CN-122028085-A - Fault determination method, device, electronic equipment, storage medium and product

CN122028085ACN 122028085 ACN122028085 ACN 122028085ACN-122028085-A

Abstract

The disclosure provides a fault determination method, a fault determination device, electronic equipment, a storage medium and a product. The method comprises the steps of obtaining first network coverage quality data of each space unit in a plurality of space units, carrying out iterative training on a network quality prediction model based on the first network coverage quality data to obtain a network quality assessment model, obtaining second network coverage quality data of each space unit in the plurality of space units, determining a network quality assessment result corresponding to each space unit by utilizing the network quality assessment model, and determining fault information in the plurality of space units based on the network quality assessment result, so that hidden faults can be actively found, and the accuracy of fault location is improved.

Inventors

ZHAO YIKANG
YAO QILING
SUN CHEN
MA JIANHUI
YANG YUNFENG

Assignees

中国移动通信集团设计院有限公司
中国移动通信集团有限公司

Dates

Publication Date: 20260512
Application Date: 20251219

Claims (10)

1. A fault determination method, comprising: acquiring first network coverage quality data of each space unit in a plurality of space units; performing iterative training on a network quality prediction model based on the first network coverage quality data to obtain a network quality assessment model; Acquiring second network coverage quality data of each space unit in the plurality of space units, and determining a network quality evaluation result corresponding to each space unit by using the network quality evaluation model; Based on the network quality assessment results, fault information in the plurality of spatial units is determined.
2. The method of claim 1, wherein the obtaining the first network coverage quality data for each of the plurality of spatial units comprises: acquiring original network coverage quality data in a target building space; Dividing the target building space into a plurality of space units according to a preset size; First network coverage quality data for each spatial unit is determined based on the original network coverage quality data and the plurality of spatial units.
3. The method of claim 2, wherein the raw network coverage quality data includes at least wireless measurement data, internet data service data, and scalable data detection data.
4. The method of claim 2, wherein the determining the first network coverage quality data for each spatial unit based on the original network coverage quality data and the plurality of spatial units comprises: Acquiring a three-dimensional coordinate range corresponding to each space unit; according to the three-dimensional coordinate range corresponding to each space unit, network coverage quality data in the same space unit is determined from the original network coverage quality data; And carrying out aggregation processing on the network coverage quality data in the same space unit to obtain first network coverage quality data of each space unit.
5. The method of claim 1, wherein the determining fault information in the plurality of spatial units based on the network quality assessment results comprises: acquiring a network state index associated with a fault; determining a plurality of continuous numerical intervals according to the numerical value of the network state index, wherein each numerical interval corresponds to a network quality grade; And comparing the network quality evaluation result with the network quality grade to determine fault information in the plurality of space units.
6. The method of claim 1, wherein iteratively training a network quality prediction model based on the first network coverage quality data to obtain a network quality assessment model comprises: dividing the first network coverage quality data into training data and verification data; performing iterative training on the network quality prediction model by utilizing the training data; verifying the trained network quality prediction model by using the verification data to obtain verification accuracy; And responding to the verification accuracy reaches a preset threshold value to obtain the network quality assessment model.
7. A fault determination apparatus, comprising: an acquisition unit configured to acquire first network coverage quality data of each of a plurality of space units; The training unit is used for carrying out iterative training on the network quality prediction model based on the first network coverage quality data to obtain a network quality evaluation model; The first determining unit is used for acquiring second network coverage quality data of each space unit in the plurality of space units and determining a network quality evaluation result corresponding to each space unit by utilizing the network quality evaluation model; And a second determining unit configured to determine failure information in the plurality of spatial units based on the network quality evaluation result.
8. An electronic device, comprising: at least one processor, and A memory communicatively coupled to the at least one processor, wherein, The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 6.
9. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1 to 6.
10. A computer program product comprising a computer program which, when executed by a processor, implements the method of any one of claims 1 to 6.

Description

Fault determination method, device, electronic equipment, storage medium and product Technical Field The disclosure relates to the field of wireless technologies, and in particular, to a fault determining method, a fault determining device, an electronic device, a storage medium and a product. Background With the continuous expansion of indoor network coverage scale, indoor website has become a core scene of user traffic operation, and the operation quality of the indoor website directly influences network operation public praise and user use perception. In the related fault determination scheme, problems are mainly solved by means of user complaints, performance index degradation, dominant hardware alarms, field touch and the like, hidden faults are subjected to empirical judgment by combining back-end analysis and a large number of front-end tests, problems of lag finding and low fault positioning accuracy exist, and the requirements of efficient operation and maintenance and quality optimization of an indoor network are difficult to meet. Disclosure of Invention The disclosure provides a fault determination method, a fault determination device, an electronic device, a storage medium and a storage product, so as to solve the problems of lag discovery and low fault location accuracy in the related art. An embodiment of a first aspect of the present disclosure proposes a fault determination method, the method comprising: acquiring first network coverage quality data of each space unit in a plurality of space units; performing iterative training on the network quality prediction model based on the first network coverage quality data to obtain a network quality assessment model; acquiring second network coverage quality data of each space unit in the plurality of space units, and determining a network quality evaluation result corresponding to each space unit by using a network quality evaluation model; based on the network quality assessment results, fault information in the plurality of spatial units is determined. In one embodiment, obtaining first network coverage quality data for each of a plurality of spatial units comprises: acquiring original network coverage quality data in a target building space; dividing a target building space into a plurality of space units according to a preset size; First network coverage quality data for each spatial unit is determined based on the original network coverage quality data and the plurality of spatial units. In one embodiment, the raw network coverage quality data includes at least wireless measurement data, internet data service data, and scalable data detection data. In one embodiment, determining first network coverage quality data for each spatial unit based on the original network coverage quality data and the plurality of spatial units comprises: Acquiring a three-dimensional coordinate range corresponding to each space unit; According to the three-dimensional coordinate range corresponding to each space unit, determining network coverage quality data in the same space unit from the original network coverage quality data; And carrying out aggregation processing on the network coverage quality data in the same space unit to obtain first network coverage quality data of each space unit. In one embodiment, determining fault information in a plurality of spatial units based on network quality assessment results includes: acquiring a network state index associated with a fault; determining a plurality of continuous numerical intervals according to the numerical value of the network state index, wherein each numerical interval corresponds to a network quality grade; and comparing the network quality evaluation result with the network quality grade to determine fault information in the plurality of space units. In an embodiment, based on the first network coverage quality data, performing iterative training on the network quality prediction model to obtain a network quality assessment model, including: Dividing the first network coverage quality data into training data and verification data; performing iterative training on the network quality prediction model by using training data; verifying the trained network quality prediction model by using verification data to obtain verification accuracy; And responding to the verification accuracy reaching a preset threshold value to obtain a network quality evaluation model. An embodiment of a second aspect of the present disclosure proposes a failure determination apparatus, the apparatus comprising: an acquisition unit configured to acquire first network coverage quality data of each of a plurality of space units; the training unit is used for carrying out iterative training on the network quality prediction model based on the first network coverage quality data to obtain a network quality evaluation model; the first determining unit is used for acquiring second network coverage quality data of each space unit in the