Signal acceptance method, device, electronic device and storage medium

Abstract

The present invention discloses a signal acceptance method, device, electronic device and storage medium. The method includes: in response to a head-mounted intelligent voice control device receiving a signal acceptance and debugging form, parsing the signal acceptance and debugging form to obtain at least one signal to be accepted; displaying at least one signal to be accepted on a glasses-like display screen of the head-mounted intelligent voice control device; in response to a microphone sensor of the head-mounted intelligent voice control device collecting a first voice signal, accepting at least one signal to be accepted based on the first voice signal to obtain an acceptance result of at least one signal to be accepted. The present invention solves the technical problem of low work efficiency in automated acceptance of substation automation equipment.

Description

Technical Field

[0001] The present invention relates to the field of substation operation and maintenance, and in particular to a signal acceptance method, device, electronic equipment and storage medium. Background Art

[0002] When the existing substation automation operation and maintenance personnel conduct automation signal acceptance, they use the signal verification function of the mobile phone software or the energy management system website on the company's intranet to conduct signal acceptance. The operation and maintenance personnel need to use mobile phones or office computers to log into the system on site to verify the signals. Three people are required to be on site (two people on the side of the screen cabinet and one person holding the mobile phone software or in front of the office computer) to conduct the verification. In this way, the correctness of the equipment simulation signal and the correctness of the verification signal can be guaranteed at the same time.

[0003] Since three people are required on site and the mobile phone software must be manually controlled, this automated signal acceptance method inevitably leads to low acceptance efficiency.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a signal acceptance method, device, electronic device and storage medium to at least solve the technical problem of low efficiency in automated acceptance of substation automation equipment.

[0006] According to one aspect of an embodiment of the present invention, a signal acceptance method is provided, comprising: in response to a head-mounted intelligent voice control device receiving a signal acceptance and debugging form, parsing the signal acceptance and debugging form to obtain at least one signal to be accepted; displaying at least one signal to be accepted on a glasses-like display screen of the head-mounted intelligent voice control device; in response to a microphone sensor of the head-mounted intelligent voice control device collecting a first voice signal, accepting at least one signal to be accepted based on the first voice signal to obtain an acceptance result of at least one signal to be accepted.

[0007] Furthermore, accepting at least one signal to be accepted based on the first voice signal to obtain an acceptance result of at least one signal to be accepted includes: converting the first voice signal into a first sound signal in electronic form; identifying the first sound signal to obtain an acceptance instruction; accepting at least one signal to be accepted based on the acceptance instruction to obtain an acceptance result.

[0008] Furthermore, the first sound signal is identified to obtain an acceptance instruction, including: preprocessing the first sound signal to obtain a processed signal; converting the processed signal into text data; and identifying the text data to obtain an acceptance instruction.

[0009] Further, preprocessing the first sound signal to obtain a processed signal includes: preprocessing the first sound signal through a sound signal processing unit to obtain a processed signal, wherein the preprocessing includes at least one of the following: denoising, sound enhancement and sound analysis.

[0010] Furthermore, converting the processed signal into text data includes: converting the processed signal into fixed weighted parameters through a sound wave analysis algorithm; and converting the processed signal into text data based on the fixed weighted parameters through a speech recognition engine.

[0011] Further, at least one signal to be accepted is accepted based on the acceptance instruction to obtain an acceptance result, including: determining a target signal in at least one signal to be accepted based on the acceptance instruction; and accepting the target signal through an automated signal verification function to obtain an acceptance result of the target signal.

[0012] Furthermore, the method also includes: in response to the acceptance result of any one of the at least one signal to be accepted being accepted, adjusting the display position of any one of the signals to be accepted on the glasses-type display screen to a preset position, wherein the preset position is used to characterize that any one of the signals to be accepted is displayed at the bottom of at least one of the signals to be accepted; in response to the acceptance result of any one of the at least one signal to be accepted being accepted not passed, controlling the display position of any one of the signals to be accepted on the glasses-type display screen to remain unchanged.

[0013] Furthermore, the method also includes: determining the target page to be currently displayed on the glasses-type display screen; generating digital labels for different controls contained in the target page through automated verification software; displaying the target page on the glasses-type display screen, and displaying digital labels on the target page.

