Sensory Tool Research Articles

Novel Sensory Tool Holder Design and Optimization for Multiaxis Cutting Force Sensing in Manufacturing

Novel Sensory Tool Holder Design and Optimization for Multiaxis Cutting Force Sensing in Manufacturing

OPC UA-based Force Control for Deep Rolling with Mechanical Tools

Deep rolling can increase the service life of components under cyclic loads. This is achieved by plastic deformation of the component surface using a roller. The degree of plastic deformation depends on the rolling force. For a maximum increase in service life, the rolling force applied to the roller must stay within defined limits. When performing deep rolling using mechanical deep rolling tools, the rolling force is applied via an elastic element such as a leaf spring. The deep rolling force therefore depends on the deflection of leaf spring. It varies when the workpiece bends or has a varying diameter. These variations in the deep rolling force are not desired. They must be reduced to achieve optimum process results. To achieve this, a novel deep rolling force control for mechanical deep rolling was introduced in this paper. To control the rolling force, the force was measured with a sensory tool and machine tool axes were adjusted accordingly. The adjustment of the axes was implemented using the OPC UA standard. It is shown that this can reduce the force error during mechanical deep rolling by 90%. This ensures a constant process result and improves the mechanical deep rolling process.

The gustatory stalk of the Remo flounder exemplifies how complex evolutionary novelties may arise

The appearance of evolutionary novelties is a central issue in biology. Since Darwin’s theory, difficulties in explaining how novel intricate body parts arose have often been used by creationists and other deniers to challenge evolution. Here, we describe the gustatory stalk of the Remo flounder (Oncopterus darwinii), an anatomically and functionally complex organ presumably used as a chemoreceptor probe to detect prey buried in the substrate. We demonstrate that the gustatory stalk is derived from the first dorsal-fin ray, which acquired remarkable modifications in its external morphology, integument, skeleton, muscles, and nerves. Such structural innovations are echoed in both functional and ecological specializations. We reveal that the gustatory stalk arose through the gradual accumulation of changes that evolved at different levels of the phylogenetic tree of ray-finned fishes. At least five preconditions arose in nodes preceding Oncopterus darwinii. This finding constitutes an interesting example of how evolution can deeply remodel body parts to perform entirely new functions. In this case, a trivial support structure primitively used for swimming became a sophisticated sensory tool to uncover hidden prey.

Five-Axis Finish Milling Machining for an Inconel 718 Alloy Monolithic Blisk

Blisks subjected to rough machining for channel creation must undergo finishing processes, and such processes must achieve the required tolerance limits. A high-quality surface finish and predictable long tool life are critical for the finish milling of blisks. Accordingly, the aim of this study was to optimize parameters for the finish machining of an Inconel 718 alloy monolithic blisk. Ball-cone mills were used to machine the blade surface at a constant depth. A sensory tool holder was used to collect cutting force signals during machining, and a digital microscope was used to examine tool wear. The surface texture measuring instrument was used to measure blisk blade surface roughness to evaluate processing quality. This study manipulated two cutting parameters, namely cutting speed and feed per tooth, and investigated their effects. The relationship between cutting conditions and machining efficiency was analyzed. According to the experimental results, we identified a set of optimal parameters at effective cutting speeds of 46.53 m/min, feed per tooth of 0.1 mm/tooth, and depth of cut of 0.05 mm for marginal tool wear and fast cutting speeds. Then the corresponding tool life was estimated by using the derived parameters.

CNC Machine Tool Focused Edge Computing in Manufacturing

This paper presents a method for standardized integration of external sensors and actuators into CNC machine tool systems utilizing edge computing technology. Different communication protocols and various means for triggering external devices at a chosen machining operation were studied and evaluated using a sensory tool holder. The benefits of the presented architecture are the independence of the host operating system, easy customization, lightweight architecture, and standard protocols. Focusing on the demands for modern edge devices led to containerized modules with customizable interfaces. During manufacturing processes, the system was evaluated in terms of performance and reliability.

