A method for assessing a health status of a transformer, comprising: using (S101) N transformers configured with a power quality monitoring system as a first group of transformers, and obtaining a first measurement dataset of each of the first group of transformers to obtain N first measurement datasets (S101), wherein the first measurement dataset comprises power quality monitoring data, and wherein N is a positive integer greater than or equal to a first specified value; using (S102) M transformers configured with no power quality monitoring system as a second group of transformers, and obtaining a second measurement dataset of each of the second group of transformers to obtain M second measurement datasets (S102), wherein M is a positive integer greater than or equal to a second specified value, and wherein the first measurement dataset and the second measurement dataset comprise a common data type; clustering the N transformers in the first group of transformers based on values of the common data type in the N first measurement datasets to obtain r first groups (S103), wherein r is a positive integer; clustering the M transformers in the second group of transformers based on values of the common data type in the M second measurement datasets to obtain r second groups (S104); calculating a similarity between each first group and each second group, and establishing r similarity mapping relationships between the first groups and the second groups based on a maximum similarity between two groups (S105); and assessing a health status of a transformer in each second group using a first measurement dataset of a transformer in a first group that is in a similarity mapping relationship with the second group (S106). using (S101) N transformers configured with a power quality monitoring system as a first group of transformers, and obtaining a first measurement dataset of each of the first group of transformers to obtain N first measurement datasets (S101), wherein the first measurement dataset comprises power quality monitoring data, and wherein N is a positive integer greater than or equal to a first specified value; using (S102) M transformers configured with no power quality monitoring system as a second group of transformers, and obtaining a second measurement dataset of each of the second group of transformers to obtain M second measurement datasets (S102), wherein M is a positive integer greater than or equal to a second specified value, and wherein the first measurement dataset and the second measurement dataset comprise a common data type; clustering the N transformers in the first group of transformers based on values of the common data type in the N first measurement datasets to obtain r first groups (S103), wherein r is a positive integer; clustering the M transformers in the second group of transformers based on values of the common data type in the M second measurement datasets to obtain r second groups (S104); calculating a similarity between each first group and each second group, and establishing r similarity mapping relationships between the first groups and the second groups based on a maximum similarity between two groups (S105); and assessing a health status of a transformer in each second group using a first measurement dataset of a transformer in a first group that is in a similarity mapping relationship with the second group (S106). <EOS>