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Response measurement of various functionality states of machines is an inevitable part of smooth production. An effectively efficient measurement and control system of the machinery helps the inspection engineers to detect failures. In the recent age, the concept of industry 5.0, which focuses on the interaction between humans and machines, has increased the importance of sensors in the industry. Various sensing devices may aid and support the machining process, making it more efficient. These sensing devices support machine tools and enhance productivity by reducing failures. The application of an online monitoring system that includes vibration measurement and tool wear measurement, and the electrical energy consumption is getting fame in industry and academia. This paper mainly presents a holistic review of various sensors and their application in the manufacturing processes. Advancements in the sensor for quality measurement, cutting force measurement, and tool wear measurement are discussed. Furthermore, the adoption of the Internet of Things (IoT) in machining processes and conversion of conventional manufacturing processes into modern digitalized systems are discussed. Recent trends of research to improve the sensor technology have been improved. This study provides fundamental guidelines for using and adopting the various types of sensors in machining processes.

Here, we review recent advances in precision Casimir force measurements with both non-magnetic and magnetic materials. In addition, the measurement of the geometric dependence of the Casimir force, both lateral and normal, using uniformly corrugated surfaces is briefly presented. Finally, the measurement of the thermal Casimir force in graphene is discussed.

The present study reports an in vivo, novel methodology for the dynamic measurement of the bite force generated by individual tooth using a Fiber Bragg Grating Bite Force Recorder (FBGBFR). Bite force is considered as one of the major indicators of the functional state of the masticatory system, which is dependent on the craniomandibular structure comprising functional components such as muscles of mastication, joints and teeth. The proposed FBGBFR is an intra-oral device, developed for the transduction of the bite force exerted at the occlusal surface, into strain variations on a base plate, which in turn is sensed by the FBG sensor bonded over it. The FBGBFR is calibrated against a Micro Universal Testing Machine (UTM) for 0–900N range and the resolution of the developed FBGBFR is found to be 0.54N. 36 volunteers (20 males and 16 females) performed the bite force measurement test at molar, premolar and incisor tooth on either side of the dental arch and the obtained results show clinically relevant bite forces varying from 176N to 635N. The bite forces obtained from the current study for a substantial sample size, show that the bite forces increases along the dental arch from the incisors towards the molars and are found to be higher in male than in female. The FBG sensor element utilized in FBGBFR is electrically passive, which makes it a safe in vivo intra-oral device. Hence the FBGBFR is viable to be employed in clinical studies on biomechanics of oral function.

In this work, the residual stresses and deformations developed during and after laser powder bed fusion (L-PBF) manufacture of thin quasi-2D metallic plates were investigated. Such thin structures are particularly susceptible to effects of residual stress development. A finite element analysis of the L-PBF process was validated with in situ force measurements for the first time for a thin horizontal plate. The predicted forces developed reached a steady growth rate in the corners of the sample of 4.25 N per layer deposited, compared to 3.1 to 3.6 N per layer measured by in situ load cells. The evolution of deformation and residual stress in a different configuration, thin vertical plates, during and after removal of support structures, was also studied numerically and experimentally. Here, the finite element results showed good qualitative and quantitative (to within about 30% on average) agreement for residual deformations and final geometries of the thin vertical structures when compared with stereoscopic digital image correlation measurements. The results from the simulations showed that through-thickness stresses and shear stresses are negligible, while in-plane stresses grow in magnitude during the build process and the subsequent cooling period but are relaxed when the supporting structures are severed and the built plates removed from the base-plate, leaving tension in first built layers and compression in the last built layers. The models provide a tool for designing support structures and processes for release of the structures from their supports and substrates.

