Operating Conditions Research Articles

Impact of spray drying operating conditions on yield, secondary metabolites, antioxidant potential and storage quality of grape (Vitis vinifera L.) pomace powder

In the present investigation, spray drying independent operating conditions such as the inlet air temperature (A-IAT 130, 150 and 170 °C), outlet air temperature (B-OAT 60, 70 and 80 °C), needle speed (C-NS 3S, 4S, 5S), maltodextrin concentration (D-MD 10, 15, 20 %), pump speed (E-PS 5, 10, 15 mL/min) and water/grape pomace ratio (F-W/GP ratio 10, 15, 20) were optimized to develop the spray-dried grape pomace powder (SDGPP) with maximum yield. The impact of these conditions on total phenolic contents (TPC), total flavonoid contents (TFC), and antioxidant activity (DPPH· values) of SDGPP samples were analyzed. The independent spray drying factors (IAT, OAT, NS, MD, PS, and W/GP ratio) impart a strong direct effect (p ≤ 0.05) on powder yield, TPC, TFC, and DPPH· values. The interaction effects (A × B, A × C, A × D, A × E, A × F, B × C, B × D, B × E, B × F, C × D, C × E, C × F, D × E, D × F, and E × F) of independent variables were noted non-significant (p ≥ 0.05) for response values. After validation of the model and verification of results, the independents' variables were found in the range of 170 °C (IAT), 80 °C (OAT), 4S (NS), 15 % (MD), 10 mL/min (PS) and 15 (W/GP ratio) for yield (64.7 ± 1.18 %), TPC (7.66 ± 0.53 mg GAE/g), TFC (3.19 ± 0.30 mg CE/g) and DPPH· 140.3 ± 1.59 (100 µL/mL), respectively. The decrease in TPC, TFC, and DPPH· values of SDGPP samples was noted during 60 days of storage at 25 ± 2 °C and 65 ± 5 % RH (p ≤ 0.05) but not greater than unprocessed samples. It could be concluded that the protection of phenolic contents and retention of antioxidant activity of dried powders can be achieved at optimized spray drying conditions for discerning food and byproduct processing industries.

Enhancing deep eutectic solvent systems for efficient fermentable sugar recovery from lignocellulosic fiber

Efficient conversion of sugars into fermentable sugars is a critical challenge in the cost-effective production of lignocellulosic biopolymers and biofuels. This study focuses on various sugar quantification techniques applied to Furcraea Foetida (Mauritius Hemp) samples, utilizing natural deep eutectic solvents (NADES) and deep eutectic solvents (DES) like urea, glycerol, citrates, pyrogallol (PY), and cetyltrimethylammonium bromide (CTAB). Employing a Taguchi-designed experiment, operational conditions were fine-tuned to evaluate the influence of time, concentration, and temperature on each deep eutectic solvent-based process. The emerging green solvent extraction approach demonstrated significant results, achieving notably high sugar yields compared to traditional techniques such as alkali, hot-water, and acid-mediated extraction. At a CTAB:PY molar ratio of 1:3, optimized for 60 min at 50 °C, the highest fermentable sugar (FS) yield of 0.6891 ± 0.0123 g FS/g LCB was attained—2 to 6 times higher than non-optimized values and 0.2 to 0.3 times higher than optimized traditional methods. In light of this, this research study emphasizes the pivotal significance of efficient sugar conversion through optimized deep eutectic solvent-based extraction methods, with a particular focus on Furcraea Foetida fibers, offering promising outcomes for the biofuel and biopolymer production industry.

Impact of grading capacitor on transient recovery voltage due to shunt reactor de-energization for different values of current chopping

This paper investigates the impact of grading capacitors on transient recovery voltage (TRV) during shunt reactor switching in high voltage systems, considering different levels of current chopping. Shunt reactor de-energization can result in voltage surges and instability due to current chopping effects. The study utilizes simulation models using ATP-Draw software to assess the effectiveness of grading capacitors in mitigating TRV under various operating conditions as well as of using a proposed method to mitigate the excessive TRV across the circuit breaker. The findings provide valuable insights into managing TRV during shunt reactor switching, enhancing power system stability and reliability. The results obtained showed that the TRV across the circuit breaker decreased by 61.5% by using circuit modification as well as adding a grading capacitor.

