{"title":"Micro enzymatic biofuel cells: from theoretical to experimental aspect","authors":"Yin Song, R. Agrawal, Chunlei Wang","doi":"10.1117/12.2180125","DOIUrl":"https://doi.org/10.1117/12.2180125","url":null,"abstract":"Miniaturized enzymatic biofuel cells (EBFCs) that convert biological energy into electrical energy by using enzymemodified electrodes are considered as one of the promising candidates to power the implantable medical devices and portable electronics. However, their low power density and insufficient cell lifetime are two big obstacles to need to be tackled before EBFCs become viable for practical application. In this study, the theoretical simulation of this EBFC system is conducted using finite element analysis from COMSOL 4.3a in terms of cell performance, efficiency and optimum cell configurations. We optimized the electrodes design in steady state based on a three dimensional EBFC chip and studied the effect of orientation of the microelectrode arrays in blood artery. In the experimental part, we demonstrated an EBFC system that used 3D micropillar arrays integrated with graphene/enzyme composites. The fabrication process of this system combined top-down carbon microelectromechanical system (CMEMS) technology to fabricate the 3D micropillar arrays platform and bottom-up electrophoretic deposition (EPD) to deposit graphene/enzyme composite onto the 3D micropillar arrays. The amperometric response of the graphene based bioelectrodes exhibited excellent electrochemical performance and the 3D graphene/enzyme based EBFC generated a maximum power density of 136.3 μWcm-2 at 0.59 V, which is about 7 times of the maximum power density of the bare 3D carbon based EBFC.","PeriodicalId":438348,"journal":{"name":"Sensing Technologies + Applications","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127084447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Small hole inner profile measurement methods","authors":"Yi Liao, K. Harding, Rajesh Ramamurthy","doi":"10.1117/12.2177362","DOIUrl":"https://doi.org/10.1117/12.2177362","url":null,"abstract":"It is very difficult to measure the inner profile geometry of small holes of less than a millimeter in size, yet that geometry may be important for some manufacturing operations. This paper will present a method to measure key dimensional parameters of small holes used in a variety of applications from cooling to lubrication. Precision shaped holes can consist of a hole at some angle to the surface of the part and an area around the entrance to the hole for the purpose of diffusing the air or lubricant across the surface of the part to achieve the most effective performance. The drive towards smaller and more complex hole geometries means that previous methods such as conventional touch probes do not provide a good mapping in a time that can be used as part of production. The advanced designs of the holes means simple pin gages do not provide enough information. This paper will discuss tests of various methods considered for mapping small hole inner diameters, and present some sample results of a possible solution.","PeriodicalId":438348,"journal":{"name":"Sensing Technologies + Applications","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127670264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
B. Foster, E. Reutzel, A. Nassar, C. Dickman, B. Hall
{"title":"A brief survey of sensing for metal-based powder bed fusion additive manufacturing","authors":"B. Foster, E. Reutzel, A. Nassar, C. Dickman, B. Hall","doi":"10.1117/12.2180654","DOIUrl":"https://doi.org/10.1117/12.2180654","url":null,"abstract":"Purpose – Powder bed fusion additive manufacturing (PBFAM) of metal components has attracted much attention, but the inability to quickly and easily ensure quality has limited its industrial use. Since the technology is currently being investigated for critical engineered components and is largely considered unsuitable for high volume production, traditional statistical quality control methods cannot be readily applied. An alternative strategy for quality control is to monitor the build in real time with a variety of sensing methods and, when possible, to correct any defects as they occur. This article reviews the cause of common defects in powder bed additive manufacturing, briefly surveys process monitoring strategies in the literature, and summarizes recently-developed strategies to monitor part quality during the build process. Design/methodology/approach – Factors that affect part quality in powder bed additive manufacturing are categorized as those influenced by machine variables and those affected by other build attributes. Within each category, multiple process monitoring methods are presented. Findings – A multitude of factors contribute to the overall quality of a part built using PBFAM. Rather than limiting processing to a pre-defined build recipe and assuming complete repeatability, part quality will be ensured by monitoring the process as it occurs and, when possible, altering the process conditions or build plan in real-time. Recent work shows promise in this area and brings us closer to the goal of wide-spread adoption of additive manufacturing technology. Originality/value - This work serves to introduce and define the possible sources of defects and errors in metal-based PBFAM, and surveys sensing and control methods which have recently been investigated to increase overall part quality. Emphasis has been placed on novel developments in the field and their contribution to the understanding of the additive manufacturing process.","PeriodicalId":438348,"journal":{"name":"Sensing Technologies + Applications","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129448048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Johann Veras, R. Muise, K. Hines, Abhijit Mahalanobis, M. Neifeld
