粗差也被称为过失误差或异常误差。测量者的主观因素或测试条件突然变化导致

Gross error is also called gross error or abnormal error. Obvious inconsistency errors in the measurement results caused by the subjective factors of the measurer or sudden changes in the test conditions For example, improper operation of the meter is caused by inadvertent factors such as incorrect readings, recording and calculation errors, sudden failure of the test system, and environmental conditions. The gross error observation value is called a bad value or an abnormal value, and it is judged and removed by a certain method, and does not affect the measurement result. <br>In the calculation of level measurement adjustment, probabilistic and statistical methods are usually used to eliminate inconsistent values ​​between observations, which are observations with a series of accidental errors. For various systematic errors that co-exist with accidental errors, in order to eliminate or weaken the influence on the observation results during the observation process, and to check whether there is rough error in the observation value when the closed-circuit error exceeds the limit, the system error is not considered in the adjustment calculation. And roughness. <br>Regarding the gross error, its location and size have not been investigated in advance, and the gross error only affects very individual observation data. The self-check adjustment method that eliminates compensation and influence cannot be applied. In recent years, we have developed two basic gross error processing methods: identification and adjustment. Recognition is a kind of exploration, and it is deleted after detection. Adjustment refers to the use of strong anti-interference estimation methods to control the influence of gross errors on the adjustment results. This section mainly discusses the method of removing gross errors.

Roughness is also known as error of error or abnormal error. A significant error of inconsistent measurement results due to subjective factors of the surveyor or sudden changes in test conditions. For example, improper instrument operation is due to errors caused by factors such as incorrect readings, incorrect recording and calculation, sudden failure of the test system, and environmental conditions. Rough observations are called bad values or outliers, and they are dissoated by a certain method, without affecting the measurement results.<br>In horizontal measurement of flatness calculations, probability statistics are often used to eliminate inconsistencies between observations, which are observations of a series of accidental errors. For various system errors that exist at the same time as accidental errors, in order to eliminate or reduce the effect on the observation results during the observation process, in order to check whether there is a rough difference in the observation when the closed-circuit difference exceeds the limit, the system error and roughness are not taken into account in the flatness calculation.<br>With regard to coarseness, its location and size were not pre-investigated, and coarseness affected only very individual observations. The self-checking balance method to eliminate compensation and effects cannot be applied. In recent years, we have developed two basic rough handling methods: identification and regulation. Identification is an exploration that is removed after detection. Adjustment refers to the use of strong anti-jamming estimation method to control the effect of roughness on the results of the spread. This section focuses on ways to remove roughness.

Gross error is also called gross error or abnormal error. The measurement error caused by subjective factors or sudden changes of test conditions. For example, improper operation of instruments is caused by reading errors, recording and calculation errors, sudden failure of test system and environmental conditions. Gross error observation value is called bad value or abnormal value, which can be discriminated and removed by certain methods, and does not affect the measurement results.<br>In the calculation of horizontal survey adjustment, the probability and statistics method is usually used to eliminate the inconsistent values between observations, which are a series of observations with accidental errors. In order to eliminate or weaken the influence on the observation results in the observation process, and to check whether there is roughness in the observation value when the closed-circuit error exceeds the limit, the systematic error and roughness are not considered in the adjustment calculation.<br>As for the gross error, its location and size are not investigated in advance, and the gross error only affects very individual observation data. The self checking adjustment method of eliminating compensation and influence can not be applied. In recent years, we have developed two basic gross error processing methods: recognition and adjustment. Recognition is a kind of exploration, which is deleted after detection. Adjustment refers to the use of strong anti-interference estimation method to control the influence of gross errors on the adjustment results. This section mainly discusses how to remove gross errors.<br>