CN114793233A - Wireless data storage method and device for mining frequency converter - Google Patents
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Abstract
The application relates to the field of mining frequency converters, in particular to a wireless data storage method and device of a mining frequency converter; the method comprises the following steps: acquiring an output voltage signal of a frequency converter; determining a fault signature based on the output voltage signal; determining a fault characteristic value; the information processing terminal sends a link verification module to the private cloud server, and determines a connection path and a connection path state; determining a fault characteristic value uploading position based on the connection path and the connection path state; storing the fault characteristic value to a private cloud server or a public cloud server; the fault eigenvalue comprises an eigenvector; according to the technical scheme provided by the embodiment of the application, the private cloud server and the public cloud server are arranged, the transmission link is verified, the fault characteristics to be stored are determined to be sent to the specific server, and the fault characteristics are stored; and the data transmission in the technical scheme is realized based on a wireless transmission means.
Description
Technical Field
The application relates to the field of mining frequency converters, in particular to a wireless data storage method and device of a mining frequency converter.
Background
The mining frequency converter is used as an independent speed-regulating power supply device with complete functions. In the prior art, a data transmission function is set, but the data type and the data volume related to the mining frequency converter are large. Not all data need be uploaded and stored, and the data which need to be stored most for the mining frequency converter are fault data.
And because of the problem of the working environment where the mining frequency converter is located, a link with good data transmission and data storage functions, a corresponding server and a transmission method are needed.
Disclosure of Invention
The embodiment of the application provides a wireless data storage method and device for a mining frequency converter, which are used for determining whether the frequency converter fails and determining the characteristics and the type of the failure by monitoring the real-time state of the frequency converter, storing failure information by setting a private cloud server and a public cloud server, and distributing stored data to corresponding clients.
The private cloud server has higher requirements on management, operation and maintenance and the amount of stored data than the public cloud server, but has higher privacy; the management, operation and maintenance of the public cloud and the requirements for data transmission are lower than those of the private cloud server, but the privacy is poor, and the problems of data loss and secret leakage are easy to occur compared with the private cloud server.
Therefore, the data storage mode for the mining frequency converter and the mining frequency converter needs to be determined according to specific conditions, and the private cloud is preferentially used for the mining frequency converter. The mining frequency converter wireless data storage method and device provided by the embodiment of the application are based on a wireless transmission technology, and selection of the corresponding server can be realized based on real-time network conditions and server data link conditions.
In order to achieve the above purpose, the embodiments of the present application employ the following technical solutions:
in a first aspect, an embodiment of the application provides a wireless data storage method for a mining frequency converter, which is applied to a server, wherein the server is connected with an information sending terminal, the server comprises a public cloud server and a private cloud server, and the method comprises the following steps: acquiring an output voltage signal of a frequency converter; determining a fault signature based on the output voltage signal; determining a fault characteristic value; the information processing terminal sends a link verification module to the private cloud server, and determines a connection path and a connection path state; determining a fault characteristic value uploading position based on the connection path and the connection path state; storing the fault characteristic value to a private cloud server or a public cloud server; the fault eigenvalues include eigenvectors.
Further, the acquisition of the output voltage signal of the frequency converter further comprises an overvoltage alarm and an undervoltage alarm; the method comprises the following steps: judging whether overvoltage occurs or not based on the maximum value of the main voltage, and selecting alarm; judging whether the voltage is insufficient or not based on the minimum value of the main voltage, and selecting to alarm; wherein the over-current alarm limit is 1.24 multiplied by 1.35 multiplied by U 1max Wherein U is 1max Is the main voltage maximum; wherein the undercurrent alarm limit is 0.82 × 1.35 × U 1min Wherein U is 1min Is the mains voltage minimum.
Further, before the fault characteristics are determined based on the output voltage signals, filtering processing of the output voltage signals is further performed to obtain filtered output voltage signals, and the filtering processing is achieved based on an IIR filter.
Further, determining a fault signature based on the output voltage signal includes the following processes:
obtaining the variable quantity of the frequency component of the output voltage based on the filtered output voltage signal; the fault signature is determined based on the amount of change in the frequency component of the output voltage.
