Enhanced damping of lightweight structures by semi-active joints

Summary Lightweight structures typically have low inherent structural damping. Effective vibration suppression is required, for example, in certain applications involving precision positioning. The present approach is based on friction damping in semi-active joints which allow relative sliding between the connected parts. The energy dissipation due to interfacial slip in the friction joints can be controlled by varying the normal pressure in the contact area using a piezo-stack actuator. This paper focuses on the optimal placement of semi-active joints for vibration suppression. The proposed method uses optimality criteria for actuator and sensor locations based on eigenvalues of the controllability and observability gramians. Optimal sensor/actuator placement is stated as a nonlinear multicriteria optimization problem with discrete variables and is solved by a stochastic search algorithm. At optimal locations, conventional rigid connections of a large truss structure are replaced by semi-active friction joints. Two different concepts for the control of the normal forces in the friction interfaces are implemented. In the first approach, each semi-active joint has its own local feedback controller, whereas the second concept uses a global, clipped-optimal controller. Simulation results for a 10-bay truss structure show the potential of the proposed semi-active concept. Dedicated to Professor Franz Ziegler on the occasion of his 70th birthday     

Temperature feedback control for improving the stability of a semiconductor-metal-oxide (SMO) gas sensor

Stability is a major concern of semiconductor-metal-oxide (SMO) gas sensors in practical applications, as they may cause false alarm problems. Ambient temperature is a major factor affecting the SMO gas sensor's stability. In this paper, we use a novel way to improve temperature stability of SMO (tin oxide) gas sensors by applying a temperature feedback control circuits which are compatible with our microelectromechanical systems sensor fabrication. A built-in platinum temperature sensor can precisely detect the sensor's working temperature. It provides feedback information to compensate the microheater's current to maintain the sensor's working temperature constant, regardless of ambient temperature change. Test results showed that, with this approach, significant improvement of stability has been achieved compared to SMO gas sensors without temperature compensation under the same ambient variation. The algorithm is realized through a hardware circuit, whose advantages include real time, large feedback gain, and low cost.     

Applying the topological relationships of form features to retrieve part files from a CAD system

The efficient retrieval of stored CAD files is an area that has received significant attention in recent years. Several Product Data Management products have been developed, most of which are based on the use of coding concepts to retrieve designs. However, the limited number of codes that can be used limits the flexibility of part shape representation and also versatility in retrieving existing drawings. In this paper, an integrated approach using topological relationships among form features as the search indices is proposed. The use of a feature adjacency graph and also a feature topological relation graph that acts as the interface enables this approach to translate the feature-based B-Rep model of a part that is stored in the CAD system into topological relationships that are stored in a relational database. In addition, five types of queries based on topological relationships an; used to aid the retrieval of designs. The proposed technique for design retrieval is more convenient than traditional coding based methods:     

Sensor Selection for Machine Olfaction Based on Transient Feature Extraction

Machine olfaction devices, which are often called electronic noses (e-noses), are gaining favor for odor assessment applications in several industrial sectors, such as beverage, perfumery, and food. From a design point of view, the number of sensors in these devices for a particular odor application should be minimized without degrading classification accuracy. This paper deals with selecting sensors for e-noses to make small portable devices with fast response times and reduced cost possible. Prior research efforts have been reported in the open literature and have shown that many advantages can be gained by properly selecting the input features before forwarding to a pattern classification algorithm. This selection process can reduce the dimensionality of the feature space, remove redundant and irrelevant features, speed up classification, and improve classification performance. In this paper, the transient features of an array of sensors obtained by applying a multiresolutional approximation technique from the discrete wavelet transform (DWT) are investigated to search for an optimal sensor array to be implemented in the e-nose system. A genetic algorithm is adapted to tailor a gas sensor array for two different odor data sets (coffee and soda). From the experimental results, the input features obtained by applying the DWT to the transient sensor responses not only provide a significant reduction in the number of sensors when compared to traditional features but also improve the classification rate to near 100%.     

