Self-priming Pump Research Articles

Development and Outlook for Self-priming Pumps

Background: Self-priming pumps are a type of general mechanical equipment that is widely used in the petroleum, chemical, electric power, metallurgy, mining, shipbuilding, light industry, agriculture, civil defense, and other departments, and they play an important role in the global economy. The pump system is the most common piece of equipment that consumes the most electricity, and reducing the energy consumption of the pump will save a significant amount of energy. Objective: For the benefit of scholars and engineers, this paper summarizes the most recent research on self-priming pumps, analyzes their solutions to the problem of reducing energy consumption, and discusses their advantages and disadvantages. Methods: The typical self-priming pump patents are outlined below based on the many functions of the improved self-priming pump structure, including pump body protection, high efficiency, and energy savings, ease of movement, and improved seal. The current self-priming pump patents are used to examine the development trend for these pumps. Results: The fundamental issues with self-priming pumps are outlined and studied through comparisons of various types and functions, and a future course for their development is suggested. Conclusion: The development of self-priming pump technology benefits from the improvement of self-priming pump structure. A self-priming pump with a straightforward design, automation, high efficiency, and energy conservation has a promising future.

Study on the integrated self-priming process of a vehicle-mounted self-priming pump

In order to explore the self-priming characteristics of the self-priming pump at the mobile pump truck, this paper established a complete three-dimensional circulatory piping system including the self-priming pump, tank, valves, inlet pipe and outlet pipe. The UDF(User Defined Functions) was used to realize the acceleration-constant speed operation process of the impeller, thus reflecting the actual changing state of the rotational speed. Based on the VOF(Volume Of Fluid) multiphase flow model and the Realizable k-ε turbulence model, a coupled numerical calculation of unsteady incompressible viscous flow was conducted for its self-priming process. The results show that the self-priming process of the pump can be roughly divided into four stages: the rapid suction stage, the shock exhaust stage, the rapid exhaust period and the pump residual gas discharge stage. The proportion of each stage in the total self-priming time showed an increasing trend. During the rapid suction stage, the water level in the vertical section of the inlet pipe showed a slow and then fast-rising pattern. During the shock exhaust stage, the average gas-phase volume fraction in the volute is lower than that of the impeller, and the gas content at the volute outlet is lower than that of the impeller inlet. The region at the inlet and outer edge of the impeller consistently experience significant energy losses.

Progress on Numerical Simulation of Gas-Liquid Two-Phase Flow in Self-Priming Pump

The fundamentals of the design and operation of self-priming pumps, as indispensable equipment in industry, have been the focus of research in the field of fluid mechanics. This paper begins with a comprehensive background on self-priming pumps and gas-liquid two-phase flow, and it outlines recent advances in the field. Self-priming pumps within the gas-liquid two-phase flow state and the spatial and temporal evolution of the transient characteristics of self-priming pumps determine the self-priming pump self-absorption performance. Through mastery of the self-absorption mechanism, high-performance self-absorption pump products can be formed to provide theoretical support for the development of products. In current research, numerical simulation has become an important tool for analyzing and predicting the behavior of gas-liquid two-phase flow in self-priming pumps. This paper reviews existing numerical models of gas-liquid two-phase flow and categorizes them. Reviewing these models not only provides us with a comprehensive understanding of the existing research but also offers possible directions for future research. The complexity of gas–liquid interactions and their impact on pump performance is analyzed. Through these detailed discussions, we are able to identify the challenges in the simulation process and summarize what has been achieved. In order to further improve the accuracy and reliability of simulations, this paper introduces the latest simulation techniques and research methodologies, which provide new perspectives for a deeper understanding of gas-liquid two-phase flow. In addition, this paper investigates a variety of factors which affect the operating efficiency of self-priming pumps, including the design parameters, fluid properties, and operating conditions. Comprehensive consideration of these factors is crucial for optimizing pump performance. Finally, this paper summarizes the current research results and identifies the main findings and deficiencies. Based on this, the need to improve the accuracy of numerical simulations and to study the design parameters in depth to improve pump performance is emphasized.

