Friction Noise Research Articles

AUSCULTATION OF A HEART AND VASCULAR ACTIVITY DURING AURICULAR NERVE STIMULATION

The principal objective of the research was to develop and test a multichannel system intended to capture heart (PCG) and Korotkoff sound (KS) signals in a human model of transcutaneous auricular nerve stimulation (tANS). In particular, the purpose was to develop contact auscultation transducers (transducers) capable of capturing PCG and KS at standard auscultation positions without and during the selective tANS. The scope was to develop transducers capable of capturing body sounds lying in a portion of the frequency spectrum between 20 Hz and 200 Hz. They should be as insensitive as possible to external sound or ambient noise and should be capable of compensating for friction noise due to body movements. The system developed consisted of five transducers, where four of them were intended for the auscultation of PCG generated by heart valves, while one of them was intended to capture KS. The functionality of the transducers was tested in the female model by applying four of transducers to the standard positions on the chest and one over the Brachial artery. The results show that the system developed was highly sensitive to PCG and KS, and less sensitive to external ambient sounds and friction noise. Namely, the S1 and S2 heart-sound peaks are present clearly in the recorded PCG signal as well as during the tANS. It was also shown that during the tANS, heart cycles became slightly shorter and, thus, the heart rhythm slightly higher. Finally, during the tANS, both heart sounds S1 and S2 became louder. In conclusion, the findings provide some evidence that the sounds captured by the transducers emanate from the organs under study and are related to their activity and tANS.

Prediction of the tribological properties of a polymer surface in a wide temperature range using machine learning algorithm based on friction noise

A signal processing method based on friction noise is introduced to predict the tribological properties of polymers in a wide temperature domain. Three different machine learning algorithms, XGBoost, LightGBM and CatBoost are used to establish a mapping relationship between the time–frequency domain features of friction noise and the friction coefficient. The friction coefficients of pairs of four polymers and seven metals are predicted at five temperatures and three load/speed conditions of point contacts in a wide temperature domain from − 120–25 ℃. Performance analysis reveals that the machine learning approach satisfactorily predicts the friction coefficients of different polymer–metal pairs in a wide temperature range from tribological test data. This method can be used for in-situ monitoring on tribological properties.

Limitations in the existing models for predicting accurate interdependencies between wear and friction noise,

In recent years, the investigation of friction noise has gained increasing attention within the field of tribology. Wear processes pose a significant hurdle in the industrial sector as reduce the lifespan of machine components. The replacement of damaged components, including brake systems and high-speed running machines, incurs substantial expenses. Thus, there arises a need for a method capable of identifying alterations in surface contact conditions, enabling the monitoring of the process and anticipation of the noise and rate of wear. To directly measure wear, it would be necessary to remove one of the contact surfaces (i.e., mechanical contacts such as gears and bearings.) for visual inspection, resulting in significant downtime. Alternatively, indirect measurements of wear can be performed by assessing the emitted machine noise and establishing a correlation between the noise and the alteration in surface topography caused by wear progress. Friction noise refers to the acoustic emissions generated during the contact between rough surfaces in motion. These emissions contain valuable information about the dynamics and characteristics of the sliding surfaces. Therefore, the researchers have attempted to model the interdependencies in between friction, wear and noise to find out the mentioned information and mapped it with the surface health of the mechanical contacts. The objective of this research paper is to examine all the prominent current models to discuss their approaches about how the noise can be generated from friction and later generate surface wear. This paper mainly aims to highlight their key limitations and identify the current challenges in modeling the mentioned interdependencies with accuracy.

Protein-induced delubrication: How plant-based and dairy proteins affect mouthfeel

Understanding how certain proteins cause astringency is necessary in order to improve the mouthfeel and popularity of plant-based foods. To this end, we studied protein interactions during oral processes using a PDMS-PDMS interface lubricated by ex-vivo human saliva. Friction measurements and in-contact imaging were implemented, while food consumption was simulated by introducing model plant and animal-based proteins. All but one of the protein samples caused an increase in measured friction and this correlated with astringency ratings from a human taste panel. This is attributed to delubrication as the salivary pellicle is removed, since food proteins interact with salivary proteins thus disrupting their adhesion. This interaction is shown to occur both on the surface and in the bulk of the fluid. However, the debonding of the pellicle requires frictional shear stress (i.e., rubbing) . Food proteins in isolation are themselves shown to be surface-active and form boundary films, which can adhere following removal of the pellicle. The mechanical action of protein particles in the delubrication process was isolated by filtering and shown to account for a moderate (<33%) increase in friction magnitude accompanied by a significant (>90%) increase in frictional noise. The flow and deformation of these particles was also visualised thus demonstrating how the microscale breakdown of food can be studied. • Tribological measurements combined with in-contact fluorescence imaging were used to study the breakdown of the salivary pellicle by food proteins within a simulated tongue-palate interface. • During salivary pellicle formation, salivary proteins agglomerations are trapped at the inlet and act to feed the contact. • Measured friction increase resulting from the introduction of food protein onto a saliva film on PDMS agreed with that from a biological tongue and correlated with astringency ratings from a human taste panel. • Both plant-based and dairy proteins can cause astringency by interacting with saliva proteins thus reducing their adhesion to the surface. This interaction is shown to occur both on the surface and in the bulk of the fluid. • Shear stress is required to remove the weakly bound saliva proteins to cause delubrication. • The role of insoluble food protein particles entrainment in astringency is to cause abrasive wear that increases the average friction coefficient and contributes to significant frictional noise.