A technique for separating the impact of cycle aging and temperature on Li-ion battery capacity

Reduction of battery capacity is a well-known symptom of aging, making it a universally accepted indicator of the state of health. Capacity also significantly depends on temperature, therefore, separating the effect of temperature from that due to aging has utmost important for a proper state of health assessment. However, according to the latest literature, there is a lack of information about how the temperature dependency of capacity changes with battery aging. In this respect, the study presented in this paper is based on an experimental campaign aimed at measuring battery capacity at different temperatures and cycling levels. Starting from the obtained results, an analytical model describing how the variation law of battery capacity with temperature is affected by cycling was proposed and validated. The achieved accuracy is better than 0.6 % for all the considered operating conditions.

Survival modelling of infectious human norovirus and surrogates for high-pressure inactivation in strawberry puree

Berries contaminated with human norovirus (HuNoV) have been frequently identified as a cause of foodborne gastroenteritis. To prevent virus transmission while preserving sensory and quality parameters, non-thermal treatments, such as high-pressure processing (HPP), can be applied to the berries and products thereof. Here, strawberry purees contaminated with HuNoV genogroup I (GI.3[P13]) and II (GII.4 Sydney [P16]), along with murine norovirus (MNV) and Tulane virus (TV) serving as surrogates, were exposed to HPP at several pressure-time combinations. Virus inactivation was assessed by cell culture, including the novel human intestinal enteroids (HIE) model for HuNoVs. The infectivity results showed TV more resistant than MNV to HPP, as also confirmed by kinetic mathematical modelling. Results indicated that a holding pressure of 450 MPa and an exposure time of ≥5 min are reliable operational conditions for HPP process to successfully control viral contamination. In addition, the inactivation models deduced from MNV and TV viruses were challenged with experimental HuNoV GII.4 infectivity resulting in bias factors <1 for all treatment conditions. This finding validates the proposed models for the conservative estimation of HuNoV inactivation. Our work offers a blueprint for moving forward with inactivation studies using the HIE system, which provides useful practical information on optimum treatments for the best public health outcomes.

Modeling load sensing pressure and flow control of axial piston pump by analyzing impact of bulk modulus

This research is focused on investigating the impact of the bulk modulus on the dynamics of variable delivery hydraulic axial piston pump (VAPP). The bulk modulus decreases exponentially with an increase in temperature whereas there is a linear positive relationship with pressure. The research revealed that there is a 6% (1 litre/s) increase in flow rate and a 2.6% (1.5 MPa) decrease in delivery pressure with a 38.75% (0.434 GPa) decrease in bulk modulus. Flow ripple and pressure pulsation are reduced by 39.3% and 43.2% respectively with a corresponding 38.75% decrease in bulk modulus. Pressure pulsation and flow ripple are responsible for the generation of noise and vibrations in the system. Flow rate increase contributes to better response and control of the VAPP. While a reduction in bulk modulus offers improved dynamic performance and overall response of the VAPP, it is noteworthy that a decrease in bulk modulus hurts the pump delivery pressure. The research allows the pump designer to formulate a strategy to optimize the bulk modulus under dynamic operating conditions to achieve optimal pump performance.

Power Balancing Strategy for Cascaded H-Bridge Inverter in a Grid-Connected Photovoltaic System Under Asymmetrical Operating Conditions

Power Balancing Strategy for Cascaded H-Bridge Inverter in a Grid-Connected Photovoltaic System Under Asymmetrical Operating Conditions

Strategic electromagnetic interferences suppression in boost converters: zero-switch techniques

This article delves into the growing demand for efficient power conversion technologies accompanying the rise in electric vehicle (EV) adoption. Boost converters, essential for increasing the battery pack voltage to propel EV motors, pose a challenge due to the electromagnetic interference (EMI) generated by the high switching frequency of power devices. To address this issue, practitioners employ zero-voltage switching (ZVS) and zero-current switching (ZCS) techniques. In this comparative study, we systematically evaluate the effectiveness of these soft switching techniques in reducing conducted EMI in boost converters designed for EV applications. The results illuminate the potential of both ZVS and ZCS in significantly mitigating EMI emissions when compared to conventional hard-switching methods. Notably, ZVS soft switching emerges as more efficient and effective, particularly under higher loads, while ZCS soft switching excels in reducing EMI at lighter loads. In conclusion, the study asserts that ZVS soft switching presents a more promising solution for curtailing conducted EMI in boost converters for EV applications, particularly in high-load scenarios. However, it underscores the importance of considering specific operational conditions when deciding between the two techniques.

