The jet pipe servo (JPS) valve is one key component, whose dynamic performance directly influences the aircraft’s maneuverability. In this paper, a more accurate mathematical model and a novel multiobjective hierarchical encourage particle swarm optimization genetic algorithm (HEPGA) are proposed to improve the dynamic performance of the jet pipe servo valve. By optimizing the main structure parameters of the jet pipe servo valve, the adjustment and overshoot in the dynamic performance are reduced by 24.28% and 51.39%, respectively, compared with the prototype before optimization. To obtain a more accurate mathematical model, the computational fluid dynamics (CFD) is introduced to modify the analytical model considering the turbulent submerged free jet. Different from conventional numerical simulation, the dynamic mesh technique is used to analyze the flow field distribution by considering the force interaction of various parts of the jet pipe servo valve under actual working condition. Then, the HEPGA with better convergence is utilized because of the conflict of adjustment and overshoot. This proposed hybrid algorithm introduces the concept of staff welfare system to divide the population into elite individuals and excellent individuals of particle swarm optimization and general individuals of genetic algorithm. Meanwhile, the convergency performance of the HEPGA is evaluated through the Rosenbrock function by comparing with other particle swarm genetic hybrid methods. Subsequently, the experimental platform is constructed and the dynamic performance tests are conducted on the prototype after optimization. The experimental results verify the accuracy of the established mathematical model and the significant improvement of dynamic performance of the jet pipe servo valve.

Aiming at the problem that it is difficult to accurately predict wellbore trajectory under complex geological conditions, the NOA-LSTM-FCNN prediction method for steering drilling wellbore trajectory is proposed by combining NOA, LSTM and FCNN. This method adopts LSTM layer to receive input data and capture long-term dependencies within the data, extracting important information. The FCNN layer performs nonlinear mapping on the output of the LSTM layer and further extracts relevant features to enhance prediction accuracy. NOA is employed for hyperparameter optimization of the LSTM-FCNN model. The experimental results show that the prediction effect of the proposed method is better than that of other methods. Taking the prediction results of the well deviation angle of H21 as an example, compared with traditional machine learning methods (LR, SVM and BP) and deep learning methods (CNN, LSTM and GRU), the evaluation index R² of this method was improved by 0.17887, 0.03129, 0.0259, 0.00054, 0.00032 and 0.00031 respectively, showing significant prediction accuracy advantages and strong adaptability. In addition, it applies to various types of wellbore trajectory data, effectively enhancing wellbore trajectory prediction capabilities under complex geological conditions.

The conventional overcurrent protection is ineffective in isolating faults in microgrids due to the low fault current levels contributed by inverter-interfaced distributed generations (IIDGs). To extend the microgrid protection methods, the distance protection is considered as a common alternative to detect faults. However, the fault-ride-through (FRT) requirements and the high impedance fault (HIF) detection challenge the application of the conventional distance protection. To solve the two problems, a new inverse-time distance (ITD) protection for medium-voltage AC microgrids was proposed in this paper. The primary ITD protection was designed to meet the FRT requirements, and the backup protection was coordinated to isolate faults. The fault resistance and distributed generation infeed effect on the measured impedance were mitigated by a communication-assisted method proposed in this paper. Owing to the shorter communication channel time in distribution feeders and lower communication investments without a synchronous clock, the proposed method can be used to improve the ITD protection performance. An 11 kV AC microgrid was simulated with different fault types in the islanded mode and grid-connected mode. Time domain simulation verified the effectiveness of the proposed ITD protection.

The high-frequency information of downhole vibration can record more specific details about the dynamic response of bottom hole assembly (BHA), which is conducive to analyzing downhole abnormal vibration and diagnosing drilling tool failure. However, high frequency measurements would generate a large amount of data, which is a huge challenge for data storage. To cope with this challenge, this work proposes applying compressive sensing theory to high-frequency measurement of downhole vibration signals and failure analysis of drilling tools. First, three ADCs clocked at different sub-Nyquist frequencies are used to collect and store downhole vibration signals. Then, the stored sparse vibration data is reconstructed into complete vibration signal by an improved OMP signal reconstruction algorithm. The performance of the proposed method has been investigated via a series of experiments by applying simulation and real vibration signals, which show that the proposed method can reconstruct the downhole vibration signal well and significantly reduce the pressure of acquisition and data storage. This method provides a new way to obtain the high-frequency measurement data of downhole vibration, and provides a data basis for further mastering the comprehensive law of downhole vibration, diagnosing abnormal downhole vibration, and drilling tool failure.

As an actuator control element of the electrohydraulic system in aerospace, airplanes, and other equipment, the spool valve is prone to the “hydraulic lock” problem, which may cause major accidents of these electrohydraulic systems. The grooves engraved on the spool can effectively eliminate this problem by migrating the uneven pressure distribution in the clearance film between the sleeve and the spool. The effect of migrating uneven pressure distribution depends on the groove parameters. This paper proposed an accurate mathematical model with rectangular grooves to investigate the effect. Unlike previous mathematical models based on the Reynolds equation, the proposed model is based on the Navier–Stokes equation, which is more valid in the range where the clearance film thickness is much less than the groove depth. Meanwhile, the mathematical model takes the distributions, width, depth, and the number of grooves into consideration. Then, the proposed mathematical model was used to investigate the effects of mitigating the uneven pressure distribution under various parameters of grooves. To verify the accuracy of the mathematical model, the volume flow leakage in the clearance film obtained by the proposed model and the Reynolds equation, respectively, is compared with that obtained by the experimental test. The comparison results indicate that the results obtained by the Reynolds equation could reach a maximum of 14.75% different from the experimental results, while the results obtained by the NS equation are only 5.57% different under the same conditions, implying that the mathematical model derived from the NS equation is more accurate.