[0014] Furthermore, the method also includes: in response to the microphone sensor collecting a second voice signal, determining a target control selected on the target page based on the second voice signal; executing the target control to obtain an execution result; and displaying the execution result on a glasses-like display screen.

[0015] Furthermore, determining the target control selected on the target page based on the second voice signal includes: converting the second voice signal into a second sound signal in electronic form; identifying the second sound signal to obtain a target digital label; and determining that the control corresponding to the target digital label is the target control.

[0016] Furthermore, the method further includes: in response to the signal acceptance that the debugging form has been accepted, storing the accepted debugging form in a database.

[0017] According to another aspect of an embodiment of the present invention, a signal acceptance device is also provided, including: an analysis module, used to analyze the signal acceptance and debugging form in response to a head-mounted intelligent voice control device receiving a signal acceptance and debugging form, and obtain at least one signal to be accepted; a display module, used to display at least one signal to be accepted on a glasses-like display screen of the head-mounted intelligent voice control device; an acceptance module, used to accept at least one signal to be accepted based on the first voice signal in response to a microphone sensor of the head-mounted intelligent voice control device collecting a first voice signal, and obtain an acceptance result of at least one signal to be accepted.

[0018] According to another aspect of an embodiment of the present invention, there is further provided an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the method in each embodiment of the present invention is executed when the program is running.

[0019] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided. The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0020] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0021] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0022] According to another aspect of the embodiments of the present invention, a computer program is provided. When the computer program is executed by a processor, the methods in the embodiments of the present invention are implemented.

[0023] In an embodiment of the present invention, in response to a head-mounted intelligent voice control device receiving a signal acceptance and debugging form, the signal acceptance and debugging form is parsed to obtain at least one signal to be accepted; at least one signal to be accepted is displayed on a glasses-like display screen of the head-mounted intelligent voice control device; in response to a microphone sensor of the head-mounted intelligent voice control device collecting a first voice signal, at least one signal to be accepted is accepted based on the first voice signal to obtain an acceptance result of at least one signal to be accepted. It is easy to notice that by accepting at least one signal to be accepted through the first voice signal collected by the microphone sensor of the head-mounted intelligent voice control device, the substation automation operation and maintenance personnel can perform voice control on the automation signal verification software, thereby completing the purpose of the acceptance closed-loop work, thereby achieving the technical effect of improving the work efficiency of the automated acceptance of substation automation equipment, and thereby solving the technical problem of low work efficiency of the automated acceptance of substation automation equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0025] Figure 1 is a flow chart of a signal acceptance method according to an embodiment of the present invention;

[0026] Figure 2 is a schematic diagram of a signal acceptance device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0029] Example 1

[0030] According to an embodiment of the present invention, an embodiment of a signal acceptance method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0031] Figure 1 is a flow chart of a signal acceptance method according to an embodiment of the present invention. Figure 1 As shown, the method comprises the following steps:

[0032] Step S102, in response to the head-mounted intelligent voice control device receiving the signal acceptance and debugging form, parsing the signal acceptance and debugging form to obtain at least one signal to be accepted;

[0033] Specifically, the above-mentioned head-mounted intelligent voice control device can be used to represent a head-mounted device that supports intelligent voice control.

[0034] Applied in the embodiments of the present application, the substation operation and maintenance personnel can realize voice verification of signals throughout the substation work site by wearing a head-mounted intelligent voice control device. The head-mounted intelligent voice control device can be used to perform voice control operations on the automatic signal verification software without the need for hands, thereby realizing automated acceptance and verification of remote control, telemetry, telesignaling, and remote adjustment signals.

[0035] The above-mentioned signal acceptance and debugging form can be used to indicate that the automation maintenance personnel of the substation conducts the acceptance of the four remote signals (remote control, remote measurement, remote signaling, and remote adjustment functions) of the automation equipment of the substation, including but not limited to alarm signals, fault signals, and electrical parameter signals.

[0036] Generally, the automation signal acceptance of a substation refers to the process of ensuring that the signals in the substation automation system are accurately, stably and reliably transmitted and received. This includes testing and verifying the signals sent by various sensors, monitoring systems, protection devices and other equipment to ensure that they meet the specified standards and requirements, can correctly transmit and process data, and ensure the safe operation and stable power supply of the substation. The acceptance process usually includes testing and evaluating the reliability, accuracy, timeliness and other aspects of signal transmission.

