Large Power Equipment Research Articles

A Transformer Maintenance Interval Optimization Method Considering Imperfect Maintenance and Dynamic Maintenance Costs

As one of the most critical components of the power grid system, transformer maintenance strategy planning significantly influences the safe, economical, and sustainable operation of the power system. Periodic imperfect maintenance strategies have become a research focus in preventive maintenance strategies for large power equipment due to their ease of implementation and better alignment with engineering realities. However, power transformers are characterized by long lifespans, high reliability, and limited defect samples. Existing maintenance methods have not accounted for the dynamic changes in maintenance costs over a transformer’s operational lifetime. Therefore, we propose a maintenance interval optimization method that considers imperfect maintenance and dynamic maintenance costs. Utilizing defect and maintenance cost data from 400 220 KV oil-immersed transformers in northern China, we employed Bayesian estimation for the first time to address the distribution fitting of defect data under small sample conditions. Subsequently, we introduced imperfect maintenance improvement factors to influence the number of defects occurring in each maintenance cycle, resulting in more realistic maintenance cost estimations. Finally, we established an optimization model for transformer maintenance cycles, aiming to minimize maintenance costs throughout the transformer’s entire lifespan while maintaining reliability constraints. Taking a transformer’s strong oil circulation cooling system as an example, our method demonstrates that while meeting the reliability threshold recognized by the power grid company, the system’s maintenance cost can be reduced by 41.443% over the transformer’s entire life cycle. Through parameter analysis of the optimization model, we conclude that as the maintenance cycle increases, the factors dominating maintenance costs shift from corrective maintenance to preventive maintenance.

Recent advances in control strategies and algorithms for pilot-operated electro-hydraulic proportional directional valves

Pilot-operated electro-hydraulic proportional directional valve is a key hydraulic component to control the motion of large power equipment such as construction machinery and agricultural equipment. The control accuracy and response speed of the valve control element are very important to the performance of the hydraulic system. In this paper, control strategies for dead-zone control and valve control systems are reviewed. In order to eliminate the dead-zone of pilot-operated proportional valve control, the current control schemes for dead-zone detection and dead-zone compensation are summarized, and the control schemes are evaluated. The proportional–integral–derivative-related control, nonlinear control, and robust control of the pilot-operated electro-hydraulic proportional directional valve control system are reviewed, the relationship between the control strategies is analyzed, and the different control algorithms are evaluated. The shortcomings of the research program are analyzed, and the corresponding solutions are proposed. Based on the current research, future research progresses for eliminating the control dead-zone and optimizing control strategies are presented.

Review of Recent Advances in the Drive Method of Hydraulic Control Valve

Hydraulic control valves are widely used in industrial production, agricultural equipment, construction machinery, and other large power equipment for controlling the pressure and flow of fluids in hydraulic systems. The driving method has a significant impact on the response and control accuracy of hydraulic valves. This paper reviews the driving methods of spools from five aspects: solenoid drive, material expansion drive, motor drive, hydraulic valve drive, and another drive. It summarizes the various schemes currently available for spool drive and analyzes each of them. After optimizing the driving method of the valve core, the control accuracy can reach 3%, and the minimum response time is 7 ms. According to the characteristics of the different drive methods, the differences between them are compared, the advantages and disadvantages of each drive method are analyzed, and the application scenarios for each drive method are identified. Solutions to the drawbacks of the existing drive methods are proposed, which provide directions for further optimization. We have found that solenoid drives are simple to control, low cost, and the most widely used. Material telescopic drives, motor drives, hydraulic valve drives, and other drives are costly, complex to control, and optional for use in special requirement situations. Based on the existing spool drive methods, an outlook on future drive methods is presented. This review facilitates a comprehensive understanding of the drive methods of hydraulic valve spools, points out the shortcomings of the existing drive methods, and is of great significance in improving the existing drive methods and proposing new drive methods. This paper has a positive effect on improving the control accuracy and responsiveness of hydraulic valves.

Effect of Excitation Signal on Double-Coil Inductive Displacement Transducer.

