Cable joint defect monitoring system and method based on voiceprint database

Abstract

The embodiment of the invention discloses a cable joint defect monitoring system and method based on a voiceprint database, and the method comprises the steps: receiving an uploaded sound signal for monitoring a cable joint, and obtaining cable operation parameter data associated with the sound signal, the cable operation parameter data comprising a plurality of cable operation parameters and corresponding parameter values, processing the sound signal to obtain voiceprint data to be compared, querying a preset voiceprint database based on the parameter values of the plurality of cable operation parameters to obtain corresponding voiceprint comparison data, comparing the voiceprint data to be compared with the voiceprint comparison data to obtain difference data, obtaining each preset defect type and corresponding voiceprint influence data, and comparing the preset defect types with the voiceprint influence data. And performing matching processing on the basis of the difference data and the voiceprint influence data corresponding to each preset defect type to obtain a defect type and a defect level. According to the scheme, the defect condition of the cable joint is determined through the sound signal at the cable joint, and the defect monitoring of the cable joint can be accurately carried out from the sound signal dimension.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of cable monitoring technology, and in particular to a cable joint defect monitoring system and method based on a voiceprint database. Background Art

[0002] During the operation of the cable, hidden cable defects will gradually expand, causing the insulation performance of the cable to gradually decrease, and eventually causing major accidents. Cable joint failure is the main cause of frequent cable failures. The cable joint is the connection point between the various sections of the cable line, which is used to ensure that the cable forms a continuous circuit. Its main function is to make the line unobstructed, keep the cable sealed, and ensure the insulation level at the cable joint to ensure the safe and reliable operation of the cable. If the cable joint fails, it will not only affect the normal use of the cable, but may also cause serious consequences such as wire fires and electrical accidents. Therefore, monitoring cable joint defects is crucial.

[0003] In the related technologies, most of them collect the partial discharge signal of the cable joint and generate the partial discharge spectrum, and then detect the generated partial discharge spectrum to determine whether the cable joint has defects. There is a lack of reasonable monitoring methods for cable joint defects under other reference dimensions. Summary of the invention

[0004] The embodiments of the present invention provide a cable joint defect monitoring system and method based on a voiceprint database, which solves the problem of the lack of a reasonable monitoring method for cable joint defects under other reference dimensions in the related art, and can accurately monitor the defects of cable joints from the sound signal dimension.

[0005] In a first aspect, an embodiment of the present invention provides a method for monitoring cable joint defects based on a voiceprint database, comprising:

[0006] Receive a sound signal for monitoring a cable joint uploaded by a sound signal acquisition device, and obtain cable operation parameter data associated with the sound signal, wherein the cable operation parameter data includes a plurality of cable operation parameters and corresponding parameter values;

[0007] The sound signal is processed to obtain voiceprint data to be compared, a preset voiceprint database is queried based on the parameter values ​​of the plurality of cable operation parameters to obtain corresponding voiceprint comparison data, and the voiceprint data to be compared is compared with the voiceprint comparison data to obtain difference data;

[0008] Each preset defect type and the corresponding voiceprint impact data are obtained, and matching processing is performed based on the difference data and the voiceprint impact data corresponding to each preset defect type to obtain the defect type and defect level.

[0009] Optionally, the voiceprint data to be compared includes the feature values ​​to be compared of each voiceprint feature parameter, and the voiceprint comparison data includes the feature comparison values ​​of each voiceprint feature parameter. Accordingly, the voiceprint data to be compared is compared with the voiceprint comparison data to obtain the difference data, including:

[0010] The feature values ​​to be compared of each voiceprint feature parameter in the voiceprint data to be compared are compared with the corresponding feature comparison values, and the difference data is determined according to the comparison results corresponding to each voiceprint feature parameter.

[0011] Optionally, the comparison result includes a difference value and a difference direction, and the determining of difference data according to the comparison results corresponding to each of the voiceprint feature parameters includes:

[0012] The difference values ​​corresponding to each of the voiceprint feature parameters are compared with the corresponding preset comparison values ​​respectively. When the difference values ​​of the voiceprint feature parameters are greater than the corresponding preset comparison values, the voiceprint feature parameters are determined as difference voiceprint feature parameters, and the difference voiceprint feature parameters and the corresponding difference values ​​and difference directions are combined into difference data.

[0013] Optionally, the difference data includes difference voiceprint feature parameters and corresponding difference values ​​and difference directions, and the matching process based on the difference data and the voiceprint impact data corresponding to each of the preset defect types to obtain the defect type and defect level includes:

[0014] Based on the difference voiceprint feature parameters and the corresponding difference direction, each voiceprint influence data is matched to obtain the defect type, the preset evaluation standard of the defect type is obtained, and the defect level is determined according to the difference and the preset evaluation standard.

