Search Results (93)

The integrity of bolted components primarily relies on the quality of interfacial contact, which is achieved by maintaining prescribed bolt torque levels. However, challenges arise from corrosion-induced bolt head damage, potentially compromising the bolt preload, and quantifying such effects remains unanswered. Many studies often compare bolt corrosion’s effects to bolt loosening as both affect the interfacial contact stresses to some extent. This technical study aimed to investigate whether a correlation exists between the impact of bolt head damage and the different levels of bolt torque. Guided wave ultrasonic testing (UT) was implemented for this investigation. Laboratory experiments were conducted to monitor the transmission of ultrasonic signals across the bolted interface first during the bolt-tightening process. Once the highest bolt torque was achieved, the process was repeated for a simplified corrosion scenario, simulated by artificially damaging the bolt head in a controlled manner. The analysis focused on studying the transmission of signal energy for both scenarios. The findings revealed different trends for the signal energy transmission during bolt tightening, which are subjective to the inspection frequency. On the contrary, even at an advanced level of bolt head damage corresponding to 16% mass loss, no clear or monotonic trend was observed in the total transmitted energy. While the total energy remained relatively stable across all inspection frequencies, distinct waveform changes, such as energy redistribution and the emergence of additional wave packets, were observed. The findings emphasize the need for more advanced waveform-based analysis techniques to detect and interpret subtle changes caused by bolt degradation. Full article

Red-layer soft rock has characteristics such as softening when encountering water, loose structure, and significant rheological properties. In tunnel engineering, it is necessary to sort out and analyze the stress characteristics of its support structure. This paper focuses on the mechanical behavior and support effect during the construction of Neogene red-layer soft rock tunnels. Through field monitoring, it explores the mechanical characteristics of Huizhou Tunnel under complex geological conditions in depth. This study adopted a remote wireless monitoring system to conduct real-time monitoring of key indicators including tunnel surrounding rock pressure, support structure stress, and deformation, obtaining a large amount of detailed data. An analysis revealed that the stress experienced by rock bolts is complex and varies widely, with stress values between 105 and 330.5 MPa. The peak axial force at a depth of 2.5 m reflects that the thickness of the loosened zone in the surrounding rock is approximately 2.5 m. The compressive stress in the steel arches of the primary support does not exceed 305.3 MPa. Shotcrete effectively controls the surrounding rock deformation, but the timing of support installation needs careful selection. The stress in the secondary lining is closely related to the primary support. The research findings provide an important theoretical basis and practical guidance for optimizing the support design of red-bed soft rock tunnels and enhancing construction safety and reliability. Full article

Bridges play a key and controlling role in transportation systems. Steel bridges are favored for their high strength, good seismic performance, and convenient construction. As important node connectors of steel bridges, high-strength bolts are extremely susceptible to damage such as corrosion and loosening. Therefore, accurate identification of bolt loosening is crucial. First, a new type of adhesive piezoelectric sensor is designed and prepared using PMN-PT piezoelectric single-crystal materials. The PMN-PT sensor and polyvinylidene fluoride (PVDF) sensor are subjected to steel plate fixed frequency load and swept frequency load tests to test the performance of the two sensors. Then, a steel plate component connected by high-strength bolts is designed. By applying exciter square wave load to the structure, the vibration response characteristics of the structure are analyzed to identify the loosening of the bolts. In addition, a piezoelectric smart washer sensor is designed to make up for the shortcomings of the adhesive piezoelectric sensor, and the effectiveness of the piezoelectric smart washer sensor is verified. Finally, a bolt loosening index is proposed to quantitatively evaluate the looseness of the bolt. The results show that the sensitivity of the PMN-PT sensor is 21 times that of the PVDF sensor. Compared with the peak stress change, the natural frequency change is used to identify the bolt loosening more effectively. Piezoelectric smart washer sensor and bolt loosening indicator can be used for bolt loosening identification. Full article

