Research on compound fault diagnosis of rolling bearing based on intrinsic time scale decomposition and information fusion

In view of the difficulty to effectively extract compound faults of rolling bearing from aero-engine and precisely identify their types, the paper has proposed a method integrating signal separation algorithm and information fusion. Firstly, the method decomposes the vibration acceleration signals collected by sensors from different positions at the same moment based on intrinsic time scale decomposition algorithm. Secondly, cross correlation analysis is given to the proper rotation component (PRC) of the same layer, which are obtained after decomposition and correspond to the sensors from different positions and cross-correlation function is introduced to embody information fusion. Thirdly, signals are reconstructed according to cross-correlation function of each PRC. Finally, based on the frequency spectrum of reconstructed signal, extract the characteristics of rolling bearing and identify the type of faults under different sensor combinations and multiple compound fault types. The result shows, the proposed method can effectively extract the characteristics of compound faults of bearing and precisely identify the type of faults under different sensor combinations and multiple compound fault types of rolling bearing.

Traffic noise models and noise guidelines: A review

Traffic noise is a major cause of noise pollution, and impacts of noise pollution on humans have been studied extensively. Previous studies have helped in the development of traffic noise prediction analysis using robust analytical and computational models, parameters connected with traffic, road characteristics, and environment. This study reviewed 11 traffic noise modeling strategies and parameters used by various agencies in different parts of the world. Seven out of the 11 models reviewed in this paper were based on outdoor measurements while the remaining four were based on outdoor and indoor measurements. Considering the cost and time involved in developing these models, there is need to understand existing traffic noise models, differences, and assumptions before adopting or recalibrating them for local demands. This study contributes to the larger body of knowledge and intends to serve as a reference material for future researchers in the area of traffic noise modeling and techniques.

Vibration transmissibility suppression for hydraulic excavators in working conditions via multi-objective optimization

The mass variances of materials in buckets and the movements of excavation arms greatly impact powertrain vibration transmissibility in hydraulic excavators under working conditions. If the influence of mass variation among bucket contents and excavation arm motions on vibration transmissibility is not considered, then only limited improvements can be made to vibration isolation performance. In this paper, vibration transmissibility suppression for hydraulic excavators operating under working conditions were studied via multi-objective optimization for stiffness coefficients of suspension elements (SEs). First, the rigid-flexible coupling model of a hydraulic excavator with a flexible base was built using ADAMS software. In the model, the stiffness coefficients of the SEs were the targeted variables with constrained conditions, while the multi-objectives for optimization were the vibration transmissibility and energy decoupling rates of the powertrain. Vibration isolation transmissibility (VIT) of the mounting system was compared between situations with non-optimized and optimized stiffness coefficients. Finally, the amplitude changes of the resultant SE support forces were used to illustrate the effects of powertrain vibration transmissibility suppression. We found that the average value of VITs increases significantly during the optimization process for the stiffness coefficients of SEs, which indicates that the mounting system has better vibration isolation performance. The smaller amplitudes of the resultant support force illustrate the improvements to the performance of vibration transmissibility suppression of the powertrain via the optimization process.

A new method to identify rotor–stator rubbing positions based on intrinsic time scale decomposition

To effectively identify the rotor–stator rubbing positions in aero-engine, the paper has proposed the combination of intrinsic time-scale decomposition (ITD) and classification algorithm. Regarding that with larger noise component in proper rotation component (PRC) signals after ITD, it will be more difficult to extract the characteristic information of rubbing faults, the PRC correspondings to the largest noise was eliminated. Meanwhile, signals were reconstructed based on residual proper rotation components, and positions of rubbing faults were identified according to the reconstructed signal. As rubbing extent and other factors cannot be completely the same in each rubbing, energy of reconstructed signal has been normalized to reduce the difference. Normalized energy indexes were inputted into classification algorithm as feature vectors to identify the positions of rubbing faults. To identify the superiority of approach, a comparison has been made between the proposed approach and the method of directly extracting normalized energy indexes of acceleration signals. The result of comparison shows that the two methods both work well in the identification rate of training and test samples; as for the identification rate for an unknown sample, the proposed method is superior to the other, with identification rate increasing by 17% and 9.4%.

Experimental and analytical investigation of impact dampers in free vibration reduction with coulomb friction

The presence of vibration in structures and machines can establish failures and reduce the efficiency. Passive dampers have been used extensively for vibration control because of their simple concept. One of these dampers is impact damper (ID). Impact dampers are suitable to operate in harsh environments and effective over a wide range of frequencies. In this paper, the experimental and theoretical investigation on the effect of the ID in free vibration of a cantilever beam is done. The lateral motion of the free end of the cantilever beam is modeled as one degree of freedom (1-DOF) system. The motion of the 1-DOF system equipped with the ID with Coulomb friction is studied analytically. Free vibration of cantilever beam investigated experimentally. The experimental results are presented and discussed. The damping inclination of the ID in various experimental and theoretical studies is proposed. The results show the validation between the experimental and the theoretical studies.

Behavior of cracked Euler–Bernoulli beam and inverse problem for assessing crack severity

In this present study, natural frequencies of the first two modes of bending vibration for the cracked simply supported Euler–Bernoulli beam is determined using finite element analysis (FEA). FEA natural frequencies for the cracked beam are used to investigate the behavior of the cracked beam and also used in the inverse problem of crack depth detection. Dynamic behavior of the cracked simply supported beam is observed, and it is found that normalized mode shape at crack location has great effect on amount of decreasing of natural frequencies. When normalized mode shape at crack location is increased, then natural frequencies decrease. In this study, pattern of mode shape played a vital role in decreasing or increasing natural frequencies. At the midpoint of the beam, there is largest bending moment in first bending mode and there is nodal point in second bending mode. Harmonic analysis for the cracked simply supported beam is carried out to find von Mises stress responses and appearance of peaks at frequency of first bending mode is noticed in graphs of von Mises stress response, expressing high values of von Mises stress at crack tip. Inverse problem of assessing the crack depth is performed using results of FEA first mode frequency ratio and published experimental results and the method showed good results in case of high crack depth ratios.

