This article presents a dataset generated from a cylindrical plunge grinding process conducted in an industrial piston ring manufacturing environment. The data aim to support studies focused on process capability, variability, robustness, parameter optimization, and modelling approaches in grinding research. The experimental conditions were defined following a Central Composite Design for k = 4 factors and axial distance ρ=1.5, which established the levels of Wheel infeed rate, Dressing speed, Grinding wheel peripheral speed, and Dressing depth. These parameter combinations were carried out on the shop floor under real production constraints, ensuring that the collected measurements represent industrial operating conditions rather than laboratory simulations. Two external noise factors were considered during data collection, consisting of the different mandrels and the position of the piston ring within the production package. These noise sources reflect variations commonly encountered in manufacturing and allow researchers to investigate the robustness and sensitivity of dimensional responses. A CCD with thirty runs, being sixteen factorial points, eight axial points, and six center points, organized in two blocks of experiments, was performed, associated with four noise combinations, defined according to an experimental plan. For every condition, ten repeated measurements, represented by ten piston rings sampled from the package and assembled in different mandrels, were acquired using the dimensional control fixture routinely employed in the industry, forming a dataset of 1200 runs. This procedure ensured consistency with existing quality inspection practices and provided a rich structure suitable for repeatability and uncertainty analyses. The dataset includes raw measurements, process parameters, and experimental identifiers that enable multilevel exploration of machining performance. Its structure supports diverse analytical applications, including modelling of process capability, variability, evaluation of noise effects, optimization of input parameters, statistical analysis of repeated measures, and the development or validation of data-driven and machine learning methods. Owing to its industrial origin, the dataset offers realistic variability patterns and is relevant for comparative studies, benchmarking activities, and the development of predictive or robust design frameworks in manufacturing research.

Oil transport mechanisms in piston ring assembly: CFD analysis with consideration of ring motion and deformation

Evolution of the tribofilm and wear state transition mechanism of cylinder liner and piston ring

This study investigates the applicability of diesel cranking with an external power source for evaluating piston ring friction. Experiments were conducted on an air-cooled 2Ch10.5/12 diesel engine with a nominal power of 22 kW. The temperatures of the motor oil in the crankcase and of the ambient air were maintained constant at 85 ± 1 °C and 30 ± 1 °C, respectively. Mechanical losses were evaluated by two methods: 1) diesel cranking with an external power source and 2) comparison of indicated and effective powers at 30 % of nominal engine load. Mineral oils I-20A, MS-20, as well as their mixtures, were used as motor oils during testing. Mechanical losses determined by diesel cranking with an electric motor were approximately 16 % lower than those determined by comparison of indicated and effective powers. Assuming that the major fraction of the reduction in mechanical losses is caused by a lower force pressing the piston rings against the cylinder wall, the friction coefficients of the piston rings were calculated. The obtained friction coefficient values exceeded those reported in scientific literature by more than five times. This indicates that the change in piston ring friction is not the main cause of the reduction in mechanical losses during the transition from motor operation to diesel cranking. Therefore, piston ring friction cannot be determined by comparing mechanical losses obtained in cranking and motor regimes. An analysis of the causes of the reduction in mechanical losses during the transition from motor operation to diesel cranking was carried out.

<div>To meet the requirements of luxury hybrid vehicles regarding engine power, torque, size, and NVH performance, BYD independently developed a 2.0 T flat engine. Designs such as increased intake valve lift, widened intake valve profile, swept piston bowl, and extended exhaust backflow region optimized in-cylinder airflow, enabling the BYD flat engine to achieve a maximum power of 180 kW and a peak torque of 380 N·m. This engine is 820 mm in length, 430 mm in width, and 420 mm in height, saving approximately 45% in volume compared to a competitor engine. The lubrication challenges of the flat engine were addressed through the coordinated implementation of a dry sump system, a multifunctional oil pump, and piston ring orientation design. A novel parameterized modal analysis methodology (considering phase and amplitude) was used for optimizing NVH performance. In synergy with the sandwich-type soundproof plates and four-sided acoustic encapsulation, the noise level (1-m sound pressure level, four-point averaged) of the BYD flat engine is 2.2~2.9 dB(A) lower than the lower limit of AVL’s scattering band. Owing to its desirable performance in power output, packaging compactness, and NVH characteristics, the BYD flat engine has been integrated into the powertrain of the Yangwang U7 model.</div>

