Effects of Long-Term Vibration on Cellulose Degradation in an Oil-Impregnated Pressboard under Simultaneous Thermal–Electrical–Mechanical Stress Aging

Abstract

Due to the complex operation conditions in a power transformer, an oil-impregnated pressboard (OIP) simultaneously suffers from thermal, electrical, and mechanical stress. Since most research studies have paid much attention to thermal or electrical aging of OIPs, this paper analyzes the effects of long-term mechanical vibrations on cellulose degradation in OIPs under simultaneous multi-stress. The aging experiments were firstly conducted at 130 °C, with a DC electric voltage of +6 kV, vibration amplitude of 10–50 μm, and vibration frequency of 100–300 Hz. The finite element analysis (FEA) of the pressboard vibration model was then performed on Abaqus to investigate the time–frequency domain characteristic parameters of compressive stress on the pressboard under varied vibration frequencies and amplitudes. The FEA results reveal that compressive stress on the pressboard in a multi-stress aging experiment coincided with the axial compressive stress on the insulation spacers in an SZ-50000/110 transformer. Moreover, combined with the degree of polymerization (DP) of cellulose, the effects of long-term vibration on cellulose degradation are reflected in two ways: the increase in compressive stress on the pressboard generates more links available for degradation, while more high frequency harmonic components in compressive stress accelerate the reaction rate in cellulose degradation.

Evaluation method for insulation degradation of power transformer windings based on incomplete internet of things sensing data

“…Degradation evaluation methods relying on traditional indicators [4] Proposed a method based on spectral analysis and pattern recognition using furfural content as an index Cannot be applied to online deterioration evaluation [5] Investigated a method based on the methanol content [6] Explored the correlation between water content in oil data and transformer degradation [7] Developed a model based on feedforward neural networks using the degree of polymerization as an indicator [8] Studied the impact of electrical conductivity on insulation aging Degradation evaluation methods relying on a single type of IoT data [10] Proposed a method based on statistical indices of partial discharge Lack of consideration for multiple degradation factors and data incompleteness [11,12] Proposed two methods to eliminate partial discharge in transformers by preparing nanofluid to absorb gases such as acetylene in oil [13] Proposed a degradation prediction model based on temperature data [14] Investigated the method based on leakage current [15] Studied the electrical damage trend by incrementally increasing the voltage Consider multiple degradation factors but rely on traditional indicators [17] Constructed a dynamic model under the influence of electrical and thermal stress Cannot be applied to online deterioration evaluation [18] Explored the changing trends of indicators under thermal and mechanical stresses [19] Investigated the trends of the indicators under electrical, thermal and mechanical stresses [20] Studied the method based on tensile strength and dielectric constant under thermal-mechanical stresses Data completion for a single type of IoT sensing data [21] Completed voltage data using deep learning and unscented Kalman filtering Lack of consideration of spatiotemporal correlation between multiple IoT sensing data [22] Investigated data filling method in photovoltaic power using recursive long short-term memory network [23] Used the normal distribution method for filling power data of smart meters [24] Proposed a filling method for household load data based on noisy interpolation Abbreviation: IoT, Internet of Things.…”

“…Chi et al investigated the changes in the degree of polymerization and moisture content of oil-paper insulation under thermal stress and mechanical stress, observing the trends during insulation deterioration [18]. Li et al studied the variations in polymerization degree and furfural when electrical, thermal, and mechanical stresses were simultaneously applied to insulating paper [19]. Zhou et al explored a degradation estimation method based on the tensile strength and dielectric constant of materials under thermal-mechanical aging conditions [20].…”

“…Li et al. studied the variations in polymerization degree and furfural when electrical, thermal, and mechanical stresses were simultaneously applied to insulating paper [19]. Zhou et al.…”