Ontology-based neural network for patent knowledge management in design collaboration

In order to stimulate innovation during the collaborative process of new product and production development, especially to avoid duplicating existing techniques or infringing upon others’ patents and intellectual property rights, the collaborative team of research and development, and patent engineers must accurately identify relevant patent knowledge in a timely manner. This research develops a novel knowledge management approach using ontology-based artificial neural network (ANN) algorithm to automatically classify and search knowledge documents stored in huge online patent corpuses. This research focuses on developing a smart and semantic oriented classification and search from the sources of the most critical and well-structured knowledge publications, i.e. patents, to gain valuable and practical references for the collaborative networks of technology-centric product and production development teams. The research uses the domain ontology schema created using Protégé and derives the semantic concept probabilities of key phrases that frequently occur in domain relevant patent documents. Then, by combining the term frequencies and the concept probabilities of key phrases as the ANN inputs, the method shows significant improvement in classification accuracy. In addition, this research provides an advanced semantic-oriented search algorithm to accurately identify related patent documents in the patent knowledge base. The case demonstration analyses 343 chemical mechanical polishing and 150 radio-frequency identification patents sample sets to verify and measure the performance of the proposed approach. The results are compared with the previous automatic classification methods demonstrating much improved outcomes.     

A new directed graph approach for automated setup planning in CAPP

The task of setup planning is to determine the number and sequence of setups and the machining features or operations in each setup. Now there are three main methods for setup planning, i.e., the knowledge-based approach, the graph-based approach and the intelligence algorithm-based approach. In the knowledge-based and graph-based approaches reported in the literature, the main problem is that there is no guarantee that all precedence cycles between setups can be avoided during setup formation. The methods to break precedence cycles between setups are to split one setup into smaller setups. However, the implementation of this method is difficult and complex. In the intelligence algorithm-based approach, the method to handle the precedence constraints is a penalty strategy, which does not reflect the influence of precedence constraints on setup plans explicitly. To deal with the above deficiencies, a new directed graph approach is proposed to describe precedence constraints explicitly, which consists of three parts: (1) a setup precedence graph (SPG) to describe precedence constraints between setups. During the generation of the SPG, the minimal number of tolerance violations is guaranteed preferentially by the vertex clusters algorithm for serial vertices and the minimal number of setups is achieved by using variants of the breadth-first search. Precedence cycles between setups are avoided by checking whether two serial vertex clusters can generate a cycle; (2) operation sequencing to minimise tool changes in a setup; and (3) setup sequencing to generate optimal setup plans, which could be implemented by a topological sort. The new directed graph approach will generate many optimal or near-optimal setup plans and provide more flexibility required by different job shops. An example is illustrated to demonstrate the effect of the proposed approach.     

Fuzzy modeling of measurement data acquired from physical sensors

The measurement uncertainty in physical sensors is often represented by a probabilistic approach, but such a representation is not always adapted to new intelligent systems. Therefore, a fuzzy representation, based on the possibility theory, can sometimes be preferred. We previously proposed a truncated triangular probability-possibility transformation to be applied to any unimodal and symmetric probability distribution which can be assimilated to one of the four most encountered probability laws (Gaussian, double-exponential, triangular, uniform). In this paper, we propose to build a fuzzy model of data acquired from physical sensors by applying this transformation. For this purpose, a minimum of knowledge about the probabilistic modeling of sensors is required. Three main situations are considered and for each situation, an adapted fuzzy modeling is proposed. Examples of these three situations are based on FM-chirped ultrasonic sensors     

基于自适应引力算法的桥梁监测传感器优化布置

针对桥梁健康监测中传感器布置优化问题,提出了一种基于自适应引力算法的传感器优化布置方法。以模态置信准则为基础,构造满足传感器优化布置的适应度函数;针对引力搜索算法开发能力不足,对衰减因子α进行了自适应改进。搜索初期α较小,粒子以较大步长进行全局搜索,增强了算法的搜索效率;搜索后期α较大,粒子以较小的步长进行局部搜索,提高了算法的搜索能力,避免落入局部极值点。改进后的自适应引力算法通过双重编码的方式,使算法可以解决离散型的传感器布置问题;以马水河大桥为例,验证算法的可行性。结果表明,改进后的算法有很好的寻优能力,能够准确高效的确定传感器优化位置。     

A potentiostat based on a voltage-controlled current source for usewith amperometric gas sensors

Amperometric gas-sensing devices develop a current that is proportional to the concentration of gas that is supplied to them. The circuit that maintains electrochemical stability in the sensor as well as buffering the current output is called a potentiostat. Some sensors used for gas sensing have very large electrode capacitances, which can result in instability with conventional potentiostat designs. The responses of two potentiostat designs to a gas were compared. One is based on conventional use of a current-to-voltage converter (CVC); the second is a new design which uses a voltage-controlled current source (VCCS). A frequency analysis of the VCCS potentiostat design is included     

A Bee Swarm Algorithm for Optimising Sensor Distributions for Impact Detection on a Composite Panel