[0015] Optionally, the voiceprint influencing data includes influencing voiceprint feature parameters and influencing directions, and the defect types are obtained by matching the difference voiceprint feature parameters and the corresponding difference directions with each voiceprint influencing data, including:

[0016] The difference voiceprint feature parameters are matched with the influencing voiceprint feature parameters in each of the voiceprint influencing data, and the difference direction is matched with the influencing direction in each of the voiceprint influencing data. When the influencing voiceprint feature parameters and the influencing direction are matched successfully, the corresponding preset defect type is determined as the defect type of the monitoring cable joint.

[0017] Optionally, the preset evaluation standard includes a plurality of preset comparison value intervals of defect levels, and determining the defect level according to the difference and the preset evaluation standard includes:

[0018] When there are multiple differential voiceprint feature parameters, a comprehensive reference value is calculated according to the difference between the differential voiceprint feature parameters and a preset comprehensive evaluation method, the comparison value interval into which the comprehensive reference value falls is determined, and the preset defect level corresponding to the comparison value interval is determined as the defect level of the monitoring cable joint.

[0019] Optionally, the calculating of the comprehensive reference value according to the difference of each of the difference voiceprint feature parameters and a preset comprehensive evaluation method includes:

[0020] According to the difference values ​​of each of the difference voiceprint feature parameters, the corresponding preset defect assessment value mapping table is queried to obtain multiple defect assessment values, and each defect assessment value is multiplied by the preset weight of the corresponding difference voiceprint feature parameter and superimposed to obtain a comprehensive reference value.

[0021] In a second aspect, an embodiment of the present invention further provides a cable joint defect monitoring system based on a voiceprint database, comprising:

[0022] A receiving module, used to receive the sound signal of the monitoring cable joint uploaded by the sound signal acquisition device;

[0023] An acquisition module, used for acquiring cable operation parameter data associated with the sound signal, wherein the cable operation parameter data includes a plurality of cable operation parameters and corresponding parameter values;

[0024] A signal processing module, used for processing the sound signal to obtain voiceprint data to be compared;

[0025] A query module, used for querying a preset voiceprint database based on the parameter values ​​of a plurality of the cable operation parameters to obtain corresponding voiceprint comparison data;

[0026] A comparison processing module, used for comparing the voiceprint data to be compared with the voiceprint comparison data to obtain difference data;

[0027] The acquisition module is further used to acquire each preset defect type and corresponding voiceprint impact data;

[0028] A matching processing module is used to perform matching processing based on the difference data and the voiceprint impact data corresponding to each of the preset defect types to obtain the defect type and defect level.

[0029] In a third aspect, an embodiment of the present invention further provides a cable joint defect monitoring device based on a voiceprint database, the device comprising:

[0030] one or more processors;

[0031] a storage device for storing one or more programs,

[0032] When the one or more programs are executed by the one or more processors, the one or more processors implement a cable joint defect monitoring method based on a voiceprint database according to an embodiment of the present invention.

[0033] In a fourth aspect, an embodiment of the present invention further provides a storage medium storing computer executable instructions, which, when executed by a computer processor, are used to execute a cable joint defect monitoring method based on a voiceprint database described in an embodiment of the present invention.

[0034] In an embodiment of the present invention, a sound signal for monitoring a cable joint uploaded by a sound signal acquisition device is received, and cable operation parameter data associated with the sound signal is obtained, the cable operation parameter data including a plurality of cable operation parameters and corresponding parameter values, the sound signal is processed to obtain voiceprint data to be compared, a preset voiceprint database is queried based on the parameter values ​​of a plurality of cable operation parameters to obtain corresponding voiceprint comparison data, the voiceprint data to be compared is compared with the voiceprint comparison data to obtain difference data, each preset defect type and the corresponding voiceprint impact data are obtained, and matching is performed based on the difference data and the voiceprint impact data corresponding to each preset defect type to obtain the defect type and defect level. This scheme determines the defect condition of the cable joint through the sound signal at the cable joint, solves the problem of the lack of a reasonable monitoring method for cable joint defects under other reference dimensions in the related art, and can accurately monitor the defects of the cable joint from the sound signal dimension. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A flow chart of a cable joint defect monitoring method based on a voiceprint database provided by an embodiment of the present invention;

[0036] Figure 2 A flowchart of another cable joint defect monitoring method based on a voiceprint database provided by an embodiment of the present invention;

[0037] Figure 3 A flowchart of another cable joint defect monitoring method based on a voiceprint database provided by an embodiment of the present invention;

[0038] Figure 4 A module structure block diagram of a cable joint defect monitoring system based on a voiceprint database provided by an embodiment of the present invention;

[0039] Figure 5 A schematic structural diagram of a cable joint defect monitoring device based on a voiceprint database provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0040] The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the embodiments of the present invention, rather than to limit the embodiments of the present invention. It is also necessary to explain that, for ease of description, only parts related to the embodiments of the present invention are shown in the accompanying drawings, rather than all structures.