ELEMENTS OF GAME TECHNOLOGIES AS A MOTIVATION FACTOR OF AN INCLUSIVE EDUCATIONAL ENVIRONMENT

The article describes the effectiveness of the mechanisms of practical use of game technologies in the environment of inclusive education. The search for optimal ways and the effectiveness of the educational process will be as successful as possible if learning is exciting, interesting, informative, motivating and creative. In connection with today's challenges, the issue of optimization, innovation and availability of knowledge has become relevant. The game as a means of sensory influence for the field of inclusion is extremely important, because it allows people with special needs to adapt to life's difficulties in the future. The paradigm of gaming practices grew as a result of the fact that digital education was institutionalized rather quickly and impulsively. An important transition took place in the system of educational values: the acquisition of experience in the form of informative blocks, the possession of a number of facts, statistics were replaced by the ability to effectively apply the necessary knowledge in the field of practical activity, that is, in life; to be able to choose the main thing, to find the necessary information and to be capable of its practical application. The issue of selecting original methodical practices that would be effective for comprehensive training of students with disabilities remains relevant. Participants of the educational process, who are included in the inclusive platform, are forced to undergo another, universal adaptation in the difficult realities of today. The method of pedagogical observation in combination with a Google Form survey made it possible to analyze the functional significance of game elements in classes in the disciplines of the philological cycle and to prove the effectiveness of the game as a sensory tool among people with special educational needs.

Using machine learning for cutting tool condition monitoring and prediction during machining of tungsten

ABSTRACT Machining of single-phase tungsten, used as a plasma facing material in fusion energy reactors, is commonly associated with rapid tool wear and short tool life. Conventional methods of monitoring tool wear or changing cutting tools after a predetermined period are inefficient and can lead to unnecessary tool change or risk damaging the workpiece. Tool wear can adversely affect the surface finish and dimensional tolerances of machined parts. Predicting its onset can avoid this critical damage whilst ensuring maximum tool life is utilised. In this paper, firstly the tool life results in end milling single-phase tungsten using different cutting tool geometries and cutting speeds are provided for the first time. A novel method is proposed by combining sensor signal prediction and classification machine learning models. It works by forecasting the cutting tool bending moment signal which is then used for predicting future cutting tool condition in end milling of pure dense tungsten. A series of machining experiments, covering the whole life of a cutting tool, were performed to collect the sensor signals. The current time series signal from the sensory tool holder is employed to forecast the future signal by training a 1D convolutional neural network (1D CNN) and an artificial neural network (ANN). The forecasted signal is then used to predict the state of the cutting tool in the future. Machine learning classifiers namely, random forest (RF), support vector machine (SVM) and extreme gradient boosting (XGBoost) supervised learning models were trained and validated on actual sensor signals to correlate the tool conditions with specific sensor signal features. The investigations revealed that the 1D CNN performed best in forecasting the time series sensor signal whilst achieving a mean absolute error of 3.37. In addition, the RF, when trained on Wavelet Scattering features, resulted in the most accurate classification of sensor signals for tool condition detection. The analysis showed that the combination of 1D CNN signal forecasting, feature extraction through statistical analyses and RF classifier performs best in predicting the state of a cutting tool in near future. Using this method allows for decision making for changing the tool whilst ensuring that the maximum useful life of a cutting tool is utilised. It also enables preventing undesired damage to the machined surface due to late detection of tool wear or delays in taking appropriate actions. The application of this method can reliably reduce the manufacturing costs and resource consumption associated with cutting tools for machining tungsten and minimise tool wear induced damage to the workpiece.