{"title":"Computational imaging in a multiplexed imager with static multispectral encoding","authors":"Johann Veras, R. Muise, K. Hines, Abhijit Mahalanobis, M. Neifeld","doi":"10.1117/12.2177062","DOIUrl":"https://doi.org/10.1117/12.2177062","url":null,"abstract":"We simulate and study various computational techniques for image reconstruction applied to a multiplexed Mid-wave-IR Imager. The imager consists of two arms where one is dedicated to high resolution imaging using a lower resolution Focal Plane Array and the other is a single measurement Multispectral imager which uses dispersive optics. We exploit the compressibility of images to estimate a high resolution image and its corresponding lower resolution multispectral data cube using standard computational techniques.","PeriodicalId":438348,"journal":{"name":"Sensing Technologies + Applications","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131794744","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Tait, Guoshuang Cai, M. Azer, Xiaobin Chen, Yong Liu, K. Harding
{"title":"Method for controlling a laser additive process using intrinsic illumination","authors":"R. Tait, Guoshuang Cai, M. Azer, Xiaobin Chen, Yong Liu, K. Harding","doi":"10.1117/12.2182511","DOIUrl":"https://doi.org/10.1117/12.2182511","url":null,"abstract":"One form of additive manufacturing is to use a laser to generate a melt pool from powdered metal that is sprayed from a nozzle. The laser net-shape machining system builds the part a layer at a time by following a predetermined path. However, because the path may need to take many turns, maintaining a constant melt pool may not be easy. A straight section may require one speed and power while a sharp bend would over melt the metal at the same settings. This paper describes a process monitoring method that uses the intrinsic IR radiation from the melt pool along with a process model configured to establish target values for the parameters associated with the manufacture or repair. This model is based upon known properties of the metal being used as well as the properties of the laser beam. An adaptive control technique is then employed to control process parameters of the machining system based upon the real-time weld pool measurement. Since the system uses the heat radiant from the melt pool, other previously deposited metal does not confuse the system as only the melted material is seen by the camera.","PeriodicalId":438348,"journal":{"name":"Sensing Technologies + Applications","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125270808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Measuring accuracy of in-plane and out-of-plane deformation simultaneous measurement of speckle interferometry using multi-recording method","authors":"Y. Arai","doi":"10.1117/12.2181198","DOIUrl":"https://doi.org/10.1117/12.2181198","url":null,"abstract":"A novel in-plane and out-of-plane deformation simultaneous measurement method using only two speckle patterns grabbed before and after deformation of an object with rough surfaces has been proposed. In the new optical system, a phenomenon of in-plane and out-of-plane deformation can be simultaneously recorded by only one camera by using the multi-recording method of speckle patterns. However, it is thought that there are some problems concerning measuring accuracy, because plural dimensional data has to be grabbed by single camera. The influence of factor of each error source to measuring accuracy of the method is investigated by using experimental results.","PeriodicalId":438348,"journal":{"name":"Sensing Technologies + Applications","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131517495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I. Djurović, E. Sejdić, Nikola Bulatovic, M. Simeunović
{"title":"An analysis of spectral transformation techniques on graphs","authors":"I. Djurović, E. Sejdić, Nikola Bulatovic, M. Simeunović","doi":"10.1117/12.2177188","DOIUrl":"https://doi.org/10.1117/12.2177188","url":null,"abstract":"Emerging methods for the spectral analysis of graphs are analyzed in this paper, as graphs are currently used to study interactions in many fields from neuroscience to social networks. There are two main approaches related to the spectral transformation of graphs. The first approach is based on the Laplacian matrix. The graph Fourier transform is defined as an expansion of a graph signal in terms of eigenfunctions of the graph Laplacian. The calculated eigenvalues carry the notion of frequency of graph signals. The second approach is based on the graph weighted adjacency matrix, as it expands the graph signal into a basis of eigenvectors of the adjacency matrix instead of the graph Laplacian. Here, the notion of frequency is then obtained from the eigenvalues of the adjacency matrix or its Jordan decomposition. In this paper, advantages and drawbacks of both approaches are examined. Potential challenges and improvements to graph spectral processing methods are considered as well as the generalization of graph processing techniques in the spectral domain. Its generalization to the time-frequency domain and other potential extensions of classical signal processing concepts to graph datasets are also considered. Lastly, it is given an overview of the compressive sensing on graphs concepts.","PeriodicalId":438348,"journal":{"name":"Sensing Technologies + Applications","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122079382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Van Ha Tang, A. Bouzerdoum, S. L. Phung, F. Tivive
