Engine Vibration Research Articles

The Effects of Adding TiO2 and CuO Nanoparticles to Fuel on Engine and Hand–Arm Driver Vibrations

Occupant comfort is a key consideration in automobile dynamics, with vibrations potentially causing long-term physical discomfort, especially for drivers. This study investigates the impact of adding TiO2 and CuO nanoparticles to fuel on engine-induced vibrations. Experiments were conducted at various nanoparticle concentrations (0, 50, 100, and 150 ppm) and engine speeds (1000, 2000, and 3000 rpm). Key performance metrics, including kinematic viscosity, density, heating value, thermal conductivity, and brake power (BP), were analyzed. The results indicated that increasing nanoparticle concentration led to a rise in BP. The highest reduction in root mean square (RMS) vibration accelerations occurred at 3000 rpm and 150 ppm, with vibration reductions of 30.33% for CuO and 28.61% for TiO2. Additionally, 8–10% of engine vibrations were transmitted to the steering wheel. The use of 150 ppm CuO nanoparticles resulted in reduced vibration transmission to the steering wheel at all tested speeds. These findings suggest that nanoparticle-enhanced fuels can significantly reduce engine vibrations, potentially improving driver comfort and reducing wear on vehicle components.

Assessing combustion characteristics of alternative fuels in a CI engine by use of a wavelet-based analysis of engine vibration signals

In the current work, a wavelet-based approach for assessing combustion performance of alternative fuels in compression-ignition engines, indicated that changes in cylinder pressure amplitude were reflected by commensurate changes in a proposed parameter, with a maximum of a 9% variation. The proposed parameter, the wavelet transform coefficient maximum amplitude (WMA), successfully accomplished this for various engine conditions. The wavelet transform coefficient standard deviation (WSD), a second proposed parameter, was able to track changes in the rates of pressure rise associated with changes in load conditions and fuel type, with a maximum variation in the parameter of 7%. The approach was assessed by testing six fuels in a test engine unit. Thermodynamic property data and vibration signal data were recorded for each of the fuels tested, at six loading conditions. Subsequently, combustion performance was evaluated using traditional thermodynamic parameters and using the WMA and WSD via a MATLAB based algorithm. Thus, it was surmised that the proposed approach can form the basis for a vibration-based assessment of alternative fuel combustion performance in reciprocating engines.

Experimental Investigation of Energy Harvesting by Employing Piezoelectric Element and Metallic Cantilever Beam

In this paper, in response to the worldwide energy crisis, a piezoelectric element (0.2*35*50) mounted on a host metallic cantilever beam (0.8*37*220) will be presented as a unique contribution to power generation via the micro-electrical mechanical system. It's made out of aluminium and low carbon steel, both of which have a Young modulus of elasticity of 6.8 and 196 GPa, respectively. In order to take advantage of the engine's vibration as an exciting external force to collect energy in the aforementioned piezoelectric device, the whole rig has been coupled to a diesel engine 5kw 3000 rpm (50 Hz). The average power generated by the aluminium beam was 943 microWatts, while the power generated by the low carbon steel beam was 335 microWatts, an increase of 256%. In addition, for both scenarios, (45) mm from the cantilever beam's fixed point was where the engaged piezoelectric element performed best. The used two metals have different stiffnesses, and this accounts for the obtained difference between the induced powers; increasing the stiffness will result in relatively more power created, and vice versa.

Optimized position analysis of multi-directional active mounting system based on quantification formula

This paper mainly studies the influence of active mounting system for vehicle engine vibration from both theoretical and experimental aspects. First, an active mounting system that considers both horizontal and vertical directions is proposed, modeled, analyzed and verified. The structure contains a bent beam representing the engine, two sets of actuator and elastomer forming active paths, and a straight beam representing the chassis. Second, the force and phase of the active mounts at each location combination are calculated based on static and dynamic methods. The dynamic analysis method is used to examine how the control signal changes with the input signal to learn the correlation between them. The static analysis is employed to obtain the change in force applied to the paths when the position of the input signal changes and to find the optimized placement criteria. Through the position relationship between force and mounting, a specific position where the applied force is relatively small was considered the optimized position of the active mounting system. Finally, these criteria were verified with experiments and the results are matched well with each other.