This paper describes the development of a bee swarm algorithm for optimising the distribution of impact detection sensors on a composite plate. The algorithm was initially developed and tested on a travelling salesman problem, it was then adapted to solve the sensor placement problem using an artificial neural network to assess the fitness of sensor distributions. It performed well, managing to quickly find optimum distributions within a constrained set of neural network parameters. The algorithm was modified further, to optimise the neural network parameters alongside the sensor distributions and the range that the network parameters could take was substantially increased. This led to significant increases in accuracy. The algorithm showed itself to be a very effective tool in the sensor optimisation problem as well as demonstrating the benefits of thoroughly optimising the neural network parameters.     

Networked Sensors for Cargo Screening

Sensors to monitor cargo are currently operated in standalone mode because of cost considerations, operational simplicity, and because potential benefits to having sensors share information do not appear to have been seriously considered in many cases. To identify situations where threat detection benefits offset networking costs (and where they do not), we describe a numerical algorithm for approximating the multidimensional integrals defining the false positive rates and detection probabilities for networked systems. The algorithm is sufficiently fast computationally to embed in optimization routines that search over sensor space (e.g., how to best augment an existing sensor network), as well as over threshold space (i.e., how to best determine alarm thresholds for the sensors) for both standalone and networked sensors. Results are applied to detection of elevated gamma and neutron counts. Circumstances under which networking is useful are characterized.     

A Viscoelastic Sandwich Finite Element Model for the Analysis of Passive,Active and Hybrid Structures

In this paper we present a finite element model for the analysis of active sandwich laminated plates with a viscoelastic core and laminated anisotropic face layers, as well as piezoelectric sensor and actuator layers. The model is formulated using a mixed layerwise approach, by considering a higher order shear deformation theory (HSDT) to represent the displacement field of the viscoelastic core and a first order shear deformation theory (FSDT) for the displacement field of the adjacent laminated anisotropic face layers and exterior piezoelectric layers. The dynamic problem is solved in the frequency domain with viscoelastic frequency dependent material properties for the core. Control laws are also implemented for the piezoelectric sensors and actuators. The model behaviour in dynamics is assessed with the few solutions found in the literature, including experimental data, and a laminated composite active sandwich application is proposed. In this numerical application, velocity feedback control law is implemented for active control, using co-located piezoelectric patch sensors and actuators.     

Compensation of Angular Errors Using Decision Feedback Equalizer Approach

Speed and position measurements of rotating shafts are very important in the field of mechanical engineering. In automotive applications, magnetic field sensors for such measurements (camshaft, crankshaft, anti-lock braking system, windshield wiper, etc.) have the largest market share of all sensor types. Camshaft applications are challenging due to their requirements on high angular accuracy under harsh environmental conditions. Due to mounting and packaging tolerances, the magnetic field at the sensors position varies, resulting in angular measurement errors for sensor concepts in use today. Mounting and packaging tolerances cannot be avoided; however, they can be compensated by a new filter structure which is described in this paper. The decision feedback equalizer (DFE)—known from digital communication—was analyzed and modified for the use in angular measurement applications. A new filter structure, using data prediction and an adaptive algorithm based on a physical model, is proposed. This filter calculates and compensates angular errors caused by mounting and packaging tolerances.      

网络攻击图生成方法研究

针对网络安全分析研究的要求,在已有研究的基础上,提出了一种灵活的网络攻击图生成方法.首先通过分析网络主机、用户权限、主机之间的连接关系和攻击等安全属性,建立了一个面向网络安全分析的安全模型,然后使用广度优先的正向搜索算法生成攻击路径,实现了网络攻击图的生成.通过实验和比较证明,该方法具有更高的有效性和更快的攻击图生成速度.     

Ultrasonic High-Temperature Sensors: Past Experiments and Prospects for Future Use

Ultrasonic thermometry sensors (UTS) have been intensively studied in the past to measure temperatures from 2080 K to 3380 K. This sensor, which uses the temperature dependence of the acoustic velocity in materials, was developed for experiments in extreme environments. Its major advantages, which are (a) capability of measuring a temperature profile from multiple sensors on a single probe and (b) measurement near the sensor material melting point, can be of great interest when dealing with on-line monitoring of high-temperature safety tests. Ultrasonic techniques were successfully applied in several severe accident related experiments. With new developments of alternative materials, this instrument may be used in a wide range of experimental areas where robustness and compactness are required. Long-term irradiation experiments of nuclear fuel to extremely high burn-ups could benefit from this previous experience. After an overview of UTS technology, this article summarizes experimental work performed to improve the reliability of these sensors. The various designs, advantages, and drawbacks are outlined and future prospects for long-term high-temperature irradiation experiments are discussed.     