Further, obtaining the variation of the frequency component of the output voltage based on the filtered output voltage signal specifically includes the following processes: performing multi-layer wavelet packet decomposition on the corrected output voltage signal to obtain multi-frequency component signal characteristics of multiple frequency bands; wavelet packet reconstruction is carried out on the wavelet packet coefficient, and the signal characteristics of the multi-frequency components in the multi-frequency band range after noise reduction are obtained; obtaining the energy of each frequency band signal based on the signal characteristics of multiple frequencies and multiple components; constructing a feature vector based on the energy of each frequency band signal; normalizing the feature vector to obtain a normalized feature vector; and comparing the normalized feature vector with the normal feature vector to determine fault occurrence and fault location.
Further, performing multi-layer wavelet packet decomposition on the filtering output voltage signal to obtain the signal characteristics of multi-frequency components of multiple frequency bands, and determining the optimal number of decomposition layers of the small packets; the method specifically comprises the following steps: setting an initial decomposition layer; performing layering processing on the initial decomposition layer to obtain a first decomposition layer, performing wavelet packet decomposition on the signal based on the first decomposition layer, and calculating a wavelet packet decomposition coefficient module value; averaging the modulus values of the majority of the decomposition coefficients to obtain a mean value of the modulus values; determining the number of the module values which are larger than the mean value in the module value sequence based on the mean value of the module values; dividing the total number of wavelet packet decomposition coefficients by the number larger than the mean value to obtain the energy aggregation degree of the layer; comparing the energy concentration degree of the layer with the energy concentration degree of the previous layer, if the energy concentration degree of the layer is smaller than the energy concentration degree of the previous layer, stopping decomposition, and determining the optimal number of wavelet packet decomposition layers; wherein the optimal number of layers of wavelet packet decomposition is the number of layers minus 1.
Further, the information sending terminal sends a link verification module to the private cloud server to determine a connection path and a connection path state; the method comprises the following specific processes: running a link verification module processing thread or process, and sending the link verification module; recording the sending time of the current link verification module; the receiving link verification module records the return time of the link verification module; and determining whether to send data to the private cloud server according to whether the link verification module returns to the state and the link verification module return time.
Further, determining whether to send data to the private cloud server according to whether the link verification module returns to the state and the link verification module return time includes the following specific processes: if the link verification module does not return, stopping sending the fault characteristic value to the private cloud server; if the return time of the link verification module is greater than the threshold value, stopping sending the fault characteristic value to the private cloud server; and if the link verification module returns and the return time is less than the threshold value, sending the fault characteristic value to the private cloud server.
Further, based on the connection path and the connection path state, determining a fault characteristic value uploading position, which comprises the following specific processes: if the link verification module does not return, the fault characteristic value is sent to the public cloud server; if the return time of the link verification module is greater than the threshold value, sending a fault characteristic value to the public cloud server; and if the return time of the link verification module is less than a threshold value, sending the fault characteristic value to the private cloud server.
In a second aspect, an embodiment of the present application further provides a wireless data storage device for a mining frequency converter, which is applied to a server, wherein the server is connected to an information sending terminal, and the server includes a public cloud server and a private cloud server, including:
the acquisition module is used for acquiring a variable-frequency output voltage signal;
an identification module for determining a fault signature based on the output voltage signal;
the determining module is used for determining a fault characteristic value;
and the link verification module sending module is used for sending the link verification module to the private cloud server.
According to the technical scheme provided by the embodiment of the application, the private cloud server and the public cloud server are arranged, the transmission link is verified, the fault characteristics to be stored are determined to be sent to the specific server, and the storage of the fault characteristics is realized; and the data transmission in the technical scheme is realized based on a wireless transmission means.
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In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
The methods, systems, and/or programs of the figures will be further described in accordance with the exemplary embodiments. These exemplary embodiments will be described in detail with reference to the drawings. These exemplary embodiments are non-limiting exemplary embodiments in which example numerals represent similar mechanisms throughout the various views of the drawings.