[0041] The terms "first", "second", etc. in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are generally of one type, and the number of objects is not limited. For example, the first object can be one or more. In addition, "and or or" in the specification and claims represents at least one of the connected objects, and the character "or" generally indicates that the objects associated before and after are in an "or" relationship.

[0042] The embodiment of the present application provides a method for monitoring cable joint defects based on a voiceprint database, which can be applied to monitoring cable joint defects. The embodiment of the present application provides a method for monitoring cable joint defects based on a voiceprint database, and the execution subject of each step can be a computer device, which refers to any electronic device with data calculation, processing and storage capabilities, such as mobile phones, PCs (Personal Computers), tablet computers and other terminal devices, and can also be servers and other devices, which are not limited in the embodiment of the present application.

[0043] Figure 1 A flow chart of a cable joint defect monitoring method based on a voiceprint database provided by an embodiment of the present invention, such as Figure 1 As shown, specifically including:

[0044] Step S101: receiving a sound signal for monitoring a cable joint uploaded by a sound signal acquisition device, and obtaining cable operation parameter data associated with the sound signal, wherein the cable operation parameter data includes a plurality of cable operation parameters and corresponding parameter values.

[0045] Among them, the sound signal acquisition device can be a device for collecting sound signals at cable joints. Monitoring cable joints is used to characterize the cable joints currently in the monitoring state. Cable operation parameter data can be collection data of a series of parameters that describe the performance and function of the cable and are associated with the sound signal, such as current, voltage, joint temperature and other parameters. An exemplary example can be to receive the sound signal of the monitoring cable joint a uploaded by the sound signal acquisition device A, and obtain the cable operation parameter data associated with the sound signal including the voltage of 330V, the current of 5A, and the joint temperature of 40 degrees Celsius.

[0046] Step S102: Process the sound signal to obtain voiceprint data to be compared, query a preset voiceprint database based on parameter values ​​of multiple cable operation parameters to obtain corresponding voiceprint comparison data, and compare the voiceprint data to be compared with the voiceprint comparison data to obtain difference data.

[0047] The voiceprint data to be compared may be voiceprint feature data of a sound signal to be compared. The preset voiceprint database may be a pre-set database that records voiceprint comparison data corresponding to a plurality of different cable operation parameter data. The voiceprint comparison data may be voiceprint feature data used for comparison processing. The difference data may be data related to the difference between the voiceprint data to be compared and the voiceprint comparison data. In one embodiment, the sound signal is preprocessed to remove noise and interference, and voiceprint features are extracted from the sound signal according to a preset voiceprint feature extraction method to obtain the voiceprint data to be compared. The preset voiceprint database is queried for voiceprint comparison data corresponding to the pre-stored cable operation parameter data that is the same as the cable operation parameter data, and the voiceprint data to be compared and the voiceprint comparison data are input into a trained difference comparison model for comparison processing to obtain difference data. Optionally, the voiceprint data to be compared includes the feature values ​​to be compared of each voiceprint feature parameter, and the voiceprint comparison data includes the feature comparison values ​​of each voiceprint feature parameter. A method for determining the difference data may be to compare the feature values ​​to be compared of each voiceprint feature parameter in the voiceprint data to be compared with the corresponding feature comparison values, and determine the difference data according to the comparison results corresponding to each voiceprint feature parameter. By comparing the difference data between the voiceprint data to be compared and the voiceprint comparison data, reasonable reference data can be provided for the subsequent determination of cable joint defects.

[0048] Step S103: acquiring each preset defect type and the corresponding voiceprint impact data, and performing matching processing based on the difference data and the voiceprint impact data corresponding to each preset defect type to obtain the defect type and defect level.

