Changes In Operating Conditions Research Articles

Use of Artificial Neural Networks in the Design of Adaptive Fuzzy Logic Controllers in the manufacturing of Prosthetic Knees

This paper presents real-time parameter updates that help to make adaptive machining process robust to changes in exogenous operating conditions. This work supports the commercial imperative for a customizable ‘batch size of one’ implant that does not unreasonably affect operating costs like tool life. A Neural Network (NN) is presented for use within a Computer Numerical Control (CNC) manufacturing cell to determine real-time tool offset adjustments in knee prostheses. This study integrates additional sensor inputs from the CNC cell, including improved force monitoring data for critical tools used in the machining of a Tibial component. The resulting time series force model is used to compare classification performance on Random Forest (RF) and Bi-directional Long Short Term Memory (BiLSTM) Neural Networks. In relation to network training performance, pre-processing improvements are reported for the RF algorithm using a time series data conversion process step. For the case of the BiLSTM model, 2D time series data is converted to a 3D array using a novel projection technique. The accuracy of both of methods is assessed in real-time using tool offset control applied using an adaptive fuzzy logic law. In this use case it has been observed that a RF approach exhibits less overfitting than its BiLSTM counterpart and therefore is a better choice for the dynamic computation of the tool offset height, the actuator output.

Smart Cities of the Central and Eastern Europe

Goal – the aim of this article is to discuss the essence of smart cities as one of the effects of public sector innovation. More specifically, the attention will be focused on the Central and Eastern European area, analyzing smart cities and their achievements in this region. Research methodology – the article contains review of the literature, an analysis of innovation and smart cities measures and indicators, on the basis of international rankings and good practices. Score/results – the presented statistical data and good practises indicate that the innovativeness of the public sector and a scale of smart cities is growing. Innovations play a key role in creating development and the ability to adapt to constantly changing operating conditions. The implementation of the smart cities concept can be boldly described as an effect of the innovation of the private sector. It is thanks to this type of activities that cities are able to meet the constantly changing expectations of residents, but also of potential investors. It is important to point that smart cities mean both economic and technological development, care for residents, but also sustainable development, i.e., despite striving for continuous technological development, care for the natural environment. Historical facts and belonging to the Eastern Bloc prevented countries from Central and Eastern Europe from achieving such a state of affairs. However, it is comforting to note that despite this developmental backwardness, these economies are actively trying to follow the path of innovation leaders, climbing up the innovation and smart city rankings. Originality/value – the review of the literature on the subject and the conducted analysis have highlighted serious problems with measuring innovation in the public sector and in smart cities. Moreover, the focus was on the somewhat forgotten part of the Central and Eastern Europe, which, despite its developmental backwardness, turned out to be aware of the power of innovation and the implementation of the smart city concept, which it continues to do in small or large steps.

Decay model of energy storage battery life under multiple influencing factors of grid dispatching

Energy storage batteries work under constantly changing operating conditions such as temperature, depth of discharge, and discharge rate, which will lead to serious energy loss and low utilization rate of the battery, resulting in a sharp attenuation of life, and the battery often fails before the end of its service life. Battery replacement leads to increasing energy storage costs, and in order to ensure the efficient, safe and reliable operation of batteries under complex working conditions of the power grid, effective management of batteries is required. The battery model is the theoretical basis of the management algorithm, and life prediction is the key technology to ensure battery safety. In view of the above practical application requirements, this paper studies the dynamic modeling of energy storage battery life based on multi-parameter information, and the results show that the proposed life model accurately reflects the battery life under multi-parameter information.

