The timely and effective fault diagnosis method is critical to the operation of the air-conditioning system and energy saving of buildings. In this study, a novel fault diagnosis method was proposed. It is combined with the signal demodulation method and machine learning method. The fault signals are demodulated by the demodulation method based on time-frequency analysis and principal component analysis (DPCA). The modulation characteristics of the principal component and DPCA sets with stronger features are obtained. Compared with time domain sets, the correct rate was increased by 16.38%. Then, as a machine learning method, the Visual Geometry Group—Principal Component Analysis (VGG-PCA) model is proposed in this study. The application potential of this model is discussed by using evaluation indexes of fault diagnosis performance and two typical faults of air conditioning systems. Compared with the other two convolution neural network models, the correct rate was increased by 17.1% a... [more]

Optimizing Rural Water Supply Network (RWSN) is the basis for improving rural people’s lives and improving people’s health. Currently, the RWSN in China is relatively backward and can no longer meet the needs of the unified management of rural water resources. To optimize the RWSN, this study innovatively established a Multi-Objective Optimization Mathematical Model (MOMM) of RWSN, combining economic factors and reliability. This experiment first analyzes the characteristics of the RWSN system and then establishes a MOMM of a water supply network. NSGA-II algorithm and LM algorithm are introduced to handle the multi-objective model. The research results show that compared to Web decision tools, the RWSN based on the LM-NSGA-II algorithm can save 5.4% of the total annual cost of water supply pipelines. Therefore, the MOMM of the rural water supply pipeline based on the LM-NSGA-II algorithm has better economy and reliability. The experiment aims to provide certain reference values for th... [more]

This paper investigates the failure of a regulating valve stem in a petrochemical plant, which was mainly caused by vibration fatigue under small opening conditions. The fractured valve stem was analyzed using macroscopic analysis, chemical composition analysis, mechanical property analysis, metallographic analysis, fracture surface observation, and energy spectrum analysis. Additionally, fluid-structure interaction (FSI) modal analysis was used to investigate the failure of the regulating valve. The results indicate that the valve opening had a direct impact on the vibration of the valve body, which, when operated at small openings, led to fatigue fracture at the step of variable cross-section. The paper suggests a smooth transition treatment be performed at the variable cross-section of the valve stem to avoid stress concentration. Although this study is limited to a specific case, it provides valuable insights for the failure analysis of valves operating at small openings.

Alarm systems are essential to the process safety and efficiency of complex industrial facilities. However, with the increasing size of plants and the growing complexity of industrial processes, alarm flooding is becoming a serious problem and posing challenges to alarm systems. Extracting alarm patterns from an alarm flood database can assist with an alarm root cause analysis, decision support, and the configuration of an alarm suppression model. However, due to the large size of the alarm database and the problem of sequence ambiguity in the alarm sequence, existing algorithms suffer from excessive computational overhead, incomplete alarm patterns, and redundant outputs. In order to solve these problems, we propose an alarm pattern extraction method based on the improved PrefixSpan algorithm. Firstly, a priority-based pre-matching strategy is proposed to cluster similar sequences in advance. Secondly, we improved PrefixSpan by considering timestamps to tolerate short-term order ambig... [more]

Due to their low concentration and complex nature, the low-cost online and real-time monitoring of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) is a challenge. In this paper, based on a coupling adsorption model of activated carbon and the relationship of PCDD/Fs and flue gas, an online monitoring system with real-time control of final PCDD/F emissions was built for the tracing and control of PCDD/F emissions in municipal solid waste incinerators (MSWIs). According to the online monitoring system, the effects of activated carbon concentration, the specific surface area of activated carbon (AC), operating temperature, contact time, fly ash concentration, residence carbon concentration of fly ash, and the lime concentration of final PCDD/F emissions were discussed. These MSWI operating parameters for reaching standards of 0.1 ng international toxic equivalents (TEQ)/Nm3 and 0.05 ng TEQ/Nm3 were summarized by the predicting model based on several published... [more]

The actual driving conditions of electric vehicles (EVs) are complex and changeable. Limited by road adhesion conditions, it is necessary to give priority to ensuring safety, taking into account the energy recovery ratio of the vehicle during braking to obtain better braking quality. In this work, an electric vehicle with an EHB (electro-hydraulic braking) system whose braking force adaptive distribution control strategy is studied. Firstly, the vehicle dynamics model, including seven degrees of freedom, tire, drive motor, main reducer, battery pack, and braking system, was constructed, which is attributed to the vehicle configuration and braking system scheme. Second, based on curve I and ECE regulations, the adaptive braking force distribution control strategy was formulated by taking the maximum regenerative braking torque as the inflection point, the synchronous adhesion coefficient as the desired point, and the battery SOC, road adhesion coefficient, and braking strength as the th... [more]

For the flexible regulation requirements of new power systems with a high proportion of new energy, this paper proposes a multi-point distributed energy storage system control method based on the idea of multi-agent cooperative control. On the one hand, the method transforms and upgrades the strategies of each distributed battery energy storage control system to make it a terminal agent with active response and control functions; on the other hand, a coordination agent is set between the power grid and each terminal agent, the coordinated control of the distributed energy storage system is realized by the information interaction between the coordination agent and the terminal agent. The simulation results show that the method can fully exploit the aggregate regulation ability of the distributed energy storage system, quickly stabilize the frequency fluctuation of new energy, and support the safe and economical operation of the system.

