Model of the Floating Bearing Bushing Movement in an External Gear Pump and the Relation to Its Parameterization

This article presents the modeling, simulation and experimental validation of the movement of the floating bearing bushing in an external gear pump. As a starting point, a complete pump parameterization was carried out through standard tests, and these parameters were used in a first bond graph model in order to simulate the gear pump behavior. This model was experimentally validated under working conditions in field tests. Then, a sophisticated bond graph model of the movement of the floating bushing was developed from the equations that define its lubrication. Finally, as a result, both models were merged by integrating the dynamics of the floating bushing bearing with the variation of the characteristic parameters (loss coefficients). Finally, the final model was experimentally validated both in laboratory and field tests by assembling the pump in a drilling machine to drive the auxiliary movements. The novelty of this article is the conception and construction of a simple and experimentally validated tool for the study of a gear pump, which relates its macroscopic behavior as a black box (defined by the loss coefficients) to the internal changes of the unit (defined by its internal lubrication).

FMECA and MFCC-Based Early Wear Detection in Gear Pumps in Cost-Aware Monitoring Systems

Gear pump failures in industrial settings are common due to their exposure to uneven high-pressure outputs within short time periods of machine operation and uncertainty. Improving the field and line clam are considered as the solutions for these failures, yet they are quite insufficient for optimal reliability. This research, therefore, suggests a method for early wear detection in gear pumps following an extensive failure modes, effects, and criticality analysis (FMECA) of an AP3.5/100 external gear pump manufactured by BESCO. To replicate this condition, fine particles of iron oxide (Fe2O3) were mixed with the experimental fluid, and the resulting vibration data were collected, processed, and exploited for wear detection. The intelligent wear detection process was explored using various machine learning algorithms following a mel-frequency cepstral coefficient (MFCC)-based discriminative feature extraction process. Among these algorithms, extensive performance evaluation reveals that the random forest classifier returned the highest test accuracy of 95.17%, while the k-nearest neighbour was the most cost efficient following cross validations. This study is expected to contribute to improved evaluations of gear pump failure diagnosis and prognostics.

Electro-Hydraulic Drive of the Variable Ratio Lifting Device under Active Load

Hydraulic systems fed by fixed displacement pumps driven by frequency-controlled electric motors can replace conventional throttling systems due to their ability to control the speed of hydraulic cylinders regardless of the value and direction of the load. These systems can improve the energy efficiency of the drive or even provide the possibility of energy recuperation during lowering. This paper presents experimental studies of the new drive system with volumetric control of the speed of the lifted/lowered payload using the example of a scissor lift. The system uses a reversible gear pump driven by an asynchronous motor fed by a frequency inverter operating in field-oriented control mode. Comparative studies of the mapping of the assumed speed of the hydraulic cylinder and platform are presented, as well as studies of the influence of the load change on the speed and positioning of the mechanism driven by the open-loop controlled system.

Research on Prediction Method of Hydraulic Pump Remaining Useful Life Based on KPCA and JITL

Hydraulic pumps are commonly used; however, it is difficult to predict their remaining useful life (RUL) effectively. A new method based on kernel principal component analysis (KPCA) and the just-in-time learning (JITL) method was proposed to solve this problem. First, as the research object, the non-substitute time tac-tail life experiment pressure signals of gear pumps were collected. Following the removal and denoising of the DC component of the pressure signals by the wavelet packet method, multiple characteristic indices were extracted. Subsequently, the KPCA method was used to calculate the weighted fusion of the selected feature indices. Then the state evaluation indices were extracted to characterize the performance degradation of the gear pumps. Finally, an RUL prediction method based on the k-vector nearest neighbor (k-VNN) and JITL methods was proposed. The k-VNN method refers to both the Euclidean distance and angle relationship between two vectors as the basis for modeling. The prediction results verified the feasibility and effectiveness of the proposed method. Compared to the traditional JITL RUL prediction method based on the k-nearest neighbor algorithm, the proposed prediction model of the RUL of a gear pump presents a higher prediction accuracy. The method proposed in this paper is expected to be applied to the RUL prediction and condition monitoring and has broad application prospects and wide applicability.

Experimental and Numerical Study on the Flow Ripple of Circular-arc Gear Pumps Considering the Center Distance Deviation

Novel circular-arc gear pumps effectively solve the problems of oil trapping and flow pulsation experienced with traditional gear pumps. However, the center distance deviation associated with assembly and installation during gear pump processing has an important influence on the outlet pressure pulsation characteristics of circular-arc gear pumps. First, the circular-arc tooth profile equation, conjugate curve equation and meshing line equation were derived to design the circular-arc gear meshing and center distance deviation functions. Second, the circular-arc gear tooth profile was accurately obtained. Then, a pressure pulsation characteristic simulation model for the novel circular-arc gear pumps considering the center distance deviation was established. The results show that with the increase of center distance deviation, the outlet flow rate of the arc gear pump increases first and then decreases greatly. Moreover, the center distance deviation has little effect on the independent tooth cavity pressure. Finally, the proposed fluid dynamic model is used to simulate a commercial circular-arc gear pump, which was tested within this research for modeling validation purposes. The comparisons highlight the validity of the proposed simulation approach.

The Influence of Radial and Axial Gaps on Volumetric Efficiency of External Gear Pumps

The design of gear pumps and motors is focused on more efficient units which are possible to achieve using advanced numerical simulation techniques. The flow that appears inside the gear pump is very complex, despite the simple design of the pump itself. The identification of fluid flow phenomena in areas inside the pump, considering the entire range of operating parameters, is a major challenge. This paper presents the results of simulation studies of leakages in axial and radial gaps in an external gear pump carried out for different gap shapes and sizes, as well as various operating parameters. To investigate the processes that affect pump efficiency and visualize the fluid flow phenomena during the pump’s operation, a CFD model was built. It allows for a detailed analysis of the impact of the gears’ eccentricity on leakages and pressure build-up on the circumference. Performed simulations made it possible to indicate the relationship between leakages resulting from the axial and radial gap, which has not been presented so far. To verify the CFD model, experimental investigations on the volumetric efficiency of the external gear pump were carried out. Good convergence of results was obtained; therefore, the presented CFD model is a universal tool in the study of flow inside external gear pumps.