[0049] Among them, the preset defect type is used to characterize the possible defect types of each preset cable joint. The voiceprint impact data can be the relevant data of the impact of the defect on the voiceprint at the cable joint. The defect type is used to characterize the defect type that occurs at the cable joint. The defect level is used to characterize the severity of the defect that occurs at the cable joint. In one embodiment, after obtaining each preset defect type and the corresponding voiceprint impact data, each difference data is matched with the voiceprint impact data of each preset defect type. When the difference data matches the voiceprint impact data successfully, the corresponding preset defect type is determined as the defect type of the cable joint, and the defect level comparison table corresponding to the defect type is queried according to the difference data to obtain the defect level of the cable joint. Optionally, the difference data includes difference voiceprint feature parameters and the corresponding difference value and difference direction. A matching processing method can be to match each voiceprint impact data based on the difference voiceprint feature parameters and the corresponding difference direction to obtain the defect type, obtain the preset evaluation standard of the defect type, and determine the defect level according to the difference value and the preset evaluation standard. The defect situation of the cable joint is determined by the matching processing result of the difference data and the impact data of each defect type on the voiceprint, which can improve the rationality and accuracy of the defect situation of the cable joint.

[0050] From the above, it can be known that the sound signal for monitoring the cable joint uploaded by the sound signal acquisition device is received, and the cable operation parameter data associated with the sound signal is obtained. The cable operation parameter data includes multiple cable operation parameters and corresponding parameter values. The sound signal is processed to obtain the voiceprint data to be compared. The preset voiceprint database is queried based on the parameter values ​​of multiple cable operation parameters to obtain the corresponding voiceprint comparison data. The voiceprint data to be compared is compared with the voiceprint comparison data to obtain difference data, and each preset defect type and the corresponding voiceprint impact data are obtained. Matching is performed based on the difference data and the voiceprint impact data corresponding to each preset defect type to obtain the defect type and defect level. This scheme determines the defect status of the cable joint through the sound signal at the cable joint, which solves the problem of the lack of reasonable monitoring methods for cable joint defects under other reference dimensions in the related technology, and can accurately monitor the defects of the cable joint from the sound signal dimension.

[0051] Figure 2 A flowchart of another cable joint defect monitoring method based on a voiceprint database provided by an embodiment of the present invention provides an optional specific method for determining difference data, such as Figure 2 As shown, specifically including:

[0052] Step S201: receiving a sound signal for monitoring a cable joint uploaded by a sound signal acquisition device, and obtaining cable operation parameter data associated with the sound signal, wherein the cable operation parameter data includes a plurality of cable operation parameters and corresponding parameter values.

[0053] Step S202: Process the sound signal to obtain voiceprint data to be compared, and query a preset voiceprint database based on parameter values ​​of a plurality of the cable operation parameters to obtain corresponding voiceprint comparison data.

[0054] Step S203: compare the feature values ​​to be compared of each voiceprint feature parameter in the voiceprint data to be compared with the corresponding feature comparison values, and determine the difference data according to the comparison results corresponding to each voiceprint feature parameter.

[0055] The voiceprint data to be compared includes the feature values ​​to be compared of each voiceprint feature parameter, and the voiceprint comparison data includes the feature comparison values ​​of each voiceprint feature parameter. The voiceprint feature parameter may be a parameter related to each feature of the sound signal, such as a voiceprint feature parameter such as a Mel-frequency cepstral coefficient and a fundamental frequency. Optionally, the comparison result includes a difference and a difference direction. The difference direction may be the direction of change of the feature value to be compared of the voiceprint feature parameter relative to the feature comparison value, which may be an increase or decrease. A method for determining the difference data may be to compare the difference values ​​corresponding to each voiceprint feature parameter with the corresponding preset comparison value. When the difference value of the voiceprint feature parameter is greater than the corresponding preset comparison value, the voiceprint feature parameter is determined as a difference voiceprint feature parameter, and the difference voiceprint feature parameter and the corresponding difference value and difference direction constitute the difference data. An exemplary example may be that the voiceprint feature parameters include linear prediction coefficients, Mel cepstral coefficients, and fundamental frequencies, and the feature values ​​to be compared of the linear prediction coefficients, Mel cepstral coefficients, and fundamental frequencies in the voiceprint data to be compared are respectively compared with the corresponding feature comparison values ​​to obtain respective differences and difference directions, and the differences corresponding to the linear prediction coefficients, Mel cepstral coefficients, and fundamental frequencies are respectively compared with the corresponding preset comparison values, wherein if the difference of the fundamental frequencies is greater than the corresponding preset comparison value, the fundamental frequencies are determined as the difference voiceprint feature parameters, and the fundamental frequencies and the corresponding difference and difference directions are composed of difference data. In another embodiment, the percentage of the difference corresponding to each voiceprint feature parameter to the corresponding preset comparison value is calculated, and each percentage is respectively compared with the preset percentage. When the percentage is greater than the preset percentage, the corresponding voiceprint feature parameter is determined as the difference voiceprint feature parameter, and the difference voiceprint feature parameter and the corresponding difference and difference direction are composed of difference data.