In the chemical industry, a reactor is an absolutely necessary container. The fact that its dynamic qualities are nonlinear and unknown, however, is what causes the temperature to deviate from the value that was specified. As a result, the typical PID control cannot fulfill the prerequisites of the production process. A new nonlinear function is presented to replace the function that was previously used, and a temperature controller that is based on better fractional order active disturbance rejection is devised. On the basis of a new fractional order temperature detector (FOTD), a new fractional order equilibrium state observer (FOESO), and nonlinear function, an improved fractional order active disturbance rejection controller has been developed. A model of the reactor was created, and the dynamic properties of temperature control were investigated. By simulation and experimentation, it was demonstrated that the strategy has a number of benefits and is effective. In this approach, th... [more]

Advanced control strategies, together with state-estimation methods, are frequently applied to nonlinear and complex systems. It is crucial to understand which of these are the most efficient methods for the best use of these approaches in a chemical process. In the current work, nonlinear model predictive control (NMPC) approaches were developed that considered three numerical methods: single shooting (SS), multiple shooting (MS), and orthogonal collocation (OC). Their performance was compared against the Van de Vusse reactor benchmark while considering set-point changes, unreachable set-point, disturbances, and mismatches. The results showed that the NMPC based on OC presented less computational cost than the other approaches. The extended Kalman filter (EKF), constrained extended Kalman filter (CEKF), and the moving horizon estimator (MHE) were also developed. The estimators’ performance was compared for the same benchmark by considering the computational cost and the mean squared e... [more]

Deodorization of vegetable oils may introduce potentially carcinogenic, as well as genotoxic contaminants, generating health risks for consumers. However, the deodorization step of the refining process leads to the formation of 3-monochloro-1,2-propanediol (3-MCPD). 3-MCPD has been classified as potentially carcinogenic to humans by the World Health Organization (WHO). The purpose of this study was to optimize recently updated oil treatment techniques using Instant Controlled Pressure Drop (DIC) to improve 3-MCPD elimination in edible palm oil. Based on the central composite (CCD-DoE), response surface methodology (RSM) was developed to find the best combination of two variables at five levels to remove 3-MCPD from the palm oil. Samples of palm oil were split into two groups. The first group was treated only by the traditional method, including refining, degumming, deacidification, decolorization, deodorization, dehydration, filtration, and dewaxing processes. The second group was firs... [more]

The corn-to-sugar process is difficult to control automatically because of the complex physical and chemical phenomena involved. Because the RNN-LSTN model has been shown to handle long-term time dependencies well, this article focused on the design of a model predictive control system based on this machine learning model. Based on the historical data, we first reduced the input variable dimension through data preprocessing, data dimension reduction, sensitivity analysis, etc., and then the RNN-LSTM model, with these identified key sites as inputs, and the dextrose equivalent value as the output, was constructed. Then, through model predictive control using the locally linearized RNN-LSTM as the predictive model, the objective value of the dextrose equivalent was successfully controlled at the target value by our simulation study, in different situations of setpoint changes and disturbances. This showed the potential of applying RNN-LSTM-Based model predictive control in a corn-to-suga... [more]

As a damage element, high-speed fragments have a significant effect on the ammunition safety. The impact from the fragments are also one of the basic problems of ammunition safety tests. To clarify the reaction characteristics of combustion, explosion, detonation, and so on, when hypersonic fragments hit insensitive munitions, it is necessary to carry out corresponding research on the deceleration law of hypersonic fragment in the air. In this paper, a 30 mm caliber gun with large chamber, small caliber, and large aspect ratio is proposed to drive high-speed fragments. According to STANAG 4496 standard, a near-cylinder steel fragment with Brinell hardness HB ≤ 270 and mass of 18.6 g was designed. The test system was composed of zone interception velocity measurement, chamber pressure sensor, trajectory tracking system, high-speed camera, and other equipment were also established to obtain the pressure variations in the chamber, the velocity of the fragment, and its flight orientation.... [more]