Fig. 1 is a schematic structural diagram of a wireless data storage device of a mining frequency converter provided by an embodiment of the application;
FIG. 2 is a flow chart of a method for storing wireless data of a mining frequency converter according to an embodiment of the present application;
fig. 3 is a schematic flow chart of a method for changing an output voltage frequency component in a wireless data storage method of a mining frequency converter according to an embodiment of the present application.
Detailed Description
In order to better understand the technical solutions, the technical solutions of the present application are described in detail below with reference to the drawings and specific embodiments, and it should be understood that the specific features in the embodiments and examples of the present application are detailed descriptions of the technical solutions of the present application, and are not limitations of the technical solutions of the present application, and the technical features in the embodiments and examples of the present application may be combined with each other without conflict.
In the following detailed description, numerous specific details are set forth by way of examples in order to provide a thorough understanding of the relevant teachings. It will be apparent, however, to one skilled in the art that the present application may be practiced without these specific details. In other instances, well-known methods, procedures, systems, components, and/or circuits have been described at a relatively high-level, without detail, in order to avoid unnecessarily obscuring aspects of the present application.
The present application uses flowcharts to illustrate the implementations performed by a system according to embodiments of the present application. It should be expressly understood that the execution of the flow diagrams may be performed out of order. Rather, these implementations may be performed in the reverse order or simultaneously. In addition, at least one other implementation may be added to the flowchart. One or more implementations may be deleted from the flowchart.
The processor may be an integrated circuit chip having signal processing capabilities. The Processor may be a general-purpose Processor, including 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, 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.
Referring to fig. 2, a flowchart of a method for a wireless data storage device of a mining frequency converter according to some embodiments of the present application is shown, where the method is applied to a server, and the server is connected to an information sending terminal, and is configured to perform fault identification on a fault of the frequency converter, record fault characteristics, and transmit the fault characteristics to a designated server through a wireless transmission technology for storage.
In this embodiment, the servers include a public cloud server and a private cloud server.
In this embodiment, the data to be stored is fault-related data, that is, fault characteristics. The mining frequency converter has more data, but most of the data are parameters in the control process, and the data are not necessarily stored data for the part of the data. And the storage of the fault data has higher necessity. Because the faults of the frequency converter are all special, the fault data are stored, and the obtained fault information is distributed to the user terminal through the wireless transmission technology, so that the recording of historical fault information and the release of real-time fault information can be realized.
In the embodiment, not only are technologies related and stored in wireless transmission provided, but also the transmission of the fault information is involved, so that the embodiment also provides a method for identifying the fault of the frequency converter, identifying the fault, recording the characteristic information of the fault, transmitting the characteristic information of the fault to the server for storage, and distributing the characteristic information of the fault to the corresponding client after storage.
For fault identification, the fault alarm of the existing frequency converter adopts a rapid detection circuit, some key point states in the frequency converter are sent to a microprocessor, after algorithm processing, whether the frequency converter has a fault or not is judged, and then a corresponding alarm signal is given out.
According to the wireless data storage method of the mining frequency converter, the related technology of the computer is adopted, the fault information is determined, and the fault information is transmitted into the corresponding server through the wireless transmission technology.
The method provided by this embodiment may specifically include the following steps S1-S6. On the basis of the following steps S1-S6, some alternative embodiments will be explained, which should be understood as examples and should not be understood as technical features essential for implementing the present solution.
And step S1, acquiring the output voltage signal of the frequency converter.
In the present embodiment, the voltage signal is mainly acquired through a sensor and a data acquisition card, and the sensor in the present embodiment is mainly a hall voltage sensor and a current sensor. The Hall sensor can measure voltage and current signals with arbitrary waveforms, and can realize isolated transmission of direct current and non-sinusoidal alternating current voltage and current signals.