Parallel quantized dual-level fully connected classifier for bearing fault diagnosis

The diagnosis of bearing failures in rotating mechanical equipment is critical to productivity and the quality of the manufacturing process. Traditional methods generally suffer from high human factor interference and low accuracy. This paper proposes a parallel quantized dual-level fully connected classifier (PQDFCC) for fault identification of bearings. The PQDFCC has two parts. The first part of the PQDFCC contains two types of data pre-processing. The first data pre-processing method is calculating absolute values and sorting the acquired raw signals. The second method of data pre-processing is quantizing the raw data. The second part of PQDFCC is a dual-level fully connected classifier. The first-level fully connected classifier performs the first-level fault classification on the quantized and sorted data; then, the output probability of the first-level classifier is considered as the input of the second-level fully connected classifier; finally, the second-level fully connected classifier provides the classification results of bearing faults. The data pre-processing part of the PQDFCC is a simple calculation that can simplify and not lose fault information; the dual-level fully connected classifier can fully exploit the hidden features of the data with high accuracy. The proposed PQDFCC is tested in the bearing failure, axial piston hydraulic pump, and self-priming centrifugal pump datasets; the experimental results show that the PQDFCC achieves 100% fault diagnosis accuracy.

Study on performance and structure optimization of self-priming pump based on response surface method

ABSTRACT This paper aims to improve the performance of a self-priming pump by optimizing blade geometry parameters, with the head and efficiency as the targeted objectives. Based on the Response Surface Methodology (RSM), the Computational Fluid Dynamics (CFD) were conducted to investigate the pressure distribution characteristics inside the pump chamber and the variations in pump performance parameters. By analyzing the internal pressure field of the pump, it is concluded that adjusting the blade curvature radius and the outlet angle can change the area and uniformity of the low-pressure zones within the fluid to improve the pump performance. The results show that the fitted regression equations indicate that the blade curvature radius and the blade outlet angle have a significant impact on pump performance, while the blade inlet angle has a relatively minor effect. When the outlet angle β 2 = 60 ∘ , the change of the inlet angle β 1 and the curvature radius R has basically no impact on the efficiency. The self-priming pump achieves its optimum performance when β 1 = 50.8 ∘ , β 2 = 52 ∘ and R = 84.9 mm. Compared to the original model, the optimized model’s head increases by 7.12%, H = 34.12 m; and the efficiency improves by 3.40%, η = 63.8.

Multifactor response-based optimization for enhancing cavitation performance of short injection self-priming pumps

As the heart of the water supply systems, the energy conversion efficiency of the self-priming pumps with built-in injection system under overload conditions is extremely affected by cavitation problems. This study focuses on a typical short-type injection self-priming pump devoted to improve the pump performance, especially to solve the cavitation problem under overload conditions. Through a two-factor, five-level orthogonal test that combines numerical simulation and experimental validation, the influence of key structural parameters within the ejector on cavitation performance and energy characteristics are analyzed. The results demonstrate the high level accuracy of numerical simulation, as indicated by the consistency and small error between the numerical results and the experimental results for head, efficiency, and power under full flow conditions. Regression analysis based on the orthogonal test results reveals significant correlations between the hydraulic performance of the pump and the nozzle throat diameter and nozzle outlet diameter. Under overload conditions, the high-speed jet generated by the injector induces a negative pressure at the effuser and nozzle, leading to cavitation at the effuser throat and nozzle outlet. Employing appropriate structural parameters, particularly the effuser throat diameter and nozzle outlet diameter, proves effective in increasing the operating flow range. This in turn improves the energy characteristics of the entire hydraulic system. The optimal combination identified for the ejector's structural parameters in this study is a nozzle outlet diameter of 8.2 mm and a throat diameter of 18 mm. This provides theoretical insights for the optimal design of short-type jet self-priming pumps, holding practical significance in engineering applications.

