Sensor Configuration and Test for Fault Diagnoses of Subway Braking System Based on Signed Digraph Method

Fault diagnosis of various systems on rolling stock has drawn the attention of many researchers. However, obtaining an optimized sensor set of these systems, which is a prerequisite for fault diagnosis, remains a major challenge. Available literature suggests that the configuration of sensors in these systems is presently dependent on the knowledge and engineering experiences of designers, which may lead to insufficient or redundant development of various sensors. In this paper, the optimization of sensor sets is addressed by using the signed digraph （SDG） method. The method is modified for use in braking systems by the introduction of an effect-function method to replace the traditional quantitative methods. Two criteria are adopted to evaluate the capability of the sensor sets, namely, observability and resolution. The sensors configuration method of braking system is proposed. It consists of generating bipartite graphs from SDG models and then solving the set cover problem using a greedy algorithm. To demonstrate the improvement, the sensor configuration of the HP2008 braking system is investigated and fault diagnosis on a test bench is performed. The test results show that SDG algorithm can improve single-fault resolution from 6 faults to 10 faults, and with additional four brake cylinder pressure （BCP） sensors it can cover up to 67 double faults which were not considered by traditional fault diagnosis system. SDG methods are suitable for reducing redundant sensors and that the sensor sets thereby obtained are capable of detecting typical faults, such as the failure of a release valve. This study investigates the formal extension of the SDG method to the sensor configuration of braking system, as well as the adaptation supported by the effect-function method.

Optimal sensor placement in hydropower house based on improved triaxial effective independence method

The capacity and size of hydro-generator units are increasing with the rapid development of hydroelectric enterprises, and the vibration of the powerhouse structure has increasingly become a major problem. Field testing is an important method for research on dynamic identification and vibration mechanisms. Research on optimal sensor placement has become a very important topic due to the need to obtain effective testing information from limited test resources. To overcome inadequacies of the present methods, this paper puts forward the triaxial effective independence driving-point residue （EfI3-DPR3） method for optimal sensor placement. The Efl3-DPR3 method can incorporate both the maximum triaxial modal kinetic energy and linear independence of the triaxial target modes at the selected nodes. It was applied to the optimal placement oftriaxial sensors for vibration testing in a hydropower house, and satisfactory results were obtained. This method can provide some guidance for optimal placement of triaxial sensors of underground powerhouses.

Multi-type sensor placement and response reconstruction for building structures: Experimental investigations

Estimation of lateral displacement and acceleration responses is essential to assess safety and serviceability of high-rise buildings under dynamic loadings including earthquake excitations. However, the measurement information from the limited number of sensors installed in a building structure is often insufficient for the complete structural performance assessment. An integrated multi-type sensor placement and response reconstruction method has thus been proposed by the authors to tackle this problem. To validate the feasibility and effectiveness of the proposed method, an experimental investigation using a cantilever beam with multi-type sensors is performed and reported in this paper. The experimental setup is first introduced. The finite element modelling and model updating of the cantilever beam are then performed. The optimal sensor placement for the best response reconstruction is determined by the proposed method based on the updated FE model of the beam. After the sensors are installed on the physical cantilever beam, a number of experiments are carried out. The responses at key locations are reconstructed and compared with the measured ones. The reconstructed responses achieve a good match with the measured ones, manifesting the feasibility and effectiveness of the proposed method. Besides, the proposed method is also examined for the cases of different excitations and unknown excitation, and the results prove the proposed method to be robust and effective. The superiority of the optimized sensor placement scheme is finally demonstrated through comparison with two other different sensor placement schemes： the accelerometer-only scheme and non-optimal sensor placement scheme. The proposed method can be applied to high-rise buildings for seismic performance assessment.

Sensor placement of long-term health monitoring for large bridges based on the real-time correction of finite element model

The process of optimized placement of long-term health monitoring sensors for large bridges generally begins with finite element models, but there will arise great discrepancies between theoretically-calculated results and actual measurements.Therefore, rectified finite element models need to be rectified by virtue of model rectifying technology. Firstly, the result of construction monitoring and finished state load test is used to real-time modification of finite element model. Subsequently, an accurate finite element model is established. Secondly, the optimizing the layout of sensor with following orthogonality guarantees orthogonal property and linear independence for the measured data. Lastly, the effectiveness and feasibility of method in the paper is tested by real-time modifying finite element model and optimizing the layout of sensor for Nujiang Bridge.

