# Performance and Measurement Devices for Membrane Buildings in Civil Engineering: A Review
## 4 Development of Measurement Devices  
### Measurement Methods  
Given the thinness and lightness of membranes, traditional contact measurement methods are no longer suitable because the weight of the instrument may affect the structure. This is in contrast to the distinct advantages of measuring membrane structures with non-contact instruments, including lasers, cameras, three-dimensional (3D) scanners, and other devices.  
The laser sensor can measure the deformation of the membrane surface at a certain point of the structure. Moreover, based on the measurement results, the stress and prestress of the membrane structure and other data related to the proper functioning of the structure can be calculated. A frequent non-destructive structural investigation method is structural excitation. [PERSON] et al. [124] developed a non-destructive detection method for the preteiso-surface concept to discover and localize membrane damage by acquiring the modes of the structure. Using laser-induced breakdown (LIB) as an excitation means allowed both low-frequency and high-frequency data to be deployed for localization damage.  
With laser sensors, for example, the sensor is only able to acquire the response of the structure at one location. Thus, a large number of sensors are required to collect the response of the entire field, resulting in a complex and expensive measurement system. Instruments such as 3D scanners, laser scanners, cameras, and other similar devices can measure multiple points simultaneously to obtain the displacement field of the entire structure, as it is beneficial in accurately determining the response of structures with large deformation and flexibility, such as membrane structures. The dynamic shape of small buildings can be measured using 3D scanners. Laser scanning provides highly accurate static profiles of structures regardless of their size. Different structural data are captured by altering the number of cameras. A one-camera system obtains a static shape of the structure, while a system of several cameras obtains a dynamic shape. Its principle is shown in Figure 22. The 3D model is required to meet complex analytical needs, but the accuracy of results is limited by systematic and statistical errors [127; 128]. Calibration algorithms based on MATLAB or OpenCV are typical ways to reduce system errors. Potential inaccuracies in acquiring data and detecting structural faults might be minimized by increasing the number of cameras and employing the least-squares method [129]. [PERSON] et al. [130; 131; 132] formed a link structure by discretizing a continuous surface into mesh based on the acquired measurement geometry, simplified the load on the structure as a nodal load, and then computed the stress distribution by using the force-finding method. The size of the mesh discretized from the surface had a minimal effect on the calculation results. The increased size of the meshes resulted in a slight decrease in the projected maximum stresses on the structure. In addition, this method could be applied to inflatable membrane structures made of different types of membranes since the calculation did not consider the mechanical properties of the material. [PERSON] et al. [133; 134] formed a stereo-vision measurement system to observe the wind-induced aeroelastic response of a membrane structure, which consisted of a charge-coupled device, optical lenses, and an image acquisition card as the main components. The position of the camera arrangement was directly related to the measurement accuracy, so the cameras had to face the target to guarantee the quality of the acquired images, with any lateral deviation causing errors. Furthermore, insufficient illumination also made it hard to achieve the required measurement accuracy.  
Figure 22: Camera measurement principle [133].