[0056] Step S204: Acquire each preset defect type and the corresponding voiceprint impact data, and perform matching processing based on the difference data and the voiceprint impact data corresponding to each preset defect type to obtain the defect type and defect level.

[0057] As can be seen from the above, after querying the preset voiceprint database based on the parameter values ​​of multiple cable operation parameters to obtain the corresponding voiceprint comparison data, the feature values ​​to be compared of each voiceprint feature parameter in the voiceprint data to be compared are compared with the corresponding feature comparison values, and the difference data is determined according to the comparison results corresponding to each voiceprint feature parameter. This solution can provide reasonable reference data for the subsequent determination of cable joint defects by comparing the difference data between the voiceprint data to be compared and the voiceprint comparison data.

[0058] Figure 3 A flowchart of another cable joint defect monitoring method based on a voiceprint database provided by an embodiment of the present invention provides an optional specific method for determining the defect type and defect level, such as Figure 3 As shown, specifically including:

[0059] Step S301: receiving a sound signal for monitoring a cable joint uploaded by a sound signal acquisition device, and obtaining cable operation parameter data associated with the sound signal, wherein the cable operation parameter data includes a plurality of cable operation parameters and corresponding parameter values.

[0060] Step S302: Process the sound signal to obtain voiceprint data to be compared, query a preset voiceprint database based on parameter values ​​of multiple cable operation parameters to obtain corresponding voiceprint comparison data, and compare the voiceprint data to be compared with the voiceprint comparison data to obtain difference data.

[0061] Step S303, obtaining each preset defect type and the corresponding voiceprint impact data, matching the difference voiceprint feature parameters and the corresponding difference directions with each voiceprint impact data to obtain the defect type, obtaining the preset evaluation standard for the defect type, and determining the defect level according to the difference and the preset evaluation standard.

[0062] Among them, the preset evaluation standard can be a standard data pre-set for evaluating the level of cable joint defects. Optionally, the voiceprint influencing data includes influencing voiceprint characteristic parameters and influencing directions, the influencing voiceprint characteristic parameters can be voiceprint characteristic parameters affected by defects, and the influencing directions can be the direction of change of the value of the defect-affected voiceprint characteristic parameters. A method for determining the defect type can be to match the difference voiceprint characteristic parameters with the influencing voiceprint characteristic parameters in each voiceprint influencing data, and to match the difference direction with the influencing direction in each voiceprint influencing data. When the influencing voiceprint characteristic parameters and the influencing directions are successfully matched, the corresponding preset defect type is determined as the defect type of the monitored cable joint. An exemplary example may be that the preset defect types include preset defect type a, preset defect type b, and preset defect type c. The influencing voiceprint characteristic parameter corresponding to the preset defect type a is the fundamental frequency, and the influencing direction is rising. The influencing voiceprint characteristic parameter corresponding to the preset defect type b is the Mel cepstral coefficient, and the influencing direction is rising. The influencing voiceprint characteristic parameter corresponding to the preset defect type c is the linear prediction coefficient, and the influencing direction is falling. The difference voiceprint characteristic parameter is the fundamental frequency, and the influencing direction is rising. If all of them successfully match the voiceprint influence data of the preset defect type a, then the preset defect type a is determined as the defect type for monitoring the cable joint.

[0063] In one embodiment, the preset evaluation standard includes a comparison value interval of multiple preset defect levels. A method for determining the defect level may be, when there are multiple differential voiceprint feature parameters, calculating the comprehensive reference value according to the difference of each differential voiceprint feature parameter and the preset comprehensive evaluation method, determining the comparison value interval in which the comprehensive reference value falls, and determining the preset defect level corresponding to the comparison value interval as the defect level of the monitored cable joint. Optionally, a method for calculating the comprehensive reference value may be, according to the difference of each differential voiceprint feature parameter, respectively querying the corresponding preset defect assessment value mapping table to obtain multiple defect assessment values, and multiplying each defect assessment value by the preset weight of the corresponding differential voiceprint feature parameter and superimposing them to obtain the comprehensive reference value. An exemplary example may be that the differential voiceprint feature parameters include linear prediction coefficient, Mel cepstral coefficient, and fundamental frequency, and the corresponding preset weights are 0.3, 0.2, and 0.5, respectively. The defect assessment value corresponding to the difference in linear prediction coefficient is 60, the defect assessment value corresponding to the difference in Mel cepstral coefficient is 50, and the defect assessment value corresponding to the difference in fundamental frequency is 40. The comprehensive reference value is 48 (0.3*60+0.2*50+0.5*40). The defect type of the monitored cable joint is defect a. The comparison value interval corresponding to the first defect level of defect a is (0, 30], and the comparison value interval corresponding to the second defect level is ( 30, 60], the comparison value interval corresponding to the third defect level is (60, 80], the comparison value interval corresponding to the fourth defect level is (80, 100], and the comparison value interval in which the comprehensive reference value falls is (30, 60], that is, the defect level of the monitored cable joint is the second defect level. In another embodiment, when there are multiple difference voiceprint feature parameters, the comparison value intervals in which the differences of each difference voiceprint feature parameter fall are determined respectively, and the highest preset defect level among the preset defect levels corresponding to each comparison value interval is determined, and the highest preset defect level is determined as the defect level of the monitored cable joint.

