CAJ | 학술논문

针对地下工程沉降变形预测中测量数据可能含有有色噪声甚至粗差的问题，基于抗差Kalman滤波理论提出一种自适应的沉降变形预测算法。以水准观测沉降量、沉降速度和加速度作为状态向量，通过构造自适应因子和等价权函数来处理系统模型误差和观测粗差对变形预测结果的影响，避免了岩土工程中本构关系和力学参数不易确定的问题，便于实现应用。采用上海某隧道沉降监测数据对该算法进行验证实验，结果表明该算法能较好地对变形监测点进行一步预测，并对系统模型误差和观测粗差具有较好的适应性和容错性，取得了良好的工程实验效果，适合测量环境复杂的地下工程沉降变形预测应用。
침대지하공정침강변형예측중측량수거가능함유유색조성심지조차적문제，기우항차Kalman려파이론제출일충자괄응적침강변형예측산법。이수준관측침강량、침강속도화가속도작위상태향량，통과구조자괄응인자화등개권함수래처리계통모형오차화관측조차대변형예측결과적영향，피면료암토공정중본구관계화역학삼수불역학정적문제，편우실현응용。채용상해모수도침강감측수거대해산법진행험증실험，결과표명해산법능교호지대변형감측점진행일보예측，병대계통모형오차화관측조차구유교호적괄응성화용착성，취득료량호적공정실험효과，괄합측량배경복잡적지하공정침강변형예측응용。
Aiming at the problem of settlement observation data containing colored noise even gross errors in underground engineering, a prediction algorithm of settlement is presented based on the a-daptive robust Kalman filtering theory.Taking the value, velocity and acceleration of leveling settle-ment as the state vector, the effects of system model error and measurement gross error on prediction are controlled by constructing self-adaptive factor and equivalent weight function.In addition, this algorithm is simple to implement, which avoids the problem of constitutive relations and the mechan-ical parameters of geotechnical engineering that are not easy to be determined.The settlement obser-vation data of the tunnels in Shanghai is used for the experiment to verify the proposed algorithm. The results show that the algorithm can effectively obtain deformation predication, and it has the ad-vantages of good adaptability and fault tolerance for system model error and measurement gross er-ror.The algorithm obtains good application effect in engineering, and it is suitable for the settlement prediction of underground engineering in complex measuring environments.