A double-coil inductive displacement transducer is a non-contact element for measuring displacement and is widely used in large power equipment systems such as construction machinery and agricultural machinery equipment. The type of coil excitation signal has an impact on the performance of the transducer, but there is little research on this. Therefore, the influence of the coil excitation signal on transducer performance is investigated. The working principle and characteristics of the double-coil inductive displacement transducer are analyzed, and the circuit simulation model of the transducer is established. From the aspects of phase shift, linearity, and sensitivity, the effects of a sine signal, a triangle signal, and a pulse signal on the transducer are compared and analyzed. The results show that the average phase shift, linearity, and sensitivity of the sine signal were 11.53°, 1.61%, and 0.372 V/mm, respectively; the average phase shift, linearity and sensitivity of the triangular signal were 1.38°, 1.56%, and 0.300 V/mm, respectively; and the average phase shift, linearity, and sensitivity of the pulse signal were 0.73°, 1.95%, and 0.621 V/mm, respectively. It can be seen that the phase shift of a triangle signal and a pulse signal is smaller than that of a sine signal, which can result in better signal phase-locked processing. The linearity of the triangle signal is better than the sine signal, and the sensitivity of the pulse signal is better than that of the sine signal.

Effect of the Coil Excitation Method on the Performance of a Dual-Coil Inductive Displacement Transducer.

A dual-coil inductive displacement transducer is a non-contact type measuring element for measuring displacement and is widely used in large power equipment systems such as construction machinery and agricultural equipment. However, the effect of the coil excitation method on the performance of dual-coil inductive displacement sensors has not been studied. This paper investigates the impact of different coil excitation methods on the operating performance of displacement transducers. The working principle, electromagnetic characteristics, and electrical characteristics were analyzed by building a mathematical model. A transducer measurement device was used to determine the relationship between core displacement and coil inductance. Three coil excitation methods were proposed, and the effects of the three coil excitation methods on the amplitude variation, phase shift, linearity, and sensitivity of the output signal were studied by simulation based on the AD630 chip as the core of the conditioning circuit. Finally, the study's feasibility was demonstrated by comparing the experiment to the simulation. The results show that, under the uniform magnetic field strength distribution in the coil, the coil voltage variation is proportional to the inductive core displacement. The amplitude variation is the largest for the dual-coil series three-wire (DCSTW) and is the same for the dual-coil series four-wire (DCSFW) and dual-coil parallel differential (DCPD). DCSFW has an enormous phase shift. DCSTW has the best linearity. The research in this paper provides a theoretical basis for selecting a suitable coil excitation, which is conducive to further improving the operating performance of dual-coil inductive displacement transducers.

Application of Improved Process Neural Network Based on the Fireworks Algorithm in the Temperature-Rise Predictions of a Large Generator Rotor

Building an effective algorithm model for large key power equipment has very important research significance and application value. Aiming at the typical operating state characteristics of large generators and taking the temperature changes as the main research indicators, the improved fireworks algorithm was used to optimize the process neural network, and the key data characteristics were studied based on the machine experiment and actual operation data of a 300 MW generator so as to find the variation and development trends of the maximum temperature rise caused by negative-sequence current. Furthermore, the effectiveness of the neural network model suitable for large generators established in this paper was verified by test functions and experiments. On this basis, the calculation method was applied to different working conditions, component materials, and heating positions of the generator. Moreover, the temperature-rise prediction results of the structural components for the generator rotor were obtained, and the optimization scheme of the slot wedge material given, which provide a reference for temperature-rise research and the selection of component materials for large generators.

Numerical Analysis of Streamer Discharge Propagation Characteristics in Natural Ester

Natural ester is viewed as the most promising future alternative to mineral oil due to its high degradability, but its inferior breakdown characteristics prevent its application of large power equipment. The purpose of this research is to investigate the breakdown characteristics of natural ester. First, the natural ester's ionization potential and molecular number density are calculated. Then, an improved natural ester streamer discharge model is developed using the Poisson's equation and the carrier continuity equation, taking into account the effect of temperature on carrier mobility and incorporating the computed ionization potential and other factors. The results for different lightning impulse voltages were analyzed by COMSOL software. Comparing the mineral oil, the results indicate that the natural ester breakdown voltage is close to and slightly lower than that of the mineral oil but the acceleration voltage is very similar to the breakdown voltage. The lower ability of esters in prevention against the development of fast and energetic streamers is consistent with the description of the experimental results. In addition, the model takes into account the effect of temperature on the carrier mobility. As the applied voltage increases, the change of temperature in the streamer channel accelerates the carrier motion and promotes the propagation of the streamer. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

Realizing high-voltage and ultralong-life supercapacitors by a universal interfacial engineering strategy