In this embodiment, the data acquisition card is a PCI-6024E multifunctional data acquisition card from NI corporation. By adopting PCI bus technology, 16-channel single-ended analog input (or 8-channel differential input), the input range is from +/-0.05 +/-10V, 2 output channels, the output range is-10V- +10V, the resolution is 12bits, the sampling highest frequency is 200kS/s, 8 digital I/O ports are arranged, 2bit counters/timers are arranged, an external clock is supported, and external digital triggering is realized. The main function is to continuously collect the signals detected by the sensor and then send the signals to a computer for corresponding analysis, judgment and processing.
In the present embodiment, acquisition for data also involves sampling frequency, sampling length, and the number of sampling points.
For the sampling frequency, in the prior art, the higher the sampling frequency is, the denser the sampling points are, and the closer the obtained digital signal is to the original signal. However, when the sampling length is constant, the higher the sampling length is, the larger the data volume is, and the larger the required computer storage volume and the calculation volume are; on the contrary, when the sampling frequency is reduced to a certain degree, the information of the original signal is lost or distorted. In this embodiment, the sampling frequency is 2.56 times the highest frequency in the signal.
For sampling length, when sampling intervals are fixed, the sampling length is longer, and the number of sampling points is larger.
With respect to the number of sampling points, in the present embodiment, calculation is performed for a set of data points of an integer power of 2.
And step S2, overvoltage alarm and undervoltage alarm.
When data acquisition is carried out, overvoltage and undervoltage alarm needs to be carried out on the acquisition of the direct-current voltage of the frequency converter.
In this embodiment, the following are specifically mentioned:
judging whether overvoltage occurs or not based on the maximum value of the main voltage, and selecting alarm;
judging whether the main voltage is under-voltage or not based on the minimum value of the main voltage, and selecting an alarm;
wherein the over-current alarm limit is 1.24 multiplied by 1.35 multiplied by U 1max Wherein U is 1max Is the maximum value of the main voltage; wherein the under-current alarm limit is 0.82 multiplied by 1.35 multiplied by U 1min Wherein U is 1min Is the mains voltage minimum.
And step S3, filtering the output voltage signal to obtain a filtered output voltage signal.
In order to reduce the interference of the collected data, improve the precision, obtain the test result which can reflect the most substantial state and ensure the best running performance of the system, the digital filtering of software is required. The digital filter comprises a Butterworth low-pass filter and a Chebyshev filter; an elliptic filter, etc.
A digital IIR filter is preferred in this embodiment.
In step S4, the variation of the output voltage frequency component is obtained based on the filtered output voltage signal.
Step S41, performing multi-layer wavelet packet decomposition on the corrected output voltage signal to obtain multi-band multi-frequency component signal characteristics.
In step S411, an initial decomposition layer is set.
Step S412, performing layer addition processing on the initial decomposition layer to obtain a first decomposition layer, performing wavelet packet decomposition on the signal based on the first decomposition layer, and calculating a wavelet packet decomposition coefficient modulus value.
In step S413, the module values of the plurality of decomposition coefficients are averaged to obtain a mean value of the module values.
Step S414, determining the number of the module values in the module value sequence greater than the mean value based on the mean value of the module values.
And step S415, dividing the total number of the wavelet packet decomposition coefficients by the number larger than the mean value to obtain the energy concentration degree of the layer.
And S416, comparing the energy concentration degree of the layer with the energy concentration degree of the previous layer, and stopping decomposition to determine the optimal wavelet packet decomposition layer number if the energy concentration degree of the layer is less than the energy concentration degree of the previous layer.
And step S417, the optimal wavelet packet decomposition layer number is the layer number minus 1.
And step S42, performing wavelet packet reconstruction on the wavelet packet coefficients to obtain the signal characteristics of the multi-frequency components in the multi-frequency band range after noise reduction.
In this embodiment, the optimal method is as follows: and (3) performing 3-layer wavelet packet decomposition on the acquisition voltage signal S (t) by using db wavelets, and respectively extracting signal characteristics of 8 frequency components from low frequency to high frequency in the 3 rd layer.
In step S43, the energy of each band signal is obtained based on the signal characteristics of the multi-frequency and multi-component signals.
Wherein, X ik Is heavyForming a signal; s. the i Is the amplitude of the discrete points.