Bi-level binary coded fully connected classifier based on residual network 50 with bottom and deep level features for bearing fault diagnosis

Among the existing bearing fault diagnosis algorithms, the diagnosis time of algorithms with high accuracy is relatively long, and the accuracy of some lightweight methods is low compared to other methods. This work proposes a bi-level binary coded fully connected classifier based on residual network 50 with bottom and deep level features (Bi-BUR) for bearing fault diagnosis, enabling both high accuracy and high-speed characteristics. The Bi-BUR has two levels of classifiers. The first level begins with a signal-to-picture method based on integer binary coding to convert the bearing fault signals into binary pictures; then, the first classification of the converted pictures is performed by the underlying feature extraction-residual network 50, which can extract both the underlying and the advanced features. The second level performs modal decomposition of the signals that are not classified successfully in the first level, performs the second classification with a fully connected classifier inserted into the underlying feature extraction module, and exports the final classification results after weighted summation of the results of each type. The Bi-BUR is simulated on the Case Western Reserve University motor, the self-priming centrifugal pump, and the axial piston hydraulic pump bearing failure datasets. All three experiments achieved more than 95% accuracy in the first level of categorization and 100% diagnosis after the second level of categorization. And the Bi-BUR is faster than other high-accuracy methods.

Pressure Pulsation Characteristics of a Self-Priming Pump under Typical Operating Conditions

To investigate the pressure pulsation characteristics of self-priming pumps under different flow conditions, Fluent 19.2 software was used to numerically calculate the internal flow inside a self-priming pump by means of the RNG k-ε model. The pressure pulsation characteristics, as well as the standard deviation in the volute and impeller domains, were analyzed under different flow conditions. As a result, under rated- and high-flow conditions, the monitoring points in the volute channel have obvious periodic patterns, and the peak pressure pulsations all occur in the octave band of the blade frequency. The pressure pulsation amplitude is larger under the high-flow condition than in the other two conditions. The monitoring points L1 and L5 on the impeller channel centerline are located near the impeller’s inlet and outlet, respectively, so the pressure pulsations are larger than other monitoring points.

A Numerical Study on the Effect of the Backflow Hole Position on the Performances of a Self-Priming Pump

A Numerical Study on the Effect of the Backflow Hole Position on the Performances of a Self-Priming Pump

Technical Summary of Tunnel Mud Pumping Treatment and a Method of Pressure Reduction by Water Release

With the rapid development of China’s economy and the increasing demand for resources in various regions, the speed and volume of railway operations are increasing, and diseases such as mud pumping and mud pumping in railway tunnels are becoming more and more serious. Although various construction units have taken diverse measures to rectify the diseases, they often have poor results, repeated rectification, and repeated failure, which consumes a lot of financial and material resources but cannot cure the mud pumping disease, allowing the disease to seriously endanger the driving safety of the line. This paper is based on the long-established loess tunnel base mud pumping disease treatment project in the Lanzhou Railway Bureau of the China Railway. Firstly, the influence of train load, structural fracture, and tunnel drainage systems on the mechanism of disease is expounded. Then, the key technologies and processes of the commonly used disease treatment schemes are sorted out and summarized, and the advantages and disadvantages of the commonly used schemes and the additional drainage tunnel and self-priming pump technology proposed in this paper are compared in detail. The analysis shows that the universally used treatment technology applies to the treatment of local mud pumping disease in the tunnel, and there are shortcomings in these measures for the long-established tunnel. The drainage tunnel and self-priming pump technology can reduce and maintain the small content of groundwater in the surrounding rock of the tunnel basement and can resolve the mud pumping disease of the loess tunnel basement from the root. At present, this technology has been applied to many tunnel projects and has achieved certain comprehensive benefits, which could provide a reference for similar projects.

