Method for detecting and diagnosing a fault in a heating, ventilation and air conditioning system, comprising the steps: - determining a plurality of key performance indicators, wherein the key performance indicators describe an operating state of at least one component of the system, - providing a knowledge base, which describes known interdependencies between the key performance indicators in a fault free state, - comparing the determined key performance indicators with the known interdependencies from the knowledge base for the detecting and diagnosing a fault, in a first analysis path, wherein the first analysis path is a knowledge based approach which is dealing with general behavior of groups of key performance indicators healthy and faulty system behavior, - providing a model database, which describes models (M1, M2) for interdependencies between the key performance indicators, wherein for determining the models (M1, M2) predetermined faults are provided, wherein for determining the models (M1, M2), a control loop for controlling an operation of the at least one component is simulated and the predetermined faults are provided by a change of the simulated control loop, wherein the models (M1, M2) of the interdependencies of the key performance indicators are determined by means of a statistical method based on learning data, wherein the models (M1, M2) are updated continuously, and - comparing the determined key performance indicators with the models (M1, M2) for the detecting and diagnosing a fault in a second analysis path parallel to the first analysis path, to perform a condition-based maintenance of the heating, ventilation and air conditioning system, wherein the second analysis path is dealing with automatic data based pattern recognition using reference mathematical models of the key performance indicators, - wherein the two analysis paths (AP1, AP2) are running in parallel and are complementary to each other to detect different types of faults and malfunctions with each analysis path (AP1, AP2). - determining a plurality of key performance indicators, wherein the key performance indicators describe an operating state of at least one component of the system, - providing a knowledge base, which describes known interdependencies between the key performance indicators in a fault free state, - comparing the determined key performance indicators with the known interdependencies from the knowledge base for the detecting and diagnosing a fault, in a first analysis path, wherein the first analysis path is a knowledge based approach which is dealing with general behavior of groups of key performance indicators healthy and faulty system behavior, - providing a model database, which describes models (M1, M2) for interdependencies between the key performance indicators, wherein for determining the models (M1, M2) predetermined faults are provided, wherein for determining the models (M1, M2), a control loop for controlling an operation of the at least one component is simulated and the predetermined faults are provided by a change of the simulated control loop, wherein the models (M1, M2) of the interdependencies of the key performance indicators are determined by means of a statistical method based on learning data, wherein the models (M1, M2) are updated continuously, and - comparing the determined key performance indicators with the models (M1, M2) for the detecting and diagnosing a fault in a second analysis path parallel to the first analysis path, to perform a condition-based maintenance of the heating, ventilation and air conditioning system, wherein the second analysis path is dealing with automatic data based pattern recognition using reference mathematical models of the key performance indicators, - wherein the two analysis paths (AP1, AP2) are running in parallel and are complementary to each other to detect different types of faults and malfunctions with each analysis path (AP1, AP2).