[0037] In an optional embodiment, when the substation operation and maintenance personnel need to perform automated signal acceptance, the master station personnel complete the database entry from the master station end dispatch automation system and establish a signal acceptance and debugging form. The document is transmitted from area I of the master station to the automated signal verification software in area III. The substation operation and maintenance personnel wear a head-mounted intelligent voice control device, which has a glasses-like display, an Android system, and automated signal verification software installed, as well as a microphone sensor. The substation operation and maintenance personnel can view the above-mentioned signal acceptance and debugging form through the automated signal verification software installed in the head-mounted intelligent voice control device.

[0038] Furthermore, by parsing the viewed signal acceptance and debugging list, at least one signal to be accepted can be obtained, and then the at least one signal to be accepted can be automatically accepted one by one.

[0039] Step S104, displaying at least one signal to be accepted on the glasses-like display screen of the head-mounted intelligent voice control device;

[0040] Specifically, since the head-mounted intelligent voice control device has its own eye-shaped display screen, at least one signal to be accepted can be displayed on the eyeglass-shaped display screen, which is convenient for substation operation and maintenance personnel to obtain at least one signal to be accepted and perform operation acceptance of at least one signal to be accepted by automated voice commands.

[0041] Generally, a glasses-type display screen is a new type of display technology that integrates a display screen into glasses so that users can see images and information directly on the glasses. This technology can be used in augmented reality applications, allowing users to see virtual information and images on their glasses while maintaining awareness of their surroundings. Glasses-type displays can be used in products such as smart glasses and head-mounted display devices. In this application, a glasses-type display screen can be set on a head-mounted intelligent voice control device to display at least one signal to be accepted.

[0042] Step S106, in response to the microphone sensor of the head-mounted intelligent voice control device collecting the first voice signal, at least one signal to be accepted is accepted based on the first voice signal to obtain an acceptance result of the at least one signal to be accepted.

[0043] Specifically, the first voice signal can be used to represent a signal corresponding to a voice operation instruction issued by a substation operator. Generally, the voice information issued by the substation operator can be collected by a microphone sensor to obtain the first voice signal.

[0044] In an optional embodiment, after the microphone sensor of the head-mounted intelligent voice control device collects the first voice signal sent by the substation operation and maintenance personnel, at least one signal to be accepted can be accepted based on the operation instructions carried by the first voice instructions to obtain an acceptance result of at least one signal to be accepted.

[0045] Specifically, in the process of accepting at least one signal to be accepted based on the operation instruction carried by the first voice instruction, voice control can be performed step by step through the automated UI (User Interface) tree. Specifically, after the substation operation and maintenance personnel put on and turn on the head-mounted intelligent voice control device, the head-mounted intelligent voice control device performs the system desktop, and the system desktop has previously been installed with the automated signal verification software. The automated UI tree is automatically loaded on the glasses-like display screen of the head-mounted intelligent voice control device, and the automated UI tree can display digital labels on the interface of the automated signal verification software, wherein each digital label corresponds to a corresponding button in the automated signal verification software. The substation operation and maintenance personnel can use the microphone to say the digital label corresponding to the button that needs to be clicked on the automated signal verification software, and voice control of the button trigger can be realized, thereby realizing the acceptance of at least one signal to be accepted.

[0046] The above automation UI tree is a root element in the UI automation tree, which represents the system desktop window ("desktop"), and its child elements represent application windows. Each of these child elements can contain elements that represent parts of the UI, such as menus, buttons, toolbars, and list boxes. These elements can contain elements, such as list items. The UI automation tree is not a fixed structure. It rarely appears in its entirety, because it may contain thousands of elements. Some parts of the UI automation tree are required by the client, and the structure of the tree changes as elements are added, moved, or deleted.

[0047] Specifically, the substation operation and maintenance personnel can use voice control to trigger the corresponding digital labels in the automated signal verification software, such as system login, account login, signal verification module, signal acceptance and debugging form, etc., to obtain at least one signal to be accepted and accept at least one signal to be accepted. By voice control, the start button of a signal acceptance is turned on, and the automated signal verification software completes the confirmation of at least one signal to be accepted. Finally, after all the signals on the signal acceptance and debugging form are accepted, the master station personnel will archive the signal acceptance and debugging form that has been accepted from the dispatching automation master station system.

