Bearing Vibration Research Articles

Phase-based video vibration measurement and fault feature extraction method for compound faults of rolling bearings

Vibration characterization of rotating machinery is crucial for determining rotational and failure frequencies. Traditional contact measurement methods have limitations, while high-speed cameras offer a non-contact alternative for measuring target vibrations, spatial phase-based techniques have recently been widely used in detecting subtle vibrations and show good robustness to imaging noise. In this paper, a vision-based vibration extraction method for rotating machinery is proposed, aiming at extracting minor vibrations of bearings from them and further analyzing their fault frequencies. To address the challenge of separating a single fault frequency from the extracted compound faulty vibration signals, kurtosis is employed to analyze the inverse convolution period of multiple periodic components, and the MOMEDA filter length is optimized using the golden section algorithm. MOMEDA is then used to enhance each periodic pulse separately, and fault frequency is obtained through envelope spectrum demodulation. In the experimental part, a phase-based method is used to extract minor vibration displacements from rotor vibration video, which is subsequently compared with eddy current sensors in both time and frequency domains to verify the accuracy of the proposed method in extracting vibration displacements based on vision. Finally, vibration signals are extracted from the bearing compound fault video, and the single fault frequency characteristics of the bearing are successfully separated using the adaptive MOMEDA method, which provides an efficient and reliable method in the field of rotating machinery fault diagnosis.

Experimental study on the influence of flexible structure and gas supply method on the characteristics of aerostatic tilting-pad bearing

Purpose This paper aims to propose novel flexible structure-supported tilting-pad aerostatic bearings and to improve operational stability and vibration reduction of aerostatic bearings. Design/methodology/approach The authors established an aerostatic bearing-rotor test rig and designed two aerostatic tilting-pad bearings with different flexible support structure and an ordinary aerostatic tilting-pad bearing and then examined their effects in dynamic performance to assess the vibration reduction performance of different flexible structures. Furthermore, the authors proposed three gas supply methods and conducted experiments to study the influence of gas supply methods in the performance of bearings. Findings The experimental results show that among the three structures, the double-layer flexible structure-supported tilting-pad bearing demonstrates outstanding vibration damping performance and it significantly enhances the operational stability of the bearing-rotor system. Furthermore, the experimental results indicate that the gas supply method has a significant impact on the performance of the aerostatic bearing. There is a certain pressure difference between the gas supply pressure for the loading pads and that for the nonloading pads, which is advantageous for increasing the operational stability and reducing system vibration. Originality/value The authors designed novel flexible aerostatic tilting-pad journal bearing structures, which can enhance the operational stability and reduce vibrations of the bearing. Additionally, this article proposes an air supply method advantageous for increasing the stability of the bearing and reducing system vibrations.

Dynamic Forces and Vibrations of the Planetary Gear-Set Radial Bearings with the Roller Dimension Deviation

Double planetary gear trains (DPGTs) have high loading capacity and transmission, making them indispensable in various heavy rotating machinery applications. However, the presence of planetary gear-set radial bearing roller dimension deviation (PBRDD) from real-world manufacturing discrepancies poses a significant challenge to the dynamics of the DPGTs. Previous dynamic models often overlooked the internal excitations of the planetary gear-set radial bearing, focusing only on the single planetary gear train dynamics, rendering them inadequate for studying the impact of the PBRDD on DPGTs. Therefore, this paper proposes a coupling method integrating the PBRDD model with the DPGT dynamic model, taking into consideration the planetary gear-set radial bearing’s internal excitations, to reveal the impact of PBRDD on DPGTs’ dynamics. Specifically, the changes in roller–ring contact force and roller–cage collision force induced by PBRDD are considered. Through comprehensive simulation and experimental analyses, the accuracy of the dynamic model is assessed and its efficacy in capturing the effects of PBRDD on DPGTs’ dynamics is validated. The results show that the DPGTs’ dynamics increment with the increment of PBRDD.

