Based on signal decomposition, a tractor engine state recognition method is proposed to explore the degree of information recognition of vibration signals at measurement points at different distances from the engine and the degree of correlation in different directions. The accuracy of engine operating state information recognition was obtained by analyzing the vibration signals of the tractor at different measurement points. The main contents are as follows: Based on variational mode decomposition (VMD), the modal component, which includes the state information, was obtained by measuring the vibration signal of the tractor at each measurement point under different driving conditions, and the exogenous excitation of the tractor under different road conditions was simulated by changing the tire pressure. Then, the state characteristics of the modal component were quantified based on permutation entropy (PE), and the correlation coefficient was used as the evaluation index to select the... [more]

Stall flow patterns occur frequently in pump turbines under off-design operating conditions. These flow patterns may cause intensive pressure pulsations, sudden increases in the hydraulic forces of the runner, or other adverse consequences, and are some of the most notable subjects in the study of pump turbines. Existing methods for identifying stall flow patterns are not, however, sufficiently objective and accurate. In this study, a convolutional neural network (CNN) is built to identify and analyze stall flow patterns. The CNN consists of input, convolutional, downsampling, fully connected, and output layers. The runner flow field data from a model pump−turbine are simulated with three-dimensional computational fluid dynamics and part of the classifiable data are used to train and test the CNN. The testing results show that the CNN can predict whether or not a blade channel is stalled with an accuracy of 100%. Finally, the CNN is used to predict the flow status of the unclassifiable... [more]

In this article, the authors assumed that the “iGeneration” is the leading driving force for the SMART orientation of modern cities. Dynamic and multidirectional technical and technological processes introduce a new level of changes in urban space, adapting it to the present and future requirements of its inhabitants in a sustainable manner. An important infrastructure element of the urban space is the crosswalk, being an inseparable element of everyday life in the city. As part of a clear emphasis on the issue of vulnerable road users’ protection, the aim of the article is to examine the perception of users regarding crosswalks in Poland, based on the example of Szczecin. The main aim of the article is to identify the dimensions of crosswalk perception. The specific objectives include the determination of the state of knowledge about the essence and typology of crosswalks and the identification of good practices in their designation. Literature analysis, questionnaire research, and a... [more]

High-order harmonics in the traction power supply show negative effects on the safe and stable operation of the railway transportation system. There is a fixed resonant frequency in the traction network. When the harmonic current frequency produced by the locomotive matches the resonant frequency of the traction network, it will cause high-frequency resonant overvoltage. The propagation path of the high-order harmonics of the traction load is analyzed based on a V/v wiring traction transformer. The propagation characteristics of high-order harmonics on self-used equipment at 380 V low-voltage side and 27.5 kV high-voltage side are expounded. A simulation model for the low-voltage self-consumption power system is established and the singular value decomposition algorithm is proposed to identify the harmonic impedance. The simulation results show that the proposed method can reduce the error to within 0.1%. Under realistic conditions, the overvoltage caused by high-order harmonics is dif... [more]

Although the interest in metallurgical accident investigation of blast furnace gas (BFG) leakage has increased to explore the engineering failures, more effort is needed to address the individual and organizational causative factors to clear and determine the weak links for improving safety management and accident prevention to achieve green metallurgical manufacturing. This study aims to examine the causative factors and evolution paths of BFG leakage by introducing a combined method, the 24 model and Bayesian network (BN), based on 50 cases of fire, explosion and suffocation accidents caused by BFG leakage. A BN model of BFG leakage was established based on the identification of 25 causative factors by the 24 model. Results showed that eight nodes, including A1 (unsafe operation), A2 (unsafe behavior), A4 (unsafe condition), B1 (valve failure), B2 (improper gas safety operation), X4 (use of BFG violates regulations), X5 (water gas is not cut off before shutdown reduction) and X6 (inc... [more]

The scientific judgement of the structural abrupt transition characteristics of the carbon market price is an important means to comprehensively analyze its fluctuation law and effectively prevent carbon market risks. However, the existing methods for identifying structural changes of the carbon market based on carbon price data mostly regard the carbon price series as a deterministic time series and pay less attention to the uncertainty implied by the carbon price series. We propose a framework for identifying abrupt transitions in the carbon market from the perspective of a complex network by considering the influence of random factors on the carbon price series, expressing the carbon price series as a sequence of probability density functions, using the distribution of probability density to reveal the uncertainty information implied by carbon price series and constructing a recurrence network of carbon price probability density. Based on the community structure, the break index and... [more]

