CN-122026617-A - Fault early warning monitoring method and system for auxiliary holographic sensing of transformer substation

CN122026617ACN 122026617 ACN122026617 ACN 122026617ACN-122026617-A

Abstract

The invention provides a fault early warning monitoring method and system for auxiliary holographic sensing of a transformer substation, and relates to the technical field of fault early warning monitoring. Holographic data acquisition is realized by arranging multiple types of sensors, heterogeneous data are standardized into multidimensional abnormal components, then intrinsic association and deterioration effects among multiple parameters in equipment are deeply excavated by constructing equipment area abnormal coupling characteristic parameters, a neighborhood abnormal influence coefficient is calculated by combining space relative distances among the equipment to quantify space propagation risks of faults, a holographic association characteristic parameter is finally obtained by combining self coupling states and neighborhood influences, and a fault evolution index representing the deterioration trend is further calculated by combining abnormal change rates at historical moments to carry out dynamic threshold comparison, so that the technical effects of early discovery, accurate positioning, trend prejudgment and dynamic early warning of faults of substation equipment are achieved.

Inventors

LI DONGTAO

Assignees

武汉光谷瑞源智能技术有限公司

Dates

Publication Date: 20260512
Application Date: 20260415

Claims (10)

1. The fault early warning and monitoring method for auxiliary holographic sensing of the transformer substation is characterized by comprising the following steps of: Step S1, constructing a substation equipment area set, and arranging a temperature and humidity sensor, an infrared thermal image acquisition device, an acoustic acquisition device and a partial discharge monitoring node in the substation equipment area; Step S2, constructing a data acquisition time sequence, namely constructing an average temperature abnormal component, an average humidity abnormal component, a thermal image abnormal component, an average acoustic abnormal component and a partial discharge abnormal component; Step S3, calculating the abnormal coupling characteristic parameters of the equipment area of the transformer substation equipment at the data acquisition time point, calculating the space relative distance between any two pieces of equipment, and calculating the neighborhood abnormal influence coefficient of the transformer substation equipment area at the data acquisition time point based on the abnormal coupling characteristic parameters of the equipment area and the space relative distance; And step S4, calculating holographic associated characteristic parameters and fault evolution indexes of the substation equipment area at the data acquisition time point, presetting a threshold value, marking the substation equipment area as a fault early warning area if the fault evolution indexes are greater than or equal to the threshold value, and performing active fault early warning monitoring.
2. The substation-oriented auxiliary holographic sensing fault early warning monitoring method according to claim 1, wherein the specific implementation process of the step S1 comprises the following steps: acquiring a substation equipment layout, dividing a substation area into a plurality of substation equipment areas based on the substation equipment layout, wherein one substation equipment area comprises one equipment, constructing a substation equipment area set, and recording as , wherein, Representing an a-th substation equipment area, wherein A represents the total number of the substation equipment areas; In the substation equipment area Temperature and humidity sensors, infrared thermal image acquisition devices, acoustic acquisition devices and partial discharge monitoring nodes are arranged in the transformer substation equipment area, wherein the infrared thermal image acquisition devices and the partial discharge monitoring nodes are arranged in the transformer substation equipment area On the equipment in the transformer substation, an infrared thermal image acquisition device and a partial discharge monitoring node are correspondingly arranged on one equipment, and a temperature and humidity sensor and an acoustic acquisition device are arranged in the transformer substation equipment area And at least one temperature and humidity sensor and an acoustic acquisition device are arranged in one substation equipment area.
3. The substation-oriented auxiliary holographic sensing fault early warning monitoring method according to claim 2, wherein the specific implementation process of the step S2 comprises the following steps: constructing a data acquisition time sequence, which is recorded as , wherein, Indicating the ith data acquisition time point, wherein I indicates the total number of the data acquisition time points, and acquiring the data acquisition time points Substation equipment area of collection down Average temperature data, average humidity data, thermographic temperature rise distribution data, average acoustic spectrum data, and partial discharge pulse data, respectively, and are respectively noted as And ; Constructing a data acquisition time point according to historical normal operation data and factory parameters of the equipment Lower substation equipment area The average temperature data reference value, the average humidity data reference value, the thermal image temperature rise distribution data reference value, the average acoustic spectrum data reference value and the partial discharge pulse data reference value of the temperature sensor are respectively calculated to deviate from the reference value, and Min-Max normalization operation is carried out based on historical data statistics to obtain an average temperature abnormal component Abnormal component of average humidity Abnormal thermal image component Average acoustic anomaly component Abnormal component of partial discharge 。
