CN109870621B - Operation judgment method and device - Google Patents
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Abstract
The embodiment of the application provides an operation judgment method and device, and relates to the field of power equipment operation monitoring. The method comprises the following steps: determining a normal operation value of the transformer in the current operation state according to the obtained real-time audio data and preset audio data, wherein the real-time audio data are obtained based on the fact that the transformer generates sound with preset duration in the current operation state, and the preset audio data are obtained based on the fact that the transformer generates sound with preset duration in the normal operation state; judging whether the normal operation value is greater than or equal to a preset normal operation threshold value or not; and if so, judging that the transformer is in a normal operation state. The technical problem that the monitored parameters such as voltage and current can be abnormal only after the transformer is damaged can be solved by detecting the abnormal sound which is originally emitted by the transformer in the running state to judge the running state of the transformer.
Description
Technical Field
The application relates to the technical field of power equipment operation monitoring, in particular to an operation judgment method and device.
Background
The dry-type transformer has the advantages of flame retardancy, safety, convenience in maintenance, small size and the like, and is widely applied to places such as local illumination, high-rise buildings, airports and the like. The dry type transformer comprises a magnetic core and a coil, wherein the magnetic core and the coil are fixed into a whole and can be directly exposed in the air or placed indoors. The wide application of the transformer makes the detection of the operation state of the transformer important to ensure the normal operation of the transformer.
At present, the operation of the transformer is generally monitored by monitoring parameters such as voltage and current of the transformer. However, the transformer is generally damaged to cause abnormality of the monitored voltage and current parameters, for example, a short circuit occurs in one of the three phases of the transformer to cause a phase change of the current or voltage. Therefore, the loss caused by the damage of the transformer cannot be avoided by monitoring parameters such as voltage and current.
Disclosure of Invention
The present application aims to provide an operation judgment method and an operation judgment device to effectively improve the technical defects.
The embodiment of the application is realized by the following steps:
in a first aspect, an embodiment of the present application provides an operation determination method, where the method includes: determining a normal operation value of the transformer in the current operation state according to the obtained real-time audio data and preset audio data, wherein the real-time audio data are obtained based on the fact that the transformer generates sound with preset duration in the current operation state, and the preset audio data are obtained based on the fact that the transformer generates sound with preset duration in the normal operation state; judging whether the normal operation value is greater than or equal to a preset normal operation threshold value or not; and if so, judging that the transformer is in a normal operation state.
With reference to the technical solution provided by the first aspect, in some possible implementation manners, the real-time audio data includes M groups of real-time audio data elements, the preset audio data includes M groups of preset audio data elements, M is a positive integer, and a normal operation value of the transformer in the current operation state is determined according to the obtained real-time audio data and the preset audio data, including: determining N groups of real-time audio data elements in the M groups of real-time audio data elements to form a target real-time audio data group; determining N groups of preset audio data elements in the M groups of preset audio data elements to form a target preset audio data group, wherein N is a positive integer not greater than M; calculating a target operation comparison audio data set according to the target real-time audio data set and the target preset audio data set; and calculating the target operation comparison audio data set according to a first preset calculation formula to obtain a first operation characteristic value, calculating the target operation comparison audio data set according to a second preset calculation formula to obtain a second operation characteristic value, and determining the ratio of the first operation characteristic value to the second operation characteristic value as a normal operation value of the transformer in the current operation state.
With reference to the technical solution provided by the first aspect, in some possible implementation manners, calculating a target operation comparison audio data set according to a target real-time audio data set and a target preset audio data set includes: combining the target real-time audio data set with N preset parameters to obtain a combined target real-time audio data set, and sequentially performing fast Fourier transform and conjugate calculation on the combined target real-time audio data set to obtain a calculated target real-time audio data set; combining the target preset audio data group with the N preset parameters to obtain a combined target preset audio data group, and sequentially performing fast Fourier transform and conjugate calculation on the combined target preset audio data group to obtain a calculated target preset audio data group; and multiplying the calculated target real-time audio data group with the calculated target preset audio data group to obtain an operation comparison audio data group, and then performing fast Fourier inverse transformation on the operation comparison audio data group to obtain a target operation comparison audio data group.
With reference to the technical solution provided by the first aspect, in some possible implementation manners, calculating the target operation comparison audio data set according to a first preset calculation formula to obtain a first operation characteristic value, calculating the target operation comparison audio data set according to a second preset calculation formula to obtain a second operation characteristic value, and determining that a ratio of the first operation characteristic value to the second operation characteristic value is a normal operation value of the transformer in a current operation state includes: selecting a first parameter value with the maximum absolute value from a plurality of parameter values in a target operation contrast audio data set, and multiplying the first parameter value by the number of the plurality of parameter values to obtain a first operation characteristic value; sequentially carrying out absolute value calculation on each parameter value in the plurality of parameter values in the target operation comparison audio data set to obtain each parameter value in the plurality of calculated parameter values, and carrying out summation calculation on each parameter value in the plurality of calculated parameter values to obtain a second operation characteristic value; the ratio of the first operation characteristic value to the second operation characteristic value is a normal operation value of the transformer in the current operation state.