The Maigaiti Slope is a significant oil-gas-bearing field in the Tarim Basin. Based on 3D and 2D seismic data, systematic interpretation, stage sorting and genetic analysis of strike-slip faults in the Maigaiti Slope were carried out for the first time. The relationship between strike-slip faults and hydrocarbon accumulation was studied in combination with the fine dissection of hydrocarbon reservoirs. The study suggested that: (1) Staging and segmentation characteristics of strike-slip faults are evidently presented in the Maigaiti Slope. According to active periods, strike-slip faults can be divided into early Caledonian period, late Caledonian period, Hercynian period, and Himalayan period. According to plane distribution characteristics, strike-slip faults can be divided into the west Maigaiti Segment, mid-Maigaiti Segment, Madong Segment, and Bachu Segment. The main active periods and plane distribution of strike-slip faults in different sections are remarkably different. This ana... [more]

Electron beam melting (EBM) is one example of a 3D printing technology that has shown great promise and advantages in the fabrication of medical devices such as dental and orthopedic implants. However, these products require high surface quality control to meet the specifications; thus, post-processing, such as with machining processes, is required to improve surface quality. This paper investigates the influence of two-part orientations of Ti6Al4V EBM parts on the CNC machining (turning) process. The two possible EBM part orientations used in this work are across EBM layers (AL) and parallel to the EBM layer (PL). The effect of the EBM Ti6Al4V part orientations is examined on surface roughness, power consumption, chip morphology, tool flank wear, and surface morphology during the dry turning, while using uncoated carbide tools at different feed rates and cutting speeds. The results showed that the AL orientation had better surface quality control and integrity after machining than PL... [more]

Brake-by-wire (BBW) technology is crucial in driverless cars. The BBW technology, which has a faster reaction time and greater stability, can improve passenger safety in driverless cars. BBW technology refers to the removal of some complicated mechanical and hydraulic components from the traditional braking system in favor of using wires to transmit braking signals, which improves braking performance. Firstly, this paper summarized BBW’s development history as well as its structure, classification, and operating principles. Subsequently, various control strategies of the BBW system were analyzed, and the development trend and research status of the motor brake-control strategy and wheel-cylinder pressure-control strategy in the braking force-distribution strategy were analyzed respectively, and the brake fault-tolerance technology and regenerative-braking technology were also analyzed and summarized. Finally, this paper summarized the various technologies of BBW, taking the electromech... [more]

Hydraulic synchronous control systems are widely used in various industrial fields. This paper deeply analyzes the research status and development trend of the hydraulic synchronous control system. Firstly, it gives a brief introduction of the research significance control theory and control methods of the hydraulic synchronous control system. Secondly, the hydraulic synchronization control system is classified, the synchronization error is analyzed, and some solutions to synchronization error are given. Then, according to the classification of the hydraulic synchronous control system, relevant research is carried out. In this paper, three control modes (equivalent, master−slave and cross-coupling) and related control algorithms (fuzzy PID control, sliding mode control, robust control, machine learning control, neural network control, etc.) of closed-loop hydraulic synchronous control systems are studied in detail. Finally, the development trend of the hydraulic synchronization control... [more]

The ERTMS/ETCS is the newest automatic train protection system. This is a system that supports the driver in driving the train. It is currently being implemented throughout the European Union. This system’s latest specifications also provide additional functions to increase the energy efficiency of train driving in the form of ATO (automatic train operation). These functions of the ETCS will be valuable, provided they operate without failure. To achieve errorless configuration of the ETCS, a methodology for automatic system verification using the IMDS (Integrated Model of Distributed Systems) formalism and the temporal tool Dedan was applied. The main contribution is asynchronous and timed verification, which appropriately models the distributed nature of the ETCS and allows the designer not only to analyze time dependencies but also to define the range of train velocities in which the operational scenario is valid. Additionally, the novelties of the presented verification methodology... [more]

Generator fault diagnosis has a great impact on power networks. With the coupling effects, some uncertain factors, and all the complexities of generator design, fault diagnosis is difficult using any theoretical analysis or mathematical model. This paper proposes a bit-coding support vector regression (BSVR) algorithm for turbine generator fault diagnosis (GFD) based on a support vector machine (SVM) capable of processing multiple classification problems of fault diagnosis. The BSVR can simplify the design architecture and reduce the processing time for detection, where m classifier is needed for m class problems compared to the [m(m − 1)]/2 size of the original multi-class SVM. Compared with conventional methods, numerical test results showed a high accuracy, good robustness, and a faster processing performance.