Scientific bases of control of vibration of hydrodynamic origin in centrifugal pumps

The reliability and efficiency of pumps, like any machines and mechanisms, is determined by a number of factors, including their operating conditions and the ability to adapt to changing operating conditions. This article is devoted to the development of scientific foundations for controlling vibration of hydrodynamic origin in centrifugal pumps. The failure of a centrifugal pump due to fatigue failure of a rolling bearing does not occur suddenly and not instantly. First, some signs of the approach of this process appear, the nature of the vibroactivity of the aggregate changes. Against the background of a stable vibration level, some vibration outliers appear. The study of the sequence and intensity of these emissions is important information not only about the approach of the moment of destruction of the rolling bearing parts, but also about the operating time that the operating personnel still have to take measures to eliminate an emergency and complete catastrophic destruction.

How organizational culture and HRM practices affect organizational performance in Greece and Scandinavia

Purpose: The intense competition among firms and their need to respond effectively to the constant changing operational conditions, as well as employees' requirements has escalated the necessity to identify the factors that affect organisational performance. The aim of this paper is to examine the interrelations between organizational culture-related dimensions (proactivity, obligation towards others, responsibility seeking, participation) and human resource management practices- related dimensions (job design, supervisory practices, reward system) and their impact on organizational performance in different countries, such as Greece and Scandinavia. Design/Methodology/Approach: A new research model that examines the relationships between the variables of Organisational Culture, Human Resource Management Practices and their impact on Organizational Performance. Findings: Based on the appropriate research model we develop and test hypotheses that show the relationship between Organizational Culture, Human Resource Management practices and their impact on Organizational Performance in different countries such as Greece and Scandinavia. Moreover, it presents some practical implications for the companies which may assist them to increase their organizational performance. Research Limitations: A potential limitation of this study is that it is not focused only on one business sector. Originality/Value: There has not been much research comparing these specific countries, which makes it worthwhile to explore the similarities or differences that may exist. Most importantly, these differences are examined under the light of different environmental forces, such as organisational culture, human resource management practices which are analyzed in depth. Give us comprehensive insights on their impact on organisational performance in different areas. Also, this research presents some practical implications for companies. Managers who are aware of the HRM practices which are more effective can contribute to enhance organizational performance. Some preliminary results show that proper job design, empowering supervision, reward allocation drive employees' satisfaction, that raises work efficiency which in turn increases organizational performance. Though strict supervision reduces employees' satisfaction and productivity.

Predictive maintenance in railway systems: MBS-based wheel and rail life prediction exemplified for the Swedish Iron-Ore line

A successful predictive maintenance strategy for wheels and rails depends on an accurate and robust modelling of damage evolution, mainly uniform wear and Rolling Contact Fatigue (RCF). In this work a life prediction framework for wheels and rails is presented. The prediction model accounts for wear, RCF, and their interaction based on the output from MBS simulations to calculate the remaining life of the asset, given in mileage for wheels and MGTs for rails. Once the model is calibrated, the proposed methodology can predict the sensitivity of the maintenance intervals against changes in operational conditions, such as changes in contact lubrication, track gauge, operating speeds, etc. The prediction framework is then used in two operational cases on the Swedish Iron-Ore line. The studied cases are, the analysis of wheel life for the locomotives, and the analysis of rail life for gauge widening scenarios. The results demonstrate the capabilities of the MBS-based damage modelling for predictive maintenance purposes and showcase how these techniques can set the path towards Digital Twins of railway assets.

Sensitivity of atomization characteristic to operation conditions for air-assisted atomizers in snow-makers

Air-assisted atomizers play a crucial role in generating nuclei and promoting heterogeneous nucleation in outdoor snow-makers. The change of operation conditions for snow-makers leads to a marked variation of atomization characteristic of air-assisted atomizers, which directly influences the nuclei generating and snow-making efficiency. This paper investigates the sensitivity of air-assisted atomizers’ atomization characteristic to operation conditions in snow-makers. For this purpose, a transparent device is designed, structured and tested. The water-air mixing process was presented, and the atomization behaviors of two air-assisted atomizers with different mixing modes were compared in order to find an appropriate mixing mode for outdoor snow-makers. Results show that the spray cone angle first goes up and then falls down with the increase of air-water pressure ratio, while Sauter mean diameter (SMD) decreases monotonically. The unbalanced air-water pressure ratio results in the failure of atomization because of the choking phenomenon. Inside the air-assisted atomizers, there are four stable mixing patterns in sequence, i.e., full water, churning flow, annular flow and full air. With the variation of the mixing pattern, the interaction between water and air changes, which causes different atomization characteristics under different operation conditions. Another interesting finding is that the atomizers with the mixing mode in which air and water are injected independently have remarkably better performance in avoiding choking situation and improving mass flow rate, which can be a better choice for outdoor snow-makers.