With reference to the technical solution provided in the first aspect, in some possible implementation manners, determining whether the normal operation value is greater than or equal to a preset normal operation threshold includes: if not, determining a second normal operation value of the transformer in the current operation state according to the target real-time audio data set and the target preset audio data set; judging whether the second normal operation value is greater than or equal to a preset normal operation threshold value or not; if so, judging that the transformer is in a normal operation state; if not, adding 1 to the judgment times for judging whether the transformer is in the normal operation state to obtain updated judgment times, stopping judging whether the transformer is in the normal operation state again according to the fact that the updated judgment times meet the preset threshold times, and determining that the transformer is in the abnormal operation state.
With reference to the technical solution provided by the first aspect, in some possible implementation manners, if the target real-time audio data set is not determined to be the current operating state, determining a second normal operating value of the transformer in the current operating state according to the target real-time audio data set and the target preset audio data set, including: equally dividing a target real-time audio data group into X sections of real-time data, and equally dividing a target preset audio data group into X sections of preset data, wherein each section of real-time data in the X sections of real-time data comprises Y real-time audio data elements, each section of preset data in the X sections of preset data comprises Y preset audio data elements, and X and Y are integers more than 1; according to the numerical value represented by the real-time audio data elements, determining the real-time audio data elements with the maximum numerical value from Y real-time audio data elements of each segment of real-time data, and determining X real-time audio data elements with the maximum numerical value; according to the numerical value represented by the preset audio data elements, determining the preset audio data elements with the maximum numerical value from Y preset audio data elements of each section of preset data, and determining X preset audio data elements with the maximum numerical value; averaging all numerical values represented by all real-time audio data elements in the target real-time audio data set to obtain a real-time average value; averaging all numerical values represented by all preset audio data elements in the target preset audio data group to obtain a preset average value; subtracting the real-time average value from each of X numerical values represented by the X real-time audio data elements with the largest numerical value to obtain X real-time audio data elements after difference calculation; subtracting a preset average value from each of X numerical values represented by the X preset audio data elements with the maximum numerical value to obtain X preset audio data elements after the difference is obtained; and determining a second normal operation value of the transformer in the current operation state according to the X real-time audio data elements after the difference is solved and the X preset audio data elements after the difference is solved.
In a second aspect, an embodiment of the present application provides an operation determination apparatus, including: the obtaining device is used for obtaining real-time audio data and preset audio data, wherein the real-time audio data is obtained based on the fact that the transformer generates sound with preset duration in the current operation state, and the preset audio data is obtained based on the fact that the transformer generates sound with preset duration in the normal operation state; the processing module is used for determining a normal operation value of the transformer in the current operation state according to the obtained real-time audio data and the preset audio data; and the judging module is used for judging whether the normal operation value is greater than or equal to a preset normal operation threshold value.
With reference to the technical solution provided by the second aspect, in some possible implementation manners, the real-time audio data includes M groups of real-time audio data elements, the preset audio data includes M groups of preset audio data elements, and M is a positive integer; the processing module is further used for determining that N groups of real-time audio data elements in the M groups of real-time audio data elements form a target real-time audio data group; determining N groups of preset audio data elements in the M groups of preset audio data elements to form a target preset audio data group, wherein N is a positive integer not greater than M; calculating a target operation comparison audio data set according to the target real-time audio data set and the target preset audio data set; and calculating the target operation comparison audio data set according to a first preset calculation formula to obtain a first operation characteristic value, calculating the target operation comparison audio data set according to a second preset calculation formula to obtain a second operation characteristic value, and determining the ratio of the first operation characteristic value to the second operation characteristic value as a normal operation value of the transformer in the current operation state.
In combination with the technical solution provided by the second aspect, in some possible implementation manners, the processing module is further configured to combine the target real-time audio data set with the N preset parameters to obtain a combined target real-time audio data set, and sequentially perform fast fourier transform and conjugate calculation on the combined target real-time audio data set to obtain a calculated target real-time audio data set; combining the target preset audio data group with the N preset parameters to obtain a combined target preset audio data group, and sequentially performing fast Fourier transform and conjugate calculation on the combined target preset audio data group to obtain a calculated target preset audio data group; and multiplying the calculated target real-time audio data group with the calculated target preset audio data group to obtain an operation comparison audio data group, and then performing fast Fourier inverse transformation on the operation comparison audio data group to obtain a target operation comparison audio data group.
With reference to the technical solution provided by the second aspect, in some possible implementations, the apparatus further includes: the counting module is used for determining a second normal operation value of the transformer in the current operation state according to the real-time audio data and the preset audio data when the judging device judges that the normal operation value is smaller than the preset normal operation threshold value; the judging device judges whether the second normal operation value is larger than or equal to a preset normal operation threshold value, if so, the transformer is judged to be in a normal operation state, if not, the counting module adds 1 to the judgment frequency for judging whether the transformer is in the normal operation state to obtain an updated judgment frequency, the judging module judges whether the updated judgment frequency meets the preset threshold frequency, if so, the judgment module stops judging whether the transformer is in the normal operation state again, and the transformer is determined to be in an abnormal operation state.