Low energy density hinders the development of supercapacitors in the market of large hybrid power equipment and electric vehicles that demand much higher energy density. Herein, we conduct a facile and environmentally friendly method to modify the electrodes of supercapacitors through coating a dielectric thin film by atomic layer deposition (ALD) technique, which profoundly improves the electrochemical performance of the electrodes. In specific, the gravimetric capacitance of the ALD-Ti modified electrodes is characterized by 35% significant promotion comparing to the commercialized pristine counterparts, and the operational voltage window of the ALD treated electrodes can expand to 3.5 V using organic electrolyte with remarkable capacitance retention (over 83%) even after 20000 cycles. Besides, appropriate models are established to discuss the detailed charge storage mechanism and possible reasons for good stability of modified electrodes under higher operational voltage. Moreover, the excellent rate and cycling performance of ALD modified electrodes in flexible electrochemical double-layer capacitor (EDLCs) at the bending state substantiates the application superiority of ALD modified electrodes in flexible devices. The unusual combination of charge storage mechanisms of dielectric capacitors and EDLCs established in our work represents specific properties in great need for energy storage applications.

Development and Application of Real-Time Online Monitoring System for Long Transportation of Large Power Transformer

A set of transportation process monitoring system for large power transformer transportation is developed, including transportation state intelligent acquisition terminal, monitoring system platform software and mobile app. The effectiveness of the system is verified in the actual transportation monitoring of converter transformer. It solves a series of problems existing in traditional methods, ensures the transportation safety of large electric power equipment and reduces the investment.

Modification Effect of TiO<sub>2</sub> Hollow Nanoparticles on Insulating Properties of Transformer Oil

With the promoting of transmission voltage level and the continuous fluctuation of operating conditions by connecting renewable energy into the power system, more stringent requirements have been placed on the operation reliability of transformers and other large electrical equipment. Transformer oil, as the main liquid insulating medium in large power equipment, the modification of its insulating performance has always been research focus in dielectric field. Studies have proved that TiO₂ nanomaterials can not only enhance the AC and positive impulse breakdown voltage of transformer oil, but also significantly improve the aging resistance of transformer oil. However, the DC breakdown voltage of transformer oil has not been greatly increased yet, and sometime even weakened. In this paper, TiO₂ hollow nanoparticles were prepared by hard template method to modify transformer oil. AC and DC breakdown voltage and dielectric permittivity of transformer oil before and after modification were measured and analyzed. The results show that the AC breakdown voltage of the transformer oil can be increased by 32.5%. DC breakdown voltage was increased first and then reduced with the increasing of nanoparticle concentration, while no obvious improvemnet was observed. Based on breakdown mechanism and permittivity of transformer oil, we think the hollow structure of the nanoparticles can significantly enlarge the interface between particle and oil, which greatly promotes the capturing capability to fast electrons and inhibit their migration in the oil, so the AC breakdown voltage are significantly increased. Under DC stress, nanoparticles can capture electrons and meanwhile migrate along fixed direction, which increased electrical conductivity of oil and resulted in lowering of DC breakdown voltage with the increase of nanoparticle concentration.

Design of the levers at the development of new self-equalizing thrust bearings

Plain bearings are undoubtedly one of the main parts of the power machines (such as a turbine or compressor). However, there are many cases when in large power equipment is occurring asymmetrically loading on bearings due to thermal deformations, production inaccuracies, or simple deflection of the shaft. Presented research deals with the numerical analysis of levers being as the first step at the design of a new self-equalizing thrust bearing with the goal to find out its behaviour and base on that to make the improvements. The numerical analysis was done for the bearing with 12 segments using the software ANSYS. The boundary conditions were applied so to prevent the movement (collapse) of the system and at the same time use them to influence the stress distribution in the levers as little as possible. The steel 34CrNiMo6 has been used for the levers in a refined state. The achieved results confirmed the design of the levers, its sufficient stiffness, good functionality, and reliability.

SWCNTs-based MEMS gas sensor array and its pattern recognition based on deep belief networks of gases detection in oil-immersed transformers

MEMS gas sensor arrays and specially designed pattern recognition systems are the main research directions in the field of modern sensing technology in the engineering, especially in the smart sensing and monitoring of faults in large power equipment such as oil-immersed transformers. In this paper, the MEMS sensor array composed by eight SWCNTs-based (pure, OH functionalized, COOH functionalized, NH2 functionalized by ethylenediamine, NH2 functionalized by aniline, Ni-coated, Pd-doped, ZnO-doped) sensing units was palced in the fault characteristic gases (H2, CO, and C2H2) of oil-immersed transformers, and their gas-sensing characteristics were tested in single and mixed gas atmosphere. Combined with the DBN-DNN pattern recognition method, the qualitative identification and quantitative analysis of the sensor array in a mixed gas atmosphere was realized, and the accuracy and reliability of the results are higher than the traditional BPNN model.