Engineered MoSe2-rGO composite for efficient recovery of viscous crude oil spills

High-performance photothermal materials capable of harnessing the entire solar spectrum have garnered significant interest in developing solar-heating sorbents for the effective recovery of viscous oil. Herein, we developed narrow-bandgap MoSe2-loaded reduced graphene oxide (MoSe2-rGO) nanocomposite with efficient solar utilization. MoSe2-rGO with synergistically-enhanced light absorption and photothermal conversion, was first employed for fabricating melamine sponge (MS)-based sorbent (PMGP/MS sorbent) via a facile dip-coating method. The sorbent showed excellent solar-heating capability, reaching a surface temperature of 78 °C in 100 s under 1.0 sun. The sorbent proved effective in recovering highly viscous oil via solar-motivated viscosity-reduction of oil. The sorption rate for viscous crude oil increased 10.6 times under 1.0 sun compared with no sunlight illumination, and the sorption saturation reached around 55.6 g/g within 750 s. Moreover, continuous sorption was achieved under a self-priming pump based on the reduced viscosity and increased fluidity, with capacity of 1.1 g/cm2 at 650 s under 1.0 sun.

Optimal design of impeller for self-priming pump based on orthogonal method

In order to improve the efficiency of the self-priming pump in the outdoor emergency rescue mobile pump truck, this paper took the key energy conversion component-impeller as the target and used the orthogonal experimental design method to optimize its hydraulic performance. Firstly the numerical calculations were compared with the experimental results to confirm the reliability of the calculation method. Then, L9 (34) orthogonal design was applied to investigate the influence of the impeller diameter, the blade outlet width, the blade wrap angle and the number of blades on the hydraulic performance of the self-priming pump. Through range analysis, the order of influence of each influencing factor on the head and efficiency of the self-priming pump was determined, and finally obtained the optimal parameter combination scheme. The results show that the optimized self-priming pump exceeds the head of the prototype pump at all flow conditions, and the efficiency curve at high flow conditions is significantly improved and has a wide high efficiency zone.

Steady and Unsteady Flow Characteristics inside Short Jet Self-Priming Pump

Due to their great efficiency and minimal loss, self-priming jet pumps are frequently employed in a variety of sectors for sustainable development. A short jet self-priming pump’s steady and unsteady flow characteristics are investigated numerically in this study using a standard k-ε turbulence model. The precision and dependability of the numerical calculations used in this work are demonstrated by the less than 2% difference between the pump performance data from the numerical calculation and the external characteristics test results for each flow condition. It was found that due to the perpendicularity of the nozzle axis to the impeller axis, the high-flow velocity zone in the nozzle gradually deviates to the side away from the impeller under high-flow conditions. Backflow is generated on the side close to the impeller, where eccentric vortices are created. As time progresses, the asymmetry of the low-pressure zone within the impeller becomes more pronounced under high-flow conditions, and the fluid is unable to form a stable vortex structure at a specific location. This is an important cause of impeller vibration and noise. The nonlinear vibration at the impeller inlet is less periodic, while the increase in flow rate can make the nonlinear vibration generated within the impeller more regular and stable. This reflects the fact that the fluid flow at small flow rates is more likely to be affected by the blade configuration and the shape of the flow channel, which leads to fluid instability and discontinuity. For various flow rates, the main frequency of the pressure pulsation is higher at the impeller intake (W1) than it is in the impeller channel (W2~7). Additionally, the pressure pulsation is more frequent before 10 times the rotational frequency, with no significant regularity. This suggests that the impeller and injector rear chamber dynamic and static interference impacts may have some bearing on the pressure pulsation. The pressure pulsation coefficients (W2~7) in the impeller at different flow rates show an exponentially decreasing trend with the increase of multiples of five in the rotation frequency. The equations for the relationship between CP and 5NF were obtained, respectively: CP-Q1 = 0.07044 × exp(−0.2372NF), CP-Q3 = 0.06776 × exp(−0.2564 NF), CP-Q5 = 0.07005 × exp(−0.2884 NF). The findings of this study contribute to understanding the flow inhomogeneities inside the pump as well as the analysis of the internal pump vibration, enhancing the jet pump’s efficiency and lifespan.