Dual-loss nonlinear independent component estimation for augmenting explainable vibration samples of rotating machinery faults

Obtaining fault samples for diagnosing faults in rotating machinery for engineering applications can be costly. To address this challenge, fault sample augmentation methods are used to train fault diagnosis models. However, existing techniques mainly focus on comparing augmented signal loss with real ones, overlooking the underlying vibration mechanism of rotating machinery faults. Addressing this limitation, a novel approach, called dual-loss nonlinear independent component estimation (DLNICE), is proposed to enhance understanding of fault features in vibration signals. This integrates augmentation losses in both time and frequency domains to enrich fault vibration samples. DLNICE effectively utilizes limited fault samples for augmentation by estimating nonlinear independent components, capturing key fault characteristics like impulsiveness and cyclo-stationarity. Therefore, augmented fault samples become more explainable for analyzing rotating machinery faults. Experimental evaluations on bearing and gearbox vibration samples confirm the effectiveness of DLNICE. Utilizing the augmented samples leads to an average accuracy of 86.27 % in bearing fault diagnosis, and that of 81.60 % in gearbox fault diagnosis. The results demonstrate that DLNICE excels in augmenting high-quality vibration samples of rotating machinery faults.

Proper orthogonal decomposition analysis of flow characteristics of aerostatic bearings based on Large Eddy Simulation

The driving mechanism of the vibration of aerostatic bearings is still unclear. Although there are several interpretations, none of them is conclusive. The difficulty lies in the complicated information concealed beneath the turbulence flow. To this end, the proper orthogonal decomposition (POD) method was systematically implemented in the aerostatic bearing flow field analysis in the present study, and some new findings have been proposed. First, the accuracy of our large eddy simulation (LES) has been validated through quantitative comparisons with the experimental references in terms of pressure distribution. Then, the mode decomposition has been conducted at a circumferential symmetry plane and bottom surface and the influence of supply pressure has been uncovered. It turns out that the vortices within the recess dominate the flowfield when the supply energy Ps=3atm, which could be recognized as the driving mechanisms of vibrations. The convection and shearing process in the vicinity of the recess inlet becomes intense and corresponding vortices become predominant in the cases of Ps=4atm and 5atm. Eventually, the influences of film thickness have also been discussed when Ps=4atm. Different from the case of h = 10 μm, the low-frequency vortices near the recess outlet could be detected when the film thickness is increased to 20 µm. The control of corresponding flow structures might be helpful for the vibration suppression.

Effect of oil film stiffness on vibration of full ceramic ball bearing under grease lubrication

PurposeThis paper aims to understand the vibration characteristics of full ceramic ball bearings under grease lubrication, reduce the vibration of the bearings and improve their service life.Design/methodology/approachThe Hertz contact stiffness formula for full ceramic ball bearings is constructed; the equivalent comprehensive stiffness calculation model and vibration model of full ceramic ball bearings are established. The dynamic characteristic test of full ceramic ball bearing under grease lubrication was carried out by using the bearing life testing machine, and its vibration was measured, and its vibration acceleration root-mean-square was obtained by software calculation and compared with the simulation results.FindingsAt the rotational speed of 12,000 r/min, the root-mean-square value of vibration acceleration is maximum 10.82 m/s2, and the error is also maximum 7.49%. As the rotational speed increases, the oil film stiffness decreases. In the radial load of 600 N, the vibration acceleration root-mean-square is minimum 6.40 m/s2, but its error is maximum 6.56%. As the radial load increases, the vibration of the bearing decreases and then increases, so under certain conditions increasing the radial load can reduce the bearing vibration. With different types of grease, the best preload is also different; low-speed heavy load should be used when the viscosity of the grease is large, and high-speed light load should be used when the choice of smaller viscosity grease is made.Originality/valueIt provides a theoretical basis for the application of full ceramic ball bearings under grease lubrication, which is of great significance for reducing the vibration of bearings as well as enhancing the service life of bearings.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0094/

Prediction and analysis of paroxysmal impulse vibration in aero-engine inter-shaft bearings induced by localized faults in the outer ring

Prediction and analysis of paroxysmal impulse vibration in aero-engine inter-shaft bearings induced by localized faults in the outer ring

Research on Feature Extraction and Fault Diagnosis Method for Rolling Bearing Vibration Signals Based on Improved FDM-SVD and CYCBD