In step S44, a feature vector is constructed based on the energy of each band signal.
When the frequency converter fails, the energy of signals in each frequency band is influenced. Thus, a feature vector R can be constructed using energy as an element. The feature vector R is constructed as follows:
step S45, the feature vector is normalized to obtain a normalized feature vector.
When the energy is larger, it is usually a larger value, in
Usually a large value, which causes great inconvenience in analysis. The feature vector R may be normalized.
The normalized feature vector is:
and step S46, comparing the normalized feature vector with the normal feature vector to determine the fault occurrence and fault location.
In step S5, after the information processing terminal determines that a fault occurs and is located, the determined normalized feature vector, that is, the fault feature, needs to be sent to the server for storage.
Since the servers in this embodiment include the private cloud server and the public cloud server, the private cloud server has better data storage capability and data confidentiality capability, and preferentially sends the fault feature to the private cloud server.
However, the private cloud server has a limited storage capacity due to the construction and management cost of the private cloud server, and when the number of transient storages is large, the problem of insufficient data storage capacity of the private cloud server may occur. Therefore, it is necessary to determine the path connection status of the private cloud in a real-time state, thereby determining the location of data storage.
And step S51, operating the link verification module processing thread or process, and sending the link verification module to the private cloud server.
Step S52, record the current link verification module sending time.
And recording the real-time of the sending link verification module and storing the data.
Step S53, it is determined whether the link verification module returns.
And step S54, if the link verification module does not return, stopping sending the fault characteristics to the private cloud server, and sending the fault characteristics to the public cloud server.
And step S55, if the link verification module returns, the link verification module is accepted, and the return time of the link verification module is recorded.
And step S56, if the return time of the link verification module is greater than the threshold value, stopping sending the target fault characteristics to the private cloud server, and sending the fault characteristics to the public cloud server.
And step S57, if the return time of the link verification module is less than or equal to the threshold value, sending the fault characteristics to the private cloud server.
Step S6, the private cloud server stores the judged fault characteristics; and the public cloud server stores the judged fault characteristics.
And the acquired fault characteristics are stored through a private cloud server or a public cloud server and are distributed to the corresponding user terminal, so that the data distribution is realized.
The embodiment of the present application further provides a wireless data storage device for a mining frequency converter, which is used for executing the above method, and the wireless data storage of the mining frequency converter is applied to a server, and the wireless data storage device comprises:
the acquisition module is used for acquiring a variable-frequency output voltage signal;
an identification module for determining a fault signature based on the output voltage signal;
the determining module is used for determining a fault characteristic value;
the link verification module sending module is used for sending the link verification module to the private cloud server;
and the state confirmation module is used for confirming the connection path and the connection passing state of the private cloud server.
It should be understood that, for technical terms that are not noun-interpreted in the above, a person skilled in the art can deduce to determine the meaning of the reference unambiguously from the above disclosure, for example, for some terms such as threshold, coefficient, etc., a person skilled in the art can deduce and determine from the logical relationship between the front and the back, and the value range of these values can be selected according to the actual situation, for example, 0.1 to 1, for example, 1 to 10, for example, 50 to 100, which is not limited herein.
The skilled person can determine some preset, reference, predetermined, set and preference labels of technical features/technical terms, such as threshold, threshold interval, threshold range, etc., without any doubt according to the above disclosure. For some technical characteristic terms which are not explained, the skilled person is fully capable of reasonably and unambiguously deriving the technical solution based on the logical relations between the preceding and following terms, so as to clearly and completely implement the technical solution. The prefixes of unexplained technical feature terms, such as "first," "second," "example," "target," and the like, may be unambiguously derived and determined from the context. Suffixes of technical feature terms not explained, such as "set", "list", etc., can also be derived and determined unambiguously from the preceding and following text.
The above disclosure of the embodiments of the present application will be apparent to those skilled in the art from the above disclosure. It should be understood that the process of deriving and analyzing technical terms, which are not explained, by those skilled in the art based on the above disclosure is based on the contents described in the present application, and thus the above contents are not an inventive judgment of the overall scheme.