Research of Tribological Properties of 34CrNiMo6 Steel in the Production of a Newly Designed Self-Equalizing Thrust Bearing

There are many cases when in large power equipment (such as a turbine or compressor) asymmetrically loading on bearings due to thermal deformations, production inaccuracies, or simple deflection of the shaft occurs. This asymmetrically loading means misalignment of rotor against stator in angle more than several tenths of a degree and it has an influence on a journal and thrust bearings. Over the last few years, thanks to increasingly precise manufacturing, solutions that can eliminate this phenomenon have been revealed. In the case of the thrust bearing, it is a system of very precise manufactured levers, which are in close contact each to other, so they have to be not only properly designed from the geometrical point of view but the important role plays a quality of the functional surfaces of these levers. The article deals with the surface treatment effect on tribological properties of 34CrNiMo6 steel used for the production of bearing levers, which are the critical parts of a newly developing self-equalizing thrust bearing. The samples with cylindrical and plate shapes were produced from 34CrNiMo6 steel as representatives of the most suitable geometries for contact surfaces. All samples were heat-treated. The surfaces of some samples were treated by electroless nickel plating or nitriding, some of the samples were treated by tumbling. Gradually, the surface roughness, microhardness, metallographic analysis and the influence of selected types of surface treatments on the wear for individual samples were evaluated within the research presented in the article. As the testing methods for evaluation of tribological properties were selected Pin-on-disc test and frequency tribological test. The results showed that the best tribological properties achieved samples treated by electroless nickel plating compared with the nitrided or only heat-treated samples.

Predictive analytics as a way to smart maintenance of hydraulic turbines

Today, most energy companies face serious problems with the reliability and safety of large power equipment due to the long-term operation at off-design modes. This is especially true for hydraulic units that are traditionally used to ensure the required level of energy output and maintain the stability of a power grid due to their maneuverability. Off-design operational modes cause increased loads and stresses in the unit’s components, accelerate the growth of defects, stimulate premature failures, and can lead to a grave accident with large losses.Standard diagnostic systems for hydraulic units usually do not allow tracking hazardous defects such as fatigue cracks in the runner blades, guide vines, shaft, etc. The individuality of hydraulic units also excludes the use of any statistical methods to determine the time when the equipment will go to the limit state and its operation will become unreasonably dangerous. Therefore, the predictive analytics system is proposed as an additional approach to forecasting the appearance and growth of dangerous operational defects. The system realizes an analytical algorithm based on evaluating the fatigue strength of hydraulic unit elements under variable operating conditions and allows summing up damage from various external loads and in different time ranges.Input data for this predictive system is information about the actual operating time at every working mode and expected regime parameters for the upcoming period. The output data is information about actual and residual lifetime. All individual features are taken into account by the digital model which is a multidimensional matrix of equipment’s response to external influences. Data is generated in the cells for each unit’s elements with reference to the operating parameters and time scale.The proposed predictive analytics system allows not only to reduce the risk of accidents and unplanned shutdowns but it also is a way to smart maintenance of hydraulic turbines due to the development of the most effective, most reasonable, most lifetime-saving strategy of using the equipment.

Machinery Early Fault Detection Based on Dirichlet Process Mixture Model

The most commonly used single feature-based anomaly detection method for the complex machinery, such as large wind power equipment, steam turbine generator sets, and reciprocating compressors, exhibits a defect of low-alarm accuracy due to the non-stationary characteristic of the vibration signals. In order to improve the accuracy of fault detection, a novel method based on the Dirichlet process mixture model (DPMM) is proposed. First, the features of the mechanical vibration signals are used to construct the feature space of the equipment. The DPMM modeling method is then applied to self-learn the probabilistic mixture model of the feature space. The normal working condition model is used as the benchmark model. The early fault detection is realized by using a precise difference measurement method based on Kullback-Leibler divergence to calculate the difference between the real-time model and the benchmark model accurately, and by comparing the calculation result with a self-learned alarm threshold. The effectiveness and the adaptability of this novel early fault detection method are verified by comparing it to the single feature-based anomaly detection method and the Gaussian mixture model (GMM)-based early fault detection method.