[0048] In summary, in response to the head-mounted intelligent voice control device receiving a signal acceptance and debugging form, the signal acceptance and debugging form is parsed to obtain at least one signal to be accepted; at least one signal to be accepted is displayed on the glasses-like display screen of the head-mounted intelligent voice control device; in response to the microphone sensor of the head-mounted intelligent voice control device collecting a first voice signal, at least one signal to be accepted is accepted based on the first voice signal to obtain an acceptance result of at least one signal to be accepted. It is easy to notice that by accepting at least one signal to be accepted through the first voice signal collected by the microphone sensor of the head-mounted intelligent voice control device, the substation automation operation and maintenance personnel can perform voice control on the automation signal verification software, thereby completing the purpose of the acceptance closed-loop work, thereby achieving the technical effect of improving the work efficiency of the automated acceptance of substation automation equipment, and thus solving the technical problem of low work efficiency of the automated acceptance of substation automation equipment.

[0049] The present application provides a head-mounted intelligent voice control device, which eliminates the need for substation automation operation and maintenance personnel to manually control the automated signal verification software, freeing their hands and reducing the time for clicking and typing. In terms of personnel, one person can be reduced each time (the supervisor on the panel cabinet side also serves as the signal verification personnel) to verify the signal, thereby reducing staff and increasing efficiency.

[0050] Optionally, accepting at least one signal to be accepted based on the first voice signal to obtain an acceptance result of at least one signal to be accepted includes: converting the first voice signal into a first sound signal in electronic form; identifying the first sound signal to obtain an acceptance instruction; accepting at least one signal to be accepted based on the acceptance instruction to obtain an acceptance result.

[0051] Specifically, the first sound signal mentioned above can be used to represent a voice signal in the form of an electronic sound wave obtained by converting the first voice signal.

[0052] The above-mentioned acceptance instruction can be used to represent an instruction obtained by performing text recognition on the first sound signal. The acceptance instruction includes but is not limited to an instruction for voice control of different modules of the automatic signal verification software.

[0053] The above-mentioned acceptance results generally include acceptance success or acceptance failure. In this application, different processing measures can be taken based on different acceptance results.

[0054] In an optional embodiment, in the process of accepting at least one signal to be accepted to obtain a corresponding acceptance result, it is necessary to convert the first voice signal collected by the microphone sensor into the form of an electronic sound wave to obtain a corresponding first sound signal, and then perform text recognition on the first sound signal to obtain a corresponding acceptance instruction, and then accept at least one signal to be accepted based on the acceptance instruction to obtain an acceptance result.

[0055] Generally, the process of converting the first voice signal collected by the microphone sensor into an electronic sound wave to obtain the corresponding first sound signal usually involves analog-to-digital conversion, which includes the following steps: Sampling: First, the voice signal will be sampled, that is, sampled at a certain time interval, usually at a sampling frequency of 1000 times per second or higher; Quantization: The sampled signal will be quantized, that is, the continuous analog signal will be converted into a discrete digital signal. This step divides the amplitude range of the signal into a certain number of levels and quantizes the amplitude value of each sampling point into the closest level; Encoding: The quantized signal will be encoded into a digital form, usually using binary encoding. In this way, the voice signal is converted into an electronic sound wave signal, which can be transmitted, stored and processed digitally.

[0056] In addition, in the process of performing text recognition on the first sound signal to obtain the corresponding acceptance instruction, the following steps can be taken: Audio acquisition: First, the sound signal needs to be acquired through a microphone or other audio acquisition device; Preprocessing: Preprocess the collected sound signal, including noise reduction, filtering and other operations to improve the accuracy of subsequent processing; Feature extraction: Extract features from the preprocessed sound signal, such as speech frequency, energy, sound intensity and other features; Acoustic model: Establish an acoustic model to map sound features to text; Speech recognition: Use speech recognition technology to convert sound signals into text; Text post-processing: Post-process the recognized text, such as spelling checking, grammar correction and other operations to improve recognition accuracy.