In geotechnical engineering, traditional anchor bolts often have problems such as an insufficient bearing capacity, their ease of loosening, and an unsatisfactory support effect under complex geological conditions (such as soft soil or broken surrounding rock), resulting in it being difficult to guarantee engineering stability. In order to solve these problems, this paper studies the supporting performance of a hollow grouting anchor with an umbrella-shaped expansion head with an expansion pipe. Through theoretical analysis, mechanical performance analysis, and experimental analysis, the supporting mechanisms and mechanical characteristics of a hollow grouting anchor with an umbrella-shaped expansion head are systematically discussed. The calculation formula for the maximum pull-out force of the umbrella-shaped expansion head is clarified, and the fixed range of the expansion body section in relation to the loose ring is quantified. Based on the analysis results, the structural parameters and material properties of the bolt were optimized, and the optimization effect was verified by numerical simulation. The results show that the optimized bolt has significantly improved the pull-out bearing capacity, shear resistance, and reinforcement effect on the soil. The maximum pull-out force of the umbrella-shaped expansion head can be increased by up to 35%, and the fixed range of the expansion body section can be expanded by 45%. The research provides an efficient and reliable support solution for geotechnical engineering fields, such as roadway engineering and tunnel engineering, which significantly improves the stability and safety of engineering under complex geological conditions. At the same time, it provides an important theoretical basis and practical reference for the design and construction of similar projects. Full article

The structural stability of transmission towers critically depends on the integrity of bolted connections, necessitating accurate bolt loosening detection for power grid safety. Traditional methods, such as manual inspection and hammering-based auditory analysis, suffer from inefficiency and inaccuracy due to environmental noise and subjective judgment. This paper proposes a novel machine learning framework for intelligent bolt loosening detection using acoustic signature analysis. The framework integrates multi-channel acoustic data from strategically placed sensors, extracting Mel-Frequency Cepstral Coefficients (MFCCs) through pre-emphasis, framing–windowing, the Fourier transform, Mel-filter bank processing, and the discrete cosine transform. Adversarial training is employed to suppress noise interference and hammering force variability by augmenting training data with perturbed samples. Experimental validation on 110 kV and 220 kV transmission towers demonstrates the framework’s efficacy: the Support Vector Machine (SVM) achieves 89.93% accuracy, 86.26% precision, 84.89% recall, and 84.91% F1 score, outperforming Decision Tree (86.7% accuracy), K-Nearest Neighbors (89.0%), Random Forest (84.86%), and XGBoost (89.47%). The proposed solution enables reliable, scalable bolt loosening detection, significantly advancing intelligent maintenance for power transmission infrastructure. Full article

Due to the complex operating environment of combine harvesters, uneven terrain, multiple vibration sources, and complex transmission systems, failures easily occur in critical working components, especially the bolted connections of the vibrating screen. To address these issues, this study first established a bolt-tightening mechanical model. Secondly, a finite element simulation of the preload force was performed using Ansys Workbench software (2023R2). The simulation results showed that the bolt head area exhibits a ring-shaped strain distribution. To determine the critical state of bolt loosening, a single-bolt loosening test was conducted. The experimental results indicated that when the bolt pressure decreased to 78.4 N and the torque decreased to 0.5 N·m, bolt loosening intensified, and the pressure value showed a sharp decreasing trend. These pressure and torque values can be defined as the bolt loosening threshold, providing an important reference basis for subsequent monitoring and early warning. Finally, to more realistically simulate actual working conditions, a combine harvester field vibration test was conducted. By arranging triaxial acceleration sensors on the bolted connections of the vibrating screen, acceleration signals were collected under both low-speed and high-speed field operating conditions. Time–frequency analysis was performed on the signals to extract characteristic values for each measurement point. The field vibration test results showed that the characteristic values of the transmission shaft bolt structure of the vibrating screen were at a relatively high level, indicating that this part is subjected to a large vibration load. Furthermore, frequency domain feature analysis revealed that the vibration frequency components in this area are complex, which further increases the risk of bolt loosening. This study provides an in-depth analysis of the loosening characteristics and vibration characteristics of the vibrating screen’s bolted connections in combine harvesters. The results provide an important theoretical basis and technical support for the online monitoring of failures in the vibrating screen’s bolt structure. Full article