Using Detailing Concept to Assess Railway Functional Safety

The ability to assess the risks of the functional safety of railway tracks allows harmonizing characteristics of track elements under certain operating conditions under certain maintenance for the efficient use of the track structure throughout its life cycle. The concept of detailing conditions of the interaction of the rolling stock and railway track was used for the productive solution of tasks of infrastructure functional safety assessment. The paper formed an approach to the analytical solution of determination problems of deformability parameters over time using the elastic waves theory. The formation method of interconnections between the technical and economic aspects of the operation of railway infrastructure was proposed. The criteria of deformability work and intensity of use were utilized for the effective use of the track structure through its life cycle. The results of calculations are presented to assess changes in the deformability behaviour of the track elements and structure when the force and speed parameters of the operating conditions change, as well as the algorithm of the method for estimating the operation deformability of the railway track. Thus, the proposed approach can be adapted to optimize objects by railway functional safety assessment at the stage of object operation simulation.

An experimental realization of improved grid integrated multilevel inverter based PV systems with MPPT

AbstractThis research work explains a sliding mode controller‐based multilevel inverter for grid integrated photovoltaic power structure. A gravitational search algorithm based on maximum power point tracking has also been discussed for optimal photovoltaic power achievement. Moreover, a two‐stage cascaded interleaved boost converter has been employed, which provides minimised voltage/current ripple, higher current/power density, better efficacy, faster response, and reduced electromagnetic interference as major benefits. The multilevel inverter's proposed constant frequency‐based sliding mode controller provides better transient responses, high photovoltaic power tracking, and good robust behaviour under changing operating conditions. The proposed sliding mode controller has a fixed frequency operation and has low reactivity to parameter divergence. The proposed multilevel diode clamped inverter for grid integrated photovoltaic system provides a reduced number of components and a power rating. The gravitational search algorithm‐based swarm technique as a maximum power point tracking provides high convergence velocity, better accuracy, and good local search capability. The experimentation was carried out to implement control algorithms using the dSPACE platform. The designed multilevel inverter system with proposed control provides average 89.2% inverter efficiency under variation of sun insolations.

Computational design and fabrication of active 3D-printed multi-state structures for shape morphing

Active structures can change their shape, properties, and functionality as a response to changing operational conditions, which makes them more versatile than their static counterparts. However, most active structures currently lack the capability to achieve multiple, different target states with a single input actuation or require a tedious material programming step. In this work, a computational design and fabrication framework is proposed to generate structures with multiple target states for one input actuation that do not require a separate training step. A material dithering scheme based on multi-material 3D printing is combined with locally applied copper coil heating elements and sequential heating patterns to control the thermo-mechanical properties of the structures and switch between the different deformation modes. A novel topology optimization approach based on power diagrams is used to encode different target states in the structure while ensuring the fabricability of the structures. The numerical and experimental results show that the optimization framework can produce structures that show the desired motion, but experimental accuracy is limited by current fabrication methods. The generality of the proposed method makes it suitable for the development of structures for applications in many different fields from aerospace to robotics to animated fabrication in computer graphics.