Vibration and Noise of Diesel Engine Using Calophyllum inophyllum Biodiesel and MoO3 Nanoparticles: Experimental and Machine learning study

The current study deals with the evaluation of vibrations and noise generated by a diesel engine powered by Calophyllum inophyllum biodiesel blend (B20) and molybdenum trioxide (MoO3) nanoparticles, predicted using machine learning algorithms. The nanoparticles were spread out in B20 at a level of 75 ppm, along with a surfactant and a dispersant to make sure they mixed evenly with the fuel samples. The stability of the nanoparticles was then tested using the principle of photo spectroscopy and it was found that the stability of nanoparticles to which surfactants and dispersants had been added was increased. The experiment with the diesel engine was carried out to evaluate the vibrations and noise by varying different loads (3, 6, 9, and 12 kgf) and injection pressures (200, 220, and 240 bar). The vibrations and noise intensity were reduced with B20 compared to normal diesel and a further reduction was observed by adding nanoparticles together with the dispersant. With increasing load, the RMS velocity and the RMS noise also increased, but these decreased with increasing injection pressure. The most favourable result for RMS velocity and RMS noise was B20+MoO3 75ppm+ Dispersant 75ppm. At an injection pressure of 240 bar and a full load of 12 kgf, the RMS velocity was 0.568 m/s and 55.265 dB, which corresponds to an improvement of 28.76% and 9.78% respectively compared to conventional diesel for B20+MoO375ppm+ Dispersant 75ppm. Finally, the entire experimental data of 60 were predicted using various machine learning (ML) algorithms, such as Random Forest (RF), Decision Trees (DT), Artificial Neural Networks (ANNs), Support Vector Machines (SVM) and XG Boost and the predicted results correlated well with the experimental values. All algorithms have shown a good association, but XGBoost has shown a better correlation coefficient (R2). The R2 of each algorithm is in the range of 0.94-0.99, the MRE and RSME are also in the significant range for both RMS velocity and RMS noise.

Evaluating Engine Performance, Emissions, Noise, and Vibration: A Comparative Study of Diesel and Biodiesel Fuel Mixture

This study investigates the performance, emissions, noise, and vibration characteristics of a single-cylinder, air-cooled, four-stroke diesel engine running on pure diesel (D100) and biodiesel blends (B10: 90% diesel, 10% biodiesel; B20: 80% diesel, 20% biodiesel) at 1800 rpm, where the engine delivers maximum torque. Key metrics such as torque, power, brake specific fuel consumption (BSFC), exhaust gas temperature, noise, vibration, and emissions (CO, CO2, HC, O2, NOx, and smoke opacity) were analyzed. The findings indicate that B10 enhances torque, power output, and overall fuel efficiency, especially at low to medium loads, with a significant 17.54% reduction in BSFC compared to D100 at 40% engine load. Vibration levels generally increased with biodiesel addition, while B10 and B20 both reduced smoke opacity, with B20 having a more substantial effect. HC emissions decreased at idle with B10 but increased at higher loads, suggesting more complete combustion with potential thermal stress on engine components. Noise and vibration results were mixed; B20 reduced noise at higher loads but increased vibration. At 100% load, B20 decreased noise by 1.42% compared to D100. Despite benefits such as improved torque and reduced particulate emissions, biodiesel blends, particularly B20, led to increased NOx and CO2 emissions, emphasizing the need for further op-timization of blend formulations and emission control strategies. This study provides valuable insights into the tradeoffs and potential of biodiesel blends as sustainable diesel alternatives.

Analysis of transmission pathways of combustion-induced vibration in a diesel engine using wavelet cross-correlation analysis method

We experimentally investigated the transmission pathways of the combustion-induced vibration by analyzing the in-cylinder pressure, the accelerations on walls near the combustion chamber and the main bearing with wavelet cross-correlation analysis which can obtain both time delay and the correlation on the time between two signals in the frequency domain. The analysis shows that there are three possible transmission pathways of vibration from the combustion impact. First is a direct transmission from the combustion chamber to a wall near the combustion chamber or a wall near the main bearing via an engine surface wall, second is the transmission from the combustion chamber to a wall near the main bearing via the piston, connecting-rod and the crankshaft, and third is a transmission from the combustion chamber to a wall near the main bearing and there is no transmission to a wall near the combustion chamber.

Sparse regularized graph pooling network optimal sensor placement method for diesel engine vibration fault perception system

Vibration sensor network optimization increases monitoring effectiveness and reduces sensor quantity and transmission burden. However, the traditional model-driven methods depend on precise finite element models, challenging for complex machinery. This paper presents a data-driven approach using the Sparse Regularized Graph Pooling Network (SRGPN), which conceptualizes sensor networks as graphs and uses graph pooling to identify optimal sensor combinations. A sparsity regularization term related to the number of sensors is included in the loss function, aiming for the minimal yet effective sensor combination. Additionally, a monitoring capability metric suited for diesel engines with multi-source impulse signals is proposed, reflecting the sensors’ monitoring capacity. Validated through simulations and tests on a diesel engine test bench, the results show that SRGPN optimally places sensors near excitation sources, balancing sensor count and monitoring needs. This approach shows potential for optimizing sensor placements in condition monitoring.