Study, simulation and realization of a fuzzy logic-based MPPT controller in an isolated DC microgrid

This study presents a pioneering methodology for implementing the maximum power point tracking (MPPT) controller, based on fuzzy logic. Through a comprehensive performance analysis, we evaluate its effectiveness compared to the widely used perturb and observe (P&amp;amp;O) algorithm, which is a common MPPT technique. The main objective of our proposed MPPT approach is to improve the performance of a photovoltaic (PV) system. To evaluate the performance of the proposed MPPT controller and compare it with the P&amp;amp;O algorithm, we designed and simulated both controllers using MATLAB/Simulink. We also implemented a prototype of the controllers using an Arduino Mega board, and evaluated their performance under real operating conditions. The experimental results unequivocally confirm that the fuzzy logic-based MPPT controller outperforms the P&amp;amp;O algorithm in terms of performance, speed and accuracy. The fuzzy logic controller offers greater accuracy in tracking the maximum power point under various environmental circumstances, including variations in solar irradiation and connected load. Overall, this work contributes to the development of efficient and reliable MPPT controllers for PV systems, and provides a comparison of the performances of two popular MPPT techniques. Future research could explore other MPPT techniques and evaluate their performance using similar experimental setups.

Leak Detection for Natural Gas Gathering Pipelines Under Multiple Operating Conditions Using RP-1dConvLSTM-AE and Multimodel Decision

Leak Detection for Natural Gas Gathering Pipelines Under Multiple Operating Conditions Using RP-1dConvLSTM-AE and Multimodel Decision

Comprehensive evaluation of a novel pilot-scale UVA-LED photoreactor for water treatment applications: Characterization, catalytic efficiency, energy performance and economic viability

A comprehensive assessment was conducted on a novel pilot plant employing a tubular photo-reactor configuration integrated with UVA-LED technology for advanced municipal wastewater treatment applications. The plant consists of eight UVA-LED strips (150 LEDs/strip, 348–400 nm with peak emission at 370 nm) achieving a maximum irradiance of 28.1 W/m2 at 100 % power of the LED, symmetrically distributed across two borosilicate tubes. The iron concentration (0.025–0.100 mM) and UVA-LED irradiance (1.4–28.1 W/m2) combined effect on the photo-Fenton process efficiency was thoroughly examined in synthetic tap water and synthetic municipal wastewater treatment plant (MWWTP) secondary effluent using sulfamethoxazole as model microcontaminant. In general, an LED intensity threshold from which process efficiency reaches a plateau maximum value was found. The determination of the electrical energy per order (EEO) showed higher energy efficiencies as LED intensity decreases, iron concentration increases, and the water matrix is simpler. The lowest EEO obtained was 0.009 kWh/m3·order for 0.10 mM iron concentration in synthetic MWWTP secondary effluent at 5 % LED intensity. The economic study revealed that the weight of operating costs is more significant than the weight of investment costs, regardless of the selected operating conditions. Working with an iron concentration of 0.10 mM helps reduce the total costs, while operating either under excess LED intensity or insufficient LED intensity negatively impacts the total treatment cost. The lowest treatment cost (0.19 €/m3) was obtained with 0.10 mM iron concentration at only 10 % LED intensity. A comparison with the same process driven by natural solar radiation in a raceway pond reactor demonstrated the feasibility of the novel photo-reactor design in terms of treatment cost.

Machine learning assisted improved desalination pilot system design and experimentation for the circular economy

