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In real-world applications, the diagnostic efficiency of wind turbine systems, particularly rolling bearings, is significantly impaired by variable operating conditions such as fluctuating rotational speeds and varying loads, along with environmental disturbances including transient and non-Gaussian noises. These disturbances mask damage indicators, creating substantial challenges in accurate fault detection. Traditional diagnostic methods are often inadequate due to their sensitivity to noise and inability to identify failure signatures within multivariate random transient noise environments. To address these challenges in wind turbine fault diagnosis, this research introduces an adaptive signal processing regime with three key innovations: an adaptive signal tracking mechanism featuring real-time transient shift identification, a Dynamic Markov Transition Frequency with Adaptive Peak Rates (DMTF-APR) model for enhanced abnormality detection, and a Multi-Period Weighted Average Framework (MPWAF) that mitigates transient interference noise through the identification and replacement of anomalous signal fragments using periodic characteristics and weighted averages. Experimental validation with real-world wind turbine farm data demonstrates the framework’s superior fault diagnosis performance, particularly in scenarios with complex non-Gaussian or transient noise interference, achieving significant improvements in detection accuracy and reliability compared to conventional methods.
Enhancing power skiving tool longevity: the synergy of AI and robotics in manufacturing automation
(2024)
In gear manufacturing, the longevity and cost-effectiveness of power skiving tools are essential. This study presents an innovative approach that combines artificial intelligence and robotics in manufacturing automation to prevent tool breakage to improve the remaining useful life (RUL). Using a robotic cell, the system captures six images per tooth from different angles. An unsupervised generative deep learning model approach is used because it is more suitable for industrial application as it can be trained with a small number of defect-free images. It is used in a first step as a classifier and, in a second step, to segment tool wear. This approach promises economic benefits by reducing manual inspection and, through automated tool inspection, detecting wear earlier to prevent tool breakage.
In the course of a more intensive energy generation from regenerative sources, an increased number of energy storages is required. In addition to the widespread means of storing electric energy, storing energy thermally can contribute significantly. However, limited research exists on the behaviour of thermal energy storages (TES) in practical operation. While the physical processes are well known, it is nevertheless often not possible to adequately evaluate its performance with respect to the quality of thermal stratification inside the tank, which is crucial for the thermodynamic effectiveness of the TES. The behaviour of a TES is experimentally investigated in cyclic charging and discharging operation in interaction with a cogeneration (CHP) unit at a test rig in the lab. From the measurements the quality of thermal stratification is evaluated under varying conditions using different metrics such as normalised stratification factor, modified MIX number, exergy number and exergy efficiency, which extends the state of art for CHP applications. The results show that the positioning of the temperature sensors for turning the CHP unit on and off has a significant influence on both the effective capacity of a TES and the quality of thermal stratification inside the tank. It is also revealed that the positioning of at least one of these sensors outside the storage tank, i.e. in the return line to the CHP unit, prevents deterioration of thermal stratification, thereby enhancing thermodynamic effectiveness. Furthermore, the effects of thermal load and thermal load profile on effective capacity and thermal stratification are discussed, even though these are much smaller compared to the effect of positioning the temperature sensors.
Für das Gelingen der Wärmewende und des von Klimaschutzminister Robert Habeck eingeforderten Wärmepumpenhochlaufs gilt es mannigfaltige Herausforderungen zu lösen. Welche Chancen in diesem Zusammenhang eine Kombination von Wärmepumpe und Kraft-Wärme-Kopplung (KWK) eröffnet, wird im folgenden Beitrag erörtert.
Für die erfolgreiche Umsetzung der Energiewende in Deutschland ist die Kraft-Wärme-Kopplung (KWK) aufgrund ihrer hohen Effizienz und Flexibilität nicht mehr wegzudenken. Um die verfügbare Flexibilität einer KWK-Anlage unter Gewährleistung ihrer hohen Effizienz optimal nutzen zu können, ist an der Hochschule Reutlingen in mehrjährigen Forschungsarbeit ein prognosebasierter Steuerungsalgorithmus für Blockheizkraftwerke (BHKW) in Verbindung mit Wärmespeichern entwickelt worden.
