Identifying the onset of an agglomeration phenomenon at an early stage in processes utilizing gas-solid fluidized beds that operate under the influence of cohesive interparticle forces affords enough time to apply counteractive strategies and avoid a disastrous agglomeration of particles potentially leading to complete bed defluidization. In this paper, we compare the performance of different leading approaches proposed in the open literature for the advanced detection of defluidization. The approaches include the single-signal-monitoring of evolutions of total bed pressure drop, standard deviation of pressure signals, or S-value from the attractor comparison analysis as well as the simultaneous-monitoring of temperature and in-bed differential pressure signals during the process. The results show that the simultaneous-monitoring of temperature and in-bed differential pressure signals provided the best prediction of the onset of agglomeration while it demonstrated the least sensitivity to the changes in gas velocity, operating temperature, and bed inventory. (C) 2017 Elsevier B.V. All rights reserved.