[0064] As can be seen from the above, after obtaining each preset defect type and the corresponding voiceprint impact data, the defect type is obtained by matching the difference voiceprint feature parameters and the corresponding difference direction with each voiceprint impact data, and the preset evaluation standard of the defect type is obtained. The defect level is determined according to the difference and the preset evaluation standard. This solution determines the defect condition of the cable joint through the matching processing results of the difference data and the impact data of each defect type on the voiceprint, which can improve the rationality and accuracy of the defect condition of the cable joint.

[0065] Figure 4This is a module structure diagram of a cable joint defect monitoring system based on a voiceprint database provided by an embodiment of the present invention. The system is used to execute a cable joint defect monitoring method based on a voiceprint database provided by the above embodiment, and has the corresponding functional modules and beneficial effects of the execution method. Figure 4 As shown, the system specifically includes:

[0066] A receiving module 101 is used to receive a sound signal for monitoring a cable joint uploaded by a sound signal acquisition device;

[0067] An acquisition module 102, configured to acquire cable operation parameter data associated with the sound signal, wherein the cable operation parameter data includes a plurality of cable operation parameters and corresponding parameter values;

[0068] The signal processing module 103 is used to process the sound signal to obtain the voiceprint data to be compared;

[0069] A query module 104, configured to query a preset voiceprint database based on the parameter values ​​of the plurality of cable operation parameters to obtain corresponding voiceprint comparison data;

[0070] A comparison processing module 105 is used to compare the voiceprint data to be compared with the voiceprint comparison data to obtain difference data;

[0071] The acquisition module 102 is further used to acquire each preset defect type and corresponding voiceprint impact data;

[0072] The matching processing module 106 is used to perform matching processing based on the difference data and the voiceprint impact data corresponding to each of the preset defect types to obtain the defect type and defect level.

[0073] It can be seen from the above scheme that the sound signal for monitoring the cable joint uploaded by the sound signal acquisition device is received, and the cable operation parameter data associated with the sound signal is obtained. The cable operation parameter data includes multiple cable operation parameters and corresponding parameter values. The sound signal is processed to obtain the voiceprint data to be compared. The preset voiceprint database is queried based on the parameter values ​​of multiple cable operation parameters to obtain the corresponding voiceprint comparison data. The voiceprint data to be compared is compared with the voiceprint comparison data to obtain difference data, and each preset defect type and the corresponding voiceprint impact data are obtained. Matching is performed based on the difference data and the voiceprint impact data corresponding to each preset defect type to obtain the defect type and defect level. This scheme determines the defect status of the cable joint through the sound signal at the cable joint, which solves the problem of the lack of reasonable monitoring methods for cable joint defects under other reference dimensions in the related technology, and can accurately monitor the defects of the cable joint from the sound signal dimension.

[0074] In a possible embodiment, the comparison processing module 105 is specifically used to:

[0075] The feature values ​​to be compared of each voiceprint feature parameter in the voiceprint data to be compared are compared with the corresponding feature comparison values, and the difference data is determined according to the comparison results corresponding to each voiceprint feature parameter.

[0076] In a possible embodiment, the comparison processing module 105 is further used for:

[0077] The difference values ​​corresponding to each of the voiceprint feature parameters are compared with the corresponding preset comparison values ​​respectively. When the difference values ​​of the voiceprint feature parameters are greater than the corresponding preset comparison values, the voiceprint feature parameters are determined as difference voiceprint feature parameters, and the difference voiceprint feature parameters and the corresponding difference values ​​and difference directions are combined into difference data.

[0078] In a possible embodiment, the matching processing module 106 is specifically configured to:

[0079] Based on the difference voiceprint feature parameters and the corresponding difference direction, each voiceprint influence data is matched to obtain the defect type, the preset evaluation standard of the defect type is obtained, and the defect level is determined according to the difference and the preset evaluation standard.

