Flow Measurement and Instrumentation最新文献

{"title":"Flow inferential measurement for proportional control valves by combining wavelet denoising and a dual-attention-based LSTM network","authors":"Yue Xu,&nbsp;Gang Yang,&nbsp;Baoren Li,&nbsp;Zhe Wu,&nbsp;Zhixin Zhao,&nbsp;Zhaozhuo Wang","doi":"10.1016/j.flowmeasinst.2024.102713","DOIUrl":"10.1016/j.flowmeasinst.2024.102713","url":null,"abstract":"<div><div>Accurate flow inferential measurement enables accurate real-time acquisition of the flow rate for hydraulic systems, effectively replacing conventional expensive and space-consuming flowmeters. However, the high nonlinearity and complexity of valve flow pose significant challenges for achieving accurate flow inferential measurements. To address this issue, this paper proposes a novel method based on wavelet denoising and a dual-attention-based long short-term memory (DA-LSTM) network. The DA-LSTM network is innovatively proposed to learn the flow mapping relationship, and incorporates the intervariable attention mechanism and the variable self-attention mechanism to enhance learning performance. Additionally, considering the presence of noise contamination in the measurement datasets, the wavelet thresholding denoising method is employed to increase the data quality. Furthermore, the real-time performance of the proposed method is also considered. The trained model is validated against test datasets, and is also compared to three other neural network-based flow estimation methods. The experimental results demonstrate that the proposed method accurately realizes the flow inferential measurement of the proportional control valve, with a mean square error percentage of 0.6494 %. This establishes a robust foundation for accurate flow control of proportional control valves.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"100 ","pages":"Article 102713"},"PeriodicalIF":2.3,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434166","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flow regime discrimination and methodology for calculating discharge in trapezoidal sluice gates","authors":"Wanshang Meng ,&nbsp;Lin Li ,&nbsp;Shuaijie Zhao ,&nbsp;Pengcheng Li","doi":"10.1016/j.flowmeasinst.2024.102710","DOIUrl":"10.1016/j.flowmeasinst.2024.102710","url":null,"abstract":"<div><div>This study introduces a novel trapezoidal sluice gate designed for water division and flow control within irrigation networks featuring canals with trapezoidal cross-sections. Experiments were conducted on trapezoidal channels with side slopes of <em>m</em> = 1.5, 1.75, and 2.0, using trapezoidal sluice gates at various gate openings, upstream water depths, and downstream depths. A total of 411 experimental sets were conducted to study methodologies for discerning between free flow and submerged flow conditions and for determining discharge rates. A method was proposed to distinguish flow patterns of trapezoidal sluice gates: submerged flow occurs when the downstream channel depth (<em>h</em>_<em>t</em>) exceeds the submergence threshold (<em>H</em>_<em>t</em><em>'</em>), while free flow is indicated when <em>h</em>_<em>t</em> is less than <em>H</em>_<em>t</em><em>'</em>. The formula for calculating <em>H</em>_<em>t</em><em>'</em> was derived, along with formulas for computing discharge rates under free flow and submerged flow conditions for trapezoidal sluice gates. The results revealed that the average relative errors of the formulas obtained through the partition method and the submergence coefficient correction method were 2.24 % and 5.37 %, respectively, demonstrating high accuracy and reliability. The scale effects on the flow regimes and formulas of discharge rates are also discussed. Findings from this study enhance the understanding of the hydraulic characteristics of trapezoidal sluice gates, which hold significant implications for the adoption and intelligent management of such gates in irrigation areas, offering a viable solution for selecting appropriate water gate configurations in irrigation systems.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"100 ","pages":"Article 102710"},"PeriodicalIF":2.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamics and experimental study of a novel proportional directional valve with displacement feedback groove controlled by high-speed switching valves","authors":"Ruihao Zhao ,&nbsp;Weifeng Chai ,&nbsp;Yang Zhang ,&nbsp;Xiang Yuan ,&nbsp;Zisheng Lian ,&nbsp;Huiting Shi","doi":"10.1016/j.flowmeasinst.2024.102711","DOIUrl":"10.1016/j.flowmeasinst.2024.102711","url":null,"abstract":"<div><div>The intelligence of hydraulic roof support is an important guarantee for unmanned fully mechanized coal mining face. The water-based medium proportional directional valve is the main factor that restricts the intelligent realization of support system. The support control valve needs to meet the 2/3 (two-position