Application of the vibro-acoustic signal to evaluate wear in the spindle bearings of machining centres. In-service diagnostics in the automotive industry

Nawrocki, Witold; Stryjski, Roman; Kostrzewski, Mariusz; Woźniak, W; Jachowicz, Tomasz

doi:10.1016/j.jmapro.2023.02.036

Cited by 11 publications

(4 citation statements)

References 23 publications

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“…The road in the urban area had the highest values and the greatest variety of values, then the values decreased for the one-way road on the expressway, and the lowest values were obtained on the highway. The findings can help to improve road safety by describing the recommended driving style on a particular road type based on the analysis of the accelerations achieved, which can also be integrated into assistance systems [6,7].…”

Section: Literature Reviewmentioning

confidence: 99%

Influence of Accelerometer Sensor Position for Measurement of Lateral Acceleration of Delivery Van for Cargo Securement

Jagelcak,

Kubanova

2023

Sensors

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The use of sensors in monitoring lateral accelerations in delivery van transport focuses on measuring lateral accelerations on routes with roundabouts and curves to increase road safety. Using microelectromechanical system (MEMS) sensors, it measures the lateral accelerations acting on the vehicle and the load being transported during the test drives to study vehicle dynamics of delivery van for cargo securing, which is essential to the decision of where accelerometer sensors should be placed when monitoring accelerations or performing cargo securing tests. Using an accelerometer and position tracking, accelerations can be detected when traversing curves and roundabouts at selected locations on the vehicle and load. Manual labeling of acceleration events has been used to identify different lateral acceleration events and regression analysis to determine the relationship between lateral accelerations at different sensor positions. The level of acceleration on the roof of the vehicle was found to be like that occurring on a lashed load with limited movements. If we compare the mean values of the lateral accelerations of the individual events between the sensors, the sensor on the side of the vehicle body at the height of the sensor on the load had approximately 5% lower mean values than the sensor on the roof. The sensor on the load measured approximately 5% higher mean values than the sensor on the roof. Hence, the mean lateral accelerations of the individual events for the sensor on the load are 10% higher than for the sensor at the same height on the vehicle body. The values of the mean lateral accelerations of the delivery van from the sensor on the roof of the vehicle are closer to the values of the accelerations of the sensor on the load than to the values of the sensor on the body of the vehicle at the same height.

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Section: Literature Reviewmentioning

confidence: 99%

Influence of Accelerometer Sensor Position for Measurement of Lateral Acceleration of Delivery Van for Cargo Securement

Jagelcak,

Kubanova

2023

Sensors

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“…spindle bearings in mass production machines in the automotive industry to diagnose the spindle and detect wear symptoms [28].…”

Section: Nawrocki Et Al Utilized Vibroacoustic Signals Obtained Frommentioning

confidence: 99%

“…Data-driven models have been shown significant benefits in dealing with monitoring the tool condition due to the independence of the complex physical model and the systematic a priori knowledge [11,40]. It can effectively extract wear feature information from time or frequency domain signals of tools without the need for empirical knowledge [28,36]. Guan et al proposed a method based on Hilbert edge spectrum to analyze the wear signals for effective feature extraction and achieve accurate classification of tool wear conditions [11].…”

Section: Introductionmentioning

confidence: 99%

Multi-feature spatial distribution alignment enhanced domain adaptive method for tool condition monitoring

Hei,

Sun,

Wang

et al. 2023

Eksploatacja i Niezawodność – Maintenance and Reliability

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Transfer learning (TL) has been successfully implemented in tool condition monitoring (TCM) to address the lack of labeled data in real industrial scenarios. In current TL models, the domain offset in the joint distribution of input feature and output label still exists after the feature distribution of the two domains is aligned, resulting in performance degradation. A multiple feature spatial distribution alignment (MSDA) method is proposed, Including Correlation alignment for deep domain adaptation (Deep CORAL) and Joint maximum mean difference (JMMD). Deep CORAL is employed to learn nonlinear transformations, align source and target domains at the feature level through the second-order statistical correlations. JMMD is applied to improve domain alignment by aligning the joint distribution of input features and output labels. ResNet18 combining with bidirectional short-term memory network and attention mechanism is developed to extract the invariant features. TCM experiments with four transfer tasks were conducted and demonstrated the effectiveness of the proposed method.

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“…Even though the number of lethal accidents is decreasing, there are still a large number of failures that could be predicted if monitored properly [8]. Among the large variety of the monitoring devices, the following can be noted: visual systems [9], including laser-based systems [10] and multispectral image acquisition systems [11][12][13], acoustic emission systems [14][15][16][17][18][19], ultrasound detectors [20], thermovisual systems able to detect the elevated temperature of the intensely worn belt surface [21], strain gauge measurement systems [22], and others [23][24][25]. Most of the proposed solutions require the introduction or adaptation of expensive devices and exhibit limited repeatability and accuracy of the measurement.…”

Section: Introductionmentioning

confidence: 99%

Monitoring of Rubber Belt Material Performance and Damage

Ryba,

Bzinkowski,

Siemiątkowski

et al. 2024

Materials

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Conveyors play a very important role in modern manufacturing processes, and one of the most popular types is the belt conveyor. The main elements of a conveyor include a conveyor belt, roller sets, a supporting frame and a drive and control system. The reliable operation of the conveyor depends on the strength and durability of individual elements (especially the belt). Conveyor belts are made from various materials and have received a lot of attention in the scientific and research community. This article presents tests of the strength of the rubber belt material and its damage under load. The belt consists of two internal layers covered with a PVC coating on the outside, and the nominal belt thickness was 2 mm. In the experiment, various configurations of longitudinal and transverse damage were verified, and statistical methods were used to analyze the results. The obtained test results provided a new understanding of the propagation of conveyor belt damage and helped to improve the strain gauge-based monitoring system.

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Application of the vibro-acoustic signal to evaluate wear in the spindle bearings of machining centres. In-service diagnostics in the automotive industry

Cited by 11 publications

References 23 publications

Influence of Accelerometer Sensor Position for Measurement of Lateral Acceleration of Delivery Van for Cargo Securement

Influence of Accelerometer Sensor Position for Measurement of Lateral Acceleration of Delivery Van for Cargo Securement

Multi-feature spatial distribution alignment enhanced domain adaptive method for tool condition monitoring

Monitoring of Rubber Belt Material Performance and Damage

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