Different lubricant deterioration, such as high-temperature oxidation lubricant (HOL), diesel dilution lubricant (DDL) and combined degradation lubricant (CDL), on the failure of micro-textured surfaces in terms of friction modulation was investigated. Deteriorated lubricant exerts obvious adverse effect on the antiwear performance of micro-textured surface, accelerating the wear damage of the tribopair consisting of a cast-iron liner and a molybdenum-sprayed ring. Compared to non-textured tribopair, HOL only increased wear loss of piston ring paired with micro-textured cylinder liners, while DDL containing diesel catalyst particles simultaneously increased the wear depth of both micro-textured cylinder liner and paired piston ring. CDL further exacerbated the DDL wear trend. The main type of damage caused by three degraded lubricants to micro-textured frictional surfaces was abrasive wear. Micro-textured surfaces trapped abrasive particles, separating the scratches along the sliding direction. But excessive stress concentration and scratches reduced the ability of ZDDP tribofilm to resist abrasive damage.

Abstract This study investigates how piston ring end gap sizes affect diesel engine performance, specifically their influence on exhaust gas temperature (EGT), crankcase pressure, and engine vibrations across various operating speeds. Using an Isuzu C190 engine, controlled experiments were conducted to better understand the combustion and mechanical processes influenced by changes in end gap size and their overall impact on engine efficiency. Results showed a clear and consistent decrease in EGT as the end gap increased: from 92°C to 72°C at idle, 134°C to 107°C at 10 km/h, and 187°C to 145°C at 40 km/h. This strong sensitivity indicates that EGT is highly responsive to ring gap changes. In contrast, crankcase pressure remained nearly constant across all conditions, varying only between 14.62–14.64 psi at idle and 14.51–14.55 psi at higher speeds, suggesting minimal influence from end gap size. The vibration results revealed more complex behavior. At idle, the lowest vibration occurred at 0.45 mm (321.99 mm/s²), while mid-range gaps of 0.8–0.9 mm produced the highest accelerations (396.53–663.82 mm/s²), indicating unstable combustion dynamics. ANOVA results reinforced these trends: EGT showed extremely significant dependence on end gap (p = 2.26×10 -14 to 1.29×10 -25 ; η 2 = 0.9831–0.9993), crankcase pressure was significant only at 40 km/h (p = 0.0157; η 2 = 0.4674), and vibration demonstrated a strong effect only at idle (p = 6.59×10 -4 ; η 2 = 0.8703). Overall, the findings highlight exhaust gas temperature as a reliable diagnostic indicator for early piston ring end gap faults across all operating speeds. This research contributes to improved diagnostic methods and a deeper understanding of how piston ring behavior affects diesel engine performance, encouraging further investigation into these component–performance relationships.

This paper focuses on the challenge of predicting the components and full-engine reliability of automotive diesel engines and proposes an integrated approach combining mechanistic modeling with statistical data. The mechanism model was developed for engine performance, dynamics, as well as wear and fatigue damage of critical components. Uncertain parameters were processed using Monte Carlo and Latin hypercube sampling methods to compute damage distributions and reliability curves for both components and full-engine system. Using a specific automotive diesel engine as a case study, the wear model of the main bearing shell was verified on the reliability test bench, with an error of only 2.03%. Damage calculations were conducted on several critical components, the results demonstrate that damage to the components conforms to the cumulative damage phenomenon, moreover, the damage distribution for the piston ring and exhaust valve exhibits an increasing dispersion under the effects of stochastic influences. The reliability curves align with the bathtub curve . The mechanism model yields a full-engine MTBF of 7091 h (242,000 km), a B10 life of 6050 h (206,000 km), and a system-wide MTBF of 1490 h (50,000 km) after integrating subsystem failure rates. This methodology offers effective tools for engine reliability design and predictive maintenance.

