THE PARADIGM OF A DIGITAL IMAGE OF A GEOTECHNICAL OBJECT AS THE BASIS OF AN AUTOMATED WORKSTATION IN THE TASK OF NON-DESTRUCTIVE TESTING (USING THE EXAMPLE OF A MAIN PIPELINE)

The relevance of the work is determined by the automation of monitoring processes of natural and technical systems, not so much in terms of their measurement component, but in terms of interpreting monitoring results in terms of the properties of the desired object. In this work, these are submerged pipeline systems – main oil and gas pipelines, as a special case of geotechnical objects. The goal of developing an automated workstation (AWS) for a specific object is the ultimate parameterization of the interpretation procedure and the unification of the final graphical constructions within the framework of a single digital image of main pipelines. Taking into account the deterministic type of geotechnical object and the objectives of the survey, research methods include, in addition to non-destructive magnetometric testing as a method of obtaining primary data: methods of qualitative and quantitative interpretation of multi-channel magnetometry materials; methods of systematics and graphical display of primary data and the results of their interpretation. Within the framework of approaches generally accepted in the oil and gas industry, the digital image of damaged pipeline sections is based on ideas about the thinning of pipe walls and the stress states associated with thinning zones. The stressed states of the ferromagnetic walls of immersed pipelines form specific responses in an external magnetic field, while the actual thinning of the pipeline walls is detected by contact methods. The results of the surveys are reduced to a system parametrization of magnetometric non-destructive testing data within the framework of the developed automated workplace structure. The content of the conclusions is in the development of the principle for referenceless recognition of risky sections of the pipeline as a fully automated component of diagnostician’s workplace.

automated workplace, contactless diagnostics complex, parameterization, metal magnetic memory method, non-destructive testing, submerged pipeline, qualitative and quantitative interpretation