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This study aims to reveal the influence of milling process parameters on the surface roughness and morphology of superalloy GH4145.The groove milling mechanism and surface quality influence factors of superalloy GH4145 were studied experimentally.

This paper provides investigations on three-dimensional finite element model (FEM) and simulation of milling process for GH4145.The milling experiment uses Taguchi L16 experimental design and single factor experimental design. The surface morphology of the workpiece was observed by scanning electron microscopy, and the influence mechanism of milling parameters on surface quality is expounded.

The results show that the cutting force increases by 133% with the increase in milling depth. The measured minimum surface roughness is 0.035 µm. With the change in milling depth, the surface roughness increases by 249%. With the change in cutting speed, the surface roughness increased by 54.8%. As the feed rate increases, the surface roughness increases by a maximum of 91.1%. The milling experiment verifies that the error between the predicted surface roughness and the actual value is less than 8%.

The milling experiment uses a Taguchi L16 experimental design and a single-factor experimental design. Mathematical models can be used in research as a contribution to current research. In addition, the milling cutter can be changed to further test this experiment. Reveal the influence of milling process parameters on the surface roughness and morphology of superalloy GH4145.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0080/

This paper aims to develop a robotic mirror therapy system for lower limb rehabilitation, which is applicable for different patients with individual movement disability levels.

This paper puts forward a novel system that includes a four-degree-of-freedom sitting/lying lower limb rehabilitation robot and a wireless motion data acquisition system based on mirror therapy principle. The magnetorheological (MR) actuators are designed and manufactured, whose characteristics are detected theoretically and experimentally. The passive training control strategy is proposed, and the trajectory tracking experiments verify its feasibility. Also, the active training controller that is adapt to the human motor ability is designed and evaluated by the comparison experiments.

The MR actuators produce continuously variable and compliant torque for robotic joints by adjusting excitation current. The reference limb joint position data collected by the wireless motion data acquisition system can be used as the motion trajectory of the robot to drive the affected limb. The passive training strategy based on proportional-integral control proves to have great trajectory tracking performance through experiments. In the active training mode, by comparing the real-time parameters adjustment in two phases, it is certified that the proposed fuzzy-based regulated impedance controller can adjust assistance torque according to the motor ability of the affected limb.

The system developed in this paper fulfills the needs of robot-assisted mirror therapy for hemiplegic patients.

This paper aims to propose a bilateral robotic system for lower extremity hemiparesis rehabilitation. The hemiplegic patients can complete rehabilitation exercise voluntarily with the assistance of the robot. The reinforcement learning is included in the robot control system, enhancing the muscle activation of the impaired limbs (ILs) efficiently with ensuring the patients’ safety.

A bilateral leader–follower robotic system is constructed for lower extremity hemiparesis rehabilitation, where the leader robot interacts with the healthy limb (HL) and the follow robot is worn by the IL. The therapeutic training is transferred from the HL to the IL with the assistance of the robot, and the IL follows the motion trajectory prescribed by the HL, which is called the mirror therapy. The model reference adaptive impedance control is used for the leader robot, and the reinforcement learning controller is designed for the follower robot. The reinforcement learning aims to increase the muscle activation of the IL and ensure that its motion can be mastered by the HL for safety. An asynchronous algorithm is designed by improving experience relay to run in parallel on multiple robotic platforms to reduce learning time.

Through clinical tests, the lower extremity hemiplegic patients can rehabilitate with high efficiency using the robotic system. Also, the proposed scheme outperforms other state-of-the-art methods in tracking performance, muscle activation, learning efficiency and rehabilitation efficacy.

Using the aimed robotic system, the lower extremity hemiplegic patients with different movement abilities can obtain better rehabilitation efficacy.

This paper aims to establish a multi-input equilibrium manifold expansion (EME) model for gas turbine (GT). It proposes that the extension of model input dimension is realized based on similarity theory and affine structure in the framework of single-input EME model. The study aims to expand the scope of application of the EME model so that it can be used for the control or fault diagnosis of GTs.

In this paper, the concepts of corrected equilibrium manifold expansion (CEME) model and multi-cell equilibrium manifold expansion (MEME) model are first proposed. This paper uses theoretical analysis and simulation experiments to demonstrate the effectiveness of the bilayer equilibrium manifold expansion (BEME) model, which is a combination of the CEME and the MEME models. Simulation experiments include confirmatory experiments and comparative experiments.

The paper provides a new sight into building a multiple-input EME (MI-EME) model for GTs. The proposed method can build an accurate and robust MI-EME model that has superior performance compared with widely used nonlinear models including Wiener model (WM), Hammerstein model (HM), Hammerstein–Wiener model (HWM) and nonlinear autoregressive with exogenous inputs (NARX) network model. In terms of accuracy, the maximum error percentage of the proposed model is just 1.309%, far less than WM, HM and HWM. In terms of the stability of model calculation, the range of the mean error percentage of the proposed model is just a quarter of that of NARX network model.

The paper fulfills the construction of a novel multi-input nonlinear model, which has laid a foundation for the follow-up research of model-based GT fault detection and isolation or GT control.

This paper aims to focus on the high-speed rotary lip seal in aircraft engines, combining its service parameters, its own structure and application conditions, to study the influence of different eccentric forms, eccentricity, rotational speed and other factors on the performance of the rotary lip seal.

A numerical simulation model for high-speed eccentric rotary lip seals has been developed based on the theory of elastic hydrodynamic lubrication. This model comprehensively considers the coupling of multiple physical fields, including interface hydrodynamics, macroscopic solid mechanics and surface microscopic contact mechanics, under the operating conditions of rotary lip seals. The model takes into account eccentricity and uses the hazardous cross-sectional method to quantitatively predict sealing performance parameters, such as leakage rate and friction force.

Eccentricity has a large impact on lip seal performance; lips are more susceptible to wear failure under static eccentricity and to leakage failure under dynamic eccentricity.

This study provides a new idea for the design of rotary lip seal considering eccentricity, which is of guiding significance for the engineering application of rotary lip seal.