting efficiency. The research object in this paper is a new type of vacuum fish pump, with the aim of improving the hydraulic performance of the vacuum fish pump and reducing the damage to the fish body. The dependent variables include the dynamic change process of the flow state and flow field under diachronic conditions, the fluid simulation analysis of the vacuum pump body and the flow channel structure, the inlet flow rate of the fish pump, the negative pressure of the pipeline, and the impact force of the water flow on the inner wall of the tank. The independent variables include the operating conditions of the pump body and the fish pump. The Latin hypercube sampling method is used to extract 167 sets of calculation models for the independent variables, and multi-objective optimization is performed based on the NSGA-II algorithm for the hydrodynamic performance of the fish pump. On the basis of ensuring the fish body damage rate, the structural parameters of the vacuum fish pump with the optimal hydrodynamic performance under 167 sets of parameter values were obtained. The optimized parameters were then entered into the solver again, and the results showed that, in the optimal structural parameters under certain conditions, the direction of the incident water flow in the vacuum fish pump tank is close to the upper end of the tank body, which will reduce the speed of the fish-water mixed flow when entering the tank, thereby reducing the collision damage to the fish body. Currently, the water flow velocity at the water inlet is about 2.5 m/s, and the negative pressure value distribution gradient between the tank body and the water inlet pipeline is quite consistent, which can achieve good fish suction and fish lifting effects.

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Section: Introductionmentioning

confidence: 99%

Hydrodynamic Characteristic Analysis and NSGA-II Optimization of a Vacuum Fish Pump

Hong

Zhu

Zhang

et al. 2023

JMSE

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Prediction of Blade Tip Timing Sensor Waveforms Based on Radial Basis Function Neural Network

Zhang,

Chen,

Xia

et al. 2023

Applied Sciences

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As the existing Blade Tip Timing (BTT) vibration measurement methods have serious under-sampling problems, where the blade resonance frequency is usually higher than the sampling frequency of the data acquisition system of the BTT method, resulting in large errors in the identification of blade vibration parameters, new solutions are needed to extend the capability of BTT to nonlinear and multimodal vibration analysis. Therefore, it is the current research direction to pursue new and more accurate measurement and signal processing methods. By analyzing the waveform data from the BTT sensor and using it for vibration analysis, it significantly extends the BTT database. To avoid the current problems of under-sampling and low recognition accuracy, this paper conducts a study on the recognition of rotating blade vibration parameters based on the Radial Basis Function (RBF) model by establishing a RBF neural network prediction model to analyze the static calibration experimental data and predict the waveform of the BTT sensor, and comparing the prediction curves of various models. As the results show, for the RBF model, the prediction accuracy is closely related to the source data of the sampling point data, when the source data predicted by the RBF model is close to the center of the samples, the prediction accuracy is high, meanwhile, the prediction accuracy decreases as it is far away from the center of these data. At the same time, the number of samples is too small to affect the prediction ability of the RBF model. By using this method, more waveforms under the Blade Tip Clearance (BTC) can be predicted with the available sample point data, and the errors in the experimental measurement process can be corrected.

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Waveform Prediction of Blade Tip‐Timing Sensor Based on Kriging Model and Static Calibration Data

Cited by 2 publications

References 22 publications

Hydrodynamic Characteristic Analysis and NSGA-II Optimization of a Vacuum Fish Pump

Hydrodynamic Characteristic Analysis and NSGA-II Optimization of a Vacuum Fish Pump

Prediction of Blade Tip Timing Sensor Waveforms Based on Radial Basis Function Neural Network

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