Methods and systems for determining causes of conditions in components of rotary machines

An imaging and analysis computing system comprising at least one processor communicatively coupled to at least one memory device, wherein a component database is stored in the at least one memory device, wherein each of a plurality of components is associated in the component database with one of a plurality of rotary machines and at least one of a plurality of pre-identified conditions, and wherein the at least one processor is programmed to:

• receive, for each of the rotary machines, a respective machine data set including recorded historical operational sensor and control data for the associated rotary machine, a characteristic recorded during operation of the rotary machine that affects power transmitted to at least one of an electrical generator and a mechanical drive, and geographical site data for the associated rotary machine;
• receive an indication of a removal of at least some of the components from a respective rotary machine of the plurality of rotary machines;
• determine, for each of the removed components via image data of the components obtained after removal of the components from the rotary machines, at least one of the pre-identified conditions, wherein each of the pre-identified conditions includes a location and component wear or damage including at least one of cracking, pitting, and erosion, and wherein the location includes at least one of an airfoil root, an airfoil midsection, an airfoil tip, an airfoil leading edge, an airfoil trailing edge, a suction side, a pressure side, a shroud plate, and a shroud rail;
• associate, in the component database, each of the components with the corresponding identified at least one pre-identified condition and the respective one of the rotary machines from which the component was removed;
• identify, in the component database, a first set of the components each having a first of the pre-identified conditions;
• identify at least one common parameter from the machine data sets of the rotary machines associated with the first set of the components, wherein the at least one common parameter is at least one of the characteristic affecting load recorded during operation of the rotary machine, and the geographical site data of the rotary machines;
• store the at least one common parameter as a new profile template of a plurality of profile templates, the profile templates each including at least one parameter derivable from the machine data set that has been determined to be of interest in relation to determining causes of pre-identified conditions occurring in components of the plurality of rotary machines;
• identify at least one of the rotary machines having a respective machine data set matching the new profile template;
• identify, in the component database, a second set of the components associated with the at least one rotary machine, wherein a second of the pre-identified conditions is common to each of the components of the second set of the components;
• and
• report the at least one common parameter as a potential cause of the first pre- identified condition, and as a potential cause of the second pre-identified condition associated with the second set of components.

At least one non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by at least one processor, at least one processor communicatively coupled to at least one memory device, wherein a component database is stored in the at least one memory device, wherein each of a plurality of components is associated in the component database with one of a plurality of rotary machines and at least one of a plurality of pre-identified conditions, and wherein the computer-executable instructions cause the at least one processor to:

• receive, for each of a plurality of rotary machines, a respective machine data set including recorded historical operational sensor and control data, a characteristic affecting load recorded during operation, and geographical site data for the associated rotary machine;
• receive an indication of a removal of at least some of the components from a respective rotary machine of the plurality of rotary machines;
• determine, for each of the removed components via image data of the components obtained after removal of the components from the rotary machines, at least one of the pre-identified conditions, wherein each of the pre-identified conditions includes a location and component wear or damage including at least one of cracking, pitting, and erosion, and wherein the location includes at least one of an airfoil root, an airfoil midsection, an airfoil tip, an airfoil leading edge, an airfoil trailing edge, a suction side, a pressure side, a shroud plate, and a shroud rail;
• associate, in a component database, each of the components with the corresponding identified at least one pre-identified condition and the respective one of the rotary machines from which the component was removed
• identify, in the component database, a first set of the components each having a first of the pre-identified conditions;
• identify at least one common parameter from among machine data sets of the rotary machines associated with the first set of the components, wherein the at least one common parameter is at least one of the characteristic affecting load recorded during operation, and the geographical site data of the rotary machines;
• store the at least one common parameter as a new profile template of a plurality of profile templates, the profile templates each including at least one parameter derivable from the machine data set that has been determined to be of interest in relation to determining causes of pre-identified conditions occurring in components of the plurality of rotary machines;
• identify at least one of the rotary machines having a respective machine data set matching the new profile template;
• identify, in the component database, a second set of the components associated with the at least one rotary machine, wherein a second of the pre-identified conditions is common to each of the components of the second set of the components;
• and
• report the at least one common parameter as a potential cause of the first pre-identified condition, and as a potential cause of the second pre-identified condition associated with the second set of the components.