The combine harvester, as a multi-component machine comprising a cutting table, a conveyor, a threshing cylinder, and other components, experiences significant stress and bolt failures in cutting table-conveyor structures due to inherent excitation and the cutting table’s cantilevered design. To address bolt loosening monitoring in the critical joint, this paper designed a Wheatstone bridge circuit-based wireless monitoring system and a multi-channel Wheatstone bridge sensor, enabling multi-bolt monitoring on combine harvesters. Utilizing LoRa wireless communication, the system effectively overcomes the wiring complexity and deployment difficulties of traditional agricultural machinery bolt monitoring systems. The Wheatstone bridge sensor can precisely monitor pre-tightening forces up to 150 kN for M12–M24 bolts. A calibration test based on dynamic time warping (DTW) accurately fitted the sensor’s response to pressure and displacement with determination coefficients of 0.9780 and 0.9753. Then, a validation test focusing on connection bolts revealed a 95.12% overlap between the simulated measurement range and the calibration range under pre-tightening conditions. Furthermore, fitting curves for simulated measurements against tightening torque and angle yielded coefficients of determination of 0.9945 and 0.9939, which demonstrated accurate fitting of pre-tightening conditions and defined the monitoring range of 3.02 × 10¹² to 3.49 × 10¹². Finally, combined with simulation results, a field performance test confirmed the sensor’s ability to detect minute 5% pre-load reductions, achieve 200 ms data transmission to a host computer, and maintain lossless data transmission over 1.2 km. This sensor and system design provided a valuable reference for bolt loosening monitoring in combine harvesters and other agricultural machinery. Full article

As a critical fastener connecting steel rails, fish-tail bolts ensure the safety of railway transportation. To improve the efficiency of fish-tail bolt loosening detection, this paper proposes a computer vision-based method for detecting fish-tail bolt looseness under tilted perspectives. The method first identifies bolt positions and coordinates of corner points on rail clamp edges through object detection and key point detection. Then, considering diverse rail clamp dimensions and combining with bolt positions, it employs dual perspective transformations for image rectification. Finally, utilizing the Lightweight OpenPose network, angle recognition of key bolt edges is achieved through Gaussian ring-shaped smooth labels, with loosening determination made by comparing angular variations across temporal frames. In experimental validation, tests were first conducted on a public dial-reading dataset for pointer angle recognition, showing a minimum average error of only 0.8°, which verifies the algorithm’s feasibility. Subsequently, based on fish-tail bolt images captured under various tilted perspectives, we constructed a self-made dataset of bolt key edges and performed loosening detection experiments. For bolt images in boundary postures, after rotation preprocessing, the average detection error was reduced to 0.7°. When the loosening threshold was set to 2.1°, the detection accuracy reached 97%. Experimental results indicate that the proposed method effectively identifies fish bolt loosening, providing crucial technical reference for railway safety maintenance. Full article

Bolt loosening is a common mechanical failure in large-scale generator sets, especially the top cover bolts, which can lead to unstable operation, affecting the safety and efficiency of the unit. Real-time monitoring of bolt pre-tightening force and the early diagnosis of loosening are crucial for ensuring the long-term safe operation of the generator set. This study proposes a novel method for diagnosing faults in large-scale hydraulic units, with a particular focus on thread loosening failures. The proposed approach utilizes stress feature analysis and intelligent algorithms to enhance the diagnostic process. The study involves a detailed analysis of the stress transfer mechanism during bolt loosening, aiming to elucidate the relationship between changes in pre-tightening force and stress distribution in the surrounding bolts. A combined approach of monitoring the pre-tightening force and signal analysis is employed to facilitate the real-time tracking of dynamic changes. Experimental results show that loosening a single bolt causes stress distribution changes in the entire bolt group, particularly in the adjacent bolts. The study also introduces a diagnosis method combining pre-tightening force changes and VMD (Variational Mode Decomposition), which proves to be highly accurate in locating loosened bolts. Engineering applications validate that VMD analysis combined with the Spearman method effectively identifies changes in stress and has high accuracy and potential for diagnosing bolt loosening failures, providing valuable guidance for generator set maintenance. Full article