Review of Methods for Addressing Challenging Issues in the Operation of Protection Devices in Microgrids with Voltages of up to 1 kV That Integrates Distributed Energy Resources

With the large-scale integration of distributed energy resources (DER) into passive distribution networks with voltages of up to 1 kV, these networks are being converted into microgrids. When the topology and operating conditions change, several challenging issues arise related to the functioning of the protection devices (PD) that are in operation. Most DERs, including renewable generators, are integrated into microgrids by means of inverters. In the event of short circuits (SC) in microgrids, these DERs provide a fault current contribution of no more than 1.2–2.0 Irated at the fault location. This makes it difficult to identify the fault location and to carry out the selective disconnection of the faulty element by means of conventional PDs. This article provides an overview of engineering solutions for improving conventional protection schemes that have been historically used in passive distribution networks, as well as for creating modern protection schemes based on innovative principles and new methods. The use of adaptive protections built on decentralized and centralized principles in most cases ensures the reliable protection of microgrids. Modern intelligent electronic devices (IEDs), where protection functions are implemented, rank higher with respect to their technical perfection in terms of reliability, sensitivity, selectivity, and speed performance. The use of multi-agent systems in the implementation of modern protection schemes requires the availability of broadband communication channels, which hinders their use because of the high cost. The combined use of fault current limiters (FCL) and energy storage systems (ESS) allows for the reliable operation of microgrid protections. The use of modern PDs ensures the reliable operation of DERs and power supply to consumers in microgrids, both in the case of grid-connected and islanded operation modes. Since there is no unified concept of designing protection schemes for microgrids with DERs, the choice of specific approaches to the design of protection schemes should be based on the results of a comparative technical and economic analysis of different options.

Pairing Bayesian Methods and Systems Theory to Enable Test and Evaluation of Learning‐Based Systems

ABSTRACTModern engineered systems, and learning‐based systems, in particular, provide unprecedented complexity that requires advancement in our methods to achieve confidence in mission success through test and evaluation (T&E). We define learning‐based systems as engineered systems that incorporate a learning algorithm (artificial intelligence) component of the overall system. A part of the unparalleled complexity is the rate at which learning‐based systems change over traditional engineered systems. Where traditional systems are expected to steadily decline (change) in performance due to time (aging), learning‐based systems undergo a constant change which must be better understood to achieve high confidence in mission success. To this end, we propose pairing Bayesian methods with systems theory to quantify changes in operational conditions, changes in adversarial actions, resultant changes in the learning‐based system structure, and resultant confidence measures in mission success. We provide insights, in this article, into our overall goal and progress toward developing a framework for evaluation through an understanding of equivalence of testing.

The dynamics of coordination patterns in multiteam systems response to emergency: Case study from a pharmaceutical enterprise.

Effective coordination of multiteam systems (MTSs) can help enterprises respond quickly to complex and uncertain problems under disasters. However, it is unclear how MTS coordination patterns dynamically affect MTS performance in disasters. This study examined how MTSs responded to an emergency production incident at the Zhejiang Huisong Pharmaceutical Company in China during the COVID-19 pandemic through a qualitative and quantitative study. Based on social network theory, we found that a centralized coordination pattern impacts MTS performance by giving play to the leadership team's network centrality position advantage during the crisis outbreak period. In the post-crisis period, the decentralized coordination pattern impacts MTS performance by giving play to the advantages of horizontal coordination. Our results help managers to consider the dynamics of coordination patterns in crisis management in ways that assist them in adapting an effective coordination pattern to changing and uncertain operational conditions.

A new compressible flow model for pneumatic directional control valves

In this study, a new compressible flow model for small orifice openings in pneumatic proportional directional control valves has been proposed. It is crucial to precisely control pneumatic valves over all control ranges; yet, conventional flow models fail around the closed position of the valve. The main deficit of the existing studies in the literature is to assume constant values for the parameters of the flow model over changing operating conditions. It has been demonstrated that these rough assumptions are insufficient in precisely predicting the mass flow rate, particularly for small orifice openings. An enhanced experimental setup has been introduced to improve the effectiveness of the proposed model. The cracking pressure ratio and parameters of the model have been identified with experimental method. In the proposed model, new empirical coefficients have been established after a thorough investigation of the impact of supply pressure on the flow behavior of the valve. Validation studies of the model in both the filling and exhausting states of the valve have been carried out at various supply pressures and orifice openings, yielding rather promising modeling performances. In validation tests, the real pressure and the pressure produced by new model have been compared, and good agreement has been achieved with 0.0039% absolute error. According to the findings, the proposed improved flow model can be selected in precision pneumatic control applications.

