Active vibration control systems in the frequency and sub-band domain.

Active noise and vibration control has been the subject of intense study in the last two decades due to the increased speed in digital signal processors and the technological development and manufacture of smart materials. This dissertation analyzes an active control system using adaptive digital signal processing techniques and applies it to the vibration reduction of hard disk drives (HDD). Specifically, this work focuses on the implementation of the adaptive algorithm in the frequency and sub-band domains for performance improvement.In this dissertation, selective adaptation in the frequency domain is proposed to alleviate the constructive interference associated with a feedback active control system. A new sub-band adaptive filter architecture without a signal path delay is proposed, and the associated adaptive algorithm is derived. This delayless sub-band algorithm can be applied to the active control systems to improve the convergence rate and trade-off the performance from the various sub-bands. The resulting side effect of the error path delay of the analysis filter bank is analyzed, and two compensation methods are proposed to increase the performance. The frequency domain method and the sub-band decomposition technique are then combined to improve the overall performance. The single-channel active control system is extended to the multiple-channel active control system to reduce the vibration of complex mechanical structure. The optimal performances of three variants of the feedback control system have been derived in terms of the correlation coefficients of the primary disturbances and the impulse responses of the secondary paths. Real time and simulation results are performed to verify the efficiency of the proposed algorithms and techniques

Formation Flight in Dense Environments

Formation flight has a vast potential for aerial robot swarms in various applications. However, existing methods lack the capability to achieve fully autonomous large-scale formation flight in dense environments. To bridge the gap, we present a complete formation flight system that effectively integrates real-world constraints into aerial formation navigation. This paper proposes a differentiable graph-based metric to quantify the overall similarity error between formations. This metric is invariant to rotation, translation, and scaling, providing more freedom for formation coordination. We design a distributed trajectory optimization framework that considers formation similarity, obstacle avoidance, and dynamic feasibility. The optimization is decoupled to make large-scale formation flights computationally feasible. To improve the elasticity of formation navigation in highly constrained scenes, we present a swarm reorganization method which adaptively adjusts the formation parameters and task assignments by generating local navigation goals. A novel swarm agreement strategy called global-remap-local-replan and a formation-level path planner is proposed in this work to coordinate the swarm global planning and local trajectory optimizations efficiently. To validate the proposed method, we design comprehensive benchmarks and simulations with other cutting-edge works in terms of adaptability, predictability, elasticity, resilience, and efficiency. Finally, integrated with palm-sized swarm platforms with onboard computers and sensors, the proposed method demonstrates its efficiency and robustness by achieving the largest scale formation flight in dense outdoor environments.Comment: Submitted for IEEE Transactions on Robotic

Comparison of the Mitochondrial Genome Sequences of Six Annulohypoxylon stygium Isolates Suggests Short Fragment Insertions as a Potential Factor Leading to Larger Genomic Size

Mitochondrial DNA (mtDNA) is a core non-nuclear genetic material found in all eukaryotic organisms, the size of which varies extensively in the eumycota, even within species. In this study, mitochondrial genomes of six isolates of Annulohypoxylon stygium (Lév.) were assembled from raw reads from PacBio and Illumina sequencing. The diversity of genomic structures, conserved genes, intergenic regions and introns were analyzed and compared. Genome sizes ranged from 132 to 147 kb and contained the same sets of conserved protein-coding, tRNA and rRNA genes and shared the same gene arrangements and orientation. In addition, most intergenic regions were homogeneous and had similar sizes except for the region between cytochrome b (cob) and cytochrome c oxidase I (cox1) genes which ranged from 2,998 to 8,039 bp among the six isolates. Sixty-five intron insertion sites and 99 different introns were detected in these genomes. Each genome contained 45 or more introns, which varied in distribution and content. Introns from homologous insertion sites also showed high diversity in size, type and content. Comparison of introns at the same loci showed some complex introns, such as twintrons and ORF-less introns. There were 44 short fragment insertions detected within introns, intergenic regions, or as introns, some of them located at conserved domain regions of homing endonuclease genes. Insertions of short fragments such as small inverted repeats might affect or hinder the movement of introns, and these allowed for intron accumulation in the mitochondrial genomes analyzed, and enlarged their size. This study showed that the evolution of fungal mitochondrial introns is complex, and the results suggest short fragment insertions as a potential factor leading to larger mitochondrial genomes in A. stygium

Knowledge Embedded Semi-Supervised Deep Learning for Detecting Non-Technical Losses in the Smart Grid