Reciprocating compressors, which serve as core equipment in the petrochemical and natural gas transmission sectors, operate under prolonged variable loads and high-frequency impact conditions. Critical components, such as valves and piston rings, are prone to failure. Existing fault diagnosis methods suffer from inadequate spatio-temporal feature extraction and neglect spatio-temporal correlations. To address this, this paper proposes a spatio-temporal feature fusion-based fault diagnosis method for reciprocating compressors. This method constructs a spatio-temporal feature fusion model (STFFM) comprising three principal modules: First, a spatio-temporal feature extraction module employing a multi-layered stacked bidirectional gated recurrent unit (BiGRU) with batch normalisation to uncover temporal dependencies in long-term sequence data. A graph structure is constructed via k-nearest neighbours (KNN), and an enhanced graph isomorphism network (GIN) is integrated to capture spatial domain fault information variations. Second, the spatio-temporal bidirectional attention-gated fusion module employs a bidirectional multi-head attention mechanism to enhance temporal and spatial features. It incorporates a cross-modal gated update mechanism and learnable weight parameters to dynamically retain the highly discriminative features. Third, the classification output module enhances the model’s generalisation capability through multi-layer fully connected layers and regularisation design. Research findings demonstrate that this approach effectively integrates spatio-temporal coupled fault features, achieving an average accuracy of 99.14% on an experimental dataset. This provides an effective technical pathway for the precise identification of faults in the critical components of reciprocating compressors.

Effect of piston ring configuration on squeeze film damper performance with focus on axial and slit positions

The opposed rotary piston (ORP) engine represents as a promising power source for unmanned aerial vehicles (UAVs), due to its structural simplicity and exceptional power density. But the rotary piston motion gives rise to significant gas leakage challenges, which critically deteriorate engine performance. This study conducts a systematic analysis of the existing sealing configuration and establishes computational fluid dynamics (CFD) models to quantify cylinder gas leakage. The results demonstrate that strategic placement of piston rings between rotating shaft contact surfaces effectively reduces leakage flows. Reducing the engine load from 100% to 60% decreased leakage through the rotating shaft contact surfaces from 5.755 × 10 −5 to 1.841 × 10 −5 kg. Concurrently, decreasing fit clearance decreased from 0.1 to 0.06 mm reduced the circulating leakage between shafts from 5.755 × 10 −5 to 2.942 × 10 −5 kg, corresponding to a 48.8% reduction. Additionally, combustion gas blowby between adjacent chambers exhibits load-dependent characteristics, decreasing from 6.74 × 10 −6 to 1.17 × 10 −7 kg when the engine load decreases from 100% to 60%. Analysis of the sealing strip-groove interface confirms that leakage rates and gas velocities exhibit inverse proportionality to clearance dimensions.

Purpose Starting from the wear mechanism, based on the Archard wear model, the wear of the CLPR at different wear stages was modeled. Considering the influence of the physical and chemical indexes of the lubricating oil on the lubrication condition of the CLPR and the influence of the wear particle deposition effect on the change of the dynamic concentration of the wear particle, the dynamic concentration model of the internal combustion engine lubrication system at different wear stages was established. The change trend of the dynamic concentration of the wear particle in the CLPR’s lubrication system was quantified, and the evolution of the wear particle concentration was revealed, which provided support for the condition monitoring and predictive maintenance of the ICE. Design/methodology/approach First, a quantitative characterization and prediction method for wear of cylinder liner piston system (CLPS) based on online wear particle monitoring is proposed. Second, based on the wear mechanism of cylinder liner piston ring, considering the influence of abrasive deposition effect and wear nonstationary characteristics, the dynamic concentration model of cylinder liner piston ring with different wear stages of internal combustion engine lubrication system is established based on Archard wear theory, and the evolution law of abrasive concentration is simulated. Finally, the whole life wear monitoring test was carried out on the self-made test rig. Findings The physical and chemical indexes (viscosity and temperature) of lubricating oil in the CLPS at three working conditions were monitored. The monitoring results showed that the viscosity of lubricating oil decreased by 40.7 %, 45.9 % and 44.5 %, respectively, after 1,200th min monitoring test, and the temperature of lubricating oil increased by 58.2 %, 67.9 % and 64.6 %, respectively. The temperature of lubricating oil was negatively correlated with viscosity. With the increased temperature, the viscosity of lubricating oil decreased, which aggravated the wear of CLPR. By controlling the temperature of lubricating oil, the influence of temperature on the viscosity reduction of lubricating oil can be slowed down, which was beneficial to reduce the wear of CLPR. Originality/value The wear particle sedimentation coefficient was established, and the dimensionless wear coefficient K was revised. The dynamic concentration model of cylinder liner piston lubrication system in different wear stages is established. The experimental verification was carried out on the self-made test rig. The relationship between wear and temperature, viscosity was analyzed.