Systematic approach to evaluating environmental and ecological technologies for wastewater treatment

Evaluating the performance of wastewater treatment represents a challenging and complex task as it usually involves engineering, environmental and economic (3E) factors. In this study, we developed an 3E triangle model to evaluate the performance of environmental technologies (i.e., anaerobic-anoxic-oxic reactors, oxidation ditches, and membrane bioreactors) and ecological technologies (i.e., stabilization ponds, constructed wetlands, and slow-rate systems) for wastewater treatment. A total of 17 key performance indicators, such as energy consumption, pollutant removal, global warming potential and wastewater treatment fees, were considered in the 3E triangle model. The results indicated that, in terms of engineering performance, both the membrane bioreactors and constructed wetlands were stable, effective and reliable during their operating periods. When the environmental impacts of wastewater treatment technologies were compared via a life cycle assessment, the ecological technologies showed superior performance, in terms of environmental impacts, especially for the global warming potential and eutrophication potential. In general, environmental technologies exhibited higher treatment fees and unit construction costs because of their large power consumption and equipment costs. In contrast, ecological technologies had higher unit land use due to their large area requirements and low treatment capacity. In overall, both the membrane bioreactors and constructed wetlands showed excellent overall performance in the 3E triangle model. Wastewater treatment plant are typical case studies for addressing the interactions of water and energy elements. Reducing energy consumption is a hotspot for the research field of membrane bioreactors, while constructed wetlands are continually improved and optimized to have broad applications for rural wastewater treatment.

Intelligent Operation and Maintenance Technology of Converter Valve Based on Augmented Reality and Model Layering Technology

According to the DC converter valve and other large power equipment, the research model of hierarchical reconstruction technology based on traditional panoramic 3D model, construction of converter valve panoramic hierarchical model, the structural layer, the operation of the equipment electrical layers show more accurately show the relationship between assembly of internal layers between the components of the operation. Innovative use of direct slicing of 3D model, without intermediary file conversion, the geometric features of large power equipment of 3D model forming slice spire deviation of different distribution forms of lower slice contour, accurate extraction of 3D model in the section contour data specified at the height, while the physical layer, electrical layer the different internal structure of real-time hierarchical display, in order to solve the geometric model data format conversion caused by the loss of precision problem description. The monitoring data of the operation of the equipment and the virtual model integration superimposed by augmented reality show, the staff is more intuitive understanding of the inside and outside of the equipment structure, quickly get parts corresponding to the operation state, field operations personnel more accurate operation of auxiliary comprehensive judgment of equipment and parts of the overall view. Improve the efficiency of on-site inspection of large-scale power equipment and the accuracy of field equipment diagnosis.

Influence of sinusoidal and square voltages on partial discharge inception in geometries with point‐like termination

High-voltage equipment involves both electrical and electronic components. In electrical power network, which consists of rotating machine, power transformers and transmission lines, field enhancement at critical regions can lead to local breakdown [partial discharges (PD)]. The continuous occurrence of PDs can lead to complete breakdown. While in large power equipment sharp edges can be avoided, this is not the case in power converter due to the miniature nature of the semiconductor device. Sharp edges can also be present in any power equipment in the shape of conducting particles, either stuck at a barrier or freely moving in the bulk oil. This creates high-field regions, prone to PD activities. Different power equipment operates at different voltages such as AC, DC, square voltage, pulse voltage, fast-rise transient voltage etc. This study presents the influence of sinusoidal voltage, slow- and fast-rise square voltage on PDs in two different geometries using optical PD measurement technique. Fast-rise square voltage has the lowest PD inception voltage while the sinusoidal voltage has the highest. This is may be due to the influence of homo- and hetero-charges. Fast-rise square voltage displayed higher PD magnitude at inception which may be connected to the rise time of the voltage.

Similitude design for the vibration problems of plates and shells: A review

Similitude design plays a vital role in the analysis of vibration and shock problems encountered in large engineering equipment. Similitude design, including dimensional analysis and governing equation method, is founded on the dynamic similitude theory. This study reviews the application of similitude design methods in engineering practice and summarizes the major achievements of the dynamic similitude theory in structural vibration and shock problems in different fields, including marine structures, civil engineering structures, and large power equipment. This study also reviews the dynamic similitude design methods for thin-walled and composite material plates and shells, including the most recent work published by the authors. Structure sensitivity analysis is used to evaluate the scaling factors to attain accurate distorted scaling laws. Finally, this study discusses the existing problems and the potential of the dynamic similitude theory for the analysis of vibration and shock problems of structures.

Bootstrap and Maximum Entropy Based Small-sample Product Lifetime Probability Distribution

How to build the small-sample data distribution is a major issue to be addressed for analyzing large power equipment lifetime. To find a better product lifetime probability distribution function, a new method based on bootstrap and maximum entropy is proposed to study on the problem of small-sample product life probability distribution. The result shows that this new method is more accurate and feasible compared with bootstrap and maximum entropy respectively. Finally, an actual example of small-sample product lifetime distribution shows that this new approach has better guiding significance for practice.