Biological investigation and predictive modelling of foaming in anaerobic digester

Anaerobic digestion (AD) of waste has been identified as a leading technology for greener renewable energy generation as an alternative to fossil fuel. AD will reduce waste through biochemical processes, converting it to biogas which could be used as a source of renewable energy and the residue bio-solids utilised in enriching the soil. A problem with AD though is with its foaming and the associated biogas loss. Tackling this problem effectively requires identifying and effectively controlling factors that trigger and promote foaming. In this research, laboratory experiments were initially carried out to differentiate foaming causal and exacerbating factors. Then the impact of the identified causal factors (organic loading rate-OLR and volatile fatty acid-VFA) on foaming occurrence were monitored and recorded. Further analysis of foaming and nonfoaming sludge samples by metabolomics techniques confirmed that the OLR and VFA are the prime causes of foaming occurrence in AD. In addition, the metagenomics analysis showed that the phylum bacteroidetes and proteobacteria were found to be predominant with a higher relative abundance of 30% and 29% respectively while the phylum actinobacteria representing the most prominent filamentous foam causing bacteria such as Norcadia amarae and Microthrix Parvicella had a very low and consistent relative abundance of 0.9% indicating that the foaming occurrence in the AD studied was not triggered by the presence of filamentous bacteria. Consequently, data driven models to predict foam formation were developed based on experimental data with inputs (OLR and VFA in the feed) and output (foaming occurrence). The models were extensively validated and assessed based on the mean squared error (MSE), root mean squared error (RMSE), R2 and mean absolute error (MAE). Levenberg Marquadt neural network model proved to be the best model for foaming prediction in AD, with RMSE = 5.49, MSE = 30.19 and R2 = 0.9435. The significance of this study is the development of a parsimonious and effective modelling tool that enable AD operators to proactively avert foaming occurrence, as the two model input variables (OLR and VFA) can be easily adjustable through simple programmable logic controller

Proceedings - 32. Workshop Computational Intelligence: Berlin, 1. - 2. Dezember 2022

This conference volume contains the contributions of the 32nd workshop "Computational Intelligence" of the Technical Committee 5.14 of the VDI/VDE Society for Measurement and Automation Technology (GMA) of 1.12. – 2.12.2022 in Berlin. The focus is on methods, applications and tools for

Proceedings - 32. Workshop Computational Intelligence: Berlin, 1. - 2. Dezember 2022

Dieser Tagungsband enthält die Beiträge des 32. Workshops „Computational Intelligence“ des Fachausschusses 5.14 der VDI/VDE-Gesellschaft für Mess- und Automatisierungstechnik (GMA) der vom 1.12. – 2.12.2022 in Berlin stattfand. Die Schwerpunkte sind Methoden, Anwendungen und Tools für - Fuzzy-Systeme - Deep Learning - Machine Learning sowie der Methodenvergleich anhand von industriellen und Benchmark-Problemen

Multiple Damage Identification of Beam Structure Using Vibration Analysis and Artificial Intelligence Techniques

This thesis investigates the problem of multiple damage detection in vibrating structural members using the dynamic response of the system. Changes in the loading patterns, weakening/degeneration of structures with time and influence of environment may cause cracks in the structure, especially in engineering structures which are developed for prolonged life. Hence, early detection of presence of damage can prevent the catastrophic failure of the structures by appropriately monitoring the response of the system. In recent times, condition monitoring of structural systems have attracted scientists and researchers to develop on line damage diagnostic tool. Primarily, the structural health monitoring technique utilizes the methodology for damage assessment using the monitored vibration parameters. In the current analysis, special attention has been focused on those methods capable of detecting multiple cracks present in system by comparing the information for damaged and undamaged state of the structure. In the current research, methodologies have been developed for damage detection of a cracked cantilever beam with multiple cracks using analytical, Finite Element Analysis (FEA), fuzzy logic, neural network, fuzzy neuro, MANFIS, Genetic Algorithm and hybrid techniques such as GA-fuzzy, GA-neural, GA-neuro- fuzzy. Analytical study has been performed on the cantilever beam with multiple cracks to obtain the vibration characteristics of the beam member by using the expressions of strain energy release rate and stress intensity factor. The presence of cracks in a structural member introduces local flexibility that affects its dynamic response. The local stiffness matrices have been measured using the inverse of local dimensionless compliance matrix for finding out the deviation in the vibrating signatures of the cracked cantilever beam from that of the intact beam. Finite Element Analysis has been carried out to derive the vibration indices of the cracked structure using the overall flexibility matrix, total flexibility matrix, flexibility matrix of the intact beam. From the research done here, it is concluded that the performance of the damage assessment methods depends on several factors for example, the number of cracks, the number of sensors used for acquiring the dynamic response, location and severity of damages. Different artificial intelligent model based on fuzzy logic, neural network, genetic algorithm, MANFIS and hybrid techniques have been designed using the computed vibration signatures for multiple crack diagnosis in cantilever beam structures with higher accuracy and considerably low computational time