Non-technical losses (NTL) caused by fault or electricity theft is greatly harmful to the power grid. Industrial customers consume most of the power energy, and it is important to reduce this part of NTL. Currently, most work concentrates on analyzing characteristic of electricity consumption to detect NTL among residential customers. However, the related feature models cannot be adapted to industrial customers because they do not have a fixed electricity consumption pattern. Therefore, this paper starts from the principle of electricity measurement, and proposes a deep learning-based method to extract advanced features from massive smart meter data rather than artificial features. Firstly, we organize electricity magnitudes as one-dimensional sample data and embed the knowledge of electricity measurement in channels. Then, this paper proposes a semi-supervised deep learning model which uses a large number of unlabeled data and adversarial module to avoid overfitting. The experiment results show that our approach can achieve satisfactory performance even when trained by very small samples. Compared with the state-of-the-art methods, our method has achieved obvious improvement in all metrics

Discrete Element Simulation Analysis of the Bending and Toppling Failure Mechanisms of High Rock Slopes

The high rock slope situated in the Southwest stope of Taiping Mining, Inner Mongolia, is subject to dumping failure due to its instability. The dumping body rock layer of this stope shows obvious bending and lowering of the head. The overturning angle of the rock strata can reach 46°, and tension dislocation along the rock joint can be observed in exposed sections and at the bedding and lithologic interface. The sliding surface also displays a broken line morphology. Through evaluation of regional rock integrity parameters and rock soft and hard parameters, rock-mass strength based on Hoek Brown strength estimation criteria can be developed. Based on the discrete element method, the geological model of layered excavation of the thin layer slope can be constructed. Combined with indoor and outdoor assessments, the characteristics of toppling deformation of the thin layer open-air slope can be studied and summarized. In this study, simulation analysis showed that under first excavation conditions, a crack-, dump-, and antislip zone was formed. The rock in the crack zone formed a “<”-shaped fracture along the slope surface that was squeezed towards the bottom of the slope. In the lower dumping area, the deflection angle gradually increased with excavation, and the deformation range and levels in the antislip area increased with excavation. Following the third excavation, the antisliding zone disappeared and the toppling line changed from a broken line to a straight line. In the final state, the slope collapsed as a whole, with the collapse of the dumping body penetrating the top to the foot of the slope

Wet Snow Flashover Characteristics of 500-kV AC Insulator Strings with Different Arrangements

In order to study the wet snow flashover characteristics of 500-kV AC insulator strings under different arrangements, wet snow flashover tests were carried out in the large climate chamber of China Electric Power Research Institute (CEPRI). The wet snow flashover voltages were obtained by the even-rising method and the flashovers were filmed by a camera. The test results showed that the installation of an anti-icing shed of large diameter could increase the wet snow flashover voltage. The distance between the two insulators was a key parameter that influenced the discharge process and the flashover voltage. Under &Lambda;-string arrangement, for common insulators, the flashover performance of iced insulators increased with the connection angle; for anti-icing insulators, the flashover performance increased at first and then decreased with the connection angle. In wet snow conditions, when the connection angle was at the commonly adopted angle of 60&deg;, the flashover performance of the common insulators under the V-string and &Lambda;-string arrangements was almost the same. For anti-icing insulators, however, the V-string arrangement was recommended according to the tests. The results obtained in this study can provide a reference for external insulation design in wet snow conditions

The Electric&ndash;Thermal Effect of a Carbon-Fibre-Reinforced Epoxy Composite and Its Corresponding Mechanical Properties

In this work, the electric&ndash;thermal effect of a carbon-fibre-reinforced epoxy composite (CFRE) panel was studied, as well as the influence of the electric heating treatment on the mechanical properties of the composite. It was observed that the temperature of the composite increased rapidly once the current was loaded, and the equilibrium surface temperature was reached within 2 min. The electric&ndash;thermal effect and mechanical properties depended on both the current loading time and the current intensity. At 5A, the flexural modulus and strength of the CFRE increased before decreasing with the current loading time. Under the same treatment time, the flexural strength of the samples treated with 5A was evidently larger than that under the small current, and all the treated samples displayed enhanced flexural strength compared to that of untreated samples. The results depicted that the low-current treatment and short time could improve the interfacial properties between CF/epoxy, along with enhancing the flexural properties of the samples. However, a large amount of the joule heating from the larger current and a more extensive time frame is predicted to cause irreversible defects to the composite, which consequently leads to the reduction in flexural strength of the composite. TGA results indicated decreased thermal stability of the CFRE composite panels after the electric heating treatment was applied