In wind turbine systems, bolted connections in pitch bearings are subjected to working loads that reduce bolt preload. This reduction can lead to issues such as bolt loosening and eccentric loading, which in turn results in the nonuniform distribution of contact stress across joint surfaces. These issues can compromise structural integrity and reduce fatigue life. However, the study of contact stress mainly focuses on theoretical research, lacking relatively large, complex structures. Also, the stress testing methods for contact surfaces of bolted connections are limited in practical engineering. In this paper, a localized bolt connection model using the finite element method according to pitch bearings in wind turbine systems was established. The contact stress distribution patterns of bolt specimens under varying preloads were investigated. Comparative numerical simulation and experimental analysis using thin-film pressure sensors were conducted. Furthermore, the effect of bolt assembly in different tightening processes on the contours of contact stress was analyzed to identify the optimal tightening sequence. The experimental results demonstrate a positive correlation between preload and maximum contact stress, with stress distribution exhibiting symmetry around the bolt hole and decreasing radially outward. Thin-film pressure sensors can be used for contact stress detection. Furthermore, the diagonal tightening method can achieve a more uniform contact stress distribution compared to other methods, such as sequential and alternate tightening. The findings provide valuable insights for optimizing the contact stress distribution and tightening processes in bolted joint assemblies. Full article

Bolted connections are crucial in joining mechanical assemblies and ensuring the integrity and reliability of structural components. This study proposes a method for estimating bolt loosening life by practically applying material fatigue life prediction methods. First, the study employed the linear cumulative damage rule to predict the loosening life of single bolts under two-block loading conditions. Second, a test device with two bolt attachment points on a single structure was fabricated to model the multi-bolted structure, and tests were conducted. Finite element analysis (FEA) analysis was employed to identify vulnerable points. The loosening life of single bolts predicted using the linear cumulative damage rule exhibited enhanced accuracy within a ±1.2× error band compared with the experimental data despite variations in bolt types and test conditions. The FEA results for the multi-bolt structure demonstrated that the loosening life could be predicted by identifying vulnerable points and estimating the displacements. This study effectively predicts the bolt loosening life, offering valuable data for the reliability assessment of bolted structures. Full article

The demanding operational conditions of combine harvesters induce substantial vibrations and component degradation, significantly impacting harvesting efficiency, safety, and overall machine reliability. Bolt loosening, a critical failure mode at the joints of various working parts of combine harvesters, is a prevalent concern. The complexity and heterogeneity of vibration signals in these machines present a considerable challenge for the timely and accurate detection of bolt loosening. This paper proposes a novel methodology for identifying and diagnosing vibrating screen bolt failure states under multiple excitation conditions, specifically tailored for the 4LZY-1.8(PRO688Q) combine harvester. The study initially analyzes the critical torque associated with bolt connection failure. Subsequently, vibration signals are acquired from the bolt connection of the vibrating screen, and time-frequency analysis is performed to characterize the degree of bolt loosening, the predominant vibration direction, and the causative frequency components. A high-dimensional feature matrix is then constructed utilizing a Gaussian kernel function. The efficacy of the proposed methodology is evaluated through training and testing a classification decision model. This study provides a robust theoretical foundation for the vibration-based fault diagnosis of bolt structures in combine harvesters. Full article