In mechanical equipment, rolling bearing components are constantly exposed to intricate and diverse environmental conditions, rendering them vulnerable to wear, performance degradation, and potential malfunctions. To precisely extract and discern rolling bearing vibration signals amidst intricate noise interference, this paper introduces a fault feature extraction and diagnosis methodology that seamlessly integrates an improved Fourier decomposition method (FDM), singular value decomposition (SVD), and maximum second-order cyclostationary blind convolution (CYCBD). Initially, the FDM is employed to meticulously decompose the bearing fault signals into numerous signal components. Subsequently, a comprehensive weighted screening criterion is formulated, aiming to strike a balance between multiple indicators, thereby enabling the selective screening and reconstruction of pertinent signal components. Furthermore, SVD and CYCBD techniques are introduced to carry out intricate processing and envelope demodulation analysis of the reconstructed signals. Through rigorous simulation experiments and practical rolling bearing fault diagnosis tests, the method’s noteworthy effectiveness in suppressing noise interference, enhancing fault feature information, and efficiently extracting fault features is unequivocally demonstrated. Furthermore, compared to traditional time–frequency analysis methods such as EMD, EEMD, ITD, and VMD, as well as traditional deconvolution methods like MED, OMEDA, and MCKD, this method exhibits significant advantages, providing an effective solution for diagnosing rolling bearing faults in environments with strong background noise.

Recognizing Bearings’ Degradation Stage Using Multimodal Autoencoder to Learn Features from Different Time Series

Utilizing machine learning technologies to monitor assets’ health conditions can improve the effectiveness of maintenance activities. However, accurately recognizing the current health degradation stages of industrial assets requires a time-consuming manual feature extraction due to the wide range of observable measures (e.g., temperature, vibration) and behaviors characterizing assets’ degradation. To address this issue, feature learning technology can transform minimally processed time series into informative features, i.e., able to simplify the classification task (e.g., recognizing degradation stages) regardless of the specific machine learning classifier employed. In this work, minimally preprocessed time series of vibration and temperature of industrial bearings are exploited by an autoencoder-based architecture to extract degradation-representative features to be used for recognizing their degradation stages. Different autoencoder architectures are employed to compare their data fusion strategies. The effectiveness of the proposed approach is evaluated in terms of recognition performance and the quality of the learned features by using a publicly available real-world dataset and comparing the proposed approach against a state-of-the-art feature learning technology. We tested three different multimodal autoencoder-based feature learning approaches, i.e., shared-input autoencoder (SAE), multimodal autoencoder (MMAE), and partition-based autoencoder (PAE). All the AE-based architecture results in classification performances greater or comparable with the state-of-the-art feature learning technology, despite being trained in an unsupervised fashion. Also, the features provided via PAE correspond to the greatest performances in recognizing bearings’ degradation stage, providing high-quality features both from a classification and clustering perspective. Unsupervised feature learning methodologies based on multimodal autoencoders are capable of learning high-quality features. These result in greater degradation stages recognition performances when compared to supervised state-of-the-art feature learning technology. Also, this enables the correct representation of the expected progressive degradation of the bearing.

Comparison of non-linear vibration of outer race defective ball bearing using two defect functions

The aim of this article is to study the effects of evolution in defect size on vibration of a ball bearing by simulation of a ball bearing by developing a 2-DOF mathematical model and to compare the vibration responses of defective bearings obtained for two widely used defect functions, viz., rectangular function and half-sine wave function. MATLAB codes are developed to prepare a mathematical model of a ball bearing and to solve the differential equations of the model using the Runge-Kutta method. In the model, the mass supported by the bearing is considered as a lumped mass, and the contact between the races and the balls is considered as a series of springs, whose spring stiffness is obtained by using Hertz’s contact deformation theory. This model considers the contact deformation between the balls and the races and the additional displacement between the balls and the inner race due to radial clearance and defect geometry. The maximum possible radial displacement of the ball into the defect is obtained analytically and graphically from the race-ball-defect geometry. First, the impulses generated due to an outer race defect in the ball bearing are modeled using two different defect functions separately and their vibration responses are compared. Secondly, the effects of increase in defect length on vibration of the bearing are simulated separately for two defect functions, and then their responses are compared and analyzed. The results show that when the defect is modeled with a rectangular defect function, the vibration responses obtained are greater than when the defect is modeled with a half-sine wave defect function. And, vibration responses increase rapidly up to a certain level of defect length and then decrease with a further increase in defect length. The vibration analysis performed for different defect lengths can provide good support to vibration analysts and researchers.

