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In this paper, we propose a novel shape-sensing method based on deep learning with a multi-core optical fiber for the accurate shape-sensing of catheters and guidewires. Firstly, we designed a catheter with embedded multi-core fiber containing three sensing outer cores and one temperature compensation middle core. Then, we analyzed the relationship between the central wavelength shift, the curvature of the multi-core Fiber Bragg Grating (FBG), and temperature compensation methods to establish a Particle Swarm Optimization (PSO) BP neural network-based catheter shape sensing method. Finally, experiments were conducted in both constant and variable temperature environments to validate the method. The average and maximum distance errors of the PSO-BP neural network were 0.57 and 1.33 mm, respectively, under constant temperature conditions, and 0.36 and 0.96 mm, respectively, under variable temperature conditions. This well-sensed catheter shape demonstrates the effectiveness of the shape-sensing method proposed in this paper and its potential applications in real surgical catheters and guidewire. [ABSTRACT FROM AUTHOR]

Near-space airships are high-end airships that are being vigorously developed in the aerospace industry. It has important application value in the telecommunication, surveillance, monitoring, remote sensing, and exploration fields. The envelope is the key component that provides lift to the airship. Online monitoring of envelope status is critical to ensuring airship performance, safety, and reliability. However, online monitoring of the 3D shape and strain of the airship envelope is still a challenging task. A hybrid multi-core and single-core fiber-optic monitoring method with a temperature self-compensation function is proposed to address this issue. The method uses multi-core fiber optic sensors, 3D curves, and a surface reconstruction algorithm to obtain the 3D shape of the envelope. Temperature decoupling of the sensing signal is carried out via sensors on the central core of the multi-core fibers that are only sensitive to temperature, thereby eliminating the influence of temperature changes on the measurement accuracy. The strain field of the envelope skin is measured by single-core fiber optic sensors and a strain interpolation algorithm. The accuracy of the proposed method is experimentally validated. The results show that the 3D shape measurement error of the envelope skin is 4.82% when the skin is bent in the range of 10 m -1 -15.38 m -1 . When the ambient temperature changes in the range of -50 ∘ C -150 ∘ C , the position measurement error caused by the temperature change is only 1.2% of the effective measurement length (160 mm) of the multi-core fiber optic sensor. When the skin is stretched in the range of 500-5000µε, the measurement error of the average value of the skin strain field is only 0.75%. This proves that the proposed method can simultaneously measure the 3D shape and strain field of the envelope skin and also effectively suppress the influence of ambient temperature changes on the measurement accuracy. The proposed method has application prospects in the online monitoring of airship envelopes.

Rigid suckers commonly used in surgical procedures often cause absorption damage, while their soft counterparts are difficult to handle due to their weak anchoring. Alternatively, the octopus sucker is both soft and has strong suction power. Further observation revealed that its structure is self-sealing and that the tissues are layered in hardness. Inspired by said structure and the characteristics of associated materials, a bionic soft sucker with stiffness gradient and acetabular roof structure was proposed, made of silicone with varying hardness including structures such as acetabular roof and circle muscles. The automatic tensile force measurement system was used to experimentally analyze the adsorption performance of the suckers to the soft curved contact surface. Both dry and wet conditions were tested, along with practical tests on organisms. The bionic sucker adsorption force was increased by 25.1% and 34.6% on the cylindrical surface, and 45.2% and 7.3% on the spherical surface for dry and wet conditions, respectively. During the experiment, the bionic suckers did not cause notable suction damage to the contact surfaces. Thus, this type of bionic sucker shows good application prospects in the field of surgery., (© 2022 IOP Publishing Ltd.)

Temperature variations affect the accuracy of fiber-optic shape sensors; thus, temperature compensation is particularly important. This study developed a temperature self-compensation algorithm and verified the measuring accuracy of shape sensors after temperature compensation. A multicore fiber Bragg grating (FBG) sensor array was calibrated to confirm the consistency of sensor characteristics, and the relationship between the curvature and wavelength shift of FBGs was studied. A variable-temperature experiment revealed the temperature sensitivity of the FBG sensors, and these results were used by the temperature self-compensation algorithm. Further, shape reconstruction before and after temperature compensation was studied. The deformed shapes of the multicore FBG sensor array under different bending conditions were reconstructed. The results obtained after temperature compensation show that the average error between the measured and the theoretical coordinate values as less than 0.33 mm, the maximum error as less than 5.61 mm, and the relative error as less than 3.50%. The proposed temperature self-compensation algorithm has excellent prospects for application to flexible structures.