Having thus described the basic concept, it will be apparent to those skilled in the art that the foregoing detailed disclosure is to be considered as illustrative and not restrictive of the application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.
Also, this application uses specific terminology to describe embodiments of the application. Reference to "one embodiment," "an embodiment," and/or "some embodiments" means a feature, structure, or characteristic described in connection with at least one embodiment of the application. Therefore, it is emphasized and should be appreciated that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various portions of this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics of at least one embodiment of the present application may be combined as appropriate.
In addition, those skilled in the art will recognize that the various aspects of the application may be illustrated and described in terms of several patentable species or contexts, including any new and useful combination of procedures, machines, articles, or materials, or any new and useful modifications thereof. Accordingly, aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software. The above hardware or software may be referred to as a "unit", "component", or "system". Furthermore, aspects of the present application may be embodied as a computer product, located in at least one computer readable medium, which includes computer readable program code.
A computer readable signal medium may comprise a propagated data signal with computer program code embodied therein, for example, on a baseband or as part of a carrier wave. The propagated signal may take any of a variety of forms, including electromagnetic, optical, and the like, or any suitable combination. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code on a computer readable signal medium may be propagated over any suitable medium, including radio, electrical cable, fiber optic cable, RF, or the like, or any combination of the preceding.
Computer program code required for the execution of aspects of the present application may be written in any combination of one or more programming languages, including object oriented programming, such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C + +, C #, VB.NET, Python, and the like, or similar conventional programming languages, such as the "C" programming language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages, such as Python, Ruby, and Groovy, or other programming languages. The programming code may execute entirely on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any form of network, such as a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet), or in a cloud computing environment, or as a service using, for example, software as a service (SaaS).
Additionally, the order of the process elements and sequences described herein, the use of numerical letters, or other designations are not intended to limit the order of the processes and methods unless otherwise indicated in the claims. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, it should be understood that such detail is solely for that purpose and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover all modifications and equivalent arrangements that are within the spirit and scope of the embodiments herein. For example, although the system components described above may be implemented by hardware means, they may also be implemented by software-only solutions, such as installing the described system on an existing server or mobile device.
It should also be appreciated that in the foregoing description of embodiments of the present application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of at least one embodiment of the invention. However, this method of disclosure is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.
Claims (10)
1. The wireless data storage method of the mining frequency converter is characterized by being applied to a server, wherein the server is connected with an information sending terminal and comprises a public cloud server and a private cloud server; the method comprises the following steps:
acquiring an output voltage signal of the frequency converter;
determining a fault signature based on the output voltage signal;
determining a fault characteristic value;
the information processing terminal sends a link verification module to the private cloud server, and determines a connection path and a connection path state;
determining the uploading position of the fault characteristic value based on the connection path and the state of the connection path;
storing the fault characteristic value to the private cloud server or the public cloud server;
the fault signature values include a signature vector.
2. The method for wirelessly storing data of a mining frequency converter according to claim 1, wherein the obtaining of the frequency converter output voltage signal further comprises an over-voltage alarm and an under-voltage alarm; the method comprises the following steps:
judging whether overvoltage occurs or not based on the maximum value of the main voltage, and selecting alarm;
judging whether the main voltage is under-voltage or not based on the minimum value of the main voltage, and selecting an alarm;
the over-current alarm limit is 1.24 multiplied by 1.35 multiplied by U 1max Wherein U is 1max Is the maximum value of the main voltage;
the under-current alarm limit is 0.82 multiplied by 1.35 multiplied by U 1min Wherein U is 1min Is the mains voltage minimum.
3. The method for wirelessly storing data of the mining frequency converter according to claim 1, wherein before determining the fault feature based on the output voltage signal, the method further comprises filtering the output voltage signal to obtain a filtered output voltage signal, wherein the filtering is implemented based on an IIR filter.