Optimal sensor placement for enhancing sensitivity to change in stiffness for structural health monitoring

This paper focuses on optimal sensor placement for structural health monitoring (SHM), in which the goal is to find an optimal configuration of sensors that will best predict structural damage. The problem is formulated as a bound constrained mixed variable programming (MVP) problem, in which the discrete variables are categorical; i.e., they may only take on values from a pre-defined list. The problem is particularly challenging because the objective function is computationally expensive to evaluate and first-order derivatives may not be available. The problem is solved numerically using the generalized mixed variable pattern search (MVPS) algorithm. Some new theoretical convergence results are proved, and numerical results are presented, which show the potential of our approach.     

Optimum Sensor Placement for Impact Location Using Trilateration

A key problem associated with structural health monitoring (SHM) is the placement of sensors upon a structure to detect the existence, location, and the extent of any damage. Because input data coming from the sensors are groups of measurements, it is arguable that the most widely used approach to SHM nowadays is to consider it as a statistical pattern recognition problem. Artificial neural networks have made a great impact on pattern recognition practice. A problem associated with this monitoring strategy is to find a good compromise between the quality of information achieved by the sensor network, increasing with the sensor density, and the need to keep the minimum weight and instrumentation cost. Thus, the number of sensors must be kept under control, and a search of the optimal location of such sensors needs to be performed. All these aspects have been taken into account in the present work, dealing with the problem of optimum sensor placement for impact location on a multilayered composite structure. Multilayered composite structures may suffer particularly relevant trauma when subject to low‐velocity impacts, as they may produce non‐visible or barely visible damage on the structure surface, while remarkable subsurface delaminations may be present. Such hidden damage, when remaining undetected, may grow to catastrophic failure. To overcome this issue, a neural network approach has been used here to predict the impact locations on a composite panel from time‐dependent data recorded on a set of surface‐mounted piezoelectric sensors during an experimental impact test. A genetic algorithm has been used to find the optimal sensor layout that minimised the error in predicting the impact location. A new approach, based on trilateration, is discussed and compared with the traditional one and is shown to provide the same degree of accuracy at reduced computational cost.     

Location information-aided task-oriented self-organization of ad-hoc sensor systems

A novel task-oriented self-organization algorithm that accounts for mostly location-dependent tasks and heterogeneous sensors inherent in dense ad-hoc sensor systems is proposed. It forms a sensor group for an announced task by sequentially selecting the best matched sensors using a leader election algorithm and a residual task calculation algorithm. To improve the associated communication overhead, the sensor node location information is used in task broadcasting, thus confining the algorithm implementation to a dynamically maintained contributor group which comprises of those sensors which may contribute to the task. Sensor localization is based on a refinement of an algorithm in which utilizes only the neighborhood information of each sensor node corresponding to its each preset radio transmission power level. The proposed self-organization algorithm and how various system parameters affect its performance are examined via extensive simulations. In a densely deployed sensor system, when the refined localization scheme is demonstrated to achieve very good localization, the proposed self-organization algorithm consistently yields a sensor group that covers the announced task.     

Designing a practical system for spectral imaging of skylight

In earlier work [J. Opt. Soc. Am. A 21, 13-23 (2004)], we showed that a combination of linear models and optimum Gaussian sensors obtained by an exhaustive search can recover daylight spectra reliably from broadband sensor data. Thus our algorithm and sensors could be used to design an accurate, relatively inexpensive system for spectral imaging of daylight. Here we improve our simulation of the multispectral system by (1) considering the different kinds of noise inherent in electronic devices such as change-coupled devices (CCDs) or complementary metal-oxide semiconductors (CMOS) and (2) extending our research to a different kind of natural illumination, skylight. Because exhaustive searches are expensive computationally, here we switch to a simulated annealing algorithm to define the optimum sensors for recovering skylight spectra. The annealing algorithm requires us to minimize a single cost function, and so we develop one that calculates both the spectral and colorimetric similarity of any pair of skylight spectra. We show that the simulated annealing algorithm yields results similar to the exhaustive search but with much less computational effort. Our technique lets us study the properties of optimum sensors in the presence of noise, one side effect of which is that adding more sensors may not improve the spectral recovery.