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In the identification of operational behavior of earth pressure cells and structural safety assessment， measurement gross errors often coexist with abrupt changes reflecting actual structural responses， thereby compromising the accuracy of safety evaluation. To address this issue， this paper proposes an anomaly detection method for earth pressure cell measurements based on frequency domain decomposition and multi-point joint analysis. Through decomposition and reconstruction in the frequency domain， frequency components representing long-term trends and short-term fluctuations are derived. Subsequently， by integrating correlation analysis and the Isolation Forest algorithm， joint anomaly detection and diagnosis across multiple measurement points are achieved. Case studies based on actual engineering monitoring data demonstrate that the proposed method can accurately distinguish between gross errors and abrupt changes caused by structural anomalies or environmental factors， with high detection accuracy. The method enhances the diagnostic capability of earth pressure cell measurements and improves structural safety monitoring.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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