Fault Diagnosis Method of Rotating Machinery Based on Collaborative Hybrid Metaheuristic Algorithm to Optimize VMD

Table 1

Algorithm steps of MOPSO.

Step 1	Initialize the population and storage space set, assign initial values to the parameters, generate the initial population , and copy the noninferior solution in to the storage space to obtain . Let the current evolutionary algebra be , and proceed to steps 2~4 when is less than the total evolutionary algebra.
Step 2	Evolution produces the next generation of population: Let the current evolving particle complete the contents of (a)–(c) when is smaller than the population size.; (a) Calculate the density information of particles in the storage space; (b) Select the optimal particle in for particle in the population; the quality of particles determines the convergence performance of MOPSO algorithm and the diversity of noninferior solution sets. Its selection is based on the density information of particles in the storage space; (c) Update the position and velocity of particles in the population, and search the optimal solution in the particle swarm under the guidance of
Step 3	Update storage set.
Step 4	Truncate storage space set: When the number of particles in the storage space set exceeds the specified size, redundant individuals need to be deleted to maintain a stable storage space set size. For mesh with more than one particle number, calculate the number of particles to be deleted in the mesh and then delete particles randomly in mesh .
Step 5	Output particle information in the storage space set.