Modelling Frictional noise using Artificial neural network and Regression: The case of steel on steel reciprocating sliding

Modelling Frictional noise using Artificial neural network and Regression: The case of steel on steel reciprocating sliding

Modelling frictional noise using artificial neural network and regression: the case of steel on steel reciprocating sliding

Modelling frictional noise using artificial neural network and regression: the case of steel on steel reciprocating sliding

Study on the friction noise behavior of coating textured surface based on STFT time-frequency analysis

Study on the friction noise behavior of coating textured surface based on STFT time-frequency analysis

Study on the friction noise behaviour of coating textured surface based on STFT time-frequency analysis

Study on the friction noise behaviour of coating textured surface based on STFT time-frequency analysis

Frictional noise mitigation using synergetic approach of laser surface texturing and bio-lubrication

In this research study, the effect of laser surface texturing on friction induced noise under dry and lubricated sliding is investigated. Disc samples of EN 31 steel were ablated with dimples of 70 µm with varying pitch. The tribo-tests were conducted in anechoic chamber at a constant normal load of 10 N and frictional noise was studied in relation to sliding frequency and dimple pitch. Textured surfaces with 150 µm dimple pitch reduced friction and noise in lubricated conditions. FESEM and EDS were used to analyze the worn surfaces. Taguchi integrated Grey analysis revealed that optimal average frictional noise and COF are obtained under lubricated conditions with 10 Hz sliding frequency and 150 µm dimple pitch.

Effect of lubrication on frictional noise and coefficient of friction in sliding tribo-pair using Taguchi’s integrated TOPSIS method

Effect of lubrication on frictional noise and coefficient of friction in sliding tribo-pair using Taguchi’s integrated TOPSIS method

Porous asphalt mixture use asphalt rubber binders: Preparation and noise reduction evaluation

To prepare low-noise asphalt pavement with excellent noise reduction and road performance, a large amount of crumb rubber was added to asphalt binder to prepare high viscosity modified asphalt rubber, with Sasobit and waste cooking oil (WCO) selected as viscosity-reducing additives to reduce the viscosity. Moreover, the study took the prepared porous asphalt rubber mixture (PARM) as the research object and formed a systematic evaluation method for the noise reduction performance of the asphalt mixture. The temperature sweep test based on DSR, the dynamic creep test based on UTM, and the tire drop test were used to explore the damping performance of the asphalt mixture. Due to the softening effect of WCO and the high asphalt-aggregate ratio, the damping capacity of PARM with WCO is stronger. It is worth mentioning that the addition of crumb rubber can indirectly improve the damping performance of the asphalt mixture by increasing the asphalt-aggregate ratio. The impedance tube test results show that the air voids is the critical factor affecting the sound absorption performance of the asphalt mixture. The sound absorption coefficient of porous asphalt mixture (PAM) with the largest air voids is higher than PARM, and both are significantly higher than AC-13. In addition, the tire drop and pendulum instruments were designed to simulate and test tire pavement's vibration and friction noise. It can be found that the PARM mixed with WCO showed the best noise reduction effect.