three-way) structure, taking into account both manual and electro-hydraulic control functions. The current water-based proportional valve does not satisfy the structural or functional demands of the support system. In this paper, a novel 2/3 water-based proportional directional valve is presented based on the displacement-flow feedback principle, which has two control modes: manual on-off control and electro-hydraulic proportional control. The proportional valve comprises two main valve spools and two pilot valves. The pilot valve is composed of a 2/3 on-off valve with manual operation capability and a high-speed switching valve group controlled by PWM (Pulse Width Modulation). The mathematical model of the proportional valve is established, and the experimental system is built to verify the characteristics of proportional valve. The proportional valve can meet the special functional requirements of the support. In the proportional control mode, the adjustment of spool displacement is regulated through the modulation of PWM duty ratio, resulting in effective control performance of the proportional valve. Furthermore, the discontinuous flow of the high-speed switching valve causes the pressure fluctuation of the pilot hydraulic bridge. Increasing the carrier frequency of PWM can reduce the amplitude of control chamber pressure and spool displacement fluctuation. The findings of the study can offer valuable insights for the continued advancement and enhancement of water-based proportional valves used in hydraulic roof support systems.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"100 ","pages":"Article 102711"},"PeriodicalIF":2.3,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing LSPIV accuracy in low-speed flows and heterogeneous seeding conditions using image gradient","authors":"Leandro Massó ,&nbsp;Antoine Patalano ,&nbsp;Carlos M. García ,&nbsp;Santiago A. Ochoa García ,&nbsp;Andrés Rodríguez","doi":"10.1016/j.flowmeasinst.2024.102706","DOIUrl":"10.1016/j.flowmeasinst.2024.102706","url":null,"abstract":"<div><div>Flow measurement in rivers and channels is crucial for water resource management and infrastructure planning, especially under the context of climate change. However, traditional methods like mechanical current meters and hydroacoustic instruments face limitations in terms of cost, intrusiveness, and accessibility. In recent years, image-based velocimetry techniques have emerged as promising alternatives due to their non-contact nature and cost-effectiveness. Nevertheless, persistent challenges remain, particularly concerning the uniform distribution of surface tracers necessary for precise measurements. These challenges are particularly pronounced in cases involving artificial seeding, where ensuring uniform distribution poses a significant obstacle. To address this issue, this study presents a novel methodology for filtering Large Scale Particle Image Velocimetry (LSPIV) data based on indicators of pixel intensity gradients. The methodology was evaluated across various field measurements under low flow conditions, encompassing a wide range of seeding characteristics. The evaluations demonstrated improvements in mean surface velocity profile estimation, showing reductions of up to 70 % in normalized root mean square error compared to not using filters. Additionally, the results were compared with filters typically employed by experienced LSPIV users, such as background subtraction and cross-correlation coefficient thresholds, showing improvements with the proposed filter. Implementation of the proposed strategy reduces the subjectivity in LSPIV implementation, particularly for users with limited knowledge of the technique, but also require minimal post-processing efforts. The methodology is anticipated to be integrated into existing software tools, thereby enhancing the accessibility of LSPIV for individuals with limited expertise in image velocimetry. Overall, this methodology facilitates cost-effective expansion of hydrological information availability, particularly in resource-constrained regions.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"100 ","pages":"Article 102706"},"PeriodicalIF":2.3,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The stage-discharge relationship of a sharp-crested triangular weir pierced by square orifices","authors":"Alessio Nicosia ,&nbsp;Maria Angela Serio ,&nbsp;Costanza Di Stefano ,&nbsp;Vito Ferro","doi":"10.1016/j.flowmeasinst.2024.102705","DOIUrl":"10.1016/j.flowmeasinst.2024.102705","url":null,"abstract":"<div><div>In this paper, the stage-discharge equation of a sharp-crested triangular weir pierced by square orifices is deduced applying both the classical approach of the discharge coefficient <em>C</em>_<em>d</em> and the Π- Theorem of dimensional analysis and the self-similarity theory. At first, using the experimental data by Zeinivand et al. (2024), the applicability of the expression of the discharge coefficient proposed by these authors was verified. Then, applying the dimensional analysis, a new stage-discharge relationship was deduced and calibrated using the available dataset. This theoretical equation is characterized by errors in the discharge estimate that are less than or equal to ±20 % for 98.9 % of cases and ≤ ±10 % for 87.8 % of cases, and the root mean square error is equal to 0.00071 m³ s⁻¹. In conclusion, the stage-discharge relationship deduced by dimensional analysis is characterized by an improvement in the performances in the discharge estimate and also has the advantage of working without the need of estimating the discharge coefficient.