In this paper, an optical fiber composite Fabry-Perot interferometric (CFPI) sensor capable of simultaneous measurement of high temperature and strain is presented. The CFPI sensor consists of a silica-cavity intrinsic Fabry-Perot interferometer (IFPI) cascading an air-cavity extrinsic Fabry-Perot interferometer (EFPI). The IFPI is constructed at the end of the transmission single-mode fiber (SMF) by splicing a short piece of photonic crystal fiber (PCF) to SMF and then the IFPI is inserted into a quartz capillary with a reflective surface to form a single-ended sliding EFPI. In such a configuration, the IFPI is only sensitive to temperature and the EFPI is sensitive to strain, which allows the achieving of temperature-compensated strain measurement. The experimental results show that the proposed sensor has good high-temperature resistance up to 1000 °C. Strain measurement under high temperatures is demonstrated for high-temperature suitability and stable strain response. Featuring intrinsic safety, compact structure and small size, the proposed CFPI sensor may find important applications in the high-temperature harsh environment.

For engineering structures, strain flexibility-based approaches have been widely used for structural health monitoring purposes with prominent advantages. However, the applicability and robustness of the method need to be further improved. In this paper, a novel damage index based on differences in uniform load strain field (ULSF) is developed for plate-like structures. When estimating ULSF, the strain flexibility matrix (SFM) based on mass-normalized strain mode shapes (SMSs) is needed. However, the mass-normalized strain mode shapes (SMSs) are complicated and difficult to obtain when the input, i.e., the excitation, is unknown. To address this issue, the proportional strain flexibility matrix (PSFM) and its simplified construction procedure are proposed and integrated into the frames of ULSF, which can be easily obtained when the input is unknown. The identification accuracy of the method under the damage with different locations and degrees is validated by the numerical examples and experimental examples. Both the numerical and experimental results demonstrate that the proposed method provides a reliable tool for output-only damage detection of plate-like structures without estimating the mass-normalized strain mode shapes (SMSs).

In the actual process, the structure of the Heavy-duty machine are often subjected to influence of various force load and thermal load, and then structure is deformed, resulting in processing errors. Currently, one of the main factors restricting the high-duty heavy machine to further improve accuracy is machine structural deformation. International Society for Production Engineering reports that error formed by thermal deformation and structural deformation is the key factor of high-duty CNC machining precision, the error caused by deformation of machine accounted for the total deformation 40% to 75%. Reduce errors usually take error compensation, however, precondition of error compensation is to get the machine deformation field. In this paper, choose the machine column as the main object of study, and based on column structure distributed strain field to get deformation field, through theoretical analysis and experimental verification to present based on the machine column fiber grating deformation measurement and reconstruction method.

In this paper, we propose a damage identification method based on minimum mean square error estimation for a wind tunnel flexible plate condition monitoring system. Critical structural members of important equipment are large in size, and the measurement systems used to monitor their condition are often complex. The proposed damage identification method is based on the minimum mean squared error estimator and the generalized likelihood ratio test. It introduced activation function to generate the standard deviation of the data, which can then simulate the sensor output. A single sensor damage only affects a single dimension of the output data matrix of the measurement system. However, structural damage affects the output of multiple sensors. The damage identification method proposed in this paper can not only distinguish the sensor damage from the structure damage, but also locate the damaged sensor or structure damage location. This method can identify the measurement system output anomalies caused by structural damage and locate the approximate location of the damage. It can be applied to damage identification of important structural members such as flexible wind tunnel plates. The damage identification method proposed in this paper is of great significance for damage identification and localization of key components and sensor systems.