{"title":"Multi-view TWRI scene reconstruction using a joint Bayesian sparse approximation model","authors":"Van Ha Tang, A. Bouzerdoum, S. L. Phung, F. Tivive","doi":"10.1117/12.2180096","DOIUrl":"https://doi.org/10.1117/12.2180096","url":null,"abstract":"This paper addresses the problem of scene reconstruction in conjunction with wall-clutter mitigation for com- pressed multi-view through-the-wall radar imaging (TWRI). We consider the problem where the scene behind- the-wall is illuminated from different vantage points using a different set of frequencies at each antenna. First, a joint Bayesian sparse recovery model is employed to estimate the antenna signal coefficients simultaneously, by exploiting the sparsity and inter-signal correlations among antenna signals. Then, a subspace-projection technique is applied to suppress the signal coefficients related to the wall returns. Furthermore, a multi-task linear model is developed to relate the target coefficients to the image of the scene. The composite image is reconstructed using a joint Bayesian sparse framework, taking into account the inter-view dependencies. Experimental results are presented which demonstrate the effectiveness of the proposed approach for multi-view imaging of indoor scenes using a reduced set of measurements at each view.","PeriodicalId":438348,"journal":{"name":"Sensing Technologies + Applications","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115526188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"3D tracking for borescope inspections","authors":"Yong Yang, G. Song, K. Harding","doi":"10.1117/12.2176636","DOIUrl":"https://doi.org/10.1117/12.2176636","url":null,"abstract":"Service providers perform regular borescope inspection of field products to ensure system performance and prevent accidents. A full borescope inspection for large equipment usually takes several days to cover every region of interest in the turbine. One of the challenges that causes this long inspection time is the difficulty in navigating the borescope tip to some position of interest and aiming the view of the borescope in given direction. The image from the borescope tip is the only information available to the operator to judge the position of tip. In some cases, the operator can get lost due to the limited field-of-view and illumination provided by the borescope. It is very hard to tell the borescope tip position from one borescope image. This increases the difficulty of correlating the inspection results obtained at different times that might be used to predict potential machinery failure. This paper discusses various methods that have been investigated for 3D borescope tracking and presents a new approach using a shape sensor integrated in the borescope tube used with image based location determination to determine the position of the borescope tip during inspections. The shape sensor provides a real time estimate of the borescope tip position and orientation then the image based analysis uses the part CAD model to fine tune this position information. The tracking result can provide better information of the tip position for the operator. This enhanced position information can be used to better monitor defect changes over time by comparing the inspection result at different times in the parts lifetime.","PeriodicalId":438348,"journal":{"name":"Sensing Technologies + Applications","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130443943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Compressive spectral polarization imaging with coded micropolarizer array","authors":"Chen Fu, H. Arguello, Brian M. Sadler, G. Arce","doi":"10.1117/12.2177813","DOIUrl":"https://doi.org/10.1117/12.2177813","url":null,"abstract":"We present a compressive spectral polarization imager based on a prism which is rotated to different angles as the measurement shots are taken, and a colored detector with a micropolarizer array. The prism shears the scene along one spatial axis according to its wavelength components. The scene is then projected to different locations on the detector as measurement shots are taken. Composed of 0°, 45°, 90°, 135° linear micropolarizers, the pixels of the micropolarizer array matched to that of the colored detector, thus the first three Stokes parameters of the scene are compressively sensed. The four dimensional (4D) data cube is thus projected onto the two dimensional (2D) FPA. Designed patterns for the micropolarizer and the colored detector are applied so as to improve the reconstruction problem. The 4D spectral-polarization data cube is reconstructed from the 2D measurements via nonlinear optimization with sparsity constraints. Computer simulations are performed and the performance of designed patterns is compared with random patterns.","PeriodicalId":438348,"journal":{"name":"Sensing Technologies + Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121837944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}