Desalination is among the most feasible solutions to supply sustainable and clean drinking water in water scarcity areas. In this regard, Multi-Effect Desalination (MED) systems are particularly preferred for harsh feeds (high temperature and salinity) because of their robust mode of operation for water production. However, maintaining the efficient operation of the MED systems is challenging because of the large system design and variables' interdependencies that are sensitive to the distillate production. Therefore, this research leverages the power of machine learning and optimization to estimate the optimal operating conditions for the maximum distillate production from the MED system. In the first step, detailed experimentation is conducted for distillate production against hot water temperature (HWT) varying from 38 to 70 °C, and feed water temperature (FWT) is changed from 34 to 42 °C. Whereas, the feed flow rate (FFR) is investigated to be varied nearly from 3.6 to 8.7 LPM in the three stages, i.e., FFR-S1, FFR-S2 and FFR-S3. The compiled dataset is used to make the process models of the MED system by three ML-based algorithms, i.e., Artificial Neural Network (ANN), Support Vector Machine (SVM), and Gaussian Process Regression (GPR) under rigorous hyperparameters optimization. GPR exhibited superior predictive performance than those of ANN and SVM on R2 value of 0.99 and RMSE of 0.026 LPM. Monte Carlo technique-based variable significance analysis revealed that the HWT has the highest effect on distillate production with a percentage significance of 95.6 %. Then Genetic Algorithm is used to maximize the distillate production with the GPR model embedded in the optimization problem. The GPR-GA driven maximum distillate production is estimated on HWT = 70 ± 0.5 °C, FWT = 40 ± 2.5 °C, FFR-S1 = 6 ± 2.6 LPM, FFR-S2 = 7 ± 1 LPM and FFR-S3 = 7 ± 1. The ML-GA-based system analysis and optimization of the MED system can boost the distillate production that promotes operation excellence and circular economy from the desalination sector.

Design of Variable Valve Timing and Electronic Control for Honda R18A

Abstract: This paper explores the Variable Valve Timing and Lift Electronic Control (VTEC) system developed by Honda, focusing on its mechanisms, design methodology, and impact on engine performance. VTEC optimizes engine efficiency and power by switching between cam profiles suited for low-RPM stability and high-RPM power output, controlled by the engine's computer based on operational conditions. We examine the intricate workings of the VTEC system, detailing its hydraulic actuation and the resulting enhancements in torque and horsepower. Our study centers on the Honda R18A engine, targeting increased maximum RPM and power output. Using theoretical analysis validated through Ricardo Wave software and MATLAB simulations, we determine optimal valve lift and timing to achieve the desired performance. Additionally, the research addresses the geometric parameters influencing airflow through the valves, providing a comprehensive understanding of the VTEC system's contribution to engine efficiency and driving experience. This investigation not only underscores the technological advancements in variable valve timing but also presents practical insights for automotive engineering applications.

Hydrogen Production using PEM Electrolyzer

Abstract: This paper presents a simulation study of alkaline electrolysis for H2 production using Aspen Plus. The simulation model incorporates reactor, separators, mixer, and heat exchanger units to accurately represent the AWE process. The model is designed to evaluate the performance of an AWE system under different operating conditions and aims to achieve a reference H2 production rate of 0.179663 kg/hr. The simulation results demonstrate that the AWE system can successfully produce H2 at the specified rate. The model provides a detailed analysis of the system's behavior and H2 production rate, under varying operating conditions. The findings of this study provide valuable insights into optimizing the design and operation of AWE systems for large-scale H2 production

Treatment of Wastewaters with Different Ammonium Concentrations in a Sequencing Batch Reactor by Nitritation and Denitritation Processes

In the treatment of industrial and municipal wastewaters, biological nitrification and denitrification processes have been widely applied methods. However, in recent years, experimental studies have been carried out on nitritation and denitritation processes in order to reduce the cost of wastewater treatment. In this study, the removal of synthetic wastewaters containing ammonium at various concentrations through nitritation and denitritation processes was investigated in a sequence batch reactor (SBR). The SBR was operated at a low dissolved oxygen concentration of 0.7±0.2 mg/L, while the initial pH level and temperature were kept constant at 7.5 and 25 ℃, respectively, which were below the defined optimal level for nitritation. For the initial concentrations of 100, 150, and 200 mg NH4-N/L, 91, 142, and 180 mg NOx-N were produced, respectively with the specific nitritation rates of 0.69, 0.95, and 0.81 mg NH4-N/mg MLVSS.hour. Considering the operating conditions of nitritation, approximately NO2-N/NOx-N ratio of 80% could be considered as successful with the combined effect of DO limitation and NH3 inhibition on the nitrite oxidizing bacteria. During the first days of nitritation and denitritation processes, change of nitrogen concentrations was negligible because the adaptation of organisms to the oxic and anoxic conditions. After completing nitritation stage, denitritation was carried out by using methanol as an electron donor for the initial concentrations of 91, 142, and 180 mg/L of NOx-N in 96, 120 and 264 hours of reaction times, respectively.