A 2D mixed-lanthanide metal‒organic framework as dual-emitting luminescent sensor for ratiometric detection of tetracycline and nitrophenols

Solvothermal treatment of Gd(III)/Eu(III) salts with 2,3,5,6-tetrachloroterephthalic acid (H2tClbdc) and 1,10-phenanthroline (phen) afforded three two-dimensional lanthanide metal‒organic frameworks (MOFs), [Ln(tClbdc)(phen)(H2O)(NO3)]n (1-Ln, Ln = Gd, Eu, Eu0.03Gd0.97). The dual-emitting characteristic along with the excellent solution and photophysical stability of the mixed-lanthanide MOF 1-Eu0.03Gd0.97 make it a highly sensitive luminescent sensor to ratiometrically detect tetracycline (TC), picric acid (PA) and 4-nitrophenol (4-NP), with the limits of detection of 0.38 μM, 0.75 μM and 1.49 μM for TC, PA and 4-NP, respectively. The significant luminescence quenching of the lanthanide-based sensor by these organic pollutants might be ascribed to inner filtration effect (IFE), fluorescence resonance energy transfer (FRET) and hydrogen-bonding and/or electrostatic interactions between the sensor and phenolic analytes. More significantly, 1-Eu0.03Gd0.97 filled mixed-matrix membranes could be employed as an easy-to-use sensory tool for visual recognition of TC by the turn-off red emission signal.

Applying a Neural Network to Predict Surface Roughness and Machining Accuracy in the Milling of SUS304

Surface roughness and machining accuracy are essential indicators of the quality of parts in milling. With recent advancements in sensor technology and data processing, the cutting force signals collected during the machining process can be used for the prediction and determination of the machining quality. Deep-learning-based artificial neural networks (ANNs) can process large sets of signal data and can make predictions according to the extracted data features. During the final stage of the milling process of SUS304 stainless steel, we selected the cutting speed, feed per tooth, axial depth of cut, and radial depth of cut as the experimental parameters to synchronously measure the cutting force signals with a sensory tool holder. The signals were preprocessed for feature extraction using a Fourier transform technique. Subsequently, three different ANNs (a deep neural network, a convolutional neural network, and a long short-term memory network) were applied for training in order to predict the machining quality under different cutting conditions. Two training methods, namely whole-data training and training by data classification, were adopted. We compared the predictive accuracy and efficiency of the training process of these three models based on the same training data. The training results and the measurements after machining indicated that in predicting the surface roughness based on the feed per tooth classification, all the models had a percentage error within 10%. However, the convolutional neural network (CNN) and long short-term memory (LSTM) models had a percentage error of 20% based on the whole-data training, while that of the deep neural network (DNN) model was over 50%. The percentage error for the machining accuracy prediction based on the whole-data training of the DNN and CNN models was below 10%, while that of the LSTM model was as large as 20%. However, there was no significant improvement in the results of the classification training. In all the training processes, the CNN model had the best analytical efficiency, followed by the LSTM model. The DNN model performed the worst.

Energy self-sufficient, multi-sensory tool holder for sensitive monitoring of milling processes

Machining processes, especially milling, place several requirements on monitoring systems. Two prevalent ones are minimal implications towards the machine tool system and direct proximity to the machining zone to acquire high signal quality. Thereby, sensitive detection of even minor process alterations is enabled. This paper presents a suitable monitoring approach based on a sensory tool holder. An innovative wireless energy harvesting technology using spindle rotation is implemented. Obtained signal data for exemplary milling processes as well as corresponding signal analysis strategies are presented.

Improvement in the efficiency of the five-axis machining of aerospace blisks.

Blisks are not easily machined because of their complex curved surfaces and the high-precision requirements of surface machining. Lightweight alloy materials with superior mechanical properties, such as titanium alloy and stainless steel, are popular material choices for manufacturing turbine blisks. However, these materials are difficult to cut and require advanced machine tools and processing technologies. Because aerospace-grade parts are complex and require precise dimensions and high surface quality, machining these parts by using three-axis machine tools is difficult. Using multi-axis machine tools for the machining of complex parts can cause the achievement of precise dimensions, high quality, and the required surface roughness. In the multi-axis machining of aerospace blisks, tool path planning is considered the most difficult task. In this study, we examined the implementation of five-axis machining technology for the manufacturing of an aerospace blisk. Processing modules from computer-aided manufacturing software (NX10) are used for five-axis tool path generating, and 5-axis machining numerical control code is generated through post-processing calculations. Solid cutting simulation software (VERICUT) is used to verify whether tools exhibited overcut or interference. A sensory tool holder (SPIKE) is used to analyze cutting force during the rough machining of a blisk. The sensory tool holder is also adopted to evaluate the spindle runout and tool holding status. In order to obtain a consistent cutting allowance and surface accuracy, the online measurement system is used to generate a measurement path for semi-finish and finish machining. The real cut is performed with SUS304 and demonstrates the practical application. Through improvements in process planning, the machining time was shortened by 16.5%.