Investigating the effect of noise exposure on mental disorders and the work ability index among industrial workers

Noise as one of the most common hazardous physical agents in the work environment causes physical and psychological problems in occupied workers. This study aims to investigate the relationship of demographic variables and noise exposure with mental disorder and work ability index in automotive industry workers. This study aims to investigate the effect of noise exposure on mental disorder and work ability index among industry workers. In this descriptive-analytic study, 325 individuals working in auto parts supplier industry who were exposed to different level of noises were investigated. Personnel’s daily exposure to noise for each group was measured based on ISO-9612 standards using calibrated sound level meter model SVANTEK-971. Workers’ mental disorder and work ability index were determined using Kessler Psychological Distress Scale questionnaire and shortened form of work ability index, respectively. Then, collected data were analyzed using SPSS-22. The mean and standard deviation of mental disorder and work ability index for all employees was 23.46 ± 3.45 and 37.43 ± 6.14, respectively. The results of one-way ANOVA and linear regression analysis showed that there is a significant association between noise exposure with mental disorder and work ability index in term of age groups, working groups, and work experience ( p-value < .05). Regardless the effect of other variables, it can be stated that for each dB increase in noise exposure cause mental disorder increase by 0.32 and work ability index decrease by 0.157. And among the demographic variables, age was the most influential parameter on mental health and work ability index. According to the results of this study, noise exposure could lead to increased psychological distress and decreased work ability index in workers. The ability to work directly and indirectly through mental disorders can be affected by exposure to industrial noise. Considering severe exposure to noise in some units and the negative impact of noise exposure on mental health and work ability index, it is necessary to improve of controlling and protective measures against noise.

A novel intelligent fault diagnosis method based on variant sparse filtering and back-propagation

Detecting the mechanical faults of rotating machinery in time plays a key role in avoiding accidents. With the coming of the big data era, intelligent fault diagnosis methods based on machine learning models have become promising tools. To improve the feature learning ability, an unsupervised sparse feature learning method called variant sparse filtering is developed. Then, a fault diagnosis method combining variant sparse filtering with a back-propagation algorithm is presented. The involvement of the back-propagation algorithm can further optimize the weight matrix of variant sparse filtering using label data. At last, the developed diagnosis method is validated by rolling bearing and planetary gearbox experiments. The experiment results indicate that the developed method can achieve high accuracy and good stability in rotating machinery fault diagnosis.

Study on audiometer calibration at the extended high-frequency range 8–16 kHz

Audiometry is a branch of acoustical measurements that concentrated on testing the devices related to hearing and used in medical part such as audiometer. It is substantial to calibrate the audiometer to assure the measurement traceability and to safe human health. So, it is considered as a major claim. The importance of calibration comes from the request for advanced instrument to test accurately the hearing loss for human, especially for those people who might be at risk due to noise. The conventional audiometry covered from 125 to 8 kHz, while the extended high-frequency (EHF) audiometry above 8 up to 20 kHz, the last-mentioned type may be useful in early diagnosis of hearing loss. The audiometer calibration performed using ear simulator, standard or working microphone, sound level meter, and frequency analyzer according to IEC60645-1. The physical parameters such as sound pressure level, frequency and distortion may be affected by environmental conditions such as temperature change. The gained results observed that the measured value of all the tests performed was affected by temperature variation. There were deviations observed from each performed test’s nominal values in the calibration process as the temperature varies from 16 to 40°C. So, this is a detailed study for the significance, method, and uncertainty estimation for audiometer calibration covering the EHF ranges within the temperature from 16 to 40°C.

Vibration characteristics analysis and structure optimization of air-pressure subsoiler

Aiming at the problems of strong vibration, inconsistent subsoiling depth and high failure rate of air-pressure subsoiler, air-pressure subsoiler vibration characteristics was studied. In order to decrease the vibration, For the first time, the vibration characteristics of air-pressure subsoiler were obtained by modal analysis and vibration test. The vibration characteristics of the whole air-blown subsoiler are analyzed Through time domain analysis, it is found that the vibration acceleration of four deep loosening shovel is inconsistent. When the diesel engine is started, it is easy to cause inconsistent subsoiler depth. Then, by analyzing the vibration characteristics of the whole air-pressure subsoiler, it can be known that the external excitation source of the air-blown subsoiler is close to its own natural frequency. In order to avoid resonance caused by the vibration frequency of the external excitation source being close to the natural frequency of the air-pressure subsoiler, and to reduce the inconsistency of the subsoil depth, we optimize the design of air-pressure subsoiler. Instead of diesel engines, the steering gear box is connected with tractor power output shaft to provide power. The modal simulation of the optimized air-pressure subsoiler shows that the first-order natural frequency is obviously improved and the external excitation frequency is successfully avoided. It not only avoids resonance, reduces the damage of resonance components, but improves the service life of the subsoiler, greatly improves the structural reliability of the air-pressure subsoiler, at the same time, removes the main external excitation source, which greatly reduces the vibration in actual production and the inconsistency of subsoiling, which is of great significance in actual production. It provides a reference for the research of vibration characteristics, resonance avoidance and structure optimization of agricultural equipment.