In this paper, a microscopic oil displacement visualization experiment based on the glass etching model to simulate the tight oil reservoir of underground rocks is carried out. At present, water flooding technology is widely used in the development of oil and gas fields, and the remaining oil content is still very high after water flooding. It is the key to improving oil recovery to identify and study the remaining oil form distribution after water flooding. The experiment result shows there are five types of residual oil after water flooding: columnar residual oil, membranous residual oil, oil droplet residual oil, blind terminal residual oil and cluster residual oil. A convolution neural network is suitable for complex image characteristics with good robustness. In recent years, it has made a breakthrough in a set of small and efficient neural networks with SqueezeNet, Google Inception and the flattened network method put forward. In order to solve the problems of low automation, low... [more]

Although a mixed carbonate−siliciclastic system of the Strawn Group on the Eastern Shelf in King County, Texas, USA provides excellent hydrocarbon reservoirs, facies variability and reservoir properties within such systems are not well understood. We conducted prestack, simultaneous seismic inversion, and high-level petrophysical analysis to derive elastic properties of rocks to facilitate lithology identification and determination and distribution of the different carbonate facies. Our results show that (1) the Strawn Group in King County is dominated mostly by carbonates and (2) given the ratio of P- and S-wave velocity (Vp/Vs ratio), the carbonates can be separated into three facies: (a) high-Vp/Vs-ratio shelf-edge reef carbonates, in which the Vp/Vs ratio decreases linearly as porosity increases and the Vp/Vs ratio varies from ~2.1 to ≤2.6; (b) moderately low-Vp/Vs-ratio shelf (platform) carbonates, in which the Vp/Vs ratio also decreases as porosity increases and in which the Vp/V... [more]

This article presents an analysis of the driveline operation of a high-mobility Jelcz 442.32 wheeled vehicle, which uses rigid drive axles connected to drive shafts with two universal joints (another name for the Cardan joints) due to the occurrence of kinematic incompatibility. The conditions for the correct connection of the drive shafts with two universal joints (Cardan joints) were presented, and the kinematic ratio of the complete drive shaft was defined. In the analysis of kinematic incompatibility regarding (but not limited to) the method of loading the vehicle, selected characteristic conditions of vehicle movement and the initial values of the angular setting of the rigid driving axles in relation to the vehicle body were presented. It has been shown that, in the analyzed vehicle, the kinematic incompatibility in the driveline is constantly present, and the value of this incompatibility, represented by the temporary ratio of drive shafts, depends on, among other things, the wa... [more]

Asynchronous loads (AL), because of their low negative-sequence resistance, produce the effect of reduced unbalance at their connection points. Therefore, proper modeling of unbalanced load flows in power supply systems requires properly accounting for AL. Adequate models of the induction motor can be realized in the phase frame of reference. The effective use of such models is possible only if accurate data on the parameters of induction motor equivalent circuits for positive and negative sequences are available. Our analysis shows that the techniques used to determine these parameters on the basis of reference data can yield markedly disparate results. It is possible to overcome this difficulty by applying parameter identification methods that use the phase frame of reference. The paper proposes a technique for parameter identification of models of individual induction motors and asynchronous load nodes. The results of computer-aided simulation allow us to conclude that by using para... [more]

China and Russia have different interests in the Arctic but are forced to look for possible ways of cooperation in energy projects in the current external conditions. This changes the priorities of both countries and, accordingly, transforms the risks. Objectives of the research: to build an algorithm for identifying anthropogenic environmental risks in the context of two major players economic activities in the Arctic region: the Russian Federation and China. In the paper, we formulated an algorithm of environmental risk identification. We identified environmental hazards from the main parameter—the type of economic activity for the extraction of energy resources, premises, and factors for the occurrence of environmental hazards and compiled criteria for risk selection. Methods used: complex analysis (mixed method research): empirical and comparative methods, methods of expert assessments, the method of inductive statistics (inferential statistics) to compare the perception of risk at... [more]

Lithology identification is the basis for sweet spot evaluation, prediction, and precise exploratory deployment and has important guiding significance for areas with low exploration degrees. The lithology of the shale strata, which are composed of fine-grained sediments, is complex and varies regularly in the vertical direction. Identifying complex lithology is a typical nonlinear classification problem, and intelligent algorithms can effectively solve this problem, but different algorithms have advantages and disadvantages. Compared were the three typical algorithms of Fisher discriminant analysis, BP neural network, and classification and regression decision tree (C&RT) on the identification of seven lithologies of shale strata in the lower 1st member of the Shahejie Formation (Es1L) of Raoyang sag. Fisher discriminant analysis method is linear discriminant, the recognition effect is poor, the accuracy is 52.4%; the accuracy of the BP neural network to identify lithology is 82.3%, bu... [more]