[0057] Exemplarily, in the embodiments of the present application, the operating instructions of "system login" can be obtained by performing text recognition on the "system login" sound signal. After logging into the automated system, the operating instructions of "account login" can be obtained by performing text recognition on the "account login" sound signal. After logging into the account and entering the automated signal verification software, the operating instructions of the "signal verification module" can be obtained by performing text recognition on the "signal verification module". After entering the signal verification module, the operating instructions of the "signal acceptance and debugging form" can be obtained by performing text recognition on the "signal acceptance and debugging form" sound signal, so as to display the signal acceptance and debugging form on the glasses-like display screen of the head-mounted intelligent voice control device. Furthermore, the operating instructions of "A signal acceptance" can be obtained by performing text recognition on the "A signal acceptance" sound signal, thereby obtaining the acceptance result of the A signal. By analogy, all signals to be accepted in the signal acceptance and debugging form are accepted.

[0058] Optionally, recognizing the first sound signal to obtain the acceptance instruction includes: preprocessing the first sound signal to obtain a processed signal; converting the processed signal into text data; and recognizing the text data to obtain the acceptance instruction.

[0059] Specifically, the above-mentioned text data can be used to represent text data obtained by performing speech recognition on the processed signal.

[0060] In an optional embodiment, in the process of identifying the first sound signal to obtain the acceptance instruction, the first sound signal can be preprocessed, which helps to improve the accuracy of speech recognition, especially in noisy environments; then, feature extraction and speech recognition are performed on the preprocessed sound signal to obtain converted text data, and then the acceptance instruction corresponding to the first sound signal can be obtained by identifying the text data.

[0061] Among them, feature extraction of the sound signal obtained by preprocessing refers to extracting some representative features from the sound signal for use in the fields of sound recognition, speech synthesis, speech recognition, etc. Common sound signal features include: basic frequency of sound: by performing spectrum analysis on the sound signal, the basic frequency of the sound, that is, the pitch of the sound, can be obtained; energy of sound: the energy of the sound signal can be used to represent the intensity of the sound, and the energy of the sound can be obtained by performing amplitude analysis on the sound signal; spectral characteristics of sound: the spectral characteristics of the sound signal include the spectral distribution of the sound, the spectral envelope, etc., which can be obtained through spectrum analysis; time domain characteristics of sound: the time domain characteristics of the sound signal include the duration, start time, end time, etc. of the sound, which can be obtained through time domain analysis; resonance characteristics of sound: the resonance characteristics of the sound signal include the resonance peak value, resonance frequency, etc. of the sound, which can be obtained through resonance analysis. For feature extraction of sound signals, signal processing techniques such as Fourier transform, short-time Fourier transform, discrete cosine transform, etc. can be used to extract the spectral characteristics of the sound signal; machine learning techniques such as principal component analysis and wavelet transform can also be used to extract the time domain characteristics and frequency domain characteristics of the sound signal. By extracting features from sound signals, we can better understand and identify sound signals, thereby achieving automatic processing and recognition of sound signals.

[0062] In addition, speech recognition of the sound signal obtained by preprocessing can be achieved through the following steps: Feature extraction: convert the sound signal into a recognizable feature vector. Common features include Mel-frequency cepstral coefficients, acoustic features, etc.; Speech recognition model selection: select a suitable speech recognition model. Commonly used models include hidden Markov models, deep learning models (such as recurrent neural networks, long short-term memory networks, convolutional neural networks, etc.); Training model: use the feature vector obtained by preprocessing to train the selected speech recognition model to establish a recognition model; Recognition process: extract features from the sound signal obtained by preprocessing, and then use the trained speech recognition model to recognize the extracted feature vector to obtain the most likely text output; Post-processing: post-process the recognition results, such as adjusting the language model, correcting errors, etc., to improve the recognition accuracy.

[0063] Applied to the embodiments of the present application, the process of recognizing text data can be understood as voice command interpretation, that is, once the voice is recognized and converted into text, the software of the head-mounted intelligent voice control device will interpret the user's command. For example, if the substation automation operation and maintenance personnel say "1", the system will understand that the user wants to click the button on the number label 1.