Effect of wind and wave properties in modal parameter estimates of an idling offshore wind turbine from long-term monitoring data

In the long-term, the modal properties of Offshore Wind Turbines (OWT) exhibit significant variations due to constant changes in environmental and operational conditions. These variations have a substantial effect on the wind turbine loads and will lead, for instance, to large uncertainty in fatigue and useful life predictions. Due to the numerous sources of uncertainty, it is difficult to judge how independent environmental or operational parameters influence the modal properties of OWTs. In this work, we make a systematic analysis of the modal parameter estimates extracted from a long-term monitoring campaign in an OWT from the DanTysk wind farm while in its idling condition. We cluster the dataset of vibration responses of the idling OWT into bins of wind and wave characteristics, in order to isolate the effect of the different sources of uncertainty affecting the OWT modal properties. Once the trends in the data are confirmed, we use a simple linear regression model to extrapolate the damping estimates for zero wind speed and wave excitation, thus providing an estimate of the mean and standard errors of the OWT structural damping in the first fore-aft and side-to-side tower bending modes.

Mathematical modeling of the evolution of a tribosystem in the process of formation of equilibrium roughness of a frictional contact

As the science of friction developed, tribologists showed that reliable operation of friction units is determined by the wear resistance of the surface layer, its ability to adapt to changing operating conditions. In this regard, there is a need not only to create structures on the surfaces of friction units that have the properties of self-regulation and self-organization, but also to monitor changes in the characteristics of the surface layer. This article presents an innovative methodology for monitoring the life cycle of surface layers coated by vacuum ion-plasma treatment. In this paper, we propose a dynamic model based on the hypothesis that roughness is both a factor that excites mechanical vibrations and a consequence of these vibrations, whereas roughness changes as a result of wear under the influence of local dynamic forces. It is shown that a friction pair is a nonlinear system with complex feedbacks. Its stationary motion can be considered as a strange attractor. The randomness of motion in the vicinity of the limit cycle is due to the presence of a link of constant delay with rigid positive feedback in the model. As a result, there is constant reconfiguration of the amplitude and phase of the oscillations.

Weld bead geometry real-time control in gas metal arc welding processes using intelligent systems

Gas metal arc welding (GMAW) process is one of the most important in the industry, so different efforts have been made to anticipate the parameters to convert this process into a stable one capable of joining parts with minimum human interference. In this sense, controlling is essential for automated applications because properties such as the weld mechanical strength are defined by the metal composition, the microstructure, and the weld bead geometry. Nevertheless, performing this automatic control to guarantee quality characteristics similar to a human expert’s in mechanized welding systems is still tricky. Nowadays, although various sensors have been used in the monitoring for control, it is still hard to detect effective options to real-time identify geometry characteristics in the formation process of the welds. Furthermore, even today, a process much more complex is to control more than one parameter simultaneously or control the weld penetration using a single sensor. Then, this research describes two intelligence systems for real-time control of the weld bead geometry in the GMAW process. The first is a passive vision system with sensor fusion that controls the width and height; the second is an active vision system that controls the penetration. Results indicate that the proposed methodology can be applied to simultaneously control external geometrical parameters without a predefined model of the welding process. In the case of penetration, a fuzzy controller and a neural network-based model help the system adapt to input parameter variations throughout the welding process, thus correcting instabilities under changing operating conditions.