This study investigates the tribological performance of an electroless NiP-CNT nanocomposite coating developed for cast iron substrates, aiming to enhance the durability of the material for automobile piston ring applications. A low concentration of CNTs (0.5 g/L) was incorporated into the NiP bath, leveraging their superior strength, heat resistance, and self-lubricating nature. The NiP-CNT nanocomposite coating was synthesized via electroless plating, and their tribological response was assessed across varying temperatures and lubrication states. The coating exhibited a uniform nodular morphology, improved microhardness (from 325 HV for CI to ~516 HV for NiP-CNT), reduced surface roughness, and refined nanocrystalline structure (~15 nm). Tribological tests performed at room temperature, elevated temperature (350 · C), and boundary-lubricated conditions showed a significant reduction in wear rate and wear depth for the NiP-CNT coating compared with uncoated and NiP-coated substrates. Worn surface analysis revealed smoother tracks, fewer abrasive grooves, and the formation of a stable CNT-assisted tribolayer. Overall, the NiP-CNT coating markedly improved load-bearing capability and wear resistance across all operating conditions.

Blow-by is a condition in which combustion gases from the combustion chamber escape through the piston and piston ring gap into the crankcase. This symptom leads to reduced engine performance, increased fuel consumption, and accelerated component wear. This research aims to analyze the causes of blow-by in the Caterpillar D3K-XL Bulldozer engine and to determine the appropriate troubleshooting steps. The research methods include field study, operator interviews, and direct inspection of engine components such as piston rings, cylinder liners, and valves. The results indicate that the main causes of blow-by are worn piston rings and scratches on the liner wall due to insufficient periodic maintenance. Corrective actions were carried out through replacement of worn components, cleaning, and reassembly according to manufacturer standards. These improvements successfully restored engine performance and minimized the risk of further damage.

Purpose This study aims to provide a stress-strain calculation model that considers nonlinear transient thermo-structural deformation to simulate the assembly and operation processes of a spring-energised seal ring. Design/methodology/approach The assembly process and working conditions of the seal ring, along with the transient deformation caused by friction between the sealing surface and the cylinder and the motion of the piston, are investigated. Based on the leakage model of the high-pressure multi-stage seal ring and nonlinear constitutive theory, a comparison between the spring-energised seal ring and a traditional multi-piece piston ring is performed. Findings Results reveal that the sealing performance and service life of the 4.4 mm seal ring are superior to those of the 3.3 mm ring, consistent with experimental findings. Piston motion significantly influences the leakage model, with leakage rates decreasing as the friction coefficient increases. However, as the roughness of the cylinder's inner surface increases, the leakage rate of the seal ring also increases. The spring-energised seal ring offers better sealing performance than the traditional multi-piece piston ring, although with a shorter service life. Originality/value This study proposes a novel approach for stress-strain calculations that accounts for nonlinear transient deformations. The stress-strain distribution and leakage rate of the sealing rings are comprehensively analysed, and the causes of sealing failure are identified.

This study analyzes the effect of the use of B30/B35 biodiesel on the wear of heavy equipment engine components in the Indonesian mining industry. Through a longitudinal experimental design for 12 months, the study was conducted on 24 units of heavy equipment consisting of excavators, bulldozers, and articulated dump trucks in three different mining locations: a coal mine in East Kalimantan, a nickel mine in Southeast Sulawesi, and a gold mine in Papua. The results show that the use of B30/B35 biodiesel consistently reduces the wear rate of components compared to conventional diesel. Nozzle injector wear in the biodiesel group is 18.6% lower, piston ring wear is 15.3% lower, cylinder liner wear is 12.7% lower, and bearing wear is 14.2% lower. SEM and EDS analysis revealed that biodiesel forms a tribochemical layer on metal surfaces that reduces direct contact between surfaces and minimizes wear. The analysis of the lubricant showed lower concentration of metal particles and better lubricant quality parameters in the biodiesel group. The developed predictive model indicates an extension of component life of around 15-20% with the use of biodiesel, potentially providing maintenance cost savings of 12-18% per year. These findings change the perception that the use of biodiesel is solely regulatory compliance, to an operational strategy that provides economic and technical benefits. This study provides a scientific basis for the optimization of preventive maintenance programs for mining heavy equipment that uses biodiesel and supports the sustainability of the implementation of the national mandatory biodiesel policy.