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"100 ","pages":"Article 102705"},"PeriodicalIF":2.3,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142357420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flow data forecasting for the junction flow using artificial neural network","authors":"Besir Sahin ,&nbsp;Cetin Canpolat ,&nbsp;Mehmet Bilgili","doi":"10.1016/j.flowmeasinst.2024.102703","DOIUrl":"10.1016/j.flowmeasinst.2024.102703","url":null,"abstract":"<div><div>The present study aims to predict the flow characteristics downstream of a cylinder, which is the result of junction flow using an Artificial Neural Network (ANN) algorithm. The training and test datasets were obtained through Particle Image Velocimetry (PIV) experiments. The experiments were conducted at Reynolds numbers Re = 1.5 x 10³ and 4 x 10³ based on the cylinder diameter (D) at dimensionless measurement heights (Z = h/D) of Z₁ = 0.06, Z₂ = 0.4, Z₃ = 0.8, and Z₄ = 1.6 respectively. While the X- and Y-coordinate and dimensionless measurement location (Z) variables are employed as inputs to the ANN model, the output variables are vorticity ⟨ω⟩, streamwise velocity ⟨u⟩, and transverse velocity ⟨v⟩, which are derived from the time-averaged flow data. Modeling flow characteristics with easily obtainable independent variables without flow and physical properties was considered. Three various training algorithms such as Levenberg Marquardt (LM), Resilient Backpropagation (RP), and Scaled Conjugate Gradient (SCG) were employed to assess and compare their prediction performance. The results indicate that the LM learning algorithm outperforms the RP and SCG algorithms, especially at low Reynolds (Re) numbers. The ANN model, trained with the LM algorithm, exhibits significant success, achieving R = 0.9816 correlation coefficient (R), MAE = 2.4250 m/s Mean Absolute Error (MAE), and RMSE = 3.3541 m/s Root Mean Square Error (RMSE) for streamwise velocity ⟨u⟩ data. Notably, the LM algorithm for the testing process demonstrates the best predictions at Re = 1.5x10³, yielding R = 0.9779, MAE = 2.7417 m/s, and RMSE = 3.7493 m/s. The ANN-LM model's patterns closely align with experimental results, affirming its accuracy, which proves that the prediction of time-averaged velocity data solely based on spatial coordinates as input can be achieved successfully.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"100 ","pages":"Article 102703"},"PeriodicalIF":2.3,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Performance compensation model of turbine flowmeter under vibration conditions","authors":"Suna Guo ,&nbsp;Lei Yang ,&nbsp;Qianhui Wang ,&nbsp;Xiangjie Kong ,&nbsp;Fan Wang","doi":"10.1016/j.flowmeasinst.2024.102704","DOIUrl":"10.1016/j.flowmeasinst.2024.102704","url":null,"abstract":"<div><div>Vibration conditions will affect the performance of the turbine flowmeters, resulting in inaccurate or unstable measurement results. A DN10 turbine flowmeter is taken as an example to study the influence rule of vibration conditions on the turbine flowmeter performance. An experimental facility is built to simulate the vibration conditions with amplitude ranging from 35 mm to 90 mm and frequency ranging from 0 Hz to 4 Hz. A simulation method for simulating a turbine flowmeter under vibration conditions based on a dynamic coordinate system and 6DOF (Six Degrees of Freedom) is proposed. Based on the experiments and CFD (Computational Fluid Dynamics) simulation, the results show that the average meter factor of the turbine flowmeter under vibration conditions is larger than that under non-vibration conditions. The average meter factor increases with vibration amplitude and vibration frequency. The maximum relative error of the measured flow rate is 9.73 %. To reduce the measurement error, a performance compensation model of the turbine flowmeter applied to vibration conditions is proposed. The meter factor increment is taken as the dependent variable, and the frequency, amplitude, and flow rate are taken as independent variables. The results show that compared to the original model, the relative error of the turbine flowmeter with the compensation model shows an average reduction of 76.61 %.