Compared with the prior art, the embodiment of the application has the beneficial effects that:
the running state of the transformer is judged by detecting the abnormal sound which is originally emitted by the transformer in the running state, the normal running value obtained by analyzing and processing the obtained real-time audio data containing the abnormal sound and the preset audio data in the normal running state is judged, and the relation between the normal running value and the preset normal running threshold value is judged, so that the transformer can be judged to be in the normal running state or the abnormal running state. The technical problem that the monitored parameters such as voltage and current can be abnormal only after the transformer is damaged can be solved by detecting the abnormal sound which is originally emitted by the transformer in the running state to judge the running state of the transformer.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 shows a block diagram of an electronic device according to a first embodiment of the present application;
fig. 2 is a flowchart illustrating an operation determination method according to a second embodiment of the present application;
fig. 3 is a block diagram illustrating an operation determination device according to a third embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. The terms "first," "second," and the like are used solely to distinguish one from another and are not to be construed as indicating or implying relative importance.
First embodiment
The embodiment of the application provides an electronic device 10. The electronic device 10 may be a Personal Computer (PC), a tablet PC, a smart phone, a Personal Digital Assistant (PDA), or the like, or the electronic device 10 may be a web server, a database server, a cloud server, or a server assembly composed of a plurality of sub-servers, or the like.
Referring to fig. 1, the electronic device 10 may include: memory 111, communication module 112, bus 113, and processor 114. Wherein the processor 114, the communication module 112 and the memory 111 are connected by a bus 113. The processor 114 is used to execute executable modules, such as computer programs, stored in the memory 111. The components and configurations of electronic device 10 shown in FIG. 1 are for example, and not for limitation, and electronic device 10 may have other components and configurations as desired.
The Memory 111 may include a high-speed Random Access Memory (Random Access Memory RAM) and may further include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. In the present embodiment, the memory 111 stores the obtained real-time audio data and preset audio data.
The bus 113 may be an ISA bus, PCI bus, EISA bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 1, but this does not indicate only one bus or one type of bus.
The processor 114 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 114. The Processor 114 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; but may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present invention may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art.
The method performed by the apparatus or the plug flow process disclosed in any of the embodiments of the present invention may be applied to the processor 114, or may be implemented by the processor 114. After receiving the response command sent by the electronic device 10, the processor 114 controls the communication module 112 through the bus 113 to complete the judgment of the normal operation value and the preset normal operation threshold value, and determine the operation state of the transformer.
Second embodiment
Referring to fig. 2, a timing flow chart of an operation determination method according to a second embodiment of the present application is provided. The operation judgment method comprises the following steps: step S11, step S12 and step S13.
Step S11: and determining a normal operation value of the transformer in the current operation state according to the obtained real-time audio data and preset audio data, wherein the real-time audio data is obtained based on the fact that the transformer generates sound with preset duration in the current operation state, and the preset audio data is obtained based on the fact that the transformer generates sound with preset duration in the normal operation state.
Step S12: and judging whether the normal operation value is greater than or equal to a preset normal operation threshold value or not.
Step S13: and if so, judging that the transformer is in a normal operation state.
The flow of the operation judgment method will be described in detail below.
Step S11: and determining a normal operation value of the transformer in the current operation state according to the obtained real-time audio data and preset audio data, wherein the real-time audio data is obtained based on the fact that the transformer generates sound with preset duration in the current operation state, and the preset audio data is obtained based on the fact that the transformer generates sound with preset duration in the normal operation state.
The frequency of the sound is various, and the recording time length can be selected according to actual needs. The recorded audio comprises real-time audio in the time waiting state of the running state and preset audio in the normal running state of the transformer, the recorded real-time audio and the preset audio are edited, the time length of the edited real-time audio is the same as that of the preset audio, the real-time audio and the preset audio can be guaranteed to be subjected to subsequent analysis processing, and the edited real-time audio and the preset audio are stored.
The real-time audio data carried by the clipped real-time audio comprises M groups of real-time audio data elements, wherein M is a positive integer, and N groups of real-time audio data elements in the M groups of real-time audio data elements are determined to form a target real-time audio data group, wherein N is a positive integer not greater than M. The preset audio data carried by the preset audio comprises M groups of preset audio data elements, wherein M is a positive integer, and N groups of preset audio data elements in the M groups of preset audio data elements are determined to form a target preset audio data group, wherein N is a positive integer not greater than M.
Specifically, the audio duration corresponding to each real-time audio data element in the M groups of real-time audio data elements is the same as the audio duration corresponding to each preset audio data element in the M groups of preset audio data elements. Therefore, the audio duration corresponding to the target real-time audio data set composed of the N groups of real-time audio data elements is the same as the audio duration corresponding to the target preset audio data set composed of the N groups of preset audio data elements. And the audio time lengths corresponding to the target real-time audio data set and the target preset audio data set are the same, so that the target real-time audio data set and the target preset audio data set can be subjected to subsequent operation, and a normal operation value is obtained.
Selecting N groups of real-time audio data elements from the M groups to form a target real-time audio data group, so that the determined real-time audio data elements have high randomness; similarly, selecting N groups of preset audio data elements from the M groups to form the target preset audio data group can enable the determined preset audio data elements to have high randomness. The normal operation value determined by the target real-time audio data group with strong randomness and the target preset audio data group with strong randomness can be more accurate, and the operation state of the transformer can be more accurately judged.