The production of piston ring blanks from gray cast iron by the method of individual casting is complicated by the fact that the required structure of graphite and metal matrix is formed directly during the crystallization process without the use of heat treatment. In this regard, there is a need for strict control of both the chemical composition of the starting cast iron and the parameters of the casting process. The influence of overheating temperature, holding time and melt pouring temperature on the hardness and structure of cast blanks of compression piston rings of different sizes at a given chemical composition of cast iron (in wt.%) was assessed: C=3.72; Si=2.82; Mn=0.79; P=0.4; S=0.045; Ni=0.23; Cr=0.26; Cu=0.48; Mo=0.53; Ti=0.05. It is shown that fluctuations in the temperature of overheating and pouring of the melt within 10–50 °C and its holding time within 1–11 min. do not cause systemic changes in the hardness and microstructure of castings of ring blanks made of gray cast iron. The hardness along the blank rings is not uniform and is 94–112 HRB, which meets the requirements of GOST 621-87 "Piston rings for internal combustion engines". It has been established that the structure of graphite and metal matrix of castings of ring blanks from gray cast iron, despite compliance with the technological process of their production, often does not meet the requirements of the specified standard. The maximum size of graphite inclusions is 120–250 μm, which exceeds the required size of 80 μm according to GOST 621. To achieve compliance with the requirements of GOST 621-87 regarding the structure of graphite and the metal matrix, as well as to prevent a decrease in hardness after heat treatment of cast ring blanks, it is necessary to reduce the maximum size of graphite inclusions to 80 microns and ensure the formation of dispersed pearlite with no more than 5% hypoeutectoid ferrite. To obtain the required graphite structure and metal matrix, it is important not only to maintain the stability of the casting process, but also to adjust the composition of the cast iron melt taking into account the content of gases (O, N, H). Their concentration is directly related to the origin of the charge materials, among which blast furnace iron and secondary metal from our own production are of primary importance.

Abstract Piston rings are critical components of internal combustion engines, ensuring sealing between the piston and cylinder and thus directly influencing engine performance, reliability, and service life. Although graphite cast iron is commonly used for their production due to its favorable tribological properties, wear resistance, and self-lubricating ability, premature failures such as cracking and subsequent fracture may still occur during service. This study aims to identify and analyze the primary causes of piston ring cracking in graphite cast iron using a combination of experimental and analytical methods. The investigation includes macroscopic and microscopic examination of fracture surfaces, metallographic and fractographic observations, and chemical composition analysis of the material, with particular attention given to the morphology of graphite. The results provide deeper insight into the degradation mechanisms of piston rings and propose recommendations for optimizing manufacturing processes, tailoring microstructure, and improving operating conditions to enhance service life and reliability.

This study examines the effectiveness of C60 fullerenes as additives to improve lubricant performance in piston ring–cylinder liner tribological systems. Viscosity measurements of synthetic and fullerene-based oils were performed using a capillary tube viscometer under varying temperature and pressure. The data were incorporated into a CFD model of compression piston ring to assess friction, cavitation, and hydrodynamic pressure. Cavitation effects were also investigated and commented on. Results show that fullerene-enhanced lubricants retain higher viscosity at elevated temperatures and reduce friction force, enhancing engine efficiency and emission characteristics.

This paper proposes an incremental intelligent fault diagnosis method for marine diesel engines based on a Convolutional Neural Network (CNN)-Transformer architecture and cosine similarity. The method is designed to address critical limitations of conventional supervised diagnostic frameworks, including heavy reliance on labeled data, weak cross-condition generalization, and the inability to identify new or evolving fault types. The model first employs CNN to extract local temporal features from vibration signals and then uses a Transformer to learn high-level semantic representations of fault attributes. During the incremental learning phase, known fault classes—such as exhaust valve failures—are used to train the model. In the testing phase, the model calculates the cosine similarity between feature embeddings of unseen samples and the prototypes of known classes in the attribute space to determine their classification or novelty. This mechanism enables effective identification of both known and novel faults, including those in cylinder liners and piston rings, without requiring prior labeled data for the latter. Experimental results demonstrate that the proposed approach achieves superior classification accuracy, robustness, and adaptability compared to traditional supervised methods, offering a scalable and generalizable solution for intelligent marine diesel engine fault diagnostics.