Warmed-over flavour profiles, microbial changes, shelf-life and check-all-that-apply sensory analysis of cooked minced pork treated with varying levels of Moringa oleifera leaf and root powder

This study investigated warmed-over flavour profiles, microbial changes, shelf-life and sensory characteristics of minced cooked pork treated with Moringa oleifera (M. oleifera) root and leaf powder during refrigerated storage at 4 °C. A total of 8 treatments (control = no antioxidant; 0.5ML = 0.5% M. oleifera leaf; 1ML = 1% M. oleifera leaf; 0.5MR = 0.5 % M. oleifera root; 1MR = 1% M. oleifera root; 0.5MLR = 0.5% M. oleifera leaf and root mixed; 1MLR = 1% M. oleifera leaf and root mixed; BHT = 0.02% butylated hydroxytoluene) were evaluated. The minimum inhibitory concentration (MIC) of the plant extracts against the test bacteria was determined using the serial dilution in 96 well microtiter plates technique. Warmed-over flavour profiles were determined using the test for carbonyls assay where hexanal was used as a marker for warmed-over flavour. The check-all-that-apply sensory tool was used to characterise minced cooked pork treated with different antioxidants according to warmed-over flavour taste and odour intensities. The results showed that the antibacterial assay of the extracts exhibited a broad-spectrum of activity against the tested bacteria. The leaf extracts demonstrated better activity against both gram-negative and gram-positive bacteria, with most of the MICs at less than 1 mg/mL, while the root performed better against gram-negative bacteria compared to gram-positive bacteria. There was a significant rapid increase in the warmed-over flavour profiles of the control compared to the M. oleifera and BHT treated pork. The pork samples which had M. oleifera leaf, root, and their combination at inclusion levels of 1% and 0.5% displayed lower warmed-over flavour profiles that fell in the range (1.0–1.46 mg hexanal/100g fat) throughout the storage period. Consumer sensory evaluation revealed that pork samples treated with the highest inclusion level (1%) of the M. oleifera leaf powder received the lowest consumer rating scores for appearance. Based on these results, adding M. oleifera leaf and root powder can decrease warmed-over flavour development and improve the shelf-life of processed pork. Furthermore, the incorporation of M. oleifera root powder can potentially be more acceptable to consumers because of its colour compared to the leaf, which gives the product a green colour that may not be pleasant for some consumers. This suggests that the inclusion of the root powder at 1% may be well accepted for consumption by consumers.

Optimization of milling parameters based on five-axis machining for centrifugal impeller with titanium alloy

The centrifugal impeller is the core component of a turbojet engine. Due to its complex geometry, it is difficult to generate machining paths. Moreover, a lot of material is removed between the blades during the manufacturing process. This study investigates the optimization parameters of a titanium alloy centrifugal impeller for five-axis milling. Rough grooving toolpaths are obtained using Siemens NX software, and the NC program is obtained after post-processing conversion. VERICUT can perform cutting simulations to determine whether there is an interference or collision. During the initial cutting parameter experiment, a sensory tool holder is used to measure the tool bending moment during milling. After milling, a 3D digital microscope is used to observe the flank and face of the cutter to analyze the cutting bending moment and tool wear. Finally, the optimal cutting parameters are determined through a full-factor experiment, and the tool life parameters are verified. According to the cutting parameter experiment, the cutting depth is 1 mm, the cutting speed and feed rate is the same, and the maximum bending moment increases proportionally with depth. In addition, a tool life experiment is performed using the optimal cutting parameters: cutting speed of 50 m/min, feed rate of 250 mm/min, and cutting depth of 2 mm. The maximum cutting moment is below the wear limit of 27 Nm. The tool could cut seven grooves, and the machining time is 41 min 46 s.

