Flexure hinges have been used in many engineering areas where high precision and sensitivity are required. Many kinds of flexure profiles were proposed during the past decade. Therefore, a general closed-form solution for flexure hinges of different profiles that incorporates the profile selection and parameter design will be of great benefit to the hinge design. The present work brings circular, right-circular, and elliptical profiles together by proposing a generalized flexure hinge model, which we call elliptical arc flexure hinges (whose maximum eccentric angle phi(m) ranges from 0 to pi/2) to distinguish from the existing elliptical flexure hinge (phi(m)=pi/2). Based on the theories of mechanics of materials, all the elements in the compliance matrix for elliptical arc flexure hinges are deduced by introducing the eccentric angle of ellipse as the integral variable. These compliance equations simply boil down to four integrals, thus simplifying the compliance calculation. These equations also apply to elliptical (phi(m)=pi/2), circular (a=b), and right-circular (phi(m)=pi/2 and a=b) hinges. These compliance equations were checked by comparing them with the results of finite element analysis, the existing equations, and experiment results. The comparison results show that these generalized equations are concise and adequate for most design purposes.

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Conductor galloping may cause flashovers and even tower collapses. The available conductor galloping monitoring methods often employ acceleration sensors to measure the conductor translations without considering the conductor twist. In this paper, a new sensor for monitoring conductor galloping of transmission lines based on an inertial measurement unit and wireless communication is proposed. An inertial measurement unit is used for collecting the accelerations and angular rates of a conductor, which are further transformed into the corresponding geographic coordinate frame using a quaternion transformation to reconstruct the galloping of the conductor. Both the hardware design and the software design are described in details. The corresponding test platforms are established, and the experiments show the feasibility and accuracy of the proposed monitoring sensor. The field operation of the proposed sensor in a conductor spanning 734 m also shows its effectiveness.

The shortage of the existing on-line monitoring technology of transmission line conductor icing at home and abroad was analyzed, and the necessity of improving the existing icing monitoring technology was pointed out in this paper. The new on-line monitoring system of transmission line conductor icing was designed. The master-slave monitoring structure was used in the whole system design. In this paper, the new system structure and technical features were briefly described, a new mechanical model of computing icing coating was built, and the calculation method of conductor icing density and type was given in details. The testing and running results show that the shortage of existing on-line monitor technology of transmission line conductor icing can be improved by this new on-line monitoring technology what is more effective to guide the icing transmission lines de-icing.

In this article, an online monitoring technology applied to transmission line towers is proposed to overcome the problems that the foundation deformation is difficult to find in the mining area, river, hillside, and other special areas. The measurement of the stress or the strain caused by the tower foundation deformation are rarely issued, though the tower status can be possibly assessed by the stress or the strain. A new online monitoring technology of tower foundation deformation of transmission lines is developed which consists of three parts. In the first part, the stress or the strain of the key elements is effectively analyzed under the different deformations such as foundation settlement, inclination, and side-slip with the tower finite element model built and the wind load and ice load applied on the tower. In the second part, the experimental platform of tower stress tests is set up, and the internal relations between the stress variation and the tower foundation deformation are determined. In the third part, the online monitoring technology of tower foundation deformation of transmission lines is developed based on fiber Bragg grating stress sensor and successfully applied in Jibei power grid in China. The results show that all the monitored stresses fluctuating with the wind speed are small in case that the condition of tower foundation is normal; on the contrary, the corresponding stresses will change greatly.

Abstract. The insulator of transmission lines is one of the most important infrastructures, which is vital to ensure the safe operation of transmission lines under complex and harsh operating conditions. The glass insulator often self-shatters but the available identification methods are inefficient and unreliable. Then, an automatic identification and localization technology of self-shattered glass insulators is proposed, which consists of the cameras installed on the tower video monitoring devices or the unmanned aerial vehicles, the 4G/OPGW network, and the monitoring center, where the identification and localization algorithm is embedded into the expert software. First, the images of insulators are captured by cameras, which are processed to identify the region of insulator string by the presented identification algorithm of insulator string. Second, according to the characteristics of the insulator string image, a mathematical model of the insulator string is established to estimate the direction and the length of the sliding blocks. Third, local binary pattern histograms of the template and the sliding block are extracted, by which the self-shattered insulator can be recognized and located. Finally, a series of experiments is fulfilled to verify the effectiveness of the algorithm. For single insulator images, Ac, Pr , and Rc of the algorithm are 94.5%, 92.38%, and 96.78%, respectively. For double insulator images, Ac, Pr , and Rc are 90.00%, 86.36%, and 93.23%, respectively.