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One of the major tasks in process industry is solid concentration (SC) estimation in solid–liquid two-phase flow in any pipeline. The γ-ray sensor provides the most used and direct measurement to SC, but it may be inaccurate due to very local measurements and inaccurate density baseline. Alternatively, under various conditions there are a tremendous amount of indirect measurements from other sensors that can be used to adjust the accuracy of SC estimation. Consequently, there is complementarity between them, and integrating direct and indirect measurements is helpful to improve the accuracy of SC estimation. In this paper, after recovering the interrelation of these measurements, we proposed a new SC estimation method according to Kalman filter fusion. Focusing on dredging engineering fields, SCs of representative flow pattern were tested. The results show that our proposed methods outperform the fused two types of measurements in real solid–liquid two-phase flow conditions. Additionally, the proposed method has potential to be applied to other fields as well as dredging engineering.

Solid phase fraction (SPF) is one of the most important parameters in solid-liquid two-phase flow, and has been increasingly addressed on most of the measuring techniques. As an effective measuring technique, Electrical Resistance Tomography (ERT) has been applied to measure SPF owing to low-cost, fast-response, non-invasive and non-radiation characteristics. The ERT-based SPF estimation is greatly affected by different solid object sizes from the existing methods, but currently there is none efficient method to solve this problem. In this paper, a mathematical model firstly is proposed to generally approximate various object sizes and thereby reconstruct all measurements. Therefore, when all solid objects have unevenly distributed and different sizes, SPF can still be effectively computed. Experiments are implemented in three groups of actual experiments by a building platform, where the solid objects in each group have individual object size. Results show that the new method can compute the value of SPF more accurate than the existing method, and thus provide a more accurate way to SPF computation.

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