Flexible KWK – aber wie?
(2021)
Es ist mittlerweile unstrittig, dass Kraft-Wärme-Kopplungs-Anlagen (KWK-Anlagen) zunehmend flexible betrieben werden müssen. Nur so kann es gelingen, die Anlagen optimal in das elektrische Energiesystem einzubinden, beispielsweise zur Deckung der Residuallast oder zur Unterstützung der Verteilnetze, und damit zur Umsetzung der Energiewende beizutragen. Auch der Gesetzgeber fordert den flexiblen Betrieb durch die Absenkung der förderfähigen Betriebsstunden im KWK-Gesetz ein. Um vor diesem Hintergrund jedoch parallel die Deckung des erforderlichen Wärmebedarfs unter Gewährleistung der hohen Effizienz der KWK sicherzustellen, ist eine intelligente Steuerung der Geräte erforderlich. Zu diesem Zweck ist an der Hochschule Reutlingen ein vorausschauender Steuerungsalgorithmus zum „stromoptimierten“ und netzdienlichen“ Betrieb von KWK-Anlagen bei voller Nutzung der KWK-Wärme als Alternative zum standardmäßig anzutreffenden wärmegeführten Betrieb entwickelt worden.
Im Rahmen dieses Aufsatzes soll anhand eines Praxisbeispiels aufgezeigt werden, wie sich vor dem Hintergrund des aktuellen KWK-Gesetzes die Entscheidung für eine KWK-Anlage mit einer größeren Leistung bereits heute wirtschaftlich auswirkkt. Darüber hinaus wird eine Methode zur Festlegung des optimalen Pufferspeichervolumens vorgestellt.
Micro grids often consist of energy generators, storages and consumers with controllers which are not prepared for their integration into communication networks for energy systems. In this paper it will be presented, how standards from the field of energy automation can be applied in such controllers. The data for communication interfaces can be structured according to the IEC 61850- or the VHPREADY standard. It is investigated which requirements must be supported to implement such data models within the controllers. For the transmission of the data we propose the OPC UA protocol, which supports extensive security measures and which is today available for nearly all modern types of controllers and computers.
Coupling electricity and heat sector is one of the most necessary actions for the successful energy transition. Efficient electrification for space heating and domestic hot water generation is needed for buildings, which are not connected to any district heating network, as distributed heating demand momentarily is largely met by fossil fuels. Hence, hybrid energy systems will play a pivotal role for the energy transition in buildings. Heat pumps running on PV-electricity is one of the most widely discussed combination for this purpose. In this paper, a heuristic optimization method for the optimal operation of a heat pump driven by the objective for maximum onsite PV electricity utilization is presented. In this context, the thermal flexibility of the building and a thermal energy storage (TES) for generation of domestic hot water (DHW) are activated in order to shift the operation of the heat pump to times of PV-generation. Yearly simulations for a system consisting of heat pump, PV modules, building with floor heating installation and TES for DHW generation are carried out. Variation parameters for the simulation include room temperature amplitude (0.5, 1, 1.5 and 2 K) based on mean room temperature (21 °C), PV-capacity (4, 6, 8 and 10 kW) and type of heat pump (ground source and air source type). The yearly energy balances show that buildings offer significant thermal storage capacity avoiding an additional, large TES for space heating fulfillment and improving the share of onsite PV electricity utilization. With introduction of a battery, which has been analyzed as well for different sizes (1.9, 4.8, 7.7 and 10.6 kWh), the share of onsite PVelectricity utilization can even be improved. However, thermal flexibility supplemented by the varying room temperature amplitude for a bigger battery does not improve the share of onsite PV-electricity utilization. Nevertheless, even with a battery not more than 50% of the electrical load including operation of the heat pump can be covered by PV-electricity for the specific system under investigation. This is noteworthy on the one hand, since it indicates that a hybrid heating system consisting of heat pump and PV cannot solely cover the heat demand of residential buildings. One the other hand, this emphasizes the necessity to include further renewable sources like wind power, in order to draw the complete picture. This, however, is beyond the scope of this paper, which mainly focuses on introduction and verification of the novel control method with regard to a practical building.