Calculating a target operation comparison audio data set according to the target real-time audio data set and the target preset audio data set; and calculating the target operation comparison audio data set according to a first preset calculation formula to obtain a first operation characteristic value, calculating the target operation comparison audio data set according to a second preset calculation formula to obtain a second operation characteristic value, and determining the ratio of the first operation characteristic value to the second operation characteristic value as a normal operation value of the transformer in the current operation state.
In detail, calculating the operation comparison audio data set according to the target real-time audio data set and the target preset audio data set comprises: and combining the target real-time audio data set with the N preset parameters to obtain a combined target real-time audio data set, and sequentially performing fast Fourier transform and conjugate calculation on the combined target real-time audio data set to obtain a calculated target real-time audio data set. And combining the target preset audio data group with the N preset parameters to obtain a combined target preset audio data group, and sequentially performing fast Fourier transform and conjugate calculation on the combined target preset audio data group to obtain a calculated target preset audio data group. And sequentially multiplying the calculated target real-time audio data group and the calculated target preset audio data group and performing fast Fourier inverse transformation to obtain a target operation comparison audio data group, wherein the operation comparison audio data group is a group of sequences in a time domain through fast Fourier transformation.
Assume that N sets of real-time audio data elements of the M sets of real-time audio data elements are determined to constitute a target real-time audio data set, where M may be 20 and N may be 7. The 7 real-time audio data elements may be A, B, C, D, E, F, G, and the 7 real-time audio data elements are combined with 7 preset parameters, where the preset parameters may be 0, and the combination results in ABCDEFG 0000000. And determining that N groups of preset audio data elements in the M groups of preset audio data elements form a target preset audio data group, wherein M can be 20, and N can be 7. The 7 preset audio data elements may be Q, R, S, T, U, V, W, and the 7 preset audio data elements are combined with 7 preset parameters, where the preset parameters may be 0, and the combination results in QRSTUVW 0000000. And then sequentially carrying out fast Fourier transform and conjugate calculation on the combined target real-time audio data group ABCDEFG0000000, and sequentially carrying out fast Fourier transform and conjugate calculation on the combined target preset audio data group QRSTUVW0000000 to obtain a calculated target real-time audio data group and a calculated target preset audio data group. And sequentially multiplying the calculated target real-time audio data group and the calculated target preset audio data group and performing fast Fourier inverse transformation to obtain a target operation comparison audio data group.
The data length of the combined target real-time audio data set and the target preset audio data set is 2 times of the original data length, and the data length of the combined target real-time audio data set and the target preset audio data set is a non-prime number, so that the most common and rapid algorithm can be adopted for subsequent fast Fourier transform. The time domain signals which are difficult to process originally are converted into frequency domain signals which are easy to analyze after fast Fourier transform and conjugate calculation, and the fast algorithm of the fast Fourier transform is far less than the calculation amount of the discrete Fourier transform, namely, the calculation speed is improved.
The formula for obtaining the normal operation value by the calculation of the target operation contrast audio data set is as follows:
where xi is the normal operation value, theta is the number of multiple parameter values in the target operation contrast audio group, alphamaxComparing for the target run the largest first parameter value, alpha, of the absolute values of the plurality of parameter values in the audio groupiComparing each of a plurality of parameter values in an audio data set for a target runA parameter value.
The target operation contrast audio data set comprises a plurality of parameter values, a first parameter value with the largest absolute value in the plurality of parameter values in the target operation contrast audio data set is selected, and the first parameter value is multiplied by the number of the plurality of parameter values to obtain a first operation characteristic value. And sequentially carrying out absolute value calculation on each parameter value in the plurality of parameter values in the target operation comparison audio data set to obtain each parameter value in the plurality of calculated parameter values, and carrying out summation calculation on each parameter value in the plurality of calculated parameter values to obtain a second operation characteristic value. The ratio of the first operation characteristic value to the second operation characteristic value is a normal operation value of the transformer in the current operation state.
It is easily understood that the normal operation value in the current operation state may be used to represent the similarity between the real-time audio data and the preset audio data, which is represented by the similarity calculated from the real-time audio data and the preset audio data.
Assuming that the target operation contrast audio data set contains 8 parameter values, the 8 parameter values may be 1, 3, 4, 5, 7, 8, 9, 13, wherein the maximum value of the parameter values is 13, the number of the parameter values 8 is multiplied by the maximum value 13 of the 8 parameter values, and the first operation characteristic value is calculated to be 104. And (3) carrying out absolute value calculation on 8 parameter values 1, 3, 4, 5, 7, 8, 9 and 13 contained in the target operation comparison audio data set, then carrying out summation calculation on each parameter value, and calculating to obtain a second operation characteristic value of 50. The ratio of the first operation characteristic value to the second operation characteristic value is the normal operation value of the transformer in the current operation state, and the normal operation value is 2.08.
Step S12: and judging whether the normal operation value is greater than or equal to a preset normal operation threshold value or not.
And (4) judging the obtained normal operation value and the preset normal operation threshold value, wherein optionally, after multiple experiments, the preset normal operation threshold value can be 50.
It is easily understood that the normal operation threshold is related to the operation state of the transformer, and is determined by a plurality of preset audio data samples.
