提出基于约束点的测绘仪器设备状态监测数据实时压缩方法，通过特征序列重组，构建测绘仪器设备状态监测数据的共轭模型，输出监测数据的相关序列，结合自定义数据处理逻辑结构设计方法，检索监测数据库，采用全局稳态性的传感节点部署方法，采集测绘仪器设备状态监测数据。根据采集结果，利用最大扩充相容分布，结合内源融合控制，对监测数据融合聚类处理。在此基础上，采用二乘规划和线性特征拟合方法提取数据特征约束点，根据提取结果，构建数据实时压缩模型，实现了测绘仪器设备状态监测数据的实时压缩。仿真结果表明，采用该方法进行测绘仪器设备状态监测数据压缩率较高，提高了数据的存储空间，且具有较高的兼容度。

In order to improve the state monitoring and management capabilities of surveying and mapping equipment, we proposed a real-time method of compressing monitoring and mapping equipment status based on constraint points. Through feature sequence recombination, we constructed a conjugate model of surveying and mapping equipment status monitoring data, and outputted related monitoring data sequences. Combining custom data processing logic structure design methods, we retrieved monitoring databases and adopted sensor node deployment methods with global stability to collect the surveying and mapping equipment monitoring data. According to the collection results, we used the maximum expansion compatible distribution to fuse and cluster the monitoring data by combining the internal source fusion control. Based on this, we used the square programming and linear feature fitting method to extract data feature constraint points, and constructed a real-time data compression model according to the extraction results, which could achieve real-time compression of surveying and mapping equipment monitoring data. The simulation results show that the method has a higher data compression rate for surveying and mapping equipment condition monitoring, improves data storage space, and has a higher compatibility degree.