Landslide displacement monitoring plays a fundamental role in the study of landslide evolution mechanisms, forecasting, risk assessment, prevention, and control. To fill the deficiencies of traditional instrumentation for measuring landslide displacement distributed along lateral direction, a landslide displacement measurement method based on deformation-coupled pipeline trajectory measurement is proposed, and a pipeline trajectory inertial measurement instrument is developed. The developed instrument, primarily comprised of a single shaft gyro, two axis accelerometers, and an external roller encoder, is designed as an axial half strapdown-radial half platform structure combined with a mechanical gravity platform. This structure avoids the singularity of pitch angle and roll angle and can expediently calculate a pipeline trajectory with an Eulerian transformation when obtaining several basic physical variables, e.g., the axial linear velocity, pitch angle, roll angle, and azimuth angle. Additionally, the pipeline trajectory, measured at different times, possesses the ability to reflect the displacement evolution feature of landslides. The results of prototype simulation tests imply a single measurement accuracy of a 12 cm/100 m span and a singly periodic multiple (more than five times) measurement accuracy of a 3 cm/100 m span, which meets medium-precision displacement measurement requirements for a landslide. Additionally, the finished instrument has been successfully applied to the deformation monitoring of the Majiagou I# landslide, which further verifies its feasibility and offers a reference for similar landslides.

A fiber-optic gyroscope (FOG) with lower precision but higher cost advantage is typically selected according to working conditions and engineering budget. Thermal drift is the main factor affecting FOG precision. External thermal calibration methods by algorithms can effectively weaken the influence of thermal drift. This paper presents a thermal calibration method of a two-dimensional N-order polynomial (TDNP) and compares it with artificial neural network (ANN) methods to determine a software FOG thermal calibration method for landslide displacement monitoring. The TDNP thermal calibration coefficient matrix was established, and the thermal calibration capability of the TDNP method with different orders N was evaluated on the basis of error analysis. The ANN model with 1 to 18 hidden neural layers was established on the basis of LM, BR, and SCG algorithms to choose a suitable ANN. Finally, the mean absolute errors of FOG thermal calibration through the TDNP with different orders and the LM were compared. This method was applied in the Huangtupo landslide area, China. The results highlight that the TDNP method with order 5 had better performance and satisfied the requirements of landslide displacement monitoring. The research results can compensate for the lack of adaptability of the FOG thermal calibration method in landslide displacement monitoring.

Accurate measurement of surface and subsurface landslide displacement is a fundamentally important task for landslide disaster prediction and early warning. However, the conventional landslide displacement measurement methods on the basis of point measurement cannot obtain the deformation between measurement points. The methods that can make continuous deformation available are only applicable to surface displacement measurement and their measurement capability is severely affected by environmental factors. Therefore, landslide displacement measurement applications call for an innovative method that can realize continuous deformation measurement on the surface and underground. A novel landslide displacement inertial measurement system is provided in this article which adopts low-cost fiber optic gyroscopes (FOGs) and other inertial sensors, integrates a two-dimensional N-order polynomial (TDNP) algorithm, sensor misalignment error compensation algorithm, and adaptive complementary filtering algorithm. The fusion of the multialgorithm reduces errors step by step, improves the resolution of the FOGs, calibrates the inertial sensors, and solves the problems of dead band and increased error at low angular rate for FOGs. Key architecture design points of the system are also introduced in detail. Comparison field tests with total station indicate that the system has the capability to identify cm-level landslide displacement and is feasible for landslide displacement measurement. In addition, the new method can benefit subsequent research and provide a reference for the implementation of this kind of system.

This paper presents a control system of FPGA-based three-axis stepper motor with the hybrid stepper motor as the control object. The whole control system uses an external keyboard to control the start, stop, jog, acceleration, deceleration of the stepper motor, and realizes the detection of the motor speed through the rotary encoder, and the signal processed is displayed as the state of the motor running speed on the LCD screen through the VGA interface. The core of this system is the scene integration technology of digital system constituted by FPGA + Verilog HDL + EDA tool. The programming part employs the Verilog HDL hardware description language to achieve the needs of keyboard scanner program, LCD module preparation program, the motor control program, velocity program, etc by the modular design, which improves the scalability of the system performance.