Friction Noise Research Articles

Integrating Friction Noise for In Situ Monitoring of Polymer Wear Performance: A Machine Learning Approach in Tribology

Abstract Friction and wear between mating surfaces significantly affect the efficiency and performance of mechanical systems. Traditional tribological research relies on post-observation methods, limiting the understanding of dynamic friction behavior. In contrast, in situ monitoring provides real-time insights into evolving friction dynamics. This study employs machine learning to monitor polymer wear performance through friction noise. The predictive accuracy of various machine learning methods, including Extremely Randomized Trees, Gradient-Boosting Decision Trees, AdaBoost, LightGBM, Deep Forest, and Deep Neural Networks, is compared for wear-type classification. Additionally, the LSBoost regression is selected as the optimal method for predicting polymer wear-rates across various temperatures. The results underscore the potential of using friction noise and machine learning for real-time wear monitoring, offering valuable insights for tribological system maintenance and failure prediction.

Impact of easy-care and softener treatments on fabric frictional noise properties: a study on two protective fabrics

This research aimed to reduce fabric frictional noise to enhance wearing comfort, as such noise can be bothersome. This goal was achieved through chemical surface treatments, specifically cross-linker treatment and silicone softener treatment. Frictional noise from the treated fabrics was generated, recorded, and analyzed using a frictional noise generator, fast Fourier transform, and sixth-band analysis to determine the total noise level. A novel aspect of this work is the use of psychoacoustic characterization to evaluate the fabric frictional noise by calculating Zwicker’s parameters using the Brüel and Kjær application. In addition, the mechanical properties were tested using the Kawabata compression and surface testers, with data comparison achieved using Student’s t-test. The results showed that softeners are more effective than cross-linkers in reducing the total frictional noise level, loudness, and fluctuation strength. However, cross-linkers are better at reducing sharpness. Neither treatment affected the roughness of the frictional noise. In summary, both easy-care and softener treatments help reduce discomfort and produce less loud and sharp fabric frictional noise.

Investigation of friction noise in linear bushing by frequency domain analysis and theoretical model

Linear bushings, unlike existing bearings, are a system that enables linear movement of the axis. This has the advantage of allowing efficient motion due to low friction as it operates through the rotation of the ball, but has the problem of generating noise due to friction between the shaft and bushing. The purpose of this study is to identify the causes of friction noise by checking the frequencies contained in the bushing noise. To this end, a theoretical model is established by referring to conventional LM(Linear Motion) guide research that has similar behavior to bushings, and the reliability of the model is verified through experiments. To simulate actual driving situations, an experimental setup consisting of a fixed support shaft, motor, etc. is created and the noise of original and defective bushings is measured. Through this, commonly included frequencies are detected, and analyze how the frequencies change depending on faults.

Improving the mechanical and tribological properties of Cu matrix composites by doping a Mo2BC ceramic

Cu matrix composites (CMCs) are widely employed for tribological applications such as in sliding bearings and electrical contact fields. However, the Cu matrix needs to be modified to improve its mechanical and tribological properties. In this study, CMCs reinforced with Mo2BC ceramic particles (10–30wt.%) are prepared via the spark plasma sintering (SPS) route method. In comparison with the plain Cu sample, when the content of the Mo2BC particles increased to 30wt.%, the Vickers hardness, yield strength, and tensile strength of CMCs increased by 196%, 157%, and 588%, respectively. Fine grain and load transfer strengthening mechanism are considered the main strengthening mechanism. Introducing the Mo2BC ceramic effectively reduces friction and wear as well as the frictional noise vibration of CMCs. Incorporating Mo2BC ceramic into the Cu matrix can elevate the load-bearing ability, inhibiting mechanical and adhesive wear. In addition, the composite exhibits superior friction and wear properties as the content of Mo2BC ceramic increases gradually up to 30wt. %, where the friction coefficient and wear rate are as low as 0.35 and 3.25 × 10−6 mm3/Nm, respectively. A layer of tribo-film containing Fe2O3 derived from the counterparts and induced by the tribo-oxidation reaction can provide a lubricating effect. Considering the superior mechanical and tribological properties, the as-prepared CMCs could be an attractive alternative material for sliding bearing fields.

