| Summary: | 碩士 === 國立臺灣大學 === 土木工程學研究所 === 96 === The minimization and elimination of errors caused by instrumental imperfections is an important topic in survey education. Students need to learn the theories and correct procedures to compensate the errors by manipulating the instrument properly. However, to understand the theories behind the error causes requires understanding complicated spatial relationship between the parts of the instruments and the survey targets. In addition, the instrumental errors often result from the combination of imperfections in different part of the instrument. Traditional teaching methods, lack of interactive and three-dimensional illustrations, may not support the teaching activities. Students often encounter difficulties to clearly understand the reasons behind the tedious survey procedures used to eliminate errors.
In this research, I would like to simulate and visualize the causes of the errors on computers by which the students can learn and practice the survey instrument more effectively. I particularly modeled the errors by using homogeneous transformation matrices, a format which can facilitate the implementation on computers. Ten kinds of instrumental errors were included in the virtual instruments. They are caused by the imperfections in (1) the plate level axis; (2) the vertical axis; (3) the tilting axis; (4) the sighting axis; (5) the vertical circle index; (6) tripod centering; (7) tripod leveling; (8) distance measurement; (9) eccentricity of the vertical circle; and (10) eccentricity of the horizontal circle.
The error models were implemented as a module and integrated with SimuSurvey, a computer-aided instruction tool for surveying training developed previously. A user test was conducted to verify the effectiveness of using teaching-aid in surveying training. Ten students, who were taking surveying course, were involved in the test. A pretest was conducted as a base line to identify their understanding about the instrumental errors. After a sixty-minute learning section by using SimuSurvey (with error module), we conducted a posttest. The correctness rate in the pretest is 34% and the one in the pretest is 77%. By using t test analysis, we also find that posttest is significantly better than the pretest (t(9) = -11, p < 0.01). This result indicates that error module is an effective method for assisting the surveying training.
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