Design of Resilient Sensor Networks Balancing Resilience and Efficiency

In recent years,the notion of resilience has been developed and applied in many technical areas,becoming exceptionally pertinent to disaster risk science.During a disaster situation,accurate sensing information is the key to efficient recovery efforts.In general,resilience aims to minimize the impact of disruptions to systems through the fast recovery of critical functionality,but resilient design may require redundancy and could increase costs.In this article,we describe a method based on binary linear programming for sensor network design balancing efficiency with resilience.The application of the developed framework is demonstrated for the case of interior building surveillance utilizing infrared sensors in both twoand three-dimensional spaces.The method provides optimal sensor placement,taking into account critical functionality and a desired level of resilience and considering sensor type and availability.The problem formulation,resilience requirements,and application of the optimization algorithm are described in detail.Analysis of sensor locations with and without resilience requirements shows that resilient configuration requires redundancy in number of sensors and their intelligent placement.Both tasks are successfully solved by the described method,which can be applied to strengthen the resilience of sensor networks by design.The proposed methodology is suitable for large-scale optimization problems with many sensors and extensive coverage areas.

Same Origin Three-Dimensional Strain Detection FBG Sensor Based on Elliptical Ring and Its Optimization

In order to achieve the same origin three-dimensional （3D） strain measurement, one three-dimensional （3D） fiber Bragg grating （FBG） strain sensor is proposed in this paper. The metal structure of this sensor is composed by three elliptical tings with different geometrical parameters. All these elliptical tings make sure that this sensor achieves the same origin 3D strain detection and increases the strain measurement coefficient. A theory calculation model of this sensor is established. The finite element method is utilized to optimize this sensor and verify the correctness of the theory model. After sensor optimization, 1 mm is chosen as the radical thickness of this sensor based on taking high strain detection coefficient and structure strength into account. To further obtain detection characteristics of this sensor, the calibration experiment is carried out. Experimental data of FBG1 which is the core sensitive element of this sensor is chosen as the specimen to be analyzed by the least square method. When the wavelength of FBG1 is changed by external stress, wavelengths of FBG2 and FBG3 have just a little fluctuation maybe caused by the fiber demodulation instrument SM125. So sensitive elements （FBG1, FBG2, and FBG3） of this sensor have no crosstalk problem for three-dimensional detection. After data analysis, the measuring coefficient of FBG1 is 0.05 nm/N. Similarly, the coefficients of FBG2 and FBG3 are 0.045 nm/N and 0.39nm/N, respectively. All these data confirm that this sensor could achieve the same origin 3D strain measurement without the crosstalk problem and has certain practical applications.

Optimized guided mode resonant structure as thermooptic sensor and liquid crystal tunable filter

Applicability of guided mode resonant structures to tunable optical filtering and sensing is demonstrated using nematic liquid crystals. As a sensor, a minimum refractive index detectivity of 10^-5 is demonstrated while as a tunable filter, tunability range of few tens of nanometers with 2-nm bandwidth is presented. The optimum design is achieved by maximizing the evanescent field region in the analyte which maximizes the overlap integral. The device can be operated in reflection or transmission modes at normal incidence. It can also be operated at a single wavelength by measuring the angular profile of the light beam.

An Efficient Algorithm for Mobile Localization in Sensor Networks

Node localization is a fundamental problem in wireless sensor network.There are many existing algorithms to estimate the locations of the nodes.However,most of the methods did not consider the presence of obstacles.In practice,obstacles will lead to blockage and reflection of communication signals between sensor nodes.Therefore,the presence of obstacles will greatly affect the localization result.In this paper,we implement an obstacle-handling algorithm based on the localization tool developed by MIT,The experimental result shows that the enhanced algorithm can reduce the average distance error by up to 46 %,compared to the original algorithm.

Optimization of magnetic anomaly detection with single-axis sensor for pig locating in low latitude areas

When a pig mounted with permanent magnets gets stuck in the pipeline,it can be located by detecting the magnetic anomalies on the ground using a single-axis magnetic sensor.In order to collect the magnetic anomaly efficiently through single-axis magnetic sensor,a geometric detection model and calculation method for singleaxis magnetic anomaly detection is established in this paper.The distribution of magnetic inclination and declination of the measuring points is obtained.The results indicate that the magnetic inclination of all measuring points vary within a small range of 2°,and this value is highly dependent on the magnetic sensor which is configured aboveground around the geomagnetic inclination.However,the magnetic declination at different points of detection surface is subject to the geomagnetic components and the Y-axis component of the magnetic field of magnets.The magnetic declinations distribute irregularly and vary in a wide range.Therefore,to achieve a high-efficiency detection with the single-axis sensor,the sensor shall be placed in such a manner that the magnetic inclination thereof coincides with the geomagnetic inclination.The magnetic declination of the sensor can be calculated using s,the superposed Y-axis component induced by the permanent magnets,and the corresponding formula given in this paper.The article demonstrates the feasibility of locating a blocked pig in the pipeline based on the single-axis magnetic anomaly detection.It will have a practical significance in guiding the engineering detection.