Scratch-and-sniff Palestine: How olfaction shapes nonsovereign infrastructural spaces

This article makes two related arguments. First, that the continuum of hazards that people can experience in relation to waste infrastructures can include unstable epistemic and political positionings of olfaction, alongside other impingements of human excrement such as toxicity to the human body and damage to ecologies. I show this by paying attention to how people are sensitized to smell and by paying attention to how diverse forms of scientific measurement have responded to embodied attunements under nonsovereign conditions in Palestine. Second, I argue that olfaction can be key to shaping infrastructures’ specific trajectories while also creating open-ended possibilities for the making of political subjects and futures. In Palestine, olfaction is an object of interpretation, a sensory tool for interpretation, and a shifting marker of belonging to different types of collectivities. Holding one’s real or proverbial nose—or not—contributes to the conditions that facilitate or preempt livability there. This article draws on fieldwork among Palestinian environmentalists, Palestinian Authority bureaucrats, and municipal employees between 2007 and 2017 to show how human bodies—and their interpreted and interpretive attunements—must figure in our investigations of infrastructural spaces in the Middle East and beyond.

FV 2 A new neurophysiological test protocol for the assessment of the somatosensory nervous system – from the laboratory to clinical application

During clinical routine diagnostics, the integrity of the somatosensory nervous system is assessed by somatosensory-evoked potentials (SEPs), analyzing Aβ-fiber function, the posterior funiculus, brainstem, and the somatosensory cortex (Muzyka and Estephan 2019). Nevertheless, SEPs cannot provide diagnostic information on small fibers (Cruccu et al. 2004), which form around 80% of the somatosensory nervous system. These small fibers are subdivided into heat-sensitive Aδ-fibers (AMH II), mechanosensitive Aδ-fibers (AMH I), cold-sensitive Aδ-fibers, and C-fibers (mediating noxious and warm stimuli; Gasser 1941). Therefore, a combination of specific tests is required to gain a complete electrophysiological assessment of the somatosensory nervous system or to detect loss of function for specific nerve fiber subtypes. Loss of function of specific subtypes of somatosensory nerve fibers are found in neuropathic disorders, such as polyneuropathy (Bönhof et al. 2017), radiculopathy (Carlstedt 2008; Cavanaugh et al. 1997), traumatic nerve injury (Rotshenker 2011), and others (Gomatos and Rehman 2021). Large-fiber neuropathies only affect thickly myelinated nerve fibers (such as hypocobalaminemia-associated neuropathies; (Franques et al. 2019; Stabler 2013)), while other neuropathic disorders begin by an affection of small fibers (Aδ- and C-fibers), such as chemotherapy-induced polyneuropathy (Timmins et al. 2020). Some neuropathies involve specific subtypes of small nerve fibers, such as a loss of function of cold-mediating Aδ-fibers during the early stage of Fabry‘s disease (Onishi and Dyck 1974). Here, we present a novel neurophysiological test protocol, which assesses a major part of the somatosensory nervous system by recording evoked potentials of touch, pinprick, vibration, heat/heat pain, cold, and warm stimuli. This test protocol was applied on healthy subjects in a first step and then transferred to patients with painful radiculopathy and painful polyneuropathy in a second step. The EP-measurements were compared to clinical data, nerve conduction studies as well as Quantitative Sensory Testing. We found several promising analogies to clinical features of the tested patients, which motivates us and hopefully other researchers to continue on this path with the goal to form a reliable and valid electrophysiological sensory tool that could be used as an outcome measure for future neurophysiological studies and in clinical routine diagnostics.