Optimization of aero-engine condition monitoring by autoregressive model analysis based on wireless communication

The high value of aero-engines makes it necessary to extend their life in terms of econ-omy of use. Health management is an important basis for this work. Background: The vibration signal is an important representation of the working state of an aero-engine. The current usual method is based on wired communication with simple waveform presentation. The many incon-veniences of this method have seriously affected the further development of this work. Methods: This research team acquires engine vibration signals in real time through a designed wireless signal sensor, and then analyzes and visualizes the signals in depth. Results: Through this method, it can visually and effectively demonstrate signal characteristics for engineers, effectively identify fault signals, and monitor engine operating conditions in real time. Conclusions: The method enables the optimization of aero-engine work-state monitoring.

Numerical study on the forward and inverse problems of the mobile pump truck frame

Aiming at the requirements of strong mobility and high flexibility of rescue and relief mobile pump trucks, this paper designs a new type of mobile pump truck frame based on existing mobile vehicle frame models. The materials used for the frame are 40Cr and Q235, and the finite element method is utilized to carry out static mechanical analysis and dynamic characteristic analysis. Simultaneously utilizing topology optimization and multi-objective genetic algorithm to optimize the design of the frame structure. The results show that the optimized pump truck frame can meet the strength design requirements of four typical working conditions: full load bending, full load torsion, emergency turning and emergency braking, while avoiding resonance phenomena caused by road surface and diesel engine vibration. Compared with the original frame model, the weight of the optimized frame is reduced by 87.88 kg, with a weight reduction rate of 10.89%, realizing the lightweight design requirements.

Non-contact mechanical Q-factor measurement system based on electromagnetic acoustic transducer

The mechanical quality factor (Q-factor), which is the reciprocal of the vibration loss constant, is one of the most important parameters in vibration engineering; however, there are no methods for its precise measurement. Q-factor databases are thus commonly used. This study proposes a completely non-contact measurement system for the Q-factor that combines non-contact excitation (achieved using an electromagnetic acoustic transducer) with non-contact support (achieved using near-field ultrasonic levitation based on two Langevin transducers). The proposed method was used to measure the Q-factor for a stainless steel (SUS304) sample (thin cylindrical rod with a diameter of 1.5 mm and a length of 80 mm)and a duralumin (A2017). The 5 times average Q-factor was 2010 with standard deviation of 50 for stainless steel (SUS304), and 49,000 with standard deviation of 3900 for duralumin (A2017). The proposed method also allowed for the measurement of Young’s modulus, resulting in 217.17 ± 0.34 GPa for stainless steel (SUS304), and 71.39 ± 0.20 GPa for duralumin (A2017).

Fault diagnosis of new type screw compressor of helium liquefier by vibration signal

A diagnostic method for screw compressor faults using vibration signals was introduced and applied to a new type of helium oil-injected screw compressor in the 80L/h helium liquefier. The study revealed that the destruction of the oil film due to impurity particles could lead to rotor rubbing and poor meshing, compromising the reliability of these compressors. Based on frequency-domain analysis, the major vibration occurred at the meshing frequency of screw rotors and a series of its harmonics. The vibration of the characteristic frequency of bearing parts also indicated that the bearing had slight wear in the early stage. The vibration waveform’s time domain diagram exhibited clear clipping, and the axis trajectory shew disorder, which were common characteristic of rotor rubbing. When compressing helium with low molecular weight, the meshing clearance, tooth tip clearance, and end clearance of the rotor were significantly lower than those of traditional refrigerants or air media. Additionally, the thermal gap caused by thermoelastic deformation was smaller due to the large adiabatic index of helium. Therefore, rubbing faults between rotors and between rotors and casing were more likely to occur. The article recommended establishing a vibration signal monitoring system, optimizing the design of helium screw rotor profiles, and setting up reliability standards for screw compressor operation, such as limiting the vibration speed to ≤ 8 mm/s. Additionally, attention should be given to cleaning gas pipelines in cryogenic engineering and monitoring compressor vibration and noise signals during operation to prevent rotor damage due to particle impurities.