Horizontal convergence reconstruction in the longitudinal direction for shield tunnels based on conditional random field

Tunnel horizontal convergence monitoring is essential to ensure the operation safety.However,only a few representative tunnel sec-tions are chosen for monitoring due to the cost limitation.It is difficult to capture the horizontal convergence of each tunnel ring with limited measurements.Confronted with this difficulty,the paper proposes a horizontal convergence reconstruction method based on the measurements of deployed sensors.The tunnel horizontal convergence along the longitudinal direction is seen as a one-dimensional sta-tionary and ergodic random field.The reconstruction problem is then transformed into the generation of conditional random fields.Monte Carlo simulation is adopted to generate possible realizations and the mean of realizations is considered as the maximum likeli-hood reconstruction.Error analysis proves the effectiveness of the proposed reconstruction method.The proposed method is proved to be applicable in reconstructing the time-variant horizontal convergence and is verified by the monitoring results of the shield tunnel of Shanghai Metro Line 2.The effect of sensor numbers is parametrically studied,and an optimal sensor placement scheme is decided.Additional sensors placed at the deformation drastically changed location can significantly improve the performance of the proposed method.

Harris Hawks Algorithm Incorporating Tuna Swarm Algorithm and Differential Variance Strategy

Because of the low convergence accuracy of the basic Harris Hawks algorithm,which quickly falls into the local optimal,a Harris Hawks algorithm combining tuna swarm algorithm and differential mutation strategy(TDHHO)is proposed.The escape energy factor of nonlinear periodic energy decline balances the ability of global exploration and regional development.The parabolic foraging approach of the tuna swarm algorithm is introduced to enhance the global exploration ability of the algorithm and accelerate the convergence speed.The difference variation strategy is used to mutate the individual position and calculate the fitness,and the fitness of the original individual position is compared.The greedy technique is used to select the one with better fitness of the objective function,which increases the diversity of the population and improves the possibility of the algorithm jumping out of the local extreme value.The test function tests the TDHHO algorithm,and compared with other optimization algorithms,the experimental results show that the convergence speed and optimization accuracy of the improved Harris Hawks are improved.Finally,the enhanced Harris Hawks algorithm is applied to engineering optimization and wireless sensor networks(WSN)coverage optimization problems,and the feasibility of the TDHHO algorithm in practical application is further verified.

DAMAGE DETECTION STRATEGY FOR RETICULATED STRUCTURES BASED ON INCOMPLETE STRAIN MODE

Damage detection based on strain responses of vibration is highly attractive for monitoring long-span reticulated structures.However,there are a lot of structure members in reticulated structures and it is impossible to install strain sensors in each member.Therefore,how to locate and quantify damages with the incomplete mode shapes obtained from few strain sensors is a challenge topic.A new strategy,named incomplete strain mode damage detection（ISMDD） strategy,is proposed in this paper.In the strategy,the distribution of the strain sensors in the reticulated structures can be optimized through sensitive analysis on strain mode perturbation matrix,which can be obtained by perturbation theory.Mode assurance criterion（MAC） value is applied in damage location,and the members with relative large MAC values are defined as damage members.In addition,damage index obtained by solving the perturbation equation is used for damage quantification.Numerical analysis on a long-span reticulated structure,including damage location and quantification for single-and multi-member damages,detection for different damage quantity,the effect analysis of sensor quantity,are performed to verify the effectiveness of the proposed ISMDD strategy.It can be shown from the analysis that the ISMDD strategy is effective in damage location and quantification for both single-and multi-member damages.And the quantity of strain sensors has effect on damage location,but has no obvious influence on damage quantification.Additionally,the anti-noise pollution ability analysis of the ISMDD strategy is carried out,which shows that the ISMDD strategy has excellent anti-noise pollution ability for both single-and multi-damaged members.