Step S13: and if so, judging that the transformer is in a normal operation state.
When the normal operation value is greater than or equal to the preset normal operation threshold value, the transformer can be judged to be in a normal operation state.
And determining a normal operation value according to the real-time audio data and the preset audio data to be used for representing the similarity between the real-time audio data and the preset audio data, wherein the normal operation threshold is used for judging whether the real-time audio data is similar to the preset audio data or not so as to judge whether the real-time audio data is in a normal operation state or not. When the similarity of the preset audio data reaches a normal operation threshold value, the operation state of the transformer corresponding to the real-time audio data is normal.
Additionally, when the normal operation value is judged to be not more than the preset normal operation threshold value, a second normal operation value of the transformer in the current operation state is determined according to the target real-time audio data group and the target preset audio data group; judging whether the second normal operation value is greater than or equal to a preset normal operation threshold value or not; if so, judging that the transformer is in a normal operation state; if not, adding 1 to the judgment times for judging whether the transformer is in the normal operation state to obtain updated judgment times, stopping judging whether the transformer is in the normal operation state again according to the fact that the updated judgment times meet the preset threshold times, and determining that the transformer is in the abnormal operation state.
When the judgment times for judging whether the transformer is in the normal operation state do not meet the preset threshold times, the currently obtained normal operation value and the judgment times are updated until the judgment times meet the preset threshold times, so that the influence of noise existing in the environment on the normal operation value obtained by analysis and calculation can be reduced, and the misjudgment on the operation state of the transformer is reduced.
In detail, determining a second normal operation value of the transformer in the current operation state according to the target real-time audio data set and the target preset audio data set includes: equally dividing a target real-time audio data group into X sections of real-time data, and equally dividing a target preset audio data group into X sections of preset data, wherein each section of real-time data in the X sections of real-time data comprises Y real-time audio data elements, each section of preset data in the X sections of preset data comprises Y preset audio data elements, and X and Y are integers more than 1; according to the numerical value represented by the real-time audio data elements, determining the real-time audio data elements with the maximum numerical value from Y real-time audio data elements of each segment of real-time data, and determining X real-time audio data elements with the maximum numerical value; according to the numerical value represented by the preset audio data element, the preset audio data element with the maximum numerical value is determined from Y preset audio data elements of each section of preset data, and X preset audio data elements with the maximum numerical value are determined in total, and particularly, the audio time length corresponding to the X real-time audio data elements with the maximum numerical value and the X preset audio data elements with the maximum numerical value are determined is the same.
Averaging all numerical values represented by all real-time audio data elements in the target real-time audio data set to obtain a real-time average value; averaging all numerical values represented by all preset audio data elements in the target preset audio data group to obtain a preset average value; subtracting the real-time average value from each of X numerical values represented by the X real-time audio data elements with the largest numerical value to obtain X real-time audio data elements after difference calculation; subtracting a preset average value from each of X numerical values represented by the X preset audio data elements with the maximum numerical value to obtain X preset audio data elements after the difference is obtained; and determining a second normal operation value of the transformer in the current operation state according to the X real-time audio data elements after the difference is solved and the X preset audio data elements after the difference is solved.
The method comprises the steps of equally dividing a target real-time audio data group into X sections of real-time data, determining that each section of real-time data in the X sections of real-time data comprises the maximum value of a numerical value represented by Y real-time audio data elements, determining X real-time audio data elements with the maximum numerical value, and subtracting the real-time average value of the target real-time audio data group from each real-time audio data element of the X real-time audio data elements with the maximum numerical value, so that the obtained real-time data group consisting of the X real-time audio data elements with the difference can filter noise audio data in some environments, and the second normal operation characteristic value obtained by the X real-time audio data elements with the difference is more accurate.
The method comprises the steps of equally dividing a target preset audio data group into X sections of preset data, determining that each section of preset data in the X sections of preset data comprises the numerical maximum value represented by Y preset audio data elements, determining X preset audio data elements with the maximum numerical value, and subtracting the real-time average value of the target preset audio data group from each preset audio data element of the X preset audio data elements with the maximum numerical value, so that the obtained preset data group consisting of the X preset audio data elements with the difference can filter noise audio data in some environments, the second normal operation characteristic value obtained by the X preset audio data elements with the difference is more accurate, and the misjudgment of the operation state of the transformer can be reduced.