Rock bolting in underground environments is used for different fundamental reasons, including suspending potentially loosened blocks, clamping small wedges together, inducing a protective pressure arch along the contour of excavated voids to improve the self-supporting capacity of the ground, and providing passive pressure in integrated support systems. In this study, we describe a testing procedure that was developed to investigate the grouted annulus of a rock bolt using a low-cost investigation method. This diagnostic technique was based on the dynamic response of the system, where mechanical vibrations were induced within the rock bolt and the response was recorded by using geophones/accelerometers on the protruding element of the bolt (the collar and head). The collected signal was then processed to estimate the spectral response, and the amplitude spectrum was analyzed to detect the resonance frequencies. A 3D finite element model of the rock bolt and grouting was established to simulate the quality of the coupling by varying the mechanical properties of the grouting. The model’s response for the studied geometry of the rock bolt suggested that a poor quality of grouting was usually associated with flexural modes of vibration with a low resonance frequency. Good-quality grouting was associated with a frequency higher than 1400 Hz, where the axial vibration was mainly excited. Our analyses referred to short rock bolts, which are usually adopted in small tunnels. The interpretation of the experimental measurements assumed that the spectral response was significantly affected by the quality of the grouting, as demonstrated by the modeling procedure. The resonant frequency was compared with the results of the model simulation. The method was used to test the quality of rock bolts in a small experimental tunnel carved from andesite rock in Chile. Low-cost shock sensors (piezoelectric geophones) with low sensitivity but a wide frequency band were used. The main research outcome was the development of a reliable method to model the dynamic response of rock bolts in mines or for experimental applications in tunnels. Albeit limited to the current specific geometries, the modeling and testing will be adapted to other anchor/bolt options. Full article

This paper primarily investigates the mechanism of bolt loosening under the Sine-on-Random (SOR) vibration excitation. Firstly, a theoretical model of bolt loosening response under the SOR synthesized excitation is established by a time–frequency conversion method, which converts the sine excitation into Power Spectrum Density (PSD) expression in the frequency domain and superimposes it with random vibration excitation to obtain the SOR synthesized excitation spectrum. Then, by means of a four-bolt fastened structure, the bolt loosening mechanisms under both the sine and random vibration excitation are deeply studied, respectively. Ultimately, based on the time–frequency conversion method of SOR synthesized excitation, the bolt loosening responses of the structure under SOR excitation with different tightening torques are analyzed. Furthermore, a three-stage criterion including the Steady Stage, Transition Stage, and Loosen Stage for bolt loosening under SOR excitation is revealed, and the relationship among the SOR synthesized vibration responses and the two forms of single vibration responses is explored based on a corrective energy superposition method by introducing the weight factors of the two single vibration responses under different tightening torques. Finally, test verifications for the four-bolt fastened structure are conducted and good consistencies with the results of the Finite Element Analysis (FEA) are shown. This study provides valuable insights into the detection and prevention of loosening in bolted connection structures under multi-source vibration environments and has important engineering reference significance. Full article

Bolted joints, prevalent in industrial applications for component fastening, are susceptible to self-loosening—a critical issue resulting in a gradual reduction in clamping force. Gaining insight into the underlying mechanisms of self-loosening is crucial. While prior research has largely focused on evaluating component stiffness, limited attention has been given to its impact on the self-loosening behavior of bolted joints under transverse cyclic loading. This study investigates how component stiffness influences self-loosening in bolted joints by varying the material and thickness of clamped members. An experimental setup replicating real-world conditions is devised to simulate loosening caused by cyclic lateral displacement. Tests are conducted using steel and high-density polyethylene (HDPE) clamped members of different grip lengths to explore the relationship between stiffness and self-loosening. Key parameters measured include bolt axial load, transverse force on clamped members, relative displacement, and rotation between the bolt and nut. The findings provide valuable insights into the effects of stiffness across various clamped member materials and grip length combinations, which can enhance the understanding of conditions that promote loosening resistance. Moreover, by highlighting stage-II or rotational loosening, with each test resulting in complete preload loss, the study provides a comparative analysis of the influencing factors. This enables the identification of distinct loosening patterns and supports the development of improved bolted joint designs to reduce loosening. Full article