A variable gain front-end electronics for drift chambers

The cluster counting/timing technique in a drift chamber allows to have a bias free impact parameter estimate. The application of this technique requires to measuring and counting the arrival times of each individual ionization cluster to a sense wire. In a Helium based gas mixture the rise time of the signal from a cluster is approximately 1 ns, therefore a readout electronic front-end with high linearity, low distortion and sufficiently high bandwidth is required. Furthermore, it would be useful for the readout electronics to be able to easily adapt its gain to the detector’s operating point. The use of a variable gain amplifier (VGA) allows to meet the needs arising from the changed operating conditions of the detector. The market offers components capable of satisfying all these needs with dimensions compatible with high-density drift chambers. A high linear, low distortion, remotely controllable, about 1GHz bandwidth and compact VGA is presented together with the measurements performed.

Predicting Chlorine and Trihalomethanes in a Full-Scale Water Distribution System under Changing Operating Conditions

Predicting free chlorine residual and Trihalomethanes (THMs) in water distribution systems (DS) is challenging, given the variability and imprecise description of the chlorination conditions prevailing in full-scale systems. In this work, we used the variable reaction rate constant (VRRC) model, which offers the advantage of describing variable applied dosage and rechlorination conditions without the need for model recalibration. The VRRC model successfully predicted chlorine decay and THMs formation in ammonia-containing water at the lab scale. Comparing the goodness of fit results showed a better fit by the VRRC model than the 1st-order and an equally good fit compared to the parallel 1st-order model. However, the independence of the VRRC coefficients upon chlorine dosage made it a better choice for full-scale implementation than the parallel 1st-order model. Chlorine and THMs predictions in the DS were performed in 22 locations from a full-scale DS in southern Quebec (Canada). Chlorine predictions by VRRC were conducted in the spring and fall of 2021 under changing water quality conditions (temperature, DOC, dosage). With a prediction target of 0.1 mg/L absolute error, the VRRC model met this target in 77% of the points in the spring and 73% in the fall. While the predictions were comparable and slightly better than those of the 1st-order model, the main advantage of the VRRC was its applicability under variable dosage and rechlorination conditions (e.g., booster chlorination). THMs predictions in the DS were successfully performed in fall 2021. While 91% of the nodes had less than 5 μg/L of absolute prediction error with the VRRC model, the 1st-order model only met this target in 1 out of 22 points. In addition to its high precision, the VRRC can predict THMs using only the lab scale experiments for model parametrization. This enables small utilities with limited resources to predict the possibility of THMs non-compliances under changing water quality conditions with simple lab-based experiments. Changing climatic conditions can deteriorate drinking water quality, raise regulatory concerns for chlorine and THMs, and threaten public health. Water utilities can use the simple approach proposed in this work to assess the possibility of non-compliance under changing conditions. Moreover, the efficiency of different interventions or mitigation strategies to resolve or avoid non-compliance can be evaluated with this approach.

Ultrasonic Testing of Mechanical Changes in a Water-Filled Pipe with Multi-Mode and Broadband Signals and Two-Level Compensation.

Ultrasonic testing (UT) has been widely used for the Nondestructive Evaluation (NDE) of pipes due to its many favorable characteristics. However, one of the main challenges in the general use of UT for real-world pipelines is the sensitivity of this method to environmental and operational condition changes. This paper proposes a new UT method with enhanced compensation for environmental effects and operational condition changes. In particular, the effectiveness of the new method is tested in the presence of temperature variations, and changes in water flow rate inside a stainless-steel pipe. The proposed UT method uses multi-mode and broadband guided ultrasonic waves in the pipe walls, excited and received by single-element ultrasonic sensors that are spatially separated, forming a measurement zone between any pair of such transmit and receive sensors. Amplitude changes, time shifts, and frequency content variations in the ultrasonic signal due to temperature changes and water flow are evaluated and compensated for reliable UT of mechanical changes in the pipe. It is observed that spurious effects of water flow on ultrasonic response, if not properly compensated, can dominate over effects due to actual mechanical changes, but such liquid-boundary effects can be compensated effectively by the proposed time- and frequency-filtering method.