Dynamic modeling and force-vibration mapping mechanism construction of rolling bearings considering cage flexibility and local faults

Rolling bearings are one of important components of rotating machinery transmissions and thus its health condition is important for the safety of machinery. Thus, rolling bearing vibration analysis is critical for bearing health condition monitoring. Current bearing vibration analysis ignores multiple compound influencing factors for dynamic modeling. Hence, a more accurate bearing dynamic model, considering multiple factors including cage flexibility, time-varying displacement excitations caused by local defects and elastohydrodynamic (EHD) lubrication, is proposed to accurately reflect force states among bearing elements and vibration responses of bearings. Furthermore, the force states and vibration responses of bearings with localized defects in the proposed model are analyzed in details: (1) the main excitation source of the dynamic model under faulty conditions is identified as the contact force between the rolling element and the raceway by analyzing the vibration signals and main physical variables (the contact forces and the friction forces) in numerical values and change trends; (2) the mapping mechanism between the main excitation source and the vibration response is constructed. The force states among bearing elements are detailedly analyzed in the proposed model and the relationship between the forces and bearing vibration responses is revealed, facilitating the bearing health condition monitoring and vibration control of machinery.

Design and implementation of a precision levelling composite stage with active passive vibration isolation

The white-light-interference (WLI) three-dimensional topography fine detection has high requirements for the chip-loading stage on levelling and vibration isolation capacity, to ensure that the micro-meter-level structured chip is stably aligned with the WLI scanning head. To meet the high performance detection requirements, this paper designs a novel three-axis levelling and active-passive vibration isolation (LAPV) composite stage, in order to perform precision tilt levelling and wide-frequency-domain vibration isolation. The proposed LAPV stage integrates a modified quasi-zero-stiffness passive vibration isolation unit with an active actuation unit which consists of three voice coil motors (VCMs). It performs active-passive vibration isolation while ensuring a precision levelling. Considering the load bearing and motion vibration of the chip-loading stage, a miniaturized quasi-zero-stiffness mechanism having a specialized leaf spring structure is then designed to limit the vibration isolation operation to the vertical direction and coordinate the levelling motion of the tilt rotation direction, so as to establish a structural decoupling stage. Based on the dynamic and kinematic modelling analysis, a customized PID-Positive Position Feedback (PID-PPF) control scheme is implemented. Afterwards, an experimental verification is conducted. The obtained results show that the stage can achieve a precise levelling motion, reaching a levelling deviation of 33.2 μrad. Moreover, it also can achieve effective active-passive vibration isolation for various vibrations with different frequencies and amplitudes, and the vibration isolation rate can reach 90 %.

Vibration behavior of a 3D-printed hybrid polymer bearing with outer race defect

PurposeIn industry applications, polymer hybrid bearings have become widespread in recent years owing to the lack of lubricant requirements, particularly in areas requiring hygiene. The additive manufacturing method gives significant advantages to have complex machinery parts, and it has become popular in the industry in recent years. However, it has some inherent disadvantages caused by layered deposition/addition of the materials, and the probability of the localized defect is much higher than in the conventional manufacturing methods. This study aims to investigate the effect of the outer race defect on the characteristics of vibration and service lifetime of hybrid polymer ball bearings produced with the stereolithography (SLA) additive manufacturing method.Design/methodology/approachIn this study, polymer bearings’ races were produced with the additive manufacturing SLA method, and the outer race defect was analyzed with measured vibrations.FindingsThe results show that the additive manufacturing method suggests a practical solution for producing a polymer hybrid ball bearing. On the other hand, the hybrid three-dimensional-printed bearing, which has an outer race defect, worked for approximately 8 h without any problems under a 1 kg load and a shaft speed of around 1,000 rpm. In addition, when there is a defect in the outer and/or inner race of the ball bearing, the crest factor and kurtosis of the vibration are higher than faultless ball bearing, as expected.Originality/valueThis paper provides valuable information on the lifetime and vibration characteristics of polymer hybrid ball bearing produced by means of additive manufacturing.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2023-0183/

A novel method of rolling bearings fault diagnosis based on singular spectrum decomposition and optimized stochastic configuration network

Fault diagnosis of rolling bearings is essential for the safe operation of rotating machinery. However, in the production process, the rolling bearings have a complex working environment embedded with weak fault signals and a large number of interfering signals, which is a considerable challenge to automatically and accurately detect bearing fault type from the actual vibration signal. Therefore, a novel fault diagnosis scheme is proposed based on singular spectrum decomposition (SSD) and an optimized stochastic configuration network (SCN). Firstly, SSD is used to pre-process the original rolling bearings vibration signal to obtain several singular spectral components (SSCs) and the practical component is selected according to the maximum correlation coefficient for signal reconstruction. Furthermore, time domain and power spectrum entropy (PSE) features of the reconstructed signal are extracted to obtain a fault information-rich feature sets. In addition, the parameters of the SCN are optimized by marine predators algorithm (MPA) to enhance the learning ability and generalization performance of the SCN. Finally, the feature sets are input into MPA-SCN to achieve fault classification. Experimental results exhibit that the proposed method has higher accuracy in rolling bearings fault diagnosis compared with other methods, which provides a high-efficiency solution for rolling bearings fault diagnosis.