[0080] In a possible embodiment, the matching processing module 106 is further configured to:

[0081] The difference voiceprint feature parameters are matched with the influencing voiceprint feature parameters in each of the voiceprint influencing data, and the difference direction is matched with the influencing direction in each of the voiceprint influencing data. When the influencing voiceprint feature parameters and the influencing direction are matched successfully, the corresponding preset defect type is determined as the defect type of the monitoring cable joint.

[0082] In a possible embodiment, the matching processing module 106 is further configured to:

[0083] When there are multiple differential voiceprint feature parameters, a comprehensive reference value is calculated according to the difference between the differential voiceprint feature parameters and a preset comprehensive evaluation method, the comparison value interval into which the comprehensive reference value falls is determined, and the preset defect level corresponding to the comparison value interval is determined as the defect level of the monitoring cable joint.

[0084] In a possible embodiment, the matching processing module 106 is further configured to:

[0085] According to the difference values ​​of each of the difference voiceprint feature parameters, the corresponding preset defect assessment value mapping table is queried to obtain multiple defect assessment values, and each defect assessment value is multiplied by the preset weight of the corresponding difference voiceprint feature parameter and superimposed to obtain a comprehensive reference value.

[0086] Figure 5 A schematic diagram of the structure of a cable joint defect monitoring device based on a voiceprint database provided by an embodiment of the present invention is shown in FIG. Figure 5 As shown, the device includes a processor 201, a memory 202, an input device 203 and an output device 204; the number of processors 201 in the device can be one or more. Figure 5 A processor 201 is taken as an example; the processor 201, memory 202, input device 203 and output device 204 in the device can be connected by a bus or other means. Figure 5 The example of the connection via bus is taken. The memory 202, as a computer-readable storage medium, can be used to store software programs, computer executable programs and modules, such as program instructions or modules corresponding to a cable joint defect monitoring method based on a voiceprint database in an embodiment of the present invention. The processor 201 executes various functional applications and data processing of the device by running the software programs, instructions and modules stored in the memory 202, that is, realizes the above-mentioned cable joint defect monitoring method based on a voiceprint database. The input device 203 can be used to receive input digital or character information, and generate key signal input related to user settings and function control of the device. The output device 204 may include a display device such as a display screen.

[0087] An embodiment of the present invention further provides a storage medium comprising computer executable instructions, wherein the computer executable instructions are used to execute a cable joint defect monitoring method based on a voiceprint database when executed by a computer processor, the method comprising:

[0088] Receive a sound signal for monitoring a cable joint uploaded by a sound signal acquisition device, and obtain cable operation parameter data associated with the sound signal, wherein the cable operation parameter data includes a plurality of cable operation parameters and corresponding parameter values;

[0089] The sound signal is processed to obtain voiceprint data to be compared, a preset voiceprint database is queried based on the parameter values ​​of the plurality of cable operation parameters to obtain corresponding voiceprint comparison data, and the voiceprint data to be compared is compared with the voiceprint comparison data to obtain difference data;

[0090] Each preset defect type and the corresponding voiceprint impact data are obtained, and matching processing is performed based on the difference data and the voiceprint impact data corresponding to each preset defect type to obtain the defect type and defect level.

[0091] It is worth noting that in the above-mentioned embodiment of the cable joint defect monitoring method system based on voiceprint database, the various units and modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be achieved; in addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the protection scope of the embodiments of the present invention.

[0092] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the embodiments of the present invention are not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the embodiments of the present invention. Therefore, although the embodiments of the present invention are described in more detail through the above embodiments, the embodiments of the present invention are not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the embodiments of the present invention, and the scope of the embodiments of the present invention is determined by the scope of the appended claims.

Claims

1. A cable joint defect monitoring method based on voiceprint database, characterized in that: include: Receive a sound signal for monitoring a cable joint uploaded by a sound signal acquisition device, and obtain cable operation parameter data associated with the sound signal, wherein the cable operation parameter data includes a plurality of cable operation parameters and corresponding parameter values; The sound signal is processed to obtain voiceprint data to be compared, a preset voiceprint database is queried based on the parameter values ​​of the plurality of cable operation parameters to obtain corresponding voiceprint comparison data, and the voiceprint data to be compared is compared with the voiceprint comparison data to obtain difference data; Each preset defect type and the corresponding voiceprint impact data are obtained, and matching processing is performed based on the difference data and the voiceprint impact data corresponding to each preset defect type to obtain the defect type and defect level.