[0064] Finally, the process of obtaining the acceptance instruction corresponding to the first sound signal by identifying the text data usually involves the use of natural language processing and machine learning techniques. The following are some common methods: word segmentation: the process of breaking down text data into words or phrases in order to better understand and process the text; named entity recognition: identifying specific entities in the text, such as names of people, places, and organizations; part-of-speech tagging: determining the part of speech of each word in the text, such as nouns, verbs, adjectives, etc.; syntactic analysis: analyzing the structure and grammatical relations of sentences in order to understand the meaning of sentences; sentiment analysis: analyzing the emotions and sentiments in the text in order to determine the emotional tendency of the text; topic modeling: identifying topics and keywords in the text in order to understand the main content of the text; machine learning classification algorithm: using machine learning algorithms to classify text, such as text classification, spam filtering, etc. These methods can be used alone or in combination to achieve the recognition and understanding of text data. At the same time, various tools and libraries can also be used to implement these methods.

[0065] Optionally, preprocessing the first sound signal to obtain a processed signal includes: preprocessing the first sound signal by a sound signal processing unit to obtain a processed signal, wherein the preprocessing includes at least one of the following: denoising, sound enhancement and sound analysis.

[0066] Specifically, in the process of preprocessing the first sound signal to obtain the processed signal, the sound signal processing unit can be used to preprocess the first sound signal to obtain the processed signal. For example, since the substation equipment will generate a lot of noise during operation, when the substation operation and maintenance personnel need to perform automated signal acceptance on the substation equipment, the first sound signal needs to be preprocessed to remove background noise in a noisy environment and improve the accuracy of speech recognition.

[0067] Specifically, preprocessing the first sound signal can improve signal quality and enhance features. Common speech signal preprocessing steps include: sampling and quantization of speech signals: converting analog speech signals into digital signals, and sampling and quantizing them; noise removal: removing background noise in speech signals to improve the clarity and distinguishability of speech signals; framing of speech signals: dividing speech signals into small segments of frames, usually with a length of 10-30ms per frame; windowing: windowing each frame of speech signals to reduce signal discontinuity at frame boundaries; stereo signal processing: if the speech signal is stereo, channel separation or mixing is required; frequency domain filtering: filtering to enhance the spectral characteristics of speech signals; pre-emphasis: pre-emphasis of speech signals to increase the energy of high-frequency signals; silence detection and removal: detecting the silence part in the speech signal and removing it to reduce the impact of noise on the speech signal, etc.

[0068] Optionally, converting the processed signal into text data includes: converting the processed signal into fixed weighted parameters through a sound wave analysis algorithm; and converting the processed signal into text data based on the fixed weighted parameters through a speech recognition engine.

[0069] Specifically, the above-mentioned sound wave analysis algorithm is a technology that performs spectrum analysis and feature extraction on speech signals.

[0070] By converting speech signals into fixed weighted parameters, which usually include pitch, volume, spectral characteristics, etc., and mathematically processing and weighting these parameters, the characteristic representation of speech signals can be obtained. This method can be used for the recognition, classification and processing of speech signals, such as speech recognition systems, speech synthesis systems, etc. By converting speech signals into fixed weighted parameters through sound wave analysis algorithms, speech signals can be easily processed and analyzed, thereby realizing various speech applications.

[0071] The above-mentioned fixed weighted parameters can be used to represent the fixed parameters occupied by features such as pitch, volume and spectrum in the speech signal. By weighting these parameters, the feature representation of the speech signal can be obtained.

[0072] The above-mentioned speech recognition engine can be used to represent a technical system that can recognize and understand human speech. It analyzes and processes input speech signals and converts them into text or instructions, thereby realizing human-computer interaction and automated operations.

[0073] Specifically, the text conversion of voice signals through the voice recognition engine includes the following steps: Voice signal acquisition and processing: the voice recognition engine can acquire voice signals through a microphone or other audio devices, and perform digital processing on them, including operations such as denoising, enhancement and decoding; Voice recognition algorithm: the voice recognition engine has built-in various voice recognition algorithms and models, which can analyze and recognize input voice signals, including sound feature extraction, voice pattern recognition and voice-to-text technologies; Natural language processing: the voice recognition engine also needs to be able to understand and process the converted text information, and convert it into executable instructions or semantic understanding; Optimization and improvement: the voice recognition engine needs to continuously optimize and improve algorithms and models to improve recognition accuracy and speed, while adapting to different voice characteristics and environmental conditions.