4. The substation-oriented auxiliary holographic sensing fault early warning monitoring method according to claim 3, wherein the specific implementation process of the step S3 includes: Based on substation equipment area Average temperature anomaly component of (2) Abnormal component of average humidity Abnormal thermal image component Average acoustic anomaly component Abnormal component of partial discharge Calculating a data acquisition time point Lower substation equipment area The equipment region abnormal coupling characteristic parameters are calculated according to the following formula: ; Wherein, the Representing data acquisition time points Lower substation equipment area Is characterized by an abnormal coupling characteristic parameter of the equipment region, And Respectively represent preset average temperature anomaly components Abnormal thermal image component Average acoustic anomaly component Partial discharge anomaly component And an average humidity anomaly component Is a factor of influence of (1); Based on the substation equipment layout diagram, the spatial positions of all equipment in the substation are obtained, the spatial relative distance between any two pieces of equipment is calculated, and the substation equipment area is formed With substation equipment area The relative distance between the spaces is recorded as ; Based on data acquisition time points Lower substation equipment area Is a device region abnormal coupling characteristic parameter And substation equipment area With substation equipment area Relative distance of space between Calculating a data acquisition time point Lower substation equipment area The neighborhood anomaly impact coefficient of (2) is calculated as follows: ; Wherein, the Representing data acquisition time points Lower substation equipment area Is used to determine the neighborhood anomaly impact coefficient of (c), Representing data acquisition time points Lower substation equipment area Is used for the abnormal coupling characteristic parameters of the equipment area.
5. The substation-oriented auxiliary holographic sensing fault early warning monitoring method according to claim 4, wherein the specific implementation process of step S4 includes: Based on data acquisition time points Lower substation equipment area Is a device region abnormal coupling characteristic parameter And data acquisition time point Lower substation equipment area Neighborhood anomaly impact coefficient of (2) Calculating a data acquisition time point Lower substation equipment area The calculation formula of the holographic associated characteristic parameter is as follows: ; Wherein, the Representing data acquisition time points Lower substation equipment area Is characterized by holographic association of characteristic parameters; Based on data acquisition time points Lower substation equipment area Is related to characteristic parameters by hologram Calculating substation equipment area At the time point of data acquisition The following fault evolution index is calculated according to the following formula: ; Wherein, the Representing substation equipment area At the time point of data acquisition The lower failure evolution index is set up in the following, Representing data acquisition time points Lower substation equipment area Is characterized by an abnormal coupling characteristic parameter of the equipment region, And Respectively representing preset weight factors; presetting a fault evolution index threshold value, and recording as If the transformer substation equipment area At the time point of data acquisition Under failure evolution index Greater than or equal to the fault evolution index threshold Then determine the substation equipment area At the time point of data acquisition If the fault exists, marking the transformer substation equipment area Is a fault early warning area; And acquiring the fault evolution index of the substation equipment area at each data acquisition time point in real time, and carrying out dynamic fault early warning monitoring.
6. The fault early warning monitoring system for substation auxiliary holographic perception is characterized by comprising a set construction and sensor layout module, an abnormal component calculation module, a characteristic parameter calculation and influence coefficient calculation module and an index calculation and analysis early warning module; The assembly construction and sensor layout module is used for constructing a substation equipment area assembly and laying a temperature and humidity sensor, an infrared thermal image acquisition device, an acoustic acquisition device and a partial discharge monitoring node in the substation equipment area; The abnormal component calculation module is used for constructing a data acquisition time sequence, and constructing an average temperature abnormal component, an average humidity abnormal component, a thermal image abnormal component, an average acoustic abnormal component and a partial discharge abnormal component; The characteristic parameter calculation and influence coefficient calculation module is used for calculating the abnormal coupling characteristic parameters of the equipment area of the transformer substation equipment at the data acquisition time point, calculating the space relative distance between any two pieces of equipment, and calculating the neighborhood abnormal influence coefficient of the transformer substation equipment area at the data acquisition time point based on the abnormal coupling characteristic parameters of the equipment area and the space relative distance; The index calculation and analysis early warning module is used for calculating holographic association characteristic parameters and fault evolution indexes of the substation equipment area at the data acquisition time point, presetting a threshold value, marking the substation equipment area as a fault early warning area if the fault evolution indexes are larger than or equal to the threshold value, and performing active fault early warning monitoring.