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"100 ","pages":"Article 102704"},"PeriodicalIF":2.3,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pipeline impact force observation-based intelligent measurement method for liquid flow","authors":"Qiguang Li ,&nbsp;Xiru Zheng ,&nbsp;Yu He ,&nbsp;Fangmin Xu ,&nbsp;Bingji Zeng ,&nbsp;Bofang Duan ,&nbsp;Yongkun Kuang ,&nbsp;Zhihua Chen","doi":"10.1016/j.flowmeasinst.2024.102700","DOIUrl":"10.1016/j.flowmeasinst.2024.102700","url":null,"abstract":"<div><div>This paper proposes an innovative measurement method that uses the impact force generated when the liquid flows through the pipe as an observation indicator, and successfully establishes a non-linear mapping relationship between the impact force sequence and the weight of the flowing liquid by training and learning the collected impact force sequence through the CLCD (CNN-LSTM-CNN-Double) network architecture. In response to the challenges such as the prevalent interference factors and inconsistent flow time lengths in the collected data, this paper introduces a new weight ratio algorithm, WRP (Weight-Ratio-Process), which effectively improves the robustness and accuracy of data processing. The experimental results show that the effective detection rate of the method reaches 90 % when the weighing error is set to ±5<em>g</em> on the constructed fluid impact force test platform. When the error range is relaxed to ±15<em>g</em>, the effective detection rate is increased to 98 %. This achievement demonstrates the broad application potential and practical value of the method in the field of fluid transport measurement.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"100 ","pages":"Article 102700"},"PeriodicalIF":2.3,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142422598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-invasive mass flow and local heat transfer coefficient measurements in pulsating heat pipes","authors":"Fernando Seiti Misina,&nbsp;Mateus Henrique Corrêa,&nbsp;Cristiano Bigonha Tibiriçá","doi":"10.1016/j.flowmeasinst.2024.102701","DOIUrl":"10.1016/j.flowmeasinst.2024.102701","url":null,"abstract":"<div><div>A single loop Pulsating Heating Pipe (PHP) experimental setup was developed for non-invasive measurement of the local heat transfer coefficient and the mass flow along the PHP evaporator. These measurements are valuable to validate modeling tools used in the design of PHP. A two-step differential heat input method was used for measurement of mass flow and the results were compared with the optical and theoretical results. The conditions tested in the PHP were 50, 60 and 70% filling ratio, R134a as working fluid, internal diameter of 2 mm, saturation temperature of between 30 to 40 °C, inclination angles from 30 to 90° (vertical bottom heat mode) and heat loads on the evaporator from 10 up to 68 W. The results indicate a high performance in heat transfer of the PHP, with minimum internal thermal resistance values close to 0.008 K/W as well as local heat transfer coefficients greater than 10 kW/m²K for observed values of mass velocities between 60 and 140 kg/m²s. The results were compared with correlations from the literature and these were able to predict the results with a 20% average error margin, suggesting many similarities with convective boiling mechanisms.</div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"100 ","pages":"Article 102701"},"PeriodicalIF":2.3,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ECT image reconstruction algorithm based on Res-SEUnet","authors":"Xiaozhao Li ,&nbsp;Jing Liu ,&nbsp;Yuanyuan Li ,&nbsp;Guoqiang Liu ,&nbsp;Jiacheng Wei ,&nbsp;Zhiguang Lyu","doi":"10.1016/j.flowmeasinst.2024.102688","DOIUrl":"10.1016/j.flowmeasinst.2024.102688","url":null,"abstract":"<div><div>A Res-SEUnet algorithm for ECT image reconstruction is proposed to address the problem of artifacts and blurring of media boundaries in ECT (capacitance tomography) reconstructed images of high-density and small-size media. A convolutional neural network is used to extract the detail features of the LBP image and recover the edge details of the ECT inverted image. Simulation experiments are performed on various complex multi-media datasets built in Comsol and Matlab. The results of the test set show that the Res-SEUnet based ECT reconstruction algorithm can by better reconstruction results on various complex multimedia datasets.<span><figure><span><img><ol><li><span><span>Download: <span>Download high-res image (140KB)</span></span></span></li><li><span><span>Download: <span>Download full-size image</span></span></span></li></ol></span></figure></span></div></div>","PeriodicalId":50440,"journal":{"name":"Flow Measurement and Instrumentation","volume":"100 ","pages":"Article 102688"},"PeriodicalIF":2.3,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142323241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}