It is assumed that the target real-time audio data set is equally divided into 4 segments, each segment comprising 5 real-time audio data elements, wherein the 5 real-time audio data elements of the first segment represent values of 1, 2, 3, 4, 5, respectively, and the 5 real-time audio data elements of the second segment represent values of 3, 5, 6, 7, 9, respectively; the numerical values represented by the 5 real-time audio data elements of the third segment are respectively 3, 5, 9, 10 and 11, and the numerical values represented by the 5 real-time audio data elements of the fourth segment are respectively 1, 3, 4, 5 and 6; and selecting the real-time audio data element with the largest numerical value in each section of real-time data, and determining that the 4 real-time audio data elements with the largest numerical values are 5, 9, 11 and 6 respectively. The target preset audio data group is equally divided into 4 sections, each section comprises 5 preset audio data elements, wherein numerical values represented by the 5 preset audio data elements of the first section are respectively 1, 3, 4, 5 and 7, and numerical values represented by the 5 preset audio data elements of the second section are respectively 3, 5, 6, 7 and 9; the numerical values represented by the 5 preset audio data elements of the third segment are respectively 1, 3, 5, 9 and 10, and the numerical values represented by the 5 preset audio data elements of the fourth segment are respectively 1, 3, 4, 5 and 8; and selecting the preset audio data element with the largest numerical value in each section of preset data, and determining that the 4 preset audio data elements with the largest numerical values are 7, 9, 10 and 8 respectively. And averaging all numerical values represented by all real-time audio data elements in the target real-time audio data group to obtain a real-time average value, namely, adding the numerical values represented by 5 preset audio data elements of every 1 section in 4 sections and dividing the numerical values by the number of the real-time audio data elements, and calculating to obtain the real-time average value, wherein the real-time average value is 5. Averaging all numerical values represented by all preset audio data elements in the target preset audio data group to obtain a preset average value, namely, adding numerical values represented by 5 preset audio data elements in each 1 segment of 4 segments and dividing the numerical values by the number of the preset audio data elements, and calculating to obtain the preset average value which is 5. Subtracting a real-time average value from each of 4 numerical values represented by the 4 real-time audio data elements with the maximum numerical value to obtain 4 real-time audio data elements after difference calculation, wherein the numerical values represented by the 4 real-time audio data elements after difference calculation are 0, 4, 6 and 1; and subtracting a preset average value from each of 4 numerical values represented by the 4 preset audio data elements with the largest numerical value to obtain 4 subtracted preset audio data elements, wherein the numerical values represented by the 4 subtracted preset audio data elements are 2, 4, 5 and 3. And determining a second normal operation value of the transformer in the current operation state according to the 4 real-time audio data elements after the difference is solved and the 4 preset audio data elements after the difference is solved. The step of calculating the second normal operation value is the same as step S11, and is not described here.
And when the second normal operation value is determined by calculation, judging whether the second normal operation value is greater than or equal to a preset normal operation threshold value. When the second normal operation value is larger than or equal to a preset normal operation threshold value, determining that the transformer is in a normal operation state; and when the second normal operation value is smaller than the preset normal operation threshold value, adding 1 to the judgment frequency for judging whether the transformer is in the normal operation state, and obtaining the updated judgment frequency. The threshold number of times may be preset in the program, and optionally, the preset threshold number of times is 5 times. And when the updated judgment times meet the preset threshold times, stopping judging whether the transformer is in the normal operation state again, and determining that the transformer is in the abnormal operation state.
Third embodiment
Referring to fig. 3, fig. 3 is a block diagram of an operation determination device 20 according to the present embodiment, where the operation determination device 20 includes:
the obtaining module 210 is configured to obtain real-time audio data and preset audio data, where the real-time audio data is obtained based on the transformer generating a sound with a preset duration in the current operating state, and the preset audio data is obtained based on the transformer generating a sound with a preset duration in the normal operating state.
And the processing module 220 is configured to determine a normal operation value of the transformer in the current operation state according to the obtained real-time audio data and the preset audio data.
The determining module 230 is configured to determine whether the normal operation value is greater than or equal to a preset normal operation threshold.
A counting module 240, configured to, when the determining device 230 determines that the normal operation value is smaller than the preset normal operation threshold, the processing device 220 determines a second normal operation value of the transformer in the current operation state according to the real-time audio data and the preset audio data; the determining device 230 determines whether the second normal operation value is greater than or equal to a preset normal operation threshold, if so, determines that the transformer is in a normal operation state, if not, the counting module 240 adds 1 to the determination frequency for determining whether the transformer is in the normal operation state to obtain an updated determination frequency, the determining module 230 determines whether the updated determination frequency meets the preset threshold frequency, if so, terminates determining whether the transformer is in the normal operation state again, and determines that the transformer is in an abnormal operation state.
The real-time audio data comprises M groups of real-time audio data elements, the preset audio data comprises M groups of preset audio data elements, and M is a positive integer. The processing module 220 is further configured to determine that N sets of real-time audio data elements in the M sets of real-time audio data elements form a target real-time audio data set; and determining that N groups of preset audio data elements in the M groups of preset audio data elements form a target preset audio data group, wherein N is a positive integer not greater than M. Calculating a target operation comparison audio data set according to the target real-time audio data set and the target preset audio data set; and calculating the target operation comparison audio data set according to a first preset calculation formula to obtain a first operation characteristic value, calculating the target operation comparison audio data set according to a second preset calculation formula to obtain a second operation characteristic value, and determining the ratio of the first operation characteristic value to the second operation characteristic value as a normal operation value of the transformer in the current operation state.
The processing module 220 is further configured to combine the target real-time audio data set with the N preset parameters to obtain a combined target real-time audio data set, and sequentially perform fast fourier transform and conjugate calculation on the combined target real-time audio data set to obtain a calculated target real-time audio data set; combining the target preset audio data group with the N preset parameters to obtain a combined target preset audio data group, and sequentially performing fast Fourier transform and conjugate calculation on the combined target preset audio data group to obtain a calculated target preset audio data group; and multiplying the calculated target real-time audio data group with the calculated target preset audio data group to obtain an operation comparison audio data group, and then performing fast Fourier inverse transformation on the operation comparison audio data group to obtain a target operation comparison audio data group.