7. The substation-oriented auxiliary holographic-sensing fault early warning monitoring system according to claim 6, wherein the aggregate construction and sensor layout module comprises an aggregate construction unit and a sensor layout unit; The collection construction unit is used for acquiring a substation equipment layout diagram, dividing a substation area into a plurality of substation equipment areas based on the substation equipment layout diagram, wherein one substation equipment area comprises one device, and constructing a substation equipment area collection; The sensor layout unit is used for layout of a temperature and humidity sensor, an infrared thermal image acquisition device, an acoustic acquisition device and partial discharge monitoring nodes in a transformer substation equipment area, wherein the infrared thermal image acquisition device and the partial discharge monitoring nodes are laid on equipment in the transformer substation equipment area, one piece of equipment is correspondingly laid with the infrared thermal image acquisition device and the partial discharge monitoring nodes, the temperature and humidity sensor and the acoustic acquisition device are laid in the transformer substation equipment area, and one transformer substation equipment area is laid with at least one temperature and humidity sensor and one acoustic acquisition device.
8. The substation-oriented auxiliary holographic-sensing fault early warning monitoring system according to claim 6, wherein the abnormal component calculation module comprises an abnormal component calculation unit; The abnormal component calculation unit is used for constructing a data acquisition time sequence, acquiring average temperature data, average humidity data, thermal image temperature rise distribution data, average acoustic spectrum data and partial discharge pulse data of a transformer substation equipment area acquired at a data acquisition time point, constructing an average temperature data reference value, an average humidity data reference value, a thermal image temperature rise distribution data reference value, an average acoustic spectrum data reference value and a partial discharge pulse data reference value of the transformer substation equipment area at the data acquisition time point according to historical normal operation data and factory parameters of the equipment, respectively calculating a reference value deviation degree, and carrying out Min-Max normalization operation based on historical data statistics to obtain an average temperature abnormal component, an average humidity abnormal component, a thermal image abnormal component, an average acoustic abnormal component and a partial discharge abnormal component.
9. The substation-oriented auxiliary holographic-sensing fault early warning monitoring system according to claim 6, wherein the characteristic parameter calculation and influence coefficient calculation module comprises a characteristic parameter calculation unit and an influence coefficient calculation unit; The characteristic parameter calculation unit is used for calculating the abnormal coupling characteristic parameters of the equipment area of the transformer substation equipment area at the data acquisition time point based on the average temperature abnormal component, the average humidity abnormal component, the thermal image abnormal component, the average acoustic abnormal component and the partial discharge abnormal component of the transformer substation equipment area; The influence coefficient calculation unit is used for acquiring the spatial positions of all equipment in the transformer substation based on the transformer substation equipment layout, calculating the spatial relative distance between any two equipment, and calculating the neighborhood abnormal influence coefficient of the transformer substation equipment area at the data acquisition time point based on the equipment area abnormal coupling characteristic parameters of the transformer substation equipment area at the data acquisition time point and the spatial relative distance between the transformer substation equipment area.
10. The substation-oriented auxiliary holographic-sensing fault early-warning monitoring system according to claim 6, wherein the index calculation and analysis early-warning module comprises an index calculation unit and an analysis early-warning unit; the index calculation unit is used for calculating holographic association characteristic parameters of the transformer substation equipment area at the data acquisition time point based on the equipment area abnormal coupling characteristic parameters of the transformer substation equipment area at the data acquisition time point and the neighborhood abnormal influence coefficients of the transformer substation equipment area at the data acquisition time point; The analysis early warning unit is used for presetting a fault evolution index threshold, judging that the substation equipment area has faults at the data acquisition time points if the fault evolution index of the substation equipment area at the data acquisition time points is larger than or equal to the fault evolution index threshold, marking the substation equipment area as a fault early warning area, and acquiring the fault evolution index of the substation equipment area at each data acquisition time point in real time to perform dynamic fault early warning monitoring.