In this paper, a set of best practice data sharing guidelines for wind turbine fault detection model evaluation is developed, which can help practitioners overcome the main challenges of digitalisation. Digitalisation is one of the key drivers for reducing costs and risks over the whole wind energy project life cycle. One of the largest challenges in successfully implementing digitalisation is the lack of data sharing and collaboration between organisations in the sector. In order to overcome this challenge, a new collaboration framework called WeDoWind was developed in recent work. The main innovation of this framework is the way it creates tangible incentives to motivate and empower different types of people from all over the world to share data and knowledge in practice. In this present paper, the challenges related to comparing and evaluating different SCADA-data-based wind turbine fault detection models are investigated by carrying out a new case study, the “WinJi Gearbox Fault De... [more]

In industrial settings, mechanical systems for clamping workpieces onto machine tools or for lifting and handling ferrous material are often replaced by magnetic clamping systems. For large lifting applications, the most suitable magnetic clamping systems are electromagnetic (EM) and electro-permanent (EP) approaches. Their configurations, direct and induced poles or direct poles only, need to be discussed in order to choose the most appropriate and economical setup for the specific application. In addition, an evaluation of the difference in the energy efficiency between EM and EP systems, which is often not simple, is presented. To achieve this, a hybrid control system for EM or EP systems was developed and, with the help of this prototype, an analysis of these two magnetic systems was carried out to highlight the main differences. The hybrid control system consists of a single control unit that can be used by both systems, and can be achieved by simply changing the type of lifting m... [more]

In enterprises, the management of detection methods usually refers to ensuring the identification of nonconformities. This management is incomplete and incompatible with the concept of sustainability (it ignores electricity consumption and costs). To date, no models have been developed to support the analysis of detection methods in terms of the relationship of efficiency−energy consumption. The purpose of the study was to develop proprietary software to analyse the level of efficiency of detection methods for casting products in the context of their energy intensity. The model supports effective management of the quality control process, optimising the relationship of product quality−energy intensity of the process. The model integrally combines detection methods, so it was possible to identify critical product nonconformities and analyse these methods to determine their effectiveness, time efficiency, cost efficiency, and energy intensity. As a result of the implications of the softw... [more]

An appropriate microclimate is one of the most important factors of a healthy and comfortable life. The microclimate of a place is determined by the temperature, humidity and speed of the air. Those factors determine how a person feels thermal comfort and, therefore, they play an essential role in people’s lives. Control of microclimate parameters is a very important topic for buildings, as well as greenhouses, where adequate microclimate is fundamental for best-growing results. Microclimate systems require adequate monitoring and maintenance, for their failure or suboptimal performance can increase energy consumption and have catastrophic results. In recent years, Fault Detection and Diagnosis in microclimate systems have been paid more attention. The main goal of those systems is to effectively detect faults and accurately isolate them to a failing component in the shortest time possible. Sometimes it is even possible to predict and anticipate failures, which allows preventing the fa... [more]

The uncertainty brought about by the high proportion of distributed generations poses great challenges to the operational safety of novel distribution systems. Therefore, this paper proposes an online reactive power and voltage control method that integrates source−load uncertainty and a mechanism−data hybrid drive (MDHD) model. Based on the concept of a mechanism and data hybrid drive, the mechanism-driven deterministic reactive power optimization strategy and the stochastic reactive power optimization strategy are used as training data. By training the data-driven CNN−GRU network model offline, the influence of source−load uncertainty on reactive power optimization can be effectively assessed. On this basis, according to the online source and load predicted data, the proposed hybrid-driven model can be applied to quickly obtain the reactive power optimization strategy to enable fast control of voltage. As observed in the case studies, compared with the traditional deterministic and s... [more]

Industrial robots have a key role in the concept of Industry 4.0. On the one hand, these systems improve quality and productivity, but on the other hand, they require a huge amount of energy. Energy saving solutions have to be developed and applied to provide sustainable production. The purpose of this research is to develop the optimal control strategy for industrial robots in order to minimize energy consumption. Therefore, a case study was conducted for the development of two control strategies to be applied to the RV-2AJ Mitsubishi robot arm with 5 DOF, where the system is a nonlinear one. The first examined controller is the classical linear proportional integral derivative (PID) controller, while the second one is the linear model predictive control (MPC) controller. In our study, the performances of both the classical PID model and the linear MPC controller were compared. As a result, it was found that the MPC controller in the execution of the three defined reference trajectori... [more]

The article is devoted to solving the problem of managing the mode parameters of an urban electrical network in case of a discrepancy between the actual electrical load and the specific load. Such an issue leads to a deviation of the parameters, in particular, voltage asymmetry in phases due to current asymmetry. To optimize the mode parameters, it is required that the effective value of the electrical load corresponds as much as possible to the values of the specific electrical load. This depends on the following: actual power consumption, external (climatic and meteorological) factors, internal factors (structural design of residential buildings, uneven load when distributed over the phases of three-phase lines and inputs, different number of electrical receivers for consumers), and the provision of consumers with other sources of energy (both gas and heat supply, and hot water supply). To establish the influencing factors on the actual power consumption, it is proposed to generalize... [more]