[0074] In an optional embodiment, in the process of converting the processed signal into text data, it is necessary to convert the processed signal into fixed weighted parameters through a sound wave analysis algorithm. By weighted processing of these parameters, a feature representation of the speech signal can be obtained, and then the processed signal is converted into text based on the speech recognition engine to obtain text data.

[0075] Optionally, accepting at least one signal to be accepted based on the acceptance instruction to obtain an acceptance result includes: determining a target signal in at least one signal to be accepted based on the acceptance instruction; and accepting the target signal through an automated signal verification function to obtain an acceptance result of the target signal.

[0076] Specifically, in the process of accepting at least one signal to be accepted based on the acceptance instruction, it is necessary to determine the target signal from at least one signal to be accepted based on the acceptance instruction, and then use the automated signal verification function carried by the automated signal verification software to accept the target signal to obtain the acceptance result of the target signal.

[0077] Specifically, in the voice control signal acceptance process, according to the voice command of the substation automation operation and maintenance personnel, the device will perform the corresponding acceptance operation: select a certain interval, such as the 500kV A line interval -> select the telemeter / telemeter -> select the telemeter / telemeter signal -> select the start of checking the selected telemeter / telemeter signal -> the signal action is reset, and the device automatically recognizes that the signal is archived in the completed state -> select the next telemeter / telemeter signal, and so on. The acceptance of a certain signal interval is realized through voice control.

[0078] In summary, the substation operation and maintenance personnel use the head-mounted intelligent voice control device to carry out automated acceptance of substation equipment, which includes the following process:

[0079] 1. Automatic UI tree generation: Voice recognition is performed in the automatic UI tree mode. The number of elements corresponding to the opening page of the automatic signal verification software is different. By drawing digital labels on the corresponding UI menu coordinate system, when the substation operation and maintenance personnel turn on the head-mounted intelligent voice control device, the head-mounted intelligent voice control device enters the system desktop (the desktop has been installed with the automatic signal verification software), the automatic UI tree function displays digital labels on the screen of the automatic signal verification software, and each digital label corresponds to the corresponding button in the software;

[0080] 2. Voice input: The substation operation and maintenance personnel wear a head-mounted intelligent voice control device, see the numbers displayed on the automation UI tree through the glasses-like display screen, find the button to be clicked, and say the corresponding number on the corresponding button;

[0081] 3. Sound collection: The internal microphone of the head-mounted intelligent voice control device captures the user's voice input and converts it into electronic sound wave signals;

[0082] 4. Sound processing: The captured sound signal will pass through the internal sound processing unit, which is used for noise removal, sound enhancement and sound analysis, which helps to improve the accuracy of speech recognition, especially in noisy environments;

[0083] 5. Feature extraction: The speech signal is converted into fixed weighted parameters through the sound wave analysis algorithm;

[0084] 6. Voice recognition: The head-mounted intelligent voice control device has a built-in voice recognition engine, which converts the sound-processed signal into text form. This step is critical because it determines whether the device can accurately understand the user's voice commands;

[0085] 7. Voice command interpretation: Once the voice is recognized and converted into text, the software of the head-mounted intelligent voice control device will interpret the user's command. For example, if the substation automation operation and maintenance personnel say "1", the system will understand that the user wants to click the button on the number label 1;

[0086] 8. Signal acceptance operation: According to the instructions of the substation operation and maintenance personnel, the head-mounted intelligent voice control device will perform the corresponding acceptance operation. The acceptance of a certain signal interval is realized through voice control.

[0087] Optionally, the method also includes: in response to the acceptance result of any one of the at least one signal to be accepted being accepted, adjusting the display position of any one of the signals to be accepted on the glasses-type display screen to a preset position, wherein the preset position is used to characterize that any one of the signals to be accepted is displayed at the bottom of at least one signal to be accepted; in response to the acceptance result of any one of the at least one signal to be accepted being accepted failed, controlling the display position of any one of the signals to be accepted on the glasses-type display screen to remain unchanged.

[0088] Specifically, in the process of accepting at least one signal to be accepted, if the acceptance result of any one of the at least one signal to be accepted is passed, that is, there is no need to perform a second acceptance on the acceptance signal, then the display position of any one of the signals to be accepted on the glasses-type display screen is adjusted to a preset position, that is, the any one of the signals to be accepted is adjusted to the bottom of at least one signal to