Mechanism of eccentricity influence on 3-DOF aerodynamic stability: New insights into instability evolution, energy harvesting, and vibration control

The inconsistency of mass center and elastic center, i.e., eccentricity, widely exists in various engineering structures and components, including iced conductors, wind turbine blades, airfoils, and cable-supported bridges, and can also be extended to the application of energy harvesting and vibration control. Although the eccentricity influence on aerodynamic stability has already been recognized as important, the underlying mechanism remains rather unclear. This study established a comprehensive framework of explicit eigenvalue solutions, offering in-depth insights into the aerodynamic stability mechanism in a vertical-horizontal-torsional 3-degree-of-freedom linear system under all possible frequency scenarios. These solutions elucidated the coupling mechanism of eccentricity, aerodynamic damping, aerodynamic stiffness, and structural frequencies. Remarkably straightforward criteria to predict the promoting/suppressing effect of eccentricity were proposed, consisting of eccentric angle and aerodynamic forces, which not only align with the traditional principles but also offer a broader application range in terms of structure types and wind speeds. Validations of the proposed solutions were performed for all frequency cases via numerical studies. For instability tendency evaluation, numerical studies on a thin plate showed that eccentricity has a significant impact due to the strong aerodynamic effect and large ratio of width/gyration radius, highlighting the importance of considering small eccentricity errors during experiments. Examination for energy harvesting revealed that a small eccentricity can dramatically enhance power generation efficiency, and the explicit solutions successfully explained the rules governing performance changes against frequency ratio, mass center position, rotation center position, etc. The analysis of a bundled conductor showed that the double pendulum can control galloping because it diminishes the eccentricity effect by shifting the eccentric angle. The proposed explicit solution framework provides a systematic view and new insights into the aerodynamic instability mechanism influenced by eccentricity, serving as a reference for the design and studies of various engineering structures, energy harvesting, and vibration control.

K-means clustering optimization of various quantum dots and nanoparticles-added biofuels for engine performance, emission, vibration, and noise characteristics

The utilization of biodiesel as a bio-lubricant, combined with various types of nanoparticles, and quantum dots presents an innovative approach towards enhancing the performance of diesel engines. In this study, biodiesel was blended with different nanoparticles to improve its lubricating properties, and the k-means clustering method was applied to identify the optimal nanoparticle that maximizes the performance of the diesel engine. The experiment involved synthesizing biodiesel-based lubricants infused with nanoparticles of varying compositions, including but not limited to carbon nanotubes, graphene oxide, and metal oxides. The successful implementation of the Entropy-k-means hybrid model facilitated the identification of the optimal bio-lubricant for diesel engines. The experimentation uncertainty came out to be 4 % which lies in an acceptable range. Additionally, a strong Pearson r correlation was observed between Brake Thermal Efficiency (BTE) and Sound, highlighting their interrelationship. Moreover, the prioritization analysis indicated that NOx obtained the highest priority at 0.45, contrasting with the lowest priority attributed to sound at 0.01. Furthermore, the clustering analysis conclusively identified magnetic bio-lubricant as the top-performing option with minimum centroidal distance of 1.2. The optimal outcomes are BTE (30.5 %), Brake Specific Fuel Consumption (191.5 g/kWh), NOx (88 ppm), CO (7.1 g/km), Vibration (68.5 Hz), and Sound (74.5 dB). The application of k-means clustering facilitated the identification of the most effective nanoparticle for enhancing engine performance, thereby contributing to the advancement of sustainable lubrication technologies in the automotive industry.

Fault Diagnosis of Marine Diesel Engine Based on Multi-scale Time Domain Decomposition and Convolutional Neural Network

Abstract Marine diesel engines work in an environment with multiple excitation sources. Effective feature extraction and fault diagnosis of diesel engine vibration signals have become a hot research topic. Time-domain synchronous averaging (TSA) can effectively handle vibration signals. However, the key phase signal required for TSA is difficult to obtain. During signal processing, it can result in the loss of information on fault features. In addition, frequency multiplication signal waveforms are mixed. To address this problem, a multi-scale time-domain averaging decomposition (MTAD) method is proposed and combined with signal-to-image conversion and a convolutional neural network (CNN), to perform fault diagnosis on a marine diesel engine. Firstly, the vibration signals are decomposed by MTAD. The MTAD method does not require the acquisition of the key phase signal and can effectively overcome signal aliasing. Secondly, the decomposed signal components are converted into 2-D images by signal-to-image conversion. Finally, the 2-D images are input into the CNN for adaptive feature extraction and fault diagnosis. Through experiments, it is verified that the proposed method has certain noise immunity and superiority in marine diesel engine fault diagnosis.