STUDY ON VIBRATION AND TEMPERATURE RISE CHARACTERISTICS OF FULL CERAMIC BALL BEARINGS UNDER HIGH-TEMPERATURE CONDITIONS

In order to study the vibration and temperature rise characteristics of full ceramic ball bearings under high-temperature conditions, the bearing vibration test of a simulated high-temperature environment was conducted in this paper. The vibration and temperature rise properties of full ceramic ball bearings were measured under high-temperature variable working conditions in this experiment. The results demonstrate that the temperature rise and vibration acceleration of full ceramic ball bearings increase with the cavity temperature increasing from 50°C under a single load. The vibration and temperature rise increased with an increase in rotational speed. Due to the mechanical characteristics of a silicon nitride material, the change of temperature rise of a full ceramic ball bearing is relatively small. When temperature and speed were stable or only very low, full ceramic ball bearings operated stably. The results of the experiment can serve as a guide for the operational state of full ceramic ball bearings in high-temperature environments.

Research on Micro-Turbine Operating State Characterization Based on Bearing Vibration Signals Analysis

An air flow-driven micro-turbine, widely used in air-condition control systems in aircraft cabins, train coaches, etc., exhibits complex vibration behaviors under stable or unstable inlet flow conditions, and especially has a certain correlation with speeds. In this paper, the vibration responses of the micro-turbine undergoing stable and unstable inlet flows measured on a test rig are analyzed and compared by using different signal processing methods, which include time and frequency domain methods, and statistical and nonlinear methods. First, the test rig system of the airflow-driven micro-turbine, the instrument system and four typical experimental cases are introduced. Then the measured vibration signals are analyzed and compared by time domain characteristic parameters (peak-to-peak value, RMS value and kurtosis value), statistical parameters (auto-correlation and BDS), and amplitude spectra in the frequency domain, statistic spectrum indicators (SSI) based on Welch's periodogram of power spectra, and the spectra of selected IMF components based on Hilbert-Huang Transform (HHT). In particular, some nonlinear feature analyzing methods, including Pseudo-Poincare mapping diagrams and Lempel-Ziv(LZ) complexity, are also used for analyzing measured vibration responses. The obtained results using the above multiple methods are compared and show that, when the inlet flow of the turbine fluctuates significantly, the nonlinear characteristics of the turbine bearings are significantly higher than those of the relatively stable inlet flow and speed conditions. Under these circumstances, commonly used time-frequency analysis methods cannot characterize the different speed operating state of the turbine, and LZ-Complexity and other nonlinear characterization methods should be used to better understand the characteristics of different speeds under unstable conditions.This study provides references for the aerodynamic stability monitoring of the micro-turbine and its design improvement.

Theoretical and In Situ High Speed Measurement Study on Friction-Induced Vibration in Water Lubricated Rubber Bearing-Shaft System

A water-lubricated rubber stern bearing causes frictional vibration and noise under extreme conditions, severely threatening the survivability and concealment performance of underwater vehicles. To investigate the mechanism of friction-induced vibration and noise, a four-degree-of-freedom nonlinear dynamic model that included bearing support vibration, frictional bearing vibration and torsional shaft vibration was proposed. The velocity-dependent Stribeck friction model described the dynamic friction characteristics between the rubber bearing and stern shaft. Nonlinear system stability was examined using the Lyapunov indirect method and the transient dynamic responses determined by the Runge-Kutta method. Meanwhile, a high-speed in situ measurement experimental study was adopted to explore the mechanism of frictional and torsional vibrations in a water-lubricated bearing-shaft system. Results showed that nonlinear friction excitation was the fatal cause of friction-induced vibration in bearing-shaft system. Under different friction excitations, the coupling vibrations formed between the bearing and bearing support were different, resulting in two main modes of friction-induced vibration: “Chatter” and “Squeal.” The frictional vibration of the bearing and torsional vibration of the stern shaft were tightly coupled. These trends and results might provide a theoretical basis for further research on frictional vibration and wear control in water-lubricated rubber bearing-shaft systems.