4. The method for wirelessly storing data of a mining frequency converter according to claim 3, wherein the determining of the fault signature based on the output voltage signal comprises the following processes:
obtaining the variable quantity of the frequency component of the output voltage based on the filtered output voltage signal; the fault signature is determined based on the amount of change in the frequency component of the output voltage.
5. The wireless data storage method of the mining frequency converter according to claim 4, wherein the obtaining of the variation of the frequency component of the output voltage based on the filtered output voltage signal specifically includes the following steps:
performing multi-layer wavelet packet decomposition on the corrected output voltage signal to obtain multi-frequency component signal characteristics of multiple frequency bands;
wavelet packet reconstruction is carried out on the wavelet packet coefficients to obtain the signal characteristics of the multi-frequency components in the multi-frequency band range after noise reduction;
obtaining the energy of each frequency band signal based on the signal characteristics of the multiple frequencies and the multiple components;
constructing a feature vector based on the energy of each frequency band signal;
normalizing the feature vector to obtain a normalized feature vector;
and comparing the normalized feature vector with the normal feature vector to determine fault occurrence and fault location.
6. The method for wirelessly storing data of a mining frequency converter according to claim 5, wherein the filtering output voltage signal is subjected to multi-layer wavelet packet decomposition to obtain multi-band multi-frequency component signal characteristics, and further comprising determining an optimal number of layers of the wavelet packet decomposition; the method specifically comprises the following steps:
setting an initial decomposition layer;
performing layering processing on the initial decomposition layer to obtain a first decomposition layer, performing wavelet packet decomposition on the signal based on the first decomposition layer, and calculating a wavelet packet decomposition coefficient module value;
averaging the modulus values of the majority of the decomposition coefficients to obtain a mean value of the modulus values;
determining the number of the module values which are larger than the mean value in the module value sequence based on the mean value of the module values;
dividing the total number of wavelet packet decomposition coefficients by the number larger than the mean value to obtain the energy concentration degree of the layer;
comparing the energy concentration degree of the layer with the energy concentration degree of the previous layer, if the energy concentration degree of the layer is smaller than the energy concentration degree of the previous layer, stopping decomposition, and determining the optimal number of wavelet packet decomposition layers;
the optimal wavelet packet decomposition layer number is the layer number minus 1.
7. The wireless data storage method of the mining frequency converter according to claim 1, wherein the information sending terminal sends the link verification module to a private cloud server to determine a connection path and a connection path state; the method comprises the following specific processes:
running a link verification module processing thread or process, and sending the link verification module;
recording the sending time of the current link verification module;
the receiving link verification module records the return time of the link verification module;
and determining whether to send data to the private cloud server according to whether the link verification module returns the state and the link verification module return time.
8. The wireless data storage method of the mining frequency converter according to claim 7, wherein the step of determining whether to send data to the private cloud server according to whether the link verification module returns to the state and the link verification module return time comprises the following specific steps:
if the link verification module does not return, stopping sending the fault characteristic value to the private cloud server;
if the return time of the link verification module is greater than the threshold value, stopping sending the fault characteristic value to the private cloud server;
and if the link verification module returns and the return time is less than the threshold value, sending the fault characteristic value to the private cloud server.
9. The wireless data storage method of the mining frequency converter according to claim 8, wherein the determining of the fault characteristic value uploading position based on the connection path and the connection path state comprises the following specific processes:
if the link verification module does not return, the fault characteristic value is sent to the public cloud server;
if the return time of the link verification module is greater than a threshold value, sending the fault characteristic value to the public cloud server;
and if the return time of the link verification module is less than a threshold value, sending the fault characteristic value to the private cloud server.
10. The wireless data storage method and device for the mining frequency converter is characterized by being applied to a server, wherein the server is connected with an information sending terminal, comprises a public cloud server and a private cloud server, and comprises the following steps:
the acquisition module is used for acquiring a variable-frequency output voltage signal;
an identification module for determining a fault signature based on the output voltage signal;
the determining module is used for determining a fault characteristic value;
the link verification module sending module is used for sending the link verification module to the private cloud server; and the state confirmation module is used for confirming the connection path and the connection passing state of the private cloud server.
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