Recursive Engine In-Cylinder Pressure Reconstruction Using Sensor-Fused Engine Speed.

The engine in-cylinder pressure is a very important parameter for the optimization of internal combustion engines. This paper proposes an alternative recursive Kalman filter-based engine cylinder pressure reconstruction approach using sensor-fused engine speed. In the proposed approach, the fused engine speed is first obtained using the centralized sensor fusion technique, which synthesizes the information from the engine vibration sensor and engine flywheel angular speed sensor. Afterwards, with the fused speed, the engine cylinder pressure signal can be reconstructed by inverse filtering of the engine structural vibration signal. The cylinder pressure reconstruction results of the proposed approach are validated by two combustion indicators, which are pressure peak Pmax and peak location Ploc. Meanwhile, the reconstruction results are compared with the results obtained by the cylinder pressure reconstruction approach using the calculated engine speed. The results of sensor fusion can indicate that the fused speed is smoother when the vibration signal is trusted more. Furthermore, the cylinder pressure reconstruction results can display the relationship between the sensor-fused speed and the cylinder pressure reconstruction accuracy, and with more belief in the vibration signal, the reconstructed results will become better.

Theoretical modeling and analysis of an equipment–shell multiple-transmission-path system with attached liquid-filled pipe

Vibrations generated by mechanical equipment are the main source of radiation noise for ships. In actual systems, there are multiple transmission paths for mechanical vibrations from the equipment to shell. Common paths include vertical support structures, such as vibration isolators, and lateral attachment structures, such as pipes. However, most existing models only consider a single-path scenario. Multi-path systems have more complex modal and vibration transmission characteristics and introduce more complex coupling problems. There is a lack of theoretical modeling and physical analyses of common multiple transmission systems in ships. In this study, a theoretical model of an equipment–shell multiple-transmission-path system with an attached liquid-filled pipe is established as a typical multiple-transmission-path system for ships. In this model, the liquid-filled pipe is solved using a newly proposed traveling-wave method based on Kennard shell theory. Based on the theoretical model, the effects of each type of traveling wave on the pipe on the system modal characteristics, the mechanism behind each path on the system coupling characteristics, the influence of structural parameters on system modal and vibration transmission characteristics, and the proportion of vibration transmitted by the two transmission paths are analyzed. This study provides theoretical insights and guidance for practical vibration and noise reduction engineering.

A Study on the Influence of Radial Spoiler Arrangement on the Combustion Process of Wankel Rotor Engines

Wankel rotor engines are widely used in various fields due to their high power density and simple structure. This paper presents the optimisation of the Wankel rotor engine by simple modifications of the structure. We propose a radial spoiler arrangement scheme that can affect the flame propagation speed and reaction severity by altering the flow field distribution and pre-reaction distribution in the cylinder. By comparing the effects of four layout schemes on flame propagation speed and reaction intensity, including no spoilers, radial spoilers deflected at an angle of 10° in the negative direction of the Z-axis, radial spoilers deflected at an angle of 10° in the positive direction of the Z-axis, and radial spoilers arranged at the centre of the rotor combustion chamber, the benefits of different layout schemes were evaluated. We conducted a study on the influence of the arrangement of radial spoilers on the combustion process of a Wankel rotary engine through theoretical calculations. This helps to reduce engine vibration, improve engine operation stability, and enhance engine performance.

Design of diesel engine vibration signal acquisition system based on Zynq

Design of diesel engine vibration signal acquisition system based on Zynq

Frequency response sensitivity to crack for piezoelectric FGM beam subjected to moving load

Since functionally graded material (FGM) is increasingly used in high-tech engineering, free and forced vibrations of FGM structures become an important issue. This report addresses the analysis of frequency response sensitivity to crack for piezoelectric FGM beams subjected to moving load. First, a frequency domain model of a cracked FGM beam with a piezoelectric layer is conducted to derive an explicit expression of the electrical charge produced in the piezoelectric layer under the moving load. It was shown in the previous works of the authors that the electrical charge is a reliable representation of the beam frequency response to moving load and can be efficiently employed as a measured diagnostic signal for structural health monitoring. Then, a damage indicator acknowledged as a spectral damage index (SDI) calculated from the electrical frequency response is introduced and used for sensitivity analysis of the response to crack. Under the sensitivity analysis the effect also of FGM and moving load parameters on the sensitivity is examined and illustrated by numerical results.