Multi-Objective Control Strategies and Prognostic-Based Lifetime Extension of Utility-Scale Wind Turbines

Windenergie wird zunehmend als erneuerbare Energiequellen attraktiv, da Wind nachhaltig genutzt werden kann. In vielen Ländern gibt es umfangreiche Anstrengungen, die Produktion von elektrischer Energie aus Wind zu steigern. Im Vergleich zu anderen erneuerbaren Energiequellen wie Sonne, Gezeiten, Wasserkraft o.ä. ist die Energiegewinnung aus Wind technologisch ausgereifter. Daher ist die Energiegewinnung aus Wind stärker gewachsen ist als andere Technologien. Windkraft verursacht weniger nachteilige Auswirkungen auf die Umwelt als konventionelle Energiequellen. Aufgrund der vergleichsweise hohen Investitions-, Betriebs- und Wartungskosten sind trotz einer weltweit starken Verbreitung von Windenergieanlagen die Produktionskosten von Windenergie im Vergleich mit anderen alternativen Energiequellen hoch. Um die wachsende Nachfrage nachWindkraft zu befriedigen, werdenWindkraftanlagen in Größe und Leistung zunehmend skaliert. Bei zunehmender Größe dominieren die strukturellen Lasten der Turbine. Dies führt vermehrt zu Materialermüdung und Ausfällen. Ein weiterer Schwerpunkt in der Entwicklung von Windtechologie ist die Forderung nach Senkung der Produktionskosten, um einen Wettbewerbsvorteil gegenüber anderen alternativen Energiequellen zu schaffen. Im Bereich der Steuerung können niedrigere Produktionskosten durch den Betrieb der Windturbine am/oder in der Nähe der optimalen Energieeffizienz im Teillastbetrieb erreicht werden. Dies erhöht die Zuverlässigkeit durch Verringerung des Verschleißes und die erzeugte Nennleistung auf ihrem Nennwert im hohen Windregime. Häufig ist es schwierig, einen Steueralgorithmus zu realisieren, der sowohl Effizienz als auch Zuverlässigkeit gewährleistet, da diese beiden Ziele widersprechen. In dieser Arbeit werden Mehrzielsteuerungsstrategien sowohl für den Teillastbereich als auch für hohe Windgeschwindigkeits bereiche vorgestellt. Im Bereich geringer Windgeschwindigkeiten ist eine Steuerungsstrategie so zu konzipieren, dass die Stromerzeugung sowie die strukturelle Belastung im Sinne einer Balance zwischen maximalen Stromproduktion und verlängerter Lebensdauer der Windturbine optimal ist. Für den Bereich hoher Windgeschwindigkeiten wird ein multivariates Steuerungsverfahren vorgeschlagen, um das Verhältnis von Leistung/Geschwindigkeit und struktureller Lastreduzierung zu optimieren. Es wird ein Regler zur Einzelblattverstellung entworfen, um sowohl die unausgewogene Strukturlasten als auch durch die Variation des Windgeschwindigkeit verursachte Rotorscheibe, vertikale Windscherung und Gierversatz fehler zu reduzieren. Um die Zuverlässigkeit derWindturbine zu gewährleisten, ist ein Online-Schadensbewertungsmodell in den Hauptwindturbinenregelkreis integriert, so dass die Windturbine entsprechend ihres aktuellen Verschleißzustandes betrieben wird. In Abhängigkeit von der akkumulierten Schadenshöhe werden Regler zur Einzelblattverstellung mit unterschiedlichen Lastreduktionen und Kompromissen bei der Stromerzeugung eingesetzt, um zwischen den beiden Zielen verlängerte Lebensdauer und Leistungsregelung einen geeigneten Kompromiss zu erzielten. Aufgrund der Herausforderungen die mit Offshore-Windpark Standorten verbunden sind, ist diese Art von prognose-basierter Regelung im Windturbinenbetrieb vor allem im Offshore-Einsatz vorteilhaft. Insbesondere im Kontext output-basierter Vertragsformen z.B. power purchase agreement (PPA) kann dieser Ansatz zur Optimierung der Wartungsplanung genutzt werden. Die Ergebnisse zeigen, dass die vorgeschlagenen Strategien die Auflast auf Windturbinen reduzieren kann ohne sich auf andere Ziele wie die Leistungsoptimierung und Leistung/Drehzahlregelung auszuwirken. Es konnte außerdem gezeigt werden, dass eine prognostisch basierte Steuerung effektiv die Lebensdauer von Windenergieanalagen verlängern kann, ohne das Ziel der Leistungsregelung einzuschränken.Wind energy is one of the rapidly growing renewable sources of energy due to the fact that wind is abundantly available and unlikely to be exhausted like fossil fuel. Additionally, there are deliberate effort to sensitize many countries to develop polices that support production of electrical power