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This article describes an algorithm for the online extrapolation of hand-motion during remote welding. The aim is to overcome the spatial limitations of the human welder’s arms in order to cover a larger workspace with a continuous weld seam and to substantially relieve the welder from strain and fatigue. Depending on the sampled hand-motion data, an extrapolation of the given motion patterns is achieved by decomposing the input signals in a linear direction and a periodic motion component. An approach to efficiently determine the periodicity using a sampled autocorrelation function and the subsequent application of parameter identification using a spline function are presented in this paper. The proposed approach is able to resemble all practically relevant motion patterns and has been validated successfully on a remote welding system with limited input space and audio-visual feedback by an experienced welder.

This article covers the signal processing for a human–robot remote controlled welding application. For this purpose, a test and evaluation system is under development. It allows a skilled worker to weld in real time without being exposed to the associated physical stress and hazards. The torch movement of the welder in typical welding tasks is recorded by a stereoscopic sensor system. Due to a mismatch between the speed of the acquisition and the query rate for data by the robot control system, a prediction has to be developed. It should generate a suitable tool trajectory from the acquired data, which has to be a C 2 -continuous function. For this purpose, based on a frequency analysis, a Kalman-Filter in combination with a disturbance observer is applied. It reproduces the hand movement with sufficient accuracy and lag-free. The required algorithm is put under test on a real-time operating system based on Linux and Preempt_RT in connection to a KRC4 robot controller. By using this setup, the welding results in a plane are of good quality and the robot movement coincides with the manual movement sufficiently.

Welding is an essential process across various industries; however, it exposes workers to dangerous fumes, extreme heat and physical stress, which pose considerable health and safety hazards. To tackle these issues, this article introduces the creation of a remote-controlled human–robot welding system aimed at safeguarding workers while ensuring the quality of the welds. The system monitors a welder’s torch movements through a stereoscopic sensor and accurately reproduces them with a robotic arm, facilitating real-time remote welding. Operated by a student, it effectively welded standardized sheet metals in overhead positions while adhering to critical quality standards. The weld geometry met ISO 5817 requirements, tensile strength surpassed the base material specifications, and bending and hardness assessments verified the durability and integrity of the welds. When utilized in hazardous settings, the system showcases its capability to produce high-quality welds while significantly enhancing worker safety, underscoring its potential for real-world industrial applications.

The endothelial nitric oxide synthase (eNOS) is involved in the regulation of vascular tone and cardiac functions influencing the haemodynamics. Therefore, eNOS deficient knockout mice (eNOS−/−) have been studied in comparison to the wildtype C57BL mice. No data are available for these knock-out animals regarding the 24-h profiles in blood pressure and heart rate. We investigated by radiotelemetry (radiotelemetric probe: TA11PA-C40; DataSciences, Minnesota, USA) the 24-h profiles in systolic (SBP), diastolic blood pressure (DBP), HR and motor activity (MA) in 4 eNOS−/− and in 5 wild-type mice under a light:dark schedule of 12h:12h. Data collection started 5 weeks after transmitter implantation, data from 1 week were analysed. The results showed that eNOS−/− mice had a significant higher SBP/DBP (mmHg) than the wildtype with unchanged day:night pattern (higher BP during night, activity period). HR (beats/min) was greatly decreased in eNOS−/− mice compared to the wildtype, but interestingly displayed no circadian rhythm but stayed constant within 24 hours, MA (counts/15min) rhythm was unchanged with higher activity during the night, indicating a normal night-active animal. (See Table) 24h-Mean Day Mean Night Mean N-D-Difference SBP eNOS−/− 136.6 ± 13.0* 127.9 ± 10.8* 145.3 ± 16.6* 17.5 ± 10.3 (mmHg) C57BL 114.0 ± 4.3 109.2 ± 5.8 118.7 ± 3.1 9.5 ± 2.2 DBP eNOS−/− 115.0 ± 10.0* 107.5 ± 8.2* 122.4 ± 12.6* 15.0 ± 7.4 (mmHg) C57BL 89.3 ± 5.9 84.0 ± 7.7 94.6 ± 4.3 10.6 ± 1.7 HR eNOS−/− 386.4 ± 71.9* 386.4 ± 64.5* 386.0 ± 79.5* −0.7 ± 16.8 (b/15min) C57BL 519.8 ± 18.1 483.3 ± 18.4 556.4 ± 21.2 73.1 ± 23.3 Means ± SD, eNOS vs C57BL * p < 0.05. In conclusion, the genetic deletion of the eNOS lead to higher a BP and a lower HR. While the circadian rhythm in BP was unchanged, the rhythm in HR was abolished. This could be due to different activation of the eNOS in the endothelium (sheer stress, acetylcholine-receptor) and cardiomyocytes (b3-adrenoceptor) as well as due to a modulation of the baroreceptor reflex.

P-127 Means ± SD, eNOS vs C57BL;*>p < 0.05. Key Words: eNOS Knock-Out Mice, Blood Pressure and Heart Rate, Circadian Rhythms