The traditional polar rapid transfer alignment (RTA) are generally modeled under small angle misalignment assumption. Those linearized and nonlinear polar RTA error models presented, so far, are not capable of accurately representing the nonlinear properties of the system where the all-orientation large attitude errors happen between the master and slave strap-down inertial navigation systems (SINS). It cannot satisfy the accuracy for the SINS initialization and has a singularity in computation. In this article, the misalignment quaternion in the grid frame was selected as the state and observation. An innovative polar RTA algorithm using the quaternion matching and the augmented unscented Kalman filter (UKF) was then proposed to estimate all-orientation large attitude misalignments in polar regions. Furthermore, the associated error propagation equations were redesigned in the grid frame and with compensations for the lever-arm effect. The augmented UKF model was further adjusted to apply. Simulation and semi-physical experiment results demonstrated that the performance of the innovative polar RTA algorithm proposed here outperformed those via traditional polar RTA techniques, especially with 3-axis large-angle misalignments, and was even robust with the disturbance of lever-arm effect aggravated by the harsh polar environment.

The polar rapid transfer alignment (RTA) is preferred to initialize the moving base. The heading error under the grid frame accumulates with time, and the aid to navigation is required to calibrate the strapdown inertial navigation system (SINS). However, the Arctic has a complex environment where auxiliary navigation devices, customarily used in low and medium latitudes, cannot operate appropriately in polar regions. The SINS attitude reference may contain errors to contaminate the measurement quality of RTA, causing alignment failure. Thus,we introducedpolarized-light navigation to offer the heading and assist attitude matching. However, its heading error is associated with the longitude error amplifiedwith increasing latitudes, and the outputs from systems are not unified into an identical navigation frame. For success in initialization at high latitudes, this work innovatively proposed a polar rapid transfer alignment assisted by the improved polarized-light navigation. Firstly, the grid heading of the polarized-light navigation was redefined under the grid frame, and the proposed weighted-clustering algorithm was used to process the skylight polarization pattern and extract the angle out. Eventually, we established the mathematical model of RTA with disturbances and augmented the grid heading solution from the polarized-light navigation into measurements, solving the low-quality attitude reference of the master SINS. Simulations and semiphysical experiments demonstrated that the proposed algorithm performed better, and the estimate error approached only several minutes of arc when the master attitude reference had over 1-degree attitude error.

The Tri-axial high temperature superconducting (HTS) cable usually subjects to the impact of the fault currents in the power system. During the fault, a large amount of the Joule heat is generated, which may be damage cable. In this paper, an analysis model of electromagnetic thermal transient characteristics of the 10 kV/1 kA cable is built. The transient characteristics of the HTS cable are analyzed under a fault current of 15 kA rms lasting 0.14 s, and the current, resistance and temperature of the HTS cable are obtained. The maximum temperature of the HTS cable is 153.1 K under fault current. Meanwhile, the safe operating range of the HTS cable under the fault current of 15 kA to 25 kA is obtained. the analysis results will provide the theoretical basis for the quench protection and relay protection strategy of the tri-axial HTS cable in the Grid.

The gravity tends to coincide with the earth’s rotation vector in the polar region, degrading the coarse alignment azimuth of the strapdown inertial navigation system (SINS) to a large misalignment. Under a large azimuth misalignment, the linear error model inevitably renders unacceptable theoretical errors in the integrated alignment. In addition, polar region challenge such sensors as a star sensor of celestial navigation, which fails to provide high-precision attitude reference for integrated alignment. Therefore, in allusion to the misalignment mentioned above based on SINS for the polar region, an integrated alignment algorithm is proposed, assisted by the Doppler Velocity Log (DVL). Notably, the work first investigates the extent to which azimuth accuracy deteriorates in the polar region. On the premise of large azimuth misalignment, the nonlinear error model under the transverse frame is derived from the ellipsoid earth model. Additionally, the state and measurement models are constructed, combined with the velocity of DVL as an observation. An adaptive measurement variance matrix is designed for the unscented Kalman filter (UKF) to estimate the attitude error. Eventually, the semi-physical experiments demonstrate that the proposed algorithm significantly improves the initial alignment accuracy of the polar region.

In order to solve the problem that the global estimation accuracy is affected by the gradual changing fault of federated filter subsystem, the features of gradual changing fault and the advantages of a long short-term memory (LSTM) neural network classification algorithm are analyzed. On this basis, a fault detection method combining residual Chi square detection algorithm with long short-term memory neural network detection method is proposed, which can effectively detect the gradual changing fault and abrupt faults of sub filters and reduce the impact of faults on global estimation accuracy. The simulation results show that this fault detection method is better than the traditional mathematical model diagnosis methods and the convolutional neural network (CNN) detection methods when the subsystem gradual changing fault occurs.

In the polar region, the gravity vector and Earth’s rotation vector tend to be in the same direction, leading to a slower convergence speed and longer alignment time of the moving base alignment. When the alignment time is short, the alignment cannot converge, resulting in low azimuth accuracy. To address this issue, we propose a polar moving base alignment method based on a backtracking scheme. Notably, this work first derives a polar coarse alignment method with the inertial frame based on the transverse Earth model. On this basis, we designed a polar coarse alignment method based on a backtracking scheme and optimized the data storage scheme. Then, a backward navigation algorithm based on the transverse inertial navigation mechanical arrangement scheme was derived, and a polar fine alignment method based on a backtracking scheme was designed. Semi-physical simulation experiments showed that the alignment algorithm based on a backtracking scheme could converge in the 180 s with high alignment accuracy, which is 70% faster than the current polar moving base alignment method.