Технологическое обеспечение эксплуатационных свойств сопрягаемых поверхностей элементов сборной формообразующей оснастки с учетом установленной долговечности пресс-форм

Design and technological concepts are viewed at the stages of designing, manufacturing and joining process providing for the required reliability (durability) of mold elements. Recommendations are given for rationing and achieving the parameters of accuracy and quality of mating surfaces, taking into account the formation of the necessary operational properties at the main stages of the product life cycle. The factors that have the greatest impact on ensuring the correct and accurate location of forming tool elements have been elicited. The concept of determining the actual contact area and calculating the scale parameter, which provides a contact interface degree specification for conjugated surfaces, is presented. The hypothesis of the formation of reliability indicators is found, taking into account the manufacturing capability and technical capacity of production with the introduction of correction of the upper and lower dimensional deviations included in the dimension chains and ensuring the pre-set accuracy parameters of the master link. The analysis of the operating conditions of the studied type of pressmold elements is carried out. The main operational properties that provide the required operating time for shaping part failures are identified and analyzed. Special attention is paid to the study of the structural features of such parts, a comparison of the integral and prefabricated structures is made, and also, contact stresses under the joining operation for the most promising of the latter are calculated for contact interface degree simulation. This will allow developing practical recommendations for any type of compound forming tool for the benefit of basic mechanical properties rate making, accuracy indicators, including deviation allowances in the correct geometric shape, including quality parameters of the surface layer at the designing stage,processing methods dispatch and modes setting at the manufacturing and testing stages and also suggesting the amount of static loading when assembling.

Design and Performance Assessment of District Heating Systems in Latvian Region

The energy consumed by buildings for air conditioning accounts for a large percentage of global energy consumption. To promote efficiency and sustainability, the scientific community is making great efforts to develop renewable technologies. A well-known but unfortunately underestimated solution is the development of centralized heating and cooling systems that consistently reduce energy consumption.The work proposes a comparison between three heating configurations covering the demand of a settlement in the Latvian region: 1) centralized district heating (DH) system; 2) 5th generation district heating &amp; cooling (5GDHC) system and 3) individual home heating (HH) systems. Thermal and electrical loads are evaluated by transient simulations of a residential area with 80 buildings for the Riga climate and compared with the same settlement in a Mediterranean region (Milan, IT). The energy plants are based on different technologies: combined heat and power (CHP) plants, gas-fired boilers, and domestic heat pumps.The analysis includes the option of power exchange with the national grid. A transient numerical model has been developed for each solution. Every component is modelled according to performance maps provided by the manufacturers, allowing an accurate simulation in both design and off-design operating conditions. The study includes energy, economic and environmental aspects.The result of the simulation highlights the large difference between the two locations, not only in terms of annual load, but also in terms of load distribution. On an annual basis, the Latvian residential complex requires almost twice as much energy as the Italian one. The thermal losses in the district systems are 4.21% in Milan solution and 5.65% in Riga. The district heating system coupled with heat pump represents the best layout in terms of primary energy consumption in both locations, with energy savings of 50% compared to other solutions. The use of 5GDHC is a good compromise that could increase the use of renewable energy. The adoption of cogeneration plant is a good choice in case of centralized district system that allows the installation of high efficiency genset. On the contrary, for small application as residential, the installation of cogeneration system results expensive and the conversion efficiency does not justify the installation.

Brine Valorisation Using Mechanical Vapor Compression Desalination: Approaches to Consider.

Water scarcity is one of the biggest challenges we are facing due to climate change: lack of rainfall and polluted water sources are an increasing reality worldwide. Sustainable Development Goals reinforce the urgency of dealing with this issue, targeting scientific community’s efforts towards solutions for this trending topic, where desalination of seawater is one of the main proposals. However, concerns regarding to the environmental effects of residual brines, generated in the desalination process, are emerging on the spots where this technology has been applied.To contribute to the implementation of desalination technologies, the valorisation of these residual brines brings the opportunity not only to reduce the volume of wastewater generated, but increasing its final concentrations and producing more freshwater from a residue. Nevertheless, it comes with the cost of higher energy demands than in the previous stage: the higher the concentration of the fluid, the higher its energy consumption. We can approach this challenge from two different perspectives, focusing on the final amount of concentrated residue or focusing on the energy demand of the installation.While focusing on reducing the volume of residue to its minimum expression is the most attractive option for concentrating the dissolved salts, it comes with the cost of excessive energy demands. On the other hand, focusing on reducing the power consumption of the installation allows the usage of variable renewables, in a more efficient way, allowing the carbon neutrality of emissions during its operation but obtaining a lower concentrated residue. By using a computational model of the installation, we can replicate its operation and compare results from both perspectives.In this paper we will use two scenarios with fixed conditions for a basic mechanical vapor compression (MVC) desalination plant modelled in TRNSYS, where we can observe the correlations between the final volume of residual brine and the energy consumption required for achieving those results. One of the scenarios will show the biggest final concentration, while the other one will consider the minimum operating conditions for the desalination plant. Apart from those results, there will be an analysis of environmental and economic advantages that can be achieved by the implementation of this technology, as well as an early approach towards the technical aspects involving the development of the model used for these calculations.