Static and Dynamic Performances of Novel Aerostatic Bearings with Primary and Secondary Orifice Restrictors

Aerostatic bearings are crucial support components in ultra−precision manufacturing equipment. However, improvements in the load−carrying capability (LCC) of aerostatic bearings often lead to higher intensity nano−vibrations. This paper introduces a novel primary and secondary orifice restrictor (PSOR) designed to simultaneously enhance the LCC and mitigate nano−vibrations in aerostatic bearings. The static performance of complex turbulent flows occurring within the chamber of aerostatic bearings with PSORs was investigated. The dynamic performance of the turbulent flows was analyzed through 3D transient numerical simulation using the large eddy simulation method. The LCC and nano−vibration acceleration were measured experimentally, and the results indicated that the design of the secondary orifice diameter could enhance LCC and mitigate nano−vibrations, consistent with theoretical predictions. The accuracy of the proposed model was validated, confirming the effectiveness of PSOR. In the experiments, an aerostatic bearing with a secondary orifice diameter of 0.1 mm exhibited the lowest LCC and largest nano−vibration. Conversely, an aerostatic bearing with a secondary orifice diameter of 0.26 mm exhibited the highest LCC and weakest nano−vibration. This study provides insights into the formation mechanism of turbulent vortex and interaction mechanism among the primary orifice and secondary orifices in aerostatic bearings with a PSOR.

Rigid Mode Vibration Control for 250 HP Air Compressor System With Integrated Hybrid Air-Foil Magnetic Thrust Bearing (i-HFMTB)

Abstract This study aims to verify the effectiveness of the 250 HP class compressor system to which the integrated hybrid air-foil magnetic thrust bearing (i-HFMTB) proposed in (Ha et al., 2023, “Integrated Hybrid Air Foil-Magnetic Thrust Bearing (i-HFMTB) Part I: Preliminary Experimental Test for Rotordynamic Parameter Identification and Behavior With PD Control,” ASME Paper No. GT2023-102860) [1] is applied, and the vibration and instability problems of air-foil journal bearing (AFJB) occurring in the rigid mode are controlled by i-HFMTB. The compressor rotor is supported by two AFJB (journal diameter = 60 mm) and an i-HFMTB, and the length and mass of the rotor are 550 mm and 15.24 kg, respectively. i-HFMTB has a structure in which air-foil thrust bearing (AFTB) pads are inserted into eight slotted active magnetic thrust bearings (AMTB), and PD control (proportional gain: 4000; differential gain: 10) is applied. The operating area was identified through AFJB’s dynamic coefficients and rotordynamic analysis. As a result, in the experiment with the 250 HP compressor system supported only by two AFJB, sub- and super-synchronous vibrations were generated owing to the AFJB’s insufficient load capacity and damping in the rigid mode (7000 rpm) region, and this instability did not disappear even upon increasing the speed to 15,000 rpm. However, when i-HFMTB was turned on in rigid mode, it was confirmed that the sub- and super-synchronous vibrations were significantly reduced. The thrust collar tilt angle was calculated through orbit trajectory analysis of the impeller and cooling side, and it was confirmed that the tilt angle of the thrust collar was reduced during i-HFMTB operation.

Experimental investigation of relationship between bearing capacity and vibration parameters for planetary exploration legged rovers

In recent years, robots with leg mechanisms have received considerable attention as high-running planetary exploration rovers. Rovers undertaking planetary exploration require outstanding running performance to travel on loose ground on which they mostly slip and hardly move forward. The movement of the rover easily deforms the surface of loose ground. This problem can be solved by increasing the bearing capacity. The bearing capacity, the resistance force exerted on the rover legs when they make contact with the ground, needs to be sufficiently large to prevent legged rovers from slipping on loose ground. The bearing capacity can be increased by compaction of the ground by imparting vibrations. This study investigates the relationship between the bearing capacity in the horizontal direction and vibration parameters because this relationship offers valuable information for improving the running performance of legged rovers. First, we investigated the effect of changing the vibration parameters on the bearing capacity. Our experimental results show that the bearing capacity is related to vibration acceleration. These results suggest that the bearing capacity can be estimated from the vibration acceleration. Next, the frequency and amplitude were compared as vibration parameters to devise an efficient method for increasing the bearing capacity. The results of these experiments showed that high-amplitude vibrations increase the bearing capacity to a greater extent than high-frequency vibrations. The reason is that high-amplitude vibrations generate larger additional vibrations by the collision between the rod and the ground than high-frequency vibrations. This knowledge is valuable for selecting a suitable vibration that can efficiently increase the bearing capacity. This study suggests a method of facilitating further planetary exploration using legged rovers.