Method for performing diagnostics of a structure (S1-S3) subject to loads, particularly an aircraft structure, by means of a sensor arrangement which is associated with said structure (S1-S3) and designed to detect at least one state of the structure and which comprises a matrix of sensors which are located in relevant points (P i) of the structure (S1-S3) and each of which is capable of detecting a physical parameter indicative of the local state of the structure (S1-S3) and of emitting a respective electrical response signal correlated to the value assumed by said parameter, the method comprising, in a learning step: (a) based on a plurality of training data indicative of the state of the structure (S1-S3) at a plurality of relevant detection points (P i) by association with at least one load condition, establishing an associative relationship, by means of at least one neural network, between the values assumed by said parameter indicative of the state of the structure in a subset of said plurality of relevant detection points and the values of the state parameter in at least a residual relevant detection point; and in an operating step: (b) detecting the values assumed by said parameter indicative of the state of the structure in a plurality of relevant detection points (P i) in said at least one load condition; (c) based on the pre-established associative relationship, using the values assumed by said parameter indicative of the state of the structure in a subset of said plurality of detection points, estimating the values of the state parameter in at least one residual detection point; (d) comparing the estimated values and the detected values of the state parameter in said at least one residual detection point; and (e) determining an intact state of the structure if the detected and the estimated values of the state parameter substantially match, taking into consideration predetermined tolerances, or determining a defective state of the structure (900, 1000) if said values of the state parameter differ, taking into consideration the predetermined tolerances. (a) based on a plurality of training data indicative of the state of the structure (S1-S3) at a plurality of relevant detection points (P i) by association with at least one load condition, establishing an associative relationship, by means of at least one neural network, between the values assumed by said parameter indicative of the state of the structure in a subset of said plurality of relevant detection points and the values of the state parameter in at least a residual relevant detection point; and (b) detecting the values assumed by said parameter indicative of the state of the structure in a plurality of relevant detection points (P i) in said at least one load condition; (c) based on the pre-established associative relationship, using the values assumed by said parameter indicative of the state of the structure in a subset of said plurality of detection points, estimating the values of the state parameter in at least one residual detection point; (d) comparing the estimated values and the detected values of the state parameter in said at least one residual detection point; and (e) determining an intact state of the structure if the detected and the estimated values of the state parameter substantially match, taking into consideration predetermined tolerances, or determining a defective state of the structure (900, 1000) if said values of the state parameter differ, taking into consideration the predetermined tolerances.