Permanent downhole gauges (PDG) are massively installed in injection and production wells operated in different industries such as oil and gas, geological CO2 storage, and the geothermal industry. These gauges provide a vast amount of real-time pressure measurements. The pressure measurements may be divided into periods with a predominantly monotonic change of pressure in response to a sudden change of rate, called transients. These transients are caused by well operations, such as variation of injection or production rate and well shut-ins. Transient identification is one of the important steps in processing and interpreting the PDG data. Traditional transient identification is performed by processing and analyzing with human involvement, which is a step in post-operation well analysis. In modern well surveillance technology, permanent and reliable data transmission from the wellbore to the surface provide the possibility to analyze well performance in real time or proactively. So aut... [more]

The laminar structure of shale system has an important influence on the evaluation of hydrocarbon source rock quality, reservoir quality, and engineering quality, and it is receiving increasing attention. A systematic study of the lamina structure is not only of great scientific significance but also of vital practical importance for shale oil production. In this paper, the identification and description classification of shale laminae are first reviewed. Multiple scales and types indicate that a combination of different probe techniques is the basis for an accurate evaluation of shale laminar characteristics. The influence of laminae on shale reservoir, oil-bearing, mobility, and fracability properties is discussed systematically. A comparative analysis shows that shale systems with well-developed lamination facilitate the development of bedding fractures, thus improving the shale storage space. The average pore size and pore connectivity are also enhanced. These factors synergistical... [more]

A reservoir with a thickness less than 0.5 m is generally considered to be a thin reservoir, in which it is difficult to directly identify oil-water layers with conventional logging data, and the identify result coincidence rate is low. Therefore, a support vector machine method (SVM) is introduced in the field of oil-water-dry layer identification. The basic approach is to map the nonlinear problem (input space) to a new high-dimensional feature space through the introduction of a kernel function, and then construct the optimal decision surface in the high-dimensional feature space and conduct sample classification. There are plenty of thin reservoirs in Wangguantun oilfield. Therefore, 63 samples are established by integrating general logging data and oil testing data from the study area, including 42 learning samples and 21 prediction samples, which are normalized. Then, the kernel function is selected, based on previous experience, and the fluid identification model of the thin res... [more]

The emergence of the new SARS-CoV-2 virus two years ago strongly affected economic life and labour markets around the world. The pandemic affected many sectors, including the mining industry. Coal companies have had to cope with the challenges and adapt their operations to the situation. Due to the peculiarities of the mines, not only to the hazardous factors and conditions prevailing underground but also to the large number of employees who usually move in groups in the plants, the emergence of a new threat caused by a biological agent posed a real challenge for them. The aim of this paper was to present the initiatives and measures taken in the coal mining sector to ensure the safety of workers during a pandemic. The guidelines for the operation of mining plants during the SARS-CoV-2 epidemic were analysed, as well as the identification of locations in mining plants particularly vulnerable to infection with the virus. We also presented how the pandemic period affected the operations... [more]

This paper presents the Park model of a solid-rotor induction motor. In this model, the dynamic state of the motor is described by integer and noninteger order differential equations. The skin effect in the solid rotor was represented by resistance and inductance with lumped constants, and the fractional inductance was dependent on the frequency of the eddy current induced in the rotor. The parameters of the equivalent circuit were determined by the standstill frequency response test with the stationary machine on the basis of the finite element method analysis of the electromagnetic field. A simulation of the dynamic states of the induction motor with a solid rotor was carried out based on the calculated parameters. The simulation was carried out using a program written in the Matlab environment. The simulations show that the electromagnetic moment during the motor start-up is about 2 times greater than the initial torque in the steady state. On the other hand, the maximum value of th... [more]

The boiler is an essential energy conversion facility in a thermal power plant. One small malfunction or abnormal event will bring huge economic loss and casualties. Accurate and timely detection of abnormal events in boilers is crucial for the safe and economical operation of complex thermal power plants. Data-driven fault diagnosis methods based on statistical process monitoring technology have prevailed in thermal power plants, whereas the false alarm rates of those methods are relatively high. To work around this, this paper proposes a novel fault detection and identification method for furnace negative pressure system based on canonical variable analysis (CVA) and eXtreme Gradient Boosting improved by genetic algorithms (GA-XGBoost). First, CVA is used to reduce the data redundancy and construct the canonical residuals to measure the prediction ability of the state variables. Then, the fault detection model based on GA-XGBoost is schemed using the constructed canonical residual va... [more]

The stereometry of the working units of mining machines is optimized at the design stage, in terms of selected criteria based on computer simulations of the mining process. The recovered bodies of cutting heads or drums used in manufacturing are regenerated in the overhaul process. Ensuring that their dimensions comply with the nominal ones is labor-intensive and raises production costs. However, deviations of these components from the nominal shape can make it difficult to position the pick holders (which can cause collisions) or make welding them impossible (which results from too large a distance between the pick holders’ base and the side surface of the working unit). This applies especially to robotic technologies. By utilizing automatic (online) measurements of the distribution of the actual distances of the pick holders’ bases from the side surface of the working unit (taken during their positioning using a robot), it is possible to correct their positions without changing the s... [more]