Tribological properties of GO/modified SiO2 combination as lubricant additive for bearings

This study investigates the tribological performance of GO/modified SiO2 (GMS) as a composite additive and elucidates their synergistic mechanism. A four-ball friction testing machine and a Timken friction testing machine were used to evaluate the tribological performance of the GMS lubricating oil. The results show that the addition of 0.03 wt% GO and 0.12 wt% modified SiO2 (Mod-SiO2) in the oil resulted in a 48.70 % reduction in average friction coefficient, a 60.56 % decrease in wear, and a 1.43 % increase in PB, compared to pure GO oil. Compared to pure Mod-SiO2 oil, the average friction coefficient decreased by 46.09 %, wear decreased by 51.40 %, and PB increased by 1.38 %. Furthermore, under different loads, the GMS lubricating oil exhibited outstanding capability in reducing frictional noise between the bearing rollers and outer ring, as well as mitigating the trend of temperature variation. The worn surfaces of the test rollers were analyzed using EDS, SEM, CLSM, TEM and Raman spectrum. The spherical Mod-SiO2 particles adhere to the flake-like GO, preventing agglomeration and facilitating better dispersion in the lubricating oil. Therefore, GMS exhibits its significant advantages and potential as a lubricant additive.

Machine Learning Algorithms for Predicting Wear Rates on the Basis of Friction Noise

Under varying operational conditions, the contact and relative movement of a polymer and metal result in surface wear, accompanied by the emission of noise. The relationship between friction noise and wear is inherently complex and nonlinear. In light of these tribological characteristics, this paper introduces the implementation of a random forest algorithm and generalized regression neural network algorithm to establish a mathematical model for predicting the wear rate based on friction noise. To enhance the accuracy of wear rate regression, this study incorporates L2 norm feature selection and the sparrow search algorithm, which are tailored toward the friction characteristics. These techniques optimize the machine learning-based friction model, ultimately improving the regression accuracy of the wear rate.

Evaluation method for microscale mechanical properties of an epoxy resin

This study offers a detailed quantitative evaluation of microscale properties of polymers utilizing the surface and interfacial cutting analysis system (SAICAS) technique. The investigation focuses on the formation of the primary shear zone (PSZ) during cutting, leading to plastic deformation and subsequent chip curling. This research explores various cutting thicknesses, each demonstrating unique chip formation, and applies a lubricant to mitigate friction noise and stabilize chip formation. An in-depth analysis of force geometries is performed to gain insights into chip formation. The shear strength and shear viscosity are calculated using relevant equations, thus enabling the quantitative characterization of the viscoelastic behavior of polymers. Remarkably, the polymers exhibit shear thinning behavior, where their resistance to shear decreases as the shear rate increases. The shear viscosity–shear rate plot follows the Ostwald-de Waele relationship, indicative of plastic flow behavior. The viscoelastic characteristics were validated by comparing the values calculated based on Atkins's theory with the quantified values. Then, the physical meaning of those values were discussed. This study facilitates the direct measurement of mechanical properties in solidified form of the polymer, offering a more precise representation than traditional test piece measurements. In addition, shear viscosity determination of cross-linked materials without pretreatment is achieved, broadening the scope of material analysis through quantitative comparisons.

Friction-Wear and Noise Characteristics of Friction Disks with Circular Texture.

The reduction of friction-induced noise is a crucial research area for enhancing vehicle comfort, and this paper proposes a method based on circular pit texture to achieve this goal. We conducted a long-term sliding friction test using a pin-on-disc friction and a wear test bench to verify the validity of this method. To compare the friction noise of different surfaces, texture units with varying line densities were machined on the surface of friction disk samples. The resulting friction-wear and noise characteristics of the samples were analyzed in conjunction with the microscopic morphology of the worn surfaces. The results indicate that surfaces with textures can delay the onset of squeal noise, and the pattern of its development differs from that of smooth surfaces. The noise reduction effect is most evident due to the proper distribution of textures that can form furrow-like wear marks at the wear interface. The finite element results demonstrate that this morphology can improve pressure distribution at the leading point and reduce the tendency of system instability.

