Coupling cloud theory and concept hierarchy construction early warning thresholds for deformation safety of tailings dam

Scientific calculating of deformation early warning thresholds is of great significance for identifying the abnormal operation state of tailings dams. Traditional early warning studies cannot take into account the fuzziness and randomness of monitoring data, and most of them focus on single-point and single-level early warning, which cannot accurately reflect the operational state and the risk level of failure of the tailings dam. In this study, an early warning model based on cloud theory (CT) and concept hierarchy construction (CHC) is proposed to determine a reliable warning of multi-point displacement of tailings dam. The CT is used to calculate the characteristic values of displacements, including expectation ( Ex ), entropy ( En ), and hyper entropy ( He ), which can eliminate the influence of fuzziness and randomness of the monitoring data. The multi-point characteristic values of displacements are integrated via the CHC method to obtain the characteristic values representing the integral qualitative concept of the tailings dam, which can overcome the limitation of single-point early warning. The normal operation value of displacement of tailings dam is calculated according to the “3 En ” principle, and the comprehensive early warning displacement thresholds are obtained. The displacement monitoring data of Yangjiawan tailings dam demonstrates the rationality and accuracy of the developed CT–CHC model. Our work provides a new avenue to warn of the potential failure of tailings dams. Graphical abstract