It should be noted that, as those skilled in the art can clearly understand, for convenience and brevity of description, the specific working processes of the above-described apparatuses and modules may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In summary, the embodiments of the present application provide an operation determination method and an operation determination apparatus. The method comprises the following steps: determining a normal operation value of the transformer in the current operation state according to the obtained real-time audio data and preset audio data, wherein the real-time audio data are obtained based on the fact that the transformer generates sound with preset duration in the current operation state, and the preset audio data are obtained based on the fact that the transformer generates sound with preset duration in the normal operation state; judging whether the normal operation value is greater than or equal to a preset normal operation threshold value or not; and if so, judging that the transformer is in a normal operation state. The running state of the transformer is judged by detecting the abnormal sound which is originally emitted by the transformer in the running state, the normal running value obtained by analyzing and processing the obtained real-time audio data containing the abnormal sound and the preset audio data in the normal running state is judged, and the relation between the normal running value and the preset normal running threshold value is judged, so that the transformer can be judged to be in the normal running state or the abnormal running state. The technical problem that the monitored parameters such as voltage and current can be abnormal only after the transformer is damaged can be solved by detecting the abnormal sound which is originally emitted by the transformer in the running state to judge the running state of the transformer.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application. It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures.
The above description is only for the specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present application, and shall be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (6)
1. An operation determination method, characterized in that the method comprises:
determining a normal operation value of a transformer in a current operation state according to obtained real-time audio data and preset audio data, wherein the real-time audio data are obtained based on that the transformer generates sound with preset duration in the current operation state, and the preset audio data are obtained based on that the transformer generates the sound with the preset duration in the normal operation state;
judging whether the normal operation value is greater than or equal to a preset normal operation threshold value or not;
if yes, the transformer is judged to be in a normal operation state, wherein the real-time audio data comprises M groups of real-time audio data elements, the preset audio data comprises M groups of preset audio data elements, M is a positive integer, and a normal operation value of the transformer in the current operation state is determined according to the obtained real-time audio data and the preset audio data, and the method comprises the following steps:
determining that N groups of real-time audio data elements in the M groups of real-time audio data elements form a target real-time audio data group; determining that N groups of preset audio data elements in the M groups of preset audio data elements form a target preset audio data group, wherein N is a positive integer not greater than M;
calculating a target operation comparison audio data set according to the target real-time audio data set and the target preset audio data set;
calculating the target operation comparison audio data set according to a first preset calculation formula to obtain a first operation characteristic value, calculating the target operation comparison audio data set according to a second preset calculation formula to obtain a second operation characteristic value, and determining that the ratio of the first operation characteristic value to the second operation characteristic value is a normal operation value of the transformer in the current operation state, wherein the calculating of the operation comparison audio data set according to the target real-time audio data set and the target preset audio data set comprises:
combining the target real-time audio data set with N preset parameters to obtain a combined target real-time audio data set, and sequentially performing fast Fourier transform and conjugate calculation on the combined target real-time audio data set to obtain a calculated target real-time audio data set;
combining the target preset audio data set with N preset parameters to obtain a combined target preset audio data set, and sequentially performing fast Fourier transform and conjugate calculation on the combined target preset audio data set to obtain a calculated target preset audio data set;
multiplying the calculated target real-time audio data group with the calculated target preset audio data group to obtain an operation comparison audio data group, and then performing fast Fourier inverse transformation on the operation comparison audio data group to obtain a target operation comparison audio data group.
2. The operation determination method according to claim 1, wherein calculating the target operation comparison audio data set according to a first preset calculation formula to obtain a first operation characteristic value, calculating the target operation comparison audio data set according to a second preset calculation formula to obtain a second operation characteristic value, and determining a ratio of the first operation characteristic value to the second operation characteristic value as a normal operation value of the transformer in a current operation state comprises:
selecting a first parameter value with the maximum absolute value from a plurality of parameter values in the target operation contrast audio data set, and multiplying the first parameter value by the number of the plurality of parameter values to obtain a first operation characteristic value;
carrying out absolute value calculation on each parameter value in the plurality of parameter values in the target operation comparison audio data set in sequence to obtain each calculated parameter value, and carrying out summation calculation on each parameter value in the plurality of calculated parameter values to obtain a second operation characteristic value;
the ratio of the first operation characteristic value to the second operation characteristic value is a normal operation value of the transformer in the current operation state.
3. The operation determination method according to claim 1, wherein the determining whether the normal operation value is equal to or greater than a preset normal operation threshold value includes:
if not, determining a second normal operation value of the transformer in the current operation state according to the target real-time audio data set and the target preset audio data set;
judging whether the second normal operation value is greater than or equal to the preset normal operation threshold value or not;
if so, judging that the transformer is in a normal operation state; if not, adding 1 to the judgment times for judging whether the transformer is in the normal operation state to obtain updated judgment times, stopping judging whether the transformer is in the normal operation state again according to the fact that the updated judgment times meet the preset threshold times, and determining that the transformer is in the abnormal operation state.