Machine Learning-based GIS Model for 2D and 3D Vehicular Noise Modelling in a Data-scarce Environment

Abstract Vehicular traffic significantly contributes to economic growth but generates frictional noise that impacts urban environments negatively. Road traffic is a primary noise source, causing annoyance and interference. Traditional regression models predict two-dimensional (2D) noise maps, but this study explores the impact and visualization of noise using 2D and three-dimensional (3D) GIS (Geospatial Information Systems) functionalities. Two models were assessed: (i) a 2D noise model for roads and (ii) a 3D noise model for buildings, utilizing limited noise samples. Combining these models produced a comprehensive 3D noise map. Machine learning (ML) models—artificial neural network (ANN), random forest (RF), and support vector machine (SVM)—were evaluated using performance measures: correlation (R), correlation coefficient (R2), and root mean square error (RMSE). ANN outperformed others, with RF showing better results than SVM. GIS was applied to enhance the visualization of noise maps, reflecting average traffic noise levels during weekday mornings and afternoons in the study area.

Experimental investigation on brake squeal unpredictability: Role of the friction noise

Dynamic contact instabilities represent a common issue in brake industry, causing noise and passenger dissatisfaction. Past works identified mode coupling as the cause of brake squeal, but the conditions for its occurrence are still not fully understood, making this phenomenon hardly predictable. This work investigates the relationship between the friction noise, intended as the dynamic excitation generated by the local interface interactions (ruptures, impacts …), and the unstable response of the system. An experimental measurement campaign, conducted on a dedicated tribometer, highlighted that, even in presence of the same macroscopic friction coefficient, mode coupling instability occurred only when in presence of high values of friction noise. Therefore, the friction noise is proposed as a trigger factor for brake squeal occurrence.

A hybrid simulation approach for frictional vibration and noise of wiper-windshield system based on rigid-flexible and acoustic-structure coupling models

Automotive wiper-windshield friction noise is one of the important factors affecting the vehicle interior sound quality. Due to its transient, nonlinear, and uncertain characteristics, the wiper-windshield friction noise has always been a problem in vehicle engineering. Based on rigid-flexible and acoustic-structure coupling models, a hybrid simulation procedure for the friction-induced vibration and noise of a wiper-windshield system is presented in this paper. In light of the rigid-flexible coupled dynamic equations and acoustic-structure coupled automatic matched layer (AML) based on the finite element method (FEM), the software ANSYS Workbench and LMS Virtual. lab. is selected and used for modeling and simulating the frictional vibration and noise of the system under different working speeds and lubricating conditions. In the friction noise simulations, the calculated vibrational responses from the ANSYS are input into the LMS as the excitations of a virtual sound field in a vehicle cavity. Experimental verifications suggest that the proposed hybrid approach is effective and feasible for frictional vibration and noise simulation of the wiper-windshield system. The work done in this paper may provide theoretical and technical supports for acoustic design of wiper-windshield systems, and has guiding significance for interior sound-quality optimization and control of vehicles.

Characteristics and mechanism of friction noise and vibration of disk brake under DC magnetic field

As a common phenomenon, friction noise and vibration of the brake not only affect vehicle braking performance and riding comfort but also cause urban noise pollution. The studies of magnetic field tribology show that magnetic field has an important influence on tribological behavior, but research on the effect of the magnetic field on friction noise and vibration characteristics of the brake is still being carried out. Friction noise and vibration tests of the brake under a DC magnetic field were conducted on a disk brake friction noise-vibration test bench. Harmonic wavelet packet, scanning electron microscope (SEM), and energy dispersive spectroscopy (EDS) were used to reveal the influence mechanisms. Results showed that compared to the self-made collaborative brake, the commercial brake has worse friction noise and vibration phenomena. The DC magnetic field can significantly suppress the friction noise and vibration of the brake. The DC magnetic field’s main mechanism is that it attracts debris particles and promotes oxidation reactions, leading to a significant increase in oxygen, iron, and nickel elements on the wear surface, improving the morphology of the wear surface, and reducing friction noise and vibration. The research results are beneficial to enriching the research connotation of magnetic field tribology and providing a theoretical reference for exploring and developing the treatment of friction noise based on magnetic fields.