Gas-liquid flow patterns visualization in a self-priming centrifugal pump

The self-priming pumps are ubiquitous in gas-liquid mixtures lift and transportation areas. The fast self-priming time is a vital evaluation index for a self-priming pump. However, the bubble movement path and the bubble size distribution characteristics during the self-priming process are still an open issue. This paper aims to obtain the gas-liquid flow patterns inside a centrifugal pump during the self-priming process and evaluate the effect of the rotational speed and the position of the back-flow hole on the self-priming time through experiments. A centrifugal pump with a double-blade was designed as a visualization prototype. The high-speed photography technology was used to capture the bubble motion and size in the pump during the self-priming process. The bubble image processing method was used to identify the bubble size distribution in the diffuser during the self-priming process. The bubble number and size distribution images were presented to understand the influence of the rotational speed and the position of the back-flow hole. The higher rotational speed accelerates the gas-liquid mixing rate and shortens the self-priming time. However, there is a limited value of the self-priming time as the speed goes up to a certain high level. Moreover, the position of the back-flow hole slightly affects the self-priming time.

A Visualized Experimental Study on the Influence of Reflux Hole on the Double Blades Self-Priming Pump Performance

The self-priming pump is a kind of centrifugal pump product with self-priming function, and the structural parameters of its reflux hole determine the performance. In order to reveal the mechanism of the self-priming process, we summarized the influence of structure parameters of the reflux hole on the performance of the self-priming pump. In this study, the transparent experimental pump was designed and manufactured, and a visual test bench was built. The gas–liquid two-phase flow pattern during the self-priming process with different reflux hole structure parameters was captured by high-speed camera. Results showed that: (1) the reflux hole of the self-priming pump affected the self-priming performance of the pump by affecting the backflow rate of the gas and liquid phases during the self-priming process. (2) Due to the uneven distribution of liquid velocity in the pump, the position of reflux hole had an obvious impact on the duration of self-priming middle stage, and the shortest duration was 13 s when φ = +15° and the longest duration was 45 s when φ = −30°. (3) The diameter of reflux hole had a very significant impact on the duration of the self-priming middle stage, and the shortest duration was 17 s when d = 10 mm and the longest duration was 94 s when d = 0 mm.

Research on bearing fault diagnosis method based on transformer neural network

The Attention mechanism (AM) has been widely used for fault diagnosis and identifying the health of industrial equipment. Existing research has only used AM in combination with deep networks, or to replace certain components of these deep networks. This reliance on deep networks severely limits the feature extraction capability of AM. In this paper, a bearing fault diagnosis method is proposed based on a signal Transformer neural network (SiT) with pure AM. First, the raw one-dimensional vibration time-series signal is segmented and a new segmented learning strategy is introduced. Second, linear encoding and position encoding are performed on the segmented subsequences. Finally, the encoded subsequence is fed to the Transformer for feature extraction to achieve fault identification. The validity of the proposed method is verified using the Case Western Reserve University dataset and the self-priming centrifugal pump bearing dataset. Compared with other existing methods, the proposed method still achieves the highest average diagnostic accuracy without any data preprocessing. The results demonstrate that the proposed SiT based on pure AM can extract features and identify faults from the raw vibration signal, and has superior diagnostic performance.

Influence of Bionic Circular Groove Blade Surface on Wear Performance

In order to improve the anti-wear performance of a double-vane self-priming centrifugal pump during two-phase flow transfer, the construction of a streamline groove structure at the outlet end of the suction side of the vane, based on the bionic principle, is proposed. Different pump characteristics are analysed to investigate the effect of different bionic groove spacing on the resistance to particle wear and the mechanism of improvement of the bionic grooves. The results show that the effect of the bionic blades on the hydraulic characteristics of the pump is within the allowable error (±1.4%). The circular groove structure with different spacing produces a difference in the pressure distribution on the blade. At the same particle concentration, with the increase in the groove spacing distance, the average wear of the blades first decreases and then increases; the average wear rate at the spacing of 7 mm is the smallest. At a particle concentration of 90 kg/m3, the average wear rate at a groove spacing of 7 mm is ~0.63 × 10−4 kg/s∙m2, and the wear area is mainly found in the middle of the blade. The reason why the bionic blade improves the anti-wear performance of the pump is due to the reverse vortex zone in the groove, which changes the particle trajectory and collision frequency. The bionic grooves with a diameter of 2 mm and a spacing of 7 mm significantly reduce the average wear rate of the pump at different particle concentrations, while maintaining hydraulic performance.