Research on the influence of flexible wheelset rotation effect on wheel rail contact force

PurposeUnder the high-speed operating conditions, the effects of wheelset elastic deformation on the wheel rail dynamic forces will become more notable compared to the low-speed condition. In order to meet different analysis requirements and selecting appropriate models to analyzing the wheel rail interaction, it is crucial to understand the influence of wheelset flexibility on the wheel-rail dynamics under different speeds and track excitations condition.Design/methodology/approachThe wheel rail contact points solving method and vehicle dynamics equations considering wheelset flexibility in the trajectory body coordinate system were investigated in this paper. As for the wheel-rail contact forces, which is a particular force element in vehicle multibody system, a method for calculating the Jacobian matrix of the wheel-rail contact force is proposed to better couple the wheel-rail contact force calculation with the vehicle dynamics response calculation. Based on the flexible wheelset modeling approach in this paper, two vehicle dynamic models considering the wheelset as both elastic and rigid bodies are established, two kinds of track excitations, namely normal measured track irregularities and short-wave irregularities are used, wheel-rail geometric contact characteristic and wheel-rail contact forces in both time and frequency domains are compared with the two models in order to study the influence of flexible wheelset rotation effect on wheel rail contact force.FindingsUnder normal track irregularity excitations, the amplitudes of vertical, longitudinal and lateral forces computed by the flexible wheelset model are smaller than those of the rigid wheelset model, and the virtual penetration and equivalent contact patch are also slightly smaller. For the flexible wheelset model, the wheel rail longitudinal and lateral creepages will also decrease. The higher the vehicle speed, the larger the differences in wheel-rail forces computed by the flexible and rigid wheelset model. Under track short-wave irregularity excitations, the vertical force amplitude computed by the flexible wheelset is also smaller than that of the rigid wheelset. However, unlike the excitation case of measured track irregularity, under short-wave excitations, for the speed within the range of 200 to 350 km/h, the difference in the amplitude of the vertical force between the flexible and rigid wheelset models gradually decreases as the speed increase. This is partly due to the contribution of wheelset’s elastic vibration under short-wave excitations. For low-frequency wheel-rail force analysis problems at speeds of 350 km/h and above, as well as high-frequency wheel-rail interaction analysis problems under various speed conditions, the flexible wheelset model will give results agrees better with the reality.Originality/valueThis study provides reference for the modeling method of the flexible wheelset and the coupling method of wheel-rail contact force to the vehicle multibody dynamics system. Furthermore, by comparative research, the influence of wheelset flexibility and rotation on wheel-rail dynamic behavior are obtained, which is useful to the application scope of rigid and flexible wheelset models.

A deep learning methodology based on adaptive multiscale CNN and enhanced highway LSTM for industrial process fault diagnosis

Intelligent fault diagnostic techniques are crucial for ensuring the long-term reliability of manufacturing. The process variables collected by sensors in real industrial systems typically exhibit diverse time scales and data features. To overcome the above issues, we propose a comprehensive model known as adaptive multiscale CNN and enhanced highway LSTM (ACEL). To begin with, multiscale features under variable operating conditions are automatically extracted by constructing the parallel convolutional module. Then, to selectively focus on the feature representation within the channels, efficient channel attention is introduced to downplay the channels with less important information. In addition, the bidirectional LSTM is designed to generate more fine-grained hybrid features based on contextual information and local features learned by the CNN. An enhanced highway configuration is designed to be used to bolster the global temporal dependencies. Finally, ACEL is applied to the Tennessee Eastman benchmark and CSTR simulation, and multiple statistical metrics show that the proposed model outperforms other advanced fault diagnosis methods.