Prediction of friction coefficient of polymer surface using variational mode decomposition and machine learning algorithm based on noise features

Establishing a correlation between the friction coefficient and friction noise of metal-friction polymer interfaces is a challenging task in various environments. To address this issue, our study utilizes machine learning algorithms to construct a friction data-based model, elucidating the relationship between noise and friction coefficient. We propose the variational mode decomposition (VMD) along with five machine learning algorithms, each capturing unique data characteristics. Algorithm optimization is achieved through the implementation of L1 and L2 regularization methods. By comparing the regression results, we develop a tribological model that offers a novel approach for constructing a nonlinear model, enabling precise monitoring of the friction coefficient by leveraging noise signals.

Research on the Friction Noise Generation Mechanism and Suppression Method of Submarine Rubber-Based Propeller Bearings-A Review.

This article introduces the main mechanisms of friction noise generated by submarine rubber-based propeller bearings and analyzes their respective scope of application and limitations. Then, the research on suppressing friction noise through the optimization of the structure and improvement of materials of rubber-based propeller bearings is discussed. Finally, the article summarizes a promising research direction aimed at eliminating friction noise in submarine rubber-based propeller bearings. By improving the structure and materials, the friction noise of propeller bearings can be effectively suppressed, thereby improving the deterrence and stealth performance of submarines.

Effect of Reinforcement with Short Carbon Fibers on the Friction and Wear Resistance of Additively Manufactured PA12.

Reinforcing thermoplastic materials for additive manufacturing with either short, long, and continuous fibers or micro/nanoparticles is a sound means to enhance the mechanical/tribological properties of functional 3D printed objects. However, despite the fact that reinforced thermoplastics are being used extensively in modern applications, little data are found in open literature regarding the effect of such reinforcements on the friction and wear characteristics of additively manufactured objects. Therefore, this article presents a comparative study that aims to investigate the friction and wear behavior of carbon fiber-reinforced polyamide 12 (CF-PA12) as compared to pure polyamide 12 (PA12). The test specimens were prepared by selective laser sintering (SLS) at five different build orientations and examined using a pin-on-disc tribometer in dry sliding mode. The coefficient of friction (COF), interface temperature, friction-induced noise, and specific wear rate were measured. Scanning electron microscopy (SEM) was used to inspect the tribo-surfaces. The results revealed that both the COF and contact temperature of CF-PA12 are orientation-independent and are lower than those of pure PA12. Also, it was found that, compared with pure PA12, CF-PA12 has 25% smaller COF and 15-40% higher wear resistance. Further, the SEM of tribo-surfaces showed that adhesive wear dominates the surface of pure PA12, while both adhesive and abrasive wear patterns coexist in CF-PA12. Moreover, fiber crushing and thinning were observed, and this, under some circumstances, can result in a considerable increase in frictional noise.

Comprehensive modeling strategy for thermomechanical tribological behavior analysis of railway vehicle disc brake system

A comprehensive modeling strategy for studying the thermomechanical tribological behaviors is proposed in this work. The wear degradation considering the influence of temperature (T) is predicted by Archard wear model with the help of the UMESHMOTION subroutine and arbitrary Lagrangian–Eulerian (ALE) remeshing technique. Adopting the proposed method, the thermomechanical tribological behaviors of railway vehicle disc brake system composed of forged steel brake disc and Cu-based powder metallurgy (PM) friction block are studied systematically. The effectiveness of the proposed methodology is validated by experimental test on a self-designed scaled brake test bench from the perspectives of interface temperature, wear degradation, friction noise and vibration, and contact status evolution. This work can provide an effective way for the investigation of thermomechanical tribological behaviors in the engineering field.

Sensory analysis of fabric friction noise: Methodology, training, and validation of a panel to evaluate fabric friction noise perception

AbstractFabric friction generates sounds that can be expected or uncomfortable depending on the application. Indeed, acoustic properties of fabrics depend on many parameters like the weave pattern or the surface roughness and according to these properties, sounds will be differently perceived by human ear. This study establishes a list of 16 attributes and the corresponding references and also a method step by step to train the panel to evaluate and characterize textile products. An example of application is presented to show the differences or similarities between samples with different friction speed. Therefore, this work represents a step toward the standardization of the approach to the sensory analysis of fabric friction sounds and can be applied to different space products.Practical ApplicationsSensory analyses are a way to objectively characterize the attributes of different products, especially textile products. Determining whether products fulfill established criteria for some attributes is important for quality control, ensuring consumer trust or drawing some correlations between mechanical and acoustic/mechanical properties. The present study aimed to set up a standardized method for the sensory analysis of fabric friction sounds of fabrics. The sensory approach developed has enabled the sensory characterization of various fabric friction sounds using the selected descriptors, making it possible to establish a sensory profile. The follow‐up study will focus on the correlations between instrumental and sensory approach. In addition, different surface treatments (softener, cross‐linker) will be used in order to observe their influence on the sensory profiles.

Frictional vibration behaviors of a new piezo-damping composite under water-lubricated friction

Water-lubricated bearings have become an important component of marine propulsion systems due to the requirements of environmental friendliness and concealability. However, water-lubricated bearings are often subjected to bending stress, additional stress, frictional resistance and other multi-factor effects, resulting in boundary friction or even dry friction on the friction interfaces when encountering unique working conditions such as engine start-stop, steering, low-speed, and heavy-load. The severe frictional processes often induce vibration behaviors and generate frictional noise, which seriously weakens the sound concealment performance and service life of marine propulsion systems. Therefore, it is urgent to improve the vibration and sound pressure behaviors of the composite bearings under water-lubricated conditions. In this study, novel barium titanate/carbon black/polyurethane composites (BaTiO3/CB/PU) are fabricated and then explored the damping capacities and tribological properties of the new polymers. The results showed that the BaTiO3 concentrated on transforming the mechanical energy generated by frictional vibration into electrical energy which generates the thermal energy. The water cooled the frictional heat and the piezo-damping heat. This energy dissipation method increased the damping capacity to reduce the vibration and noise behaviors induced by friction. The composite with 3.0 wt% BaTiO3 performed the highest loss factor under the operating temperatures and presented the best frictional vibration reduction properties. The knowledge obtained in this study is useful not only to explore a new piezo-damping composite, but also to provide a theoretical basis for developing higher performance polymer-based water-lubricated bearing.

Review of the evolution and prevention of friction, wear, and noise for water-lubricated bearings used in ships

With the development of green tribology in the shipping industry, the application of water lubrication gradually replaces oil lubrication in stern bearings and thrust bearings. In terms of large-scale and high-speed ships, water-lubricated bearings with high performance are more strictly required. However, due to the lubricating medium, water-lubricated bearings have many problems such as friction, wear, vibration, noise, etc. This review focuses on the performance of marine water-lubricated bearings and their failure prevention mechanism. Furthermore, the research of marine water-lubricated bearings is reviewed by discussing its lubrication principle, test technology, friction and wear mechanism, and friction noise generation mechanism. The performance enhancement methods have been overviewed from structure optimization and material modification. Finally, the potential problems and the perspective of water-lubricated bearings are given in detail.

Study on the Tribological Properties of Polymer Interface and the Mapping Mechanism of Friction Noise in a Wide Temperature Range

In order to study the tribological properties and frictional noise mapping mechanism of polymer interface at a wide temperature range, tribological and frictional noise acquisition tests were carried out on a Ball-on-Three-Plates Tribology Accessory. The friction coefficient and noise signal data sets were collected for 15 minutes from the friction surfaces of polytetrafluoroethylene and 0Cr18Ni9 austenitic steel pairs at six temperatures and three constant loading-speed contact points in a wide temperature range of -150°C-25°C. The wear rate of the polymer was measured and the wear state of the polymer interface was studied by field emission environmental scanning electron microscopy (SEM). Based on the analysis of the time-frequency domain characteristics of friction noise and the qualitative mapping relationship between the wide-temperature domain tribological properties and friction noise, the theoretical and experimental basis is provided for establishing online early warning monitoring of the tribological performance of polymer-metal friction pairs based on the time-frequency domain characteristics of friction noise.