from wind. Maturity of wind energy technology has made power production from wind grow significantly compared to other renewable energy sources such as solar, tidal, hydro among others. Like many other renewable energy sources, production of power from wind has less adverse effects on the environment. Despite the growth of global cumulative installed wind capacity, its cost of production is still higher compared to other alternative energy sources due to high initial investment cost and high operation and maintenance (O&M) costs. To meet the growing demand of wind power, wind turbines are being scaled up both in size and power rating. However, as the size increases, the structural loads of the turbine become more dominant, causing increased fatigue stress on the turbine components and consequent loss of functionality before the end of lifetime. Another area of focus in wind power production is lowering its production cost; hence, making it more competitive compared to other alternative power sources. From the control point of view, low production cost of wind energy can be achieved by operating wind turbine at/or near the optimum power efficiency during partial load regime, regulating generated power to its rated value in the high wind regime as well as mitigating structural loads so as to guarantee extended lifetime. Often, it is difficult to realize a control algorithm that can effectively guarantee both efficiency and reliability because these two aspects involve conflicting objective. Therefore, it is important to optimize the trade-off between these competing control objectives. In this thesis, multi-objective control strategies for both the partial load region and high wind speed region are presented. During low wind speed, a control strategy that optimizes power production as well as mitigating structural load is designed to balance between power production maximization and extended lifetime of wind turbine. On the other hand, a multivariate control method to balance between power/speed regulation and structural load reduction is proposed for high wind speed region. More specifically, an individual blade pitch controller is designed to eliminate the unbalanced deterministic structural loads across rotor disc caused by variation in wind speed, vertical wind shear, and yaw misalignment error. To guarantee reliability in wind turbine, an online damage evaluation model is also integrated into the main wind turbine control loop such that wind turbine is operated accordance to its structural health status in order to tolerate fault or to extend its service lifetime by a given period of time. Depending on the accumulated damage level, individual pitch controllers with different degrees of load reduction and power production compromise are employed to balance between extended lifetime and power regulation objective. This kind of prognostic-based control is useful in wind turbine operation, especially in offshore application due to challenges associated with offshore wind farm sites. Additionally, in wind farms that are managed through output-based contracts such as power purchase agreement (PPA), this approach can be utilized to optimize maintenance scheduling to avoid unscheduled downtime. The results demonstrated that the proposed multi-objective control strategies can reduce structural load on wind turbine without adversely affecting other objectives of power optimization and power/speed regulation. It has also be shown that a prognostic-based control can be effectively used to extend the lifetime of wind turbine without sacrificing the objective of power regulation

Advanced Strategies for Robot Manipulators

Amongst the robotic systems, robot manipulators have proven themselves to be of increasing importance and are widely adopted to substitute for human in repetitive and/or hazardous tasks. Modern manipulators are designed complicatedly and need to do more precise, crucial and critical tasks. So, the simple traditional control methods cannot be efficient, and advanced control strategies with considering special constraints are needed to establish. In spite of the fact that groundbreaking researches have been carried out in this realm until now, there are still many novel aspects which have to be explored