4. The operation determination method according to claim 3, wherein the determining a second normal operation value of the transformer in the current operation state according to the target real-time audio data set and the target preset audio data set includes:
equally dividing the target real-time audio data group into X sections of real-time data, and equally dividing the target preset audio data group into X sections of preset data, wherein each section of real-time data in the X sections of real-time data comprises Y real-time audio data elements, each section of preset data in the X sections of preset data comprises Y preset audio data elements, and X and Y are integers greater than 1;
according to the numerical value represented by the real-time audio data elements, determining the real-time audio data elements with the maximum numerical value from Y real-time audio data elements of each segment of real-time data, and determining X real-time audio data elements with the maximum numerical value; according to the numerical values represented by the preset audio data elements, determining the preset audio data elements with the maximum numerical values from Y preset audio data elements of each section of preset data, and determining X preset audio data elements with the maximum numerical values in total;
averaging all numerical values represented by all real-time audio data elements in the target real-time audio data set to obtain a real-time average value; averaging all numerical values represented by all preset audio data elements in the target preset audio data group to obtain a preset average value;
subtracting the real-time average value from each of X numerical values represented by the X real-time audio data elements with the maximum numerical value to obtain the X real-time audio data elements after difference calculation; subtracting the preset average value from each of the X numerical values represented by the X preset audio data elements with the maximum numerical value to obtain the X preset audio data elements after the difference is obtained;
and determining a second normal operation value of the transformer in the current operation state according to the X real-time audio data elements subjected to the difference calculation and the X preset audio data elements subjected to the difference calculation.
5. An operation determination device, characterized in that the device comprises:
the device comprises an obtaining device and a processing device, wherein the obtaining device is used for obtaining real-time audio data and preset audio data, the real-time audio data is obtained based on the fact that a transformer generates sound with preset duration in the current operation state, and the preset audio data is obtained based on the fact that the transformer generates the sound with the preset duration in the normal operation state;
the processing module is used for determining a normal operation value of the transformer in the current operation state according to the obtained real-time audio data and the preset audio data;
the judging module is used for judging whether the normal operation value is greater than or equal to a preset normal operation threshold value or not, wherein the real-time audio data comprises M groups of real-time audio data elements, the preset audio data comprises M groups of preset audio data elements, and M is a positive integer;
the processing module is further configured to determine that N groups of real-time audio data elements of the M groups of real-time audio data elements form a target real-time audio data group; determining that N groups of preset audio data elements in the M groups of preset audio data elements form a target preset audio data group, wherein N is a positive integer not greater than M; calculating a target operation comparison audio data set according to the target real-time audio data set and the target preset audio data set; calculating the target operation comparison audio data set according to a first preset calculation formula to obtain a first operation characteristic value, calculating the target operation comparison audio data set according to a second preset calculation formula to obtain a second operation characteristic value, and determining the ratio of the first operation characteristic value to the second operation characteristic value as a normal operation value of the transformer in the current operation state;
the processing module is further configured to combine the target real-time audio data set with N preset parameters to obtain a combined target real-time audio data set, and sequentially perform fast fourier transform and conjugate calculation on the combined target real-time audio data set to obtain a calculated target real-time audio data set; combining the target preset audio data set with N preset parameters to obtain a combined target preset audio data set, and sequentially performing fast Fourier transform and conjugate calculation on the combined target preset audio data set to obtain a calculated target preset audio data set; and multiplying the calculated target real-time audio data set and the calculated target preset audio data set to obtain an operation comparison audio data set.
6. The operation determination device according to claim 5, characterized by further comprising: the counting module is used for determining that the normal operation value is smaller than the preset normal operation threshold value when the judging device judges that the normal operation value is smaller than the preset normal operation threshold value, and the processing module determines a second normal operation value of the transformer in the current operation state according to the real-time audio data and the preset audio data; the judging device judges whether the second normal operation value is larger than or equal to the preset normal operation threshold value, if so, the transformer is judged to be in a normal operation state, if not, the counting module adds 1 to the judgment frequency for judging whether the transformer is in the normal operation state to obtain an updated judgment frequency, the judging module judges whether the updated judgment frequency meets the preset threshold frequency, if so, the judgment module stops judging whether the transformer is in the normal operation state again, and the transformer is determined to be in an abnormal operation state.
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| CN102261948A (en) * | 2010-12-07 | 2011-11-30 | 鞍钢集团矿业公司 | System for monitoring and analyzing sound of operating state of transformer on line |
| CN102735968B (en) * | 2012-06-13 | 2014-08-27 | 江苏省电力公司南京供电公司 | GIS (Geographic Information System) fault diagnosis system and method based on vibration signal spectrum analysis |
| CN102721464B (en) * | 2012-06-13 | 2013-10-30 | 江苏省电力公司南京供电公司 | Method and system for detecting winding deformation faults of power transformer |
| CN106124902B (en) * | 2016-07-19 | 2019-08-13 | 广西电网有限责任公司电力科学研究院 | A kind of distribution transformer health state evaluation system |
| CN108414079A (en) * | 2018-03-21 | 2018-08-17 | 广东电网有限责任公司电力科学研究院 | A kind of transformer noise monitoring system |
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