2. The cable joint defect monitoring method based on voiceprint database according to claim 1 is characterized in that: The voiceprint data to be compared includes the feature values ​​to be compared of each voiceprint feature parameter, and the voiceprint comparison data includes the feature comparison values ​​of each voiceprint feature parameter. Correspondingly, the voiceprint data to be compared is compared with the voiceprint comparison data to obtain difference data, including: The feature values ​​to be compared of each voiceprint feature parameter in the voiceprint data to be compared are compared with the corresponding feature comparison values, and the difference data is determined according to the comparison results corresponding to each voiceprint feature parameter.

3. The cable joint defect monitoring method based on voiceprint database according to claim 2 is characterized in that: The comparison result includes a difference value and a difference direction, and the difference data is determined according to the comparison results corresponding to each of the voiceprint feature parameters, including: The difference values ​​corresponding to each of the voiceprint feature parameters are compared with the corresponding preset comparison values ​​respectively. When the difference values ​​of the voiceprint feature parameters are greater than the corresponding preset comparison values, the voiceprint feature parameters are determined as difference voiceprint feature parameters, and the difference voiceprint feature parameters and the corresponding difference values ​​and difference directions are combined into difference data.

4. The cable joint defect monitoring method based on voiceprint database according to any one of claims 1 to 3, characterized in that: The difference data includes difference voiceprint feature parameters and corresponding difference values ​​and difference directions. The matching process based on the difference data and the voiceprint impact data corresponding to each preset defect type to obtain the defect type and defect level includes: Based on the difference voiceprint feature parameters and the corresponding difference direction, each voiceprint influence data is matched to obtain the defect type, the preset evaluation standard of the defect type is obtained, and the defect level is determined according to the difference and the preset evaluation standard.

5. The cable joint defect monitoring method based on voiceprint database according to claim 4 is characterized in that: The voiceprint influencing data includes influencing voiceprint feature parameters and influencing directions, and the defect types are obtained by matching the difference voiceprint feature parameters and the corresponding difference directions with each voiceprint influencing data, including: The difference voiceprint feature parameters are matched with the influencing voiceprint feature parameters in each of the voiceprint influencing data, and the difference direction is matched with the influencing direction in each of the voiceprint influencing data. When the influencing voiceprint feature parameters and the influencing direction are matched successfully, the corresponding preset defect type is determined as the defect type of the monitoring cable joint.

6. The cable joint defect monitoring method based on voiceprint database according to claim 4 is characterized in that: The preset evaluation standard includes a plurality of preset comparison value intervals of defect levels, and the step of determining the defect level according to the difference and the preset evaluation standard includes: When there are multiple differential voiceprint feature parameters, a comprehensive reference value is calculated according to the difference between the differential voiceprint feature parameters and a preset comprehensive evaluation method, the comparison value interval into which the comprehensive reference value falls is determined, and the preset defect level corresponding to the comparison value interval is determined as the defect level of the monitoring cable joint.

7. The cable joint defect monitoring method based on voiceprint database according to claim 6 is characterized in that: The calculating of the comprehensive reference value according to the difference of each of the difference voiceprint characteristic parameters and a preset comprehensive evaluation method includes: According to the difference values ​​of each of the difference voiceprint feature parameters, the corresponding preset defect assessment value mapping table is queried to obtain multiple defect assessment values, and each defect assessment value is multiplied by the preset weight of the corresponding difference voiceprint feature parameter and superimposed to obtain a comprehensive reference value.

8. A cable joint defect monitoring system based on voiceprint database, characterized in that: include: A receiving module, used to receive the sound signal of the monitoring cable joint uploaded by the sound signal acquisition device; An acquisition module, used for acquiring cable operation parameter data associated with the sound signal, wherein the cable operation parameter data includes a plurality of cable operation parameters and corresponding parameter values; A signal processing module, used for processing the sound signal to obtain voiceprint data to be compared; A query module, used for querying a preset voiceprint database based on the parameter values ​​of a plurality of the cable operation parameters to obtain corresponding voiceprint comparison data; A comparison processing module, used for comparing the voiceprint data to be compared with the voiceprint comparison data to obtain difference data; The acquisition module is further used to acquire each preset defect type and corresponding voiceprint impact data; A matching processing module is used to perform matching processing based on the difference data and the voiceprint impact data corresponding to each of the preset defect types to obtain the defect type and defect level.

9. A cable joint defect monitoring device based on a voiceprint database, the device comprising: one or more processors; A storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the cable joint defect monitoring method based on the voiceprint database as described in any one of claims 1-7.

10. A storage medium storing computer executable instructions, wherein the computer executable instructions are used to execute the cable joint defect monitoring method based on voiceprint database as described in any one of claims 1 to 7 when executed by a computer processor.

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