Intelligent fault diagnosis of machine under noisy environment using ensemble orthogonal contractive auto-encoder

Despite significant advances in auto-encoder (AE) based intelligent fault diagnosis recently, their assumption of high-quality sensor data is unrealistic due to noisy environment. Aiming at such problem, this work proposes a novel ensemble orthogonal contractive auto-encoder (EOCA) method to improve diagnosis accuracy. By designing a new cost function including contractive term and orthogonal constrain, OCA can learn robust and non-redundant features from noisy input. To make fault patterns separable, fisher discriminant analysis is cascaded with OCA for mapping these features into a new coordinate space with maximum class separability. Considering the limitation of a single model, sixteen different OCAs with complementary activation functions as well as a new ensemble strategy based on expert model are developed to produce a stable diagnosis result. Additionally, to prove the effectiveness, error bound of EOCA is analyzed and theoretical basis is found for supporting OCA design. EOCA is verified on three cases including three-phase flow facility, gear box and self-priming centrifugal pump. Experiments are conducted by introducing various strength of white Gaussian noise. Results show that EOCA is better than single OCA, canonical AE, sparse AE, denoising AE and several advanced ensemble methods under strong noise.

Flow Characteristic Analysis of the Self-Priming Pump Based on the Population Balance Model

Self-priming pumps, as important two-phase fluid machinery, are widely used in disaster relief and emergency fields. The flow characteristics of the air–liquid two-phase fluid play an essential role in the self-priming pump performance. However, the traditional simulation employed the single-diameter bubbles for analysis, which cannot reflect the internal flow field characteristics. Therefore, in this article, the Population Balance Model (PBM) is employed, which divides the bubble into different diameter groups, and the collision and coalescence between the bubble are considered in the calculation to investigate the influence of different air voids and flow conditions on the performance self-priming centrifugal pumps. The result shows that the frequency of bubble coalescence at the shroud is higher, which is conducive to the formation of large-sized bubbles. Meanwhile, the increment of flow conditions has a significant effect on reducing the pressure pulsation of the gas–liquid two-phase flow, while the improvement of the air voids not only destroys the instability and asymmetry of the internal flow of the two-phase flow but also aggravates the amplitude of pressure pulsation, increasing the surface loading of the blade and radial force. Therefore, this article can provide a certain theoretical reference for the study of air–liquid two-phase flow characteristics of self-priming centrifugal pumps.

Effect of Bionic Nonsmooth Surface Vane on the Antiwear Characteristics of Double-Vane Pump.

In order to improve the antiwear characteristics of the double-vane self-priming pump, the surface structure of the Scapharca subcrenata was extracted and reconstructed according to bionic principles. Three types of nonsmooth surface models were established at the outlet end of the suction surface of the vanes, which is the most severely worn in the double-vane pump. The external characteristics, pressure field distribution, wear area distribution, and wear degree of the volute and vanes at different concentrations of nonsmooth vane structure were investigated by numerical simulation to reveal the mechanism of the nonsmooth surface structure of the wear characteristics of the vanes. The results show that the head and efficiency of pumps with four different vanes decrease and the average wear rate increases as the particle concentration increases. The different vane structures have a very small effect on the wear resistance of the volute, but a larger effect on vane wear. The circular nonsmooth surface structure, which reduces the low pressure area of the inlet section of the impeller while ensuring a smaller drop in head and efficiency, produces the best antiwear effect and improves the antiwear performance of the double-vane pump.