Qinwei Ma

Prof. Qinwei Ma

orcid

Research Focus & Metrics

Academic Career Length

7Years (2020-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
16 July 2024 in Optics & Laser Technology
Verified
Journal Article
Closed access
XCXiangnan Cheng
Xiangnan Cheng
QMQinwei Ma
Qinwei Ma
SZShichao Zhou
Shichao Zhou
LGLei Guo
Lei Guo
SMShaopeng Ma
Shaopeng Ma

15 May 2020 in Applied Sciences
Verified
Journal Article
Open access
PDF file
SZShichao Zhou
Shichao Zhou
HZHaibin Zhu
Haibin Zhu
QMQinwei Ma
Qinwei Ma
SMShaopeng Ma
Shaopeng Ma
A thermal-induced measurement error induced by thermal deformation of digital camera in photo mechanics methods that has the same magnitude of the error as that in the resistance strain measurement method reduces the accuracy of high-precision measurement substantially and must, therefore, be compensated. Starting from the underlying mechanism of a thermal-induced measurement error, we investigated the image error introduced by thermal behaviours of digital cameras widely used in photo mechanics. We experimentally determined the relationships between the thermal behaviours and temperature, derived the relationship between the image error and measurement error of photo mechanics methods, and eventually established a physical model to explain the underlying relationship between the thermal-induced measurement error and temperature. Furthermore, based on the investigation of the underlying mechanism, we introduced three types of temperature compensation methods for photo mechanics, namely the model compensation method, the preheating method, and the compensation specimen method. We experimentally demonstrated the feasibility of these compensation methods. The model compensation method only needs the data regarding the environmental temperature during operation of the digital camera to implement the correction of the measurement results and enhance the measurement accuracy of photo mechanics methods. The preheating method is suitable for indoor photo mechanics measurements wherein the environmental temperature is almost constant, which ensures that the appearance of thermal balance of the digital camera after a period of self-heating. The compensation specimen method reduces the effective resolution of the images and it also requires that the image error forms in the region of tested specimen are the same as that in the region of the compensation specimen.

30 April 2020 in Sensors
Verified
Journal Article
Open access
PDF file
SZShichao Zhou
Shichao Zhou
HZHaibin Zhu
Haibin Zhu
QMQinwei Ma
Qinwei Ma
SMShaopeng Ma
Shaopeng Ma
Digital cameras represented by industrial cameras are widely used as image acquisition sensors in the field of image-based mechanics measurement, and their thermal effect inevitably induces thermal-induced errors of the mechanics measurement. To deeply understand the errors, the research for digital camera’s thermal effect is necessary. This study systematically investigated the heat transfer processes and temperature characteristics of a working digital camera. Concretely, based on the temperature distribution of a typical working digital camera, the heat transfer of the working digital camera was investigated, and a model describing the temperature variation and distribution was presented and verified experimentally. With this model, the thermal equilibrium time and thermal equilibrium temperature of the camera system were calculated. Then, the influences of thermal parameters of digital camera and environmental temperature on the temperature characteristics of working digital camera were simulated and experimentally investigated. The theory analysis and experimental results demonstrate that the presented model can accurately describe the temperature characteristics and further calculate the thermal equilibrium state of working digital camera, all of which contribute to guiding mechanics measurement and thermal design based on such camera sensors.

8 August 2022 in Materials
Verified
Journal Article
Open access
PDF file
YYYanchun Yin
Yanchun Yin
GLGuangyan Liu
Guangyan Liu
TZTongbin Zhao
Tongbin Zhao
QMQinwei Ma
Qinwei Ma
LWLu Wang
Lu Wang
YZYubao Zhang
Yubao Zhang
As one typical heterogeneous material, the heterogeneity of rock micro parameters has an important effect on its macro mechanical behavior. The study of the heterogeneity of micro parameters is more important to reveal the root cause of deformation and failure. However, as a typical heterogeneous material, the current testing and inversion method is not suitable for micro parameters measurement for the rock. Aiming at obtaining the distribution of micro Young’s modulus and micro Poisson’s ratio of the rock, based on the digital image correlation method (DIC) and finite element method (FEM), this paper proposed a parameter field inversion method, namely the DF-PF inversion method. Its inversion accuracy is verified using numerical simulation and laboratory uniaxial compression test. Considering the influences of heterogeneity, stress state and dimension difference, the average inversion error of Young’s modulus field and Poisson’s ratio field are below 10%, and the proportion of elements with an error of less than 15% accounts for more than 86% in the whole specimen model. Compared with the conventional measuring method, the error of macro Young’s modulus and macro Poisson’s ratio calculated by the DF-PF inversion method is less than 2.8% and 9.07%, respectively. Based on the statistical analysis of Young’s modulus field and Poisson’s ratio field, the parameter homogeneity and quantitative function relation between the micro parameter and the principal strain can also be obtained in laboratory tests. The DF-PF inversion method provides a new effective method of testing Young’s modulus field and Poisson’s ratio field of the rocks under complex stress states.

1 May 2024 in Journal of Aerospace Engineering
Verified
Journal Article
Closed access
JYJunxin Yu
Junxin Yu
CWChao Wang
Chao Wang
QMQinwei Ma
Qinwei Ma

22 August 2022 in Computer Vision and Image Understanding
Verified
Journal Article
Closed access
WSWenzhang Sun
Wenzhang Sun
LWLu Wang
Lu Wang
SMShaopeng Ma
Shaopeng Ma
QMQinwei Ma
Qinwei Ma