Description

Fault early warning monitoring method and system for auxiliary holographic sensing of transformer substation Technical Field The invention relates to the technical field of fault early warning monitoring, in particular to a fault early warning monitoring method and system for auxiliary holographic sensing of a transformer substation. Background In recent years, the ideas of state maintenance and intelligent operation and maintenance gradually replace the traditional periodic maintenance mode, and become the main stream development direction of substation equipment management. To achieve this goal, substation auxiliary monitoring systems have undergone an evolution from single parameter monitoring to multi-source information fusion. Early times mainly rely on SCADA systems to collect electrical quantities (e.g., current, voltage) for threshold alarms, but this approach is difficult to find latent, progressive insulation degradation or mechanical failure. Then, an infrared thermal imaging technology, a partial discharge detection technology, an acoustic imaging technology and a temperature and humidity environment monitoring technology are sequentially introduced, and the state of the equipment is sensed from the dimensions of a thermal state, a discharge state, a sound wave spectrum, environmental stress and the like. However, at present, most monitoring systems of transformer substations are still in the stage of 'multi-system coexistence and data island', namely, various sensors are independently collected, independently analyzed and independently alarmed, and deep fusion and associated mining of multi-physical field information are lacking. Although the prior art realizes on-line monitoring of the state of substation equipment to a certain extent, significant shortages still exist in practical application. Firstly, in the perception dimension, the current scheme is mostly focused on threshold judgment of a single physical quantity, for example, whether the partial discharge amplitude exceeds the standard or whether the hot spot temperature exceeds the limit is only focused, and the coupling effect among multidimensional abnormal components such as humidity, temperature rise, acoustic frequency spectrum, discharge pulse and the like cannot be fully considered. For example, the high humidity environment can obviously aggravate the creeping discharge of the insulating surface, and simply analyzing the partial discharge amplitude change is easy to generate a missing report or a false report due to improper setting of a threshold value. Secondly, in terms of spatial correlation, the existing method often regards each device as an independent individual for monitoring, and ignores the propagation characteristics of faults in space. For example, an overheat fault of a certain circuit breaker may cause an increase in contact resistance of an adjacent isolating switch, so as to cause a cascading failure, but a traditional point-to-point monitoring manner cannot effectively capture a propagation rule of such a neighborhood abnormal influence. Finally, in the dynamic evolution level, the prior art mostly adopts a static threshold value to carry out fault judgment, lacks quantitative description of the time evolution trend of the abnormal state, and is difficult to send out early warning in the fault germination stage, so that operation and maintenance personnel can respond passively after an accident happens. Disclosure of Invention The invention aims to provide a fault early warning monitoring method and system for auxiliary holographic perception of a transformer substation, which are used for solving the technical problems that the monitoring data source is single, multi-source information is isolated and difficult to fuse, early warning is delayed and the false alarm rate is high due to the fact that the single parameter threshold value is only relied on for warning, the inherent coupling effect among multiple parameters of equipment and the propagation influence of faults in space cannot be quantified, and the evolution trend of the faults is more difficult to foresight prejudge in the traditional transformer substation monitoring method. In view of the technical problems, the invention provides a fault early warning and monitoring method and system for auxiliary holographic sensing of a transformer substation. The invention provides a fault early warning monitoring method for auxiliary holographic perception of a transformer substation, which comprises the steps of S1, constructing a transformer substation equipment area set, arranging a temperature and humidity sensor, an infrared thermal image acquisition device, an acoustic acquisition device and a partial discharge monitoring node in the transformer substation equipment area, S2, constructing a data acquisition time sequence, constructing an average temperature abnormal component, an average humidity abnormal component, a thermal image abnormal component,