Translation, Validity and Reliability of a Malay Version of the Toddler Sensory Profile 2

ABSTRACT Sensory processing is an essential development in toddlers. A common sensory measurement tool used by Malaysian occupational therapists is Toddler Sensory Profile 2 (TSP 2). However, the Malay version has yet to be translated and validated for TSP 2 among toddlers in Malaysia. The translation and validation are a necessary process due to cross-cultural differences between English-speaking and Malay-speaking communities. The main aim of this study is to translate and identify the validity and reliability of the Toddler Sensory Profile 2- Malay version (TSP 2-M). This study involved four phases: (I) Forward and backward translations; (II) Content validation by an expert panel; (III) Pre-testing through cognitive interviews; (IV) Internal consistency of psychometric measure through a pilot study. The results showed that the Content Validity Index (I-CVI) for TSP 2-M ranged from .88–1.0, while S-CVI/Ave was .99 and S-CVI/UA was equal to .89. The reliability of TSP 2-M was good with the Cronbach α coefficient .92. The Cronbach α coefficients for each section and quadrant of the TSP 2-M ranged between .66 and.87. Based on the results, this study provided preliminary support for the validity and reliability of the TSP 2-M in Malaysia.

Customization of e-textile sensory tools for people with dementia

Sensory activities are used to increase social engagement for people with dementia, who may struggle to participate in activities due to deteriorating cognitive functions. Sensory tools are used but these can be inappropriate since they are not designed for people with dementia. This paper details the design of an e-textile sensory tool for people with dementia, with stakeholders in Mainland China. The concept, a sensory wall, was derived from a previous co-design project in Hong Kong. However, the design context differs, and this work highlights barriers to implementing co-design in sensory tool design. Instead, this project took a collaborative customization approach. This paper describes the design processes and evaluations for the first and second sensory wall, with context on dementia care in Mainland China. This paper highlights considerations in the design of a sensory tool for people with dementia, and the benefits of stakeholder engagement in sensory tool design.

ConvLSTM deep learning signal prediction for forecasting bending moment for tool condition monitoring

This paper presents a new method using a Convolutional Long Short-Term Memory (ConvLSTM) network to predict the future sensor signals for cutting tool bending moment in milling. Tool bending moment is directly correlated to cutting forces and can be used for tool condition monitoring. Bending moment from a sensory tool holder was obtained and transformed into uniform sized time-frequency domain data to be used as frame inputs to the network. Future frames of sensor signals are predicted and validated by comparing the predicted frames with the ground truth. The investigations show the potential of the proposed method for predicting future signals which can be used for tool condition monitoring.

Development of a Sensory Processing Evaluation Tool for Preschool Children Based on Sensory Environment at Home

Development of a Sensory Processing Evaluation Tool for Preschool Children Based on Sensory Environment at Home

Toward a Better Understanding of Perceptive Interactions between Volatile and Nonvolatile Compounds: The Case of Proanthocyanidic Tannins and Red Wine Fruity Esters-Methodological, Sensory, and Physicochemical Approaches.

The impact of commercial proanthocyanidic tannins on fruity pool of esters, representing the fruitiness of Bordeaux red wines, was assessed in model solutions. It was shown that the presence of tannins in the matrix significantly attenuated perception of fruity notes (p = 0.013). Physicochemical analysis demonstrated that the presence of proanthocyanidic tannins in dilute alcohol solution resulted in a decrease in ester partition coefficients and thus in a decrease in ester contents in the headspace (p < 0.05). This fact highlighted the changes that may occur in wines at a pre-sensory level, prior to sensory evaluation. Finally, a new sensory tool was developed, consisting in an ISO glass containing two compartments separated by a glass wall, providing a way to compare perceived odors according to whether or not the components of the odor mixtures were actually mixed in solution (p < 0.001). This new tool was used to demonstrate the impact and the only implication of pre-sensory level in the consequences of physical mixture between proanthocyanidic tannins and esters on their odor perception.