This study introduces a multi-point optical flow cable force measurement method based on Euler motion amplification to address challenges in accurately measuring cable displacement under small displacement conditions and mitigating background interference in complex environments. The proposed method combines phase-based magnification with an optical flow method to enhance small displacement features and improve SNR (signal-to-noise ratio) in cable displacement tracking. By leveraging magnified motion data and integrating auxiliary feature points, the approach compensates for equipment-induced vibrations and background noise, allowing for precise cable displacement measurement and the identification of vibration modes. The methodology was validated using a scaled model of a cable net structure. The results demonstrate the method’s effectiveness, achieving a significantly higher SNR (e.g., from 7.5 dB to 22.24 dB) compared to traditional optical flow techniques. Vibration frequency errors were reduced from 6.2% to 1.5%, and cable force errors decreased from 11.38% to 3.13%. The multi-point optical flow cable force measurement method based on Euler motion magnification provides a practical and reliable solution for non-contact cable force measurement, offering potential applications in structural health monitoring and the maintenance of bridges and high-altitude structures.

The mean ionic activity coefficients of NaCl in the system { y NaCl + (1 −  y ) NaH 2 PO 4 }(aq) were determined by electromotive force measurements (EMF) in two series in which the NaCl ionic strength fraction was as follows: I series, y  = (0.2368; 0.3101; 0.4101; 0.5051; 0.6090; 0.7775; 0.9039) and II series, y  = (0.1998; 0.4005; 0.5993; 0.8105) in the range of total ionic strength of the solution I m  = (0.0887–1.0081) mol·kg −1 at a temperature T  = 298.15 K. A cell of the Na–ISE∣ NaCl ( m NaCl ) , Na H 2 PO 4 ( m Na H 2 PO 4 ) ∣Ag∣AgCl type was utilized for the EMF measurements. The standard electrode potential of the electrode pair was estimated as E 0  = 23.2288 mV. The values of the mean ionic activity coefficient of NaCl in the mixed electrolyte solution, γ ± NaCl , were determined using the Nerst equation. The experimental results from this study were treated with the models proposed by Pitzer, Clegg and Scatchard to estimate the mixture parameters. A high degree of agreement was found between the experimental and calculated values of the mean ionic activity coefficients of NaCl with an average standard deviation of fit being s . d . γ ± ∼ 2.5·10 –3 for each of the three models. The values of the osmotic coefficients of the system { y NaCl + (1 −  y )NaH 2 PO 4 }(aq) were estimated based on the determined model parameters and compared with literature data. Negligible differences were found between the estimated and experimental values of the osmotic coefficients.

Marker‐type vision‐based tactile sensors (VTS) realize force sensing by calibrating marker vector information. The tactile visualization can provide high‐precision and multimodal force information to promote robotic dexterous manipulation development. Considering VTS's contribution to force measurement, this article reviews the advanced force measurement technologies of VTSs. First, the working principle of marker‐type VTSs is introduced, including single‐layer markers, double‐layer markers, color coding, and optical flow. Then, the relationship between the marker type and the category of force measurement is discussed in detail. On this basis, the process of marker feature extraction is summarized, including image processing and marker‐matching technologies. According to the learning approach, force measurement methods are classified into physical and deep learning models. Further, branches of each method are analyzed in terms of input types. Combined with measuring range and precision, the correlation of sensor design, materials, and recognition methods to force measurement performance is further discussed. Finally, the difficulties and challenges are analyzed, and future developments are proposed. This review aims to deepen understanding of the research progress and applications and provide a reference for the research community to promote technology generations in related fields. Force sensing is an important function of marker‐type vision‐based tactile sensors. This review focuses on force measurement technologies based on visuotactile sensing from sensing principle, marker layer design, information process, and measurement precision, intending to provide a reference for the research community in marker layer design optimization, high‐quality force feature extraction, and robot's operating tasks.