The rapid and accurate identification of photovoltaic (PV) model parameters is of great significance in solving practical engineering problems such as PV power prediction, maximum power point tracking and battery failure model recognition. Aiming at the shortcomings of low accuracy and poor reliability and being easy to fall into local optimization when standard intelligent optimization algorithms identify PV model parameters, a novel drunken adaptive walking chaotic wolf swarm algorithm is proposed, which is named DCWPA for short. The DCWPA uses the chaotic map sequence to initialize the population, thus to improve the diversity of the initial population. It adopts the walking direction mechanism based on the drunk walking model and the adaptive walking step size to increase the randomness of walking, enhance the individual’s ability to explore and develop and improve the ability of algorithm optimization. It also designs the judgment conditions for half siege in order to accelerate t... [more]

In smart grids (SGs), the systematic utilization of consumer energy data while maintaining its privacy is of paramount importance. This research addresses this problem by energy theft detection while preserving the privacy of client data. In particular, this research identifies centralized models as more accurate in predicting energy theft in SGs but with no or significantly less data protection. Current research proposes a novel federated learning (FL) framework, namely FedDP, to tackle this issue. The proposed framework enables various clients to benefit from on-device prediction with very little communication overhead and to learn from the experience of other clients with the help of a central server (CS). Furthermore, for the accurate identification of energy theft, the use of a novel federated voting classifier (FVC) is proposed. FVC uses the majority voting-based consensus of traditional machine learning (ML) classifiers namely, random forests (RF), k-nearest neighbors (KNN), and... [more]

The aim of the present research is to assess the scale of the impact of air pollution on the level of burdening EU economies with the consequences of chronic diseases (non-communicable diseases—NCDs) in the context of limiting the potential productivity of human resources. This study attempts to identify inequalities in this area that occur in the territory of the European Union. The scale of the impact of environmental factors, and air pollution in particular, on the level of health limitations in the labor resources of EU countries was measured by the number of the years of healthy life lost (YLL and YLD) as a result of chronic diseases. The verification of the assumption of a persistently high level of dispersion was based on an analysis of the convergence process (β and σ) in the group of EU countries in 1990−2019. The results demonstrate that the level of health restrictions caused by air pollution is diverse in the group of EU-27 countries. The inequalities observed concern, in p... [more]

The middle sub-member (Es3z) within the third member (Es3) of the Eocene Shahejie formation is the main source of the generation and accumulation of hydrocarbons in the lacustrine deltas of Bonan depression. Exploration and research work in different blocks is carried out separately. Types of sedimentary facies, and their vertical and lateral evolution in Es3z are not studied in detail. To fill this knowledge gap, we did a detailed analysis of facies and lithological characteristics through integrative studies of cores, well logs and seismic data. Identification of sedimentary structures and lithology of the reservoir zone from cores are calibrated with high-quality well logs and seismic data. Depositional facies in Es3z reservoirs are identified through analysis of sedimentary structures, grain size, log’s trends and seismic sections. Es3z was deposited in the fan delta front setting where five facies associations are found, among them distributary channels consisting of MCS, CSg, PCS... [more]

The accurate extraction and analysis of slot harmonics caused by slotting in an induction motor are important for the motor’s performance evaluation and state monitoring. However, the frequency distribution of rotor slot harmonics (RSHs) varies along with the operating states of the motor, such as motor speed and slip ratio, and the voltage and current signals of the motor only contain small-amplitude RSHs compared with other harmonics; both make it difficult to extract and analyze the RSHs accurately online. While offline extraction and filters with constant parameters are mainly utilized in available works, a novel adaptive extraction method for RSHs in a multiphase induction motor is proposed here to realize online RSH extraction under different speed and load conditions. In this paper, the RSHs in the multiphase induction motors are firstly modeled by using the magnetic potential permeability method, and the influence of a skewed rotor on RSHs is analyzed through a multisection met... [more]

With the rapid development of the hydrogen energy industry, the number of hydrogen cylinders has reached a very large scale. At present, both domestic and international experiences of hydrogen cylinder inspection are zero, which makes the inspection work more challenging and unpredictable. In recent years, more and more attention has been paid to the responsibility of safety in production, but the research on the risk and safety of cylinder inspection institutions is very limited. In this paper, the Job safety analysis (JSA) method is used to carry out systematic risk identification, risk assessment, risk prevention, and other research work of the cylinder inspection station. After the JSA method and experience accumulation, the management strategy is continuously perfecting, and the security risk level is absolutely decreasing.