Design Methodology and Application of Surface Texture: A Review

Surface texture is regarded as a promising solution for enhancing the tribological features of industrial materials due to its outstanding benefits, such as minimization of the contact area, enhancement of the load bearing capacity, storage of the lubricant, and management of the transition between lubrication regimes. Surface texture can be processed under either liquid or gas conditions. As compared to laser ablation in air, employing liquids or other gases as ablation media provides high accuracy and uniformity by limiting the heat-affected zone (HAZ) and other undesired defects to a large extent, as well as high crater structural features. In addition, the synergistic use of different liquid, solid, and additive lubricants with surface roughness recently demonstrated excellent performance. Therefore, surface texture helps to improve the tribological characteristics of a material. This paper reviews the design methodologies and applications of surface texture, emphasizing the proper selection of the appropriate laser parameters and ambient conditions for the best texture quality and functionality. Recent texture geometric design features to improve the film thickness and the self-lubricating system are presented. The ablation environment is explored using various media. The interaction between the lubricants’ types and surface textures is explored based on the operating conditions. Furthermore, surface texture applications using superhydrophobic surfaces, anti-drag, and vibration and noise friction are discussed. We hope that this review plays an enlightening role in follow-up research on laser surface texture.

Flexible Dual-Channel Digital Auscultation Patch With Active Noise Reduction for Bowel Sound Monitoring and Application.

Bowel sounds (BSs) have important clinical value in the auxiliary diagnosis of digestive diseases, but due to the inconvenience of long-term monitoring and too much interference from environmental noise, they have not been well studied. Most of the current electronic stethoscopes are hard and bulky without the function of noise reduction, and their application for long-term wearable monitoring of BS in noisy clinical environments is very limited. In this paper, a flexible dual-channel digital auscultation patch with active noise reduction is designed and developed, which is wireless, wearable, and conformably attached to abdominal skin to record BS more accurately. The ambient noise can be greatly reduced through active noise reduction based on the adaptive filter. At the same time, some nonstationary noises appearing intermittently (e.g., frictional noise) can also be removed from BS by the cross validation of multichannel simultaneous acquisition. Then, two kinds of typical BS signals are taken as examples, and the feature parameters of the BS in the time domain and frequency domain are extracted through the time-frequency analysis algorithm. Furthermore, based on the short-term energy ratio between the four channels of dual patches, the two-dimensional localization of BS on the abdomen mapping plane is realized. Finally, the continuous wearable monitoring of BS for patients with postoperative ileus (POI) in the noisy ward from pre-operation (POD0) to postoperative Day 7 (POD7) was carried out. The obtained change curve of the occurrence frequency of BS provides guidance for doctors to choose a reasonable feeding time for patients after surgery and accelerate their recovery. Therefore, flexible dual-channel digital auscultation patches with active noise reduction will have promising applications in the clinical auxiliary diagnosis of digestive diseases.

Fully portable continuous real-time auscultation with a soft wearable stethoscope designed for automated disease diagnosis

Modern auscultation, using digital stethoscopes, provides a better solution than conventional methods in sound recording and visualization. However, current digital stethoscopes are too bulky and nonconformal to the skin for continuous auscultation. Moreover, motion artifacts from the rigidity cause friction noise, leading to inaccurate diagnoses. Here, we report a class of technologies that offers real-time, wireless, continuous auscultation using a soft wearable system as a quantitative disease diagnosis tool for various diseases. The soft device can detect continuous cardiopulmonary sounds with minimal noise and classify real-time signal abnormalities. A clinical study with multiple patients and control subjects captures the unique advantage of the wearable auscultation method with embedded machine learning for automated diagnoses of four types of lung diseases: crackle, wheeze, stridor, and rhonchi, with a 95% accuracy. The soft system also demonstrates the potential for a sleep study by detecting disordered breathing for home sleep and apnea detection.

Enhancing wear prediction with spectral analysis of noise and the dynamic response of the structure

High frequency noise has been observed during reciprocating sliding of metal-metal in dry contact. In tribology, the study of friction and wear, this noise was historically associated with “brake squeal;” however, it has also been found to occur within structures and systems that experience high frequency, reciprocating contact of metal constituents; typically found in the connecting locations such as the joints of a variety of jointed structures ranging from automobiles, airplanes, and HVAC systems. This type of tribological behavior and fretting fatigue has been replicated in tribology experiments where researchers found increased noise followed with the increase in sliding velocity and lowered relative humidity [1]. It was also found in these experiments, that noise is only produced during the tension phase of the fretting cycle and it only occurs when specific criteria are met in the fretting system: reduction in the coefficient of friction and the self-excited vibration of the structure. In this study, 304 SS steel samples are tested within a fretting rig apparatus that produces high frequency noise. In addition to spectral analysis of the noise produced, the dynamic response of the self-excited response of the system is developed. The combination of spectral data and structural dynamics data may allow for better correlation between noise and the prediction of wear in dry metal-to-metal contacts. T. Jibiki and M. Tamura, “A basic study of friction noise caused by fretting,” Wear 251, 1492–1503 (2001).

Effects of Laser Surface Texturing and Lubrication on the Vibrational and Tribological Performance of Sliding Contact

Various textures are fabricated by a picosecond laser machine on the surfaces of circular stainless steel specimens. Vibrational and tribological effects of laser surface textures are investigated by means of a tribometer and a data acquisition and signal processing (DASP) system. Experimental results show that surface textures can reduce the coefficients of friction (COFs), enhance the wear resistance, and improve the dynamical performance of frictional surfaces. In this study, the surface with micro circular dimples in diameter of 150 μm or textured area density of 25% has the best tribological and dynamical performance. Compared with the non-textured surface, the surface with circular dimples in diameter of 150 μm and 15% textured area density has 27% reduction of COFs, 95% reduction of frictional vibrations, and 66% reduction of frictional noise. The frictional vibrations and noise in the sliding contacts can be effectively reduced by adding graphene to the lubrication oil, and the surface textures enhance the frictional noise reduction performance of lubrication.

Prediction of frictional braking noise based on brake dynamometer test and artificial intelligent algorithms

Based on brake noise dynamometer test data, combined with the artificial intelligent algorithms, frictional braking noise is quantitatively analyzed and predicted in this study. To achieve this goal, a frictional braking noise prediction method is indicatively proposed, which consists of two main parts: first, based on the experimental data obtained from the brake noise dynamometer tests, and combining with the improved Long-Short-Term Memory (LSTM) algorithm, the coefficients of friction (COFs) are predicted under various braking test conditions. Then, based on the predicted braking COFs and other selected critical braking parameters, the quantitative prediction of frictional braking noise is obtained by means of the optimized eXtreme Gradient Boosting (XGBoost) algorithm. Finally, the inherent features of the XGBoost algorithm are employed to qualitatively analyze the importance of the main factors affecting the frictional braking noise. The prediction algorithms of COFs and frictional braking noise are validated by the brake dynamomter test data, and the R2 (R square) scores of both the LSTM and XGBoost prediction algorithms are 0.9, which verifies the feasibility of both algorithms. The main contribution of this work is to predict the braking noise based on a large set of test data and combined with the LSTM and XGBoost artificial intelligent algorithms, which can significantly save time for the brake system development and braking performance testing, and has significance to the rapid prediction of braking frictional noise and fast NVH (noise, vibration, and harshness) optimal design of frictional braking systems.

Tribological Properties and Frictional Noise Behavior of Inconel 625 with Micro-texture Filled by Sn-Ag-Cu

Tribological Properties and Frictional Noise Behavior of Inconel 625 with Micro-texture Filled by Sn-Ag-Cu

Analysis of Ship Noise Characteristics Generated According to Sailing Conditions of the G/T 1000-ton Stern Fishing Trawler

In this study, we conducted onboard noise measurement experiments under the conditions of anchoring, sailing, casting, and hauling to determine whether noise generated in the G/T 1000-ton fishing trawler triggers zone-specific effects upon vessel operation. It was shown that most accommodation areas of the trawler comfortably met the IMO acceptance criteria regardless of the sailing condition, but most of the stern area, where the fishing actually occurs, exceeded the permitted limit of 75 dB (A). Furthermore, the statistical analysis revealed a significant difference (p &lt; 0.05) only in the bow and the stern, which are both open areas. In the case of the former, improvements were deemed possible due to the influence of the fluid emission noise from the seawater piping in the bow, and the acceptance criteria were also appropriate. However, in the case of the latter, a significant difference was seen in hauling conditions, and on-site analysis confirmed frictional noise from hydraulic oil in the trawl winch and between the chains and the metal hull, leading to the conclusion that various improvements are required, such as the mandatory wearing of safety equipment by workers and stricter legal standards for permitted noise levels.

Investigation of friction noise properties of M50 matrix curved microporous channel composites filled with Sn-Ag-Cu

PurposeThis paper aims to investigate the friction noise properties of M50 matrix curved microporous channel composites filled with solid lubricant Sn-Ag-Cu (MS). Design/methodology/approachPure M50 (MA) and MS are prepared by selective laser melting and vacuum-pressure infiltration technology. The tribological and friction noise properties of MA and MS are tested through dry sliding friction and then the influential mechanism of surface wear sate on friction noise is investigated by analyzing the variation law of noise signals and the worn surface characteristics of MS. FindingsExperimental results show that the friction noise sound pressure level of MS is only 75.6 dB, and it mainly consists of low-frequency noise. The Sn-Ag-Cu improves the surface wear state, which reduces self-excited vibration of the interface caused by fluctuation of friction force, leading to the decrease of friction noise. Originality/valueThis investigation is meaningful to improve the tribological property and suppress the friction noise of M50 bearing steel.