Background Whole-body vibration training (WBV) performed on a vibration platform can significantly improve physical performance in patients with chronic obstructive pulmonary disease. It has been suggested that an important mechanism of this improvement is based on an improvement in balance. Therefore, the aim of this study was to investigate the effects of WBV compared to conventional balance training. Methods 48 patients with severe COPD (FEV 1 : 37 ± 7%predicted) and low exercise performance (6 min walk distance (6MWD): 55 ± 10%predicted) were included in this randomized controlled trial during a 3 week inpatient pulmonary rehabilitation. All patients completed a standardized endurance and strength training program. Additionally, patients performed 4 different balance exercises 3x/week for 2 sets of 1 min each, either on a vibration platform (Galileo) at varying frequencies (5–26 Hz) (WBV) or on a conventional balance board (BAL). The primary outcome parameter was the change in balance performance during a semi tandem stance with closed eyes assessed on a force measurement platform. Muscular power during a countermovement jump, the 6MWD, and 4 m gait speed test (4MGST) were secondary outcomes. Non-parametric tests were used for statistical analyses. Results Static balance performance improved significantly more ( p  = 0.032) in favor of WBV (path length during semi-tandem stand: − 168 ± 231 mm vs. + 1 ± 234 mm). Muscular power also increased significantly more ( p  = 0.001) in the WBV group (+ 2.3 ± 2.5 W/kg vs. − 0.1 ± 2.0 W/kg). 6MWD improved to a similar extent in both groups (WBV: 48 ± 46 m, p  < 0.001 vs. BAL: 38 ± 32 m; p  < 0.001) whereas the 4MGST increased significantly only in the WBV-group (0.08 ± 0.14 m/s 2 , p  = 0.018 vs. 0.01 ± 0.11 m/s 2 , p  = 0.71). Conclusions WBV can improve balance performance and muscular power significantly more compared to conventional balance training. Trial registration: Clinical-Trials registration number: NCT03157986; date of registration: May 17, 2017. https://clinicaltrials.gov/ct2/results?cond=&term=NCT03157986&cntry=&state=&city=&dist  =

Automatic tool changer system (ATCS) and drawbar mechanism (DM) are two of key basic parts for realizing the automatic tool-changing cycle in machining centers. The dynamic force in a tool-changing cycle plays an essential role in condition monitoring, fault diagnosis, and failure warning for the ATCS and DM. However, existing force detection systems have limitations in practical application. In this paper, a novel dynamic force measurement system (DFMS) is developed, which is based on a force sensing element installed on the BT40 tool holder and operating through a wireless network. The force sensing element is used to convert the dynamic force into the electrical signal. Digital measurements are collected from the 24-bit sigma-delta analog-to-digital converter with a programmable gain array, which then are transmitted to the upper computer software via a wireless transceiver. Besides, a Teager energy operator based dual-threshold two sentences endpoint detection method is proposed to recognize the temporal onset and offset of each force event in the dynamic force recording. Experimental results show that the DFMS is reliable and suitable to measure the dynamic force in automatic tool-changing cycles.

Ultra-high-precision single-point diamond turning (SPDT) is the state-of-the-art machining technology for the advanced manufacturing of critical components with an optical surface finish and surface roughness down to one nanometer. One of the critical factors that directly affects the quality of the diamond-cutting process is the cutting force. Increasing the cutting force can induce tool wear, increase the cutting temperature, and amplify the positioning errors of the diamond tool caused by the applied cutting force. It is important to measure the cutting force during the SPDT process to monitor the tool wear and surface defects in real time. By measuring the cutting force in different cutting conditions, the optimum cutting parameters can be determined and the best surface accuracies with minimum surface roughness can be achieved. In this study a smart cutting tool for in-process force measurement and nanopositioning of the cutting tool for compensating the displacements of the diamond tool during the cutting process is designed and analyzed. The proposed smart cutting tool can measure applied forces to the diamond tool and correct the nanometric positioning displacements of the diamond tool in three dimensions. The proposed cutting tool is wireless and can be used in hybrid and intelligent SPDT platforms to achieve the best results in terms of optical surface finish. The simulation results are shown to be almost consistent with the results of the derived analytical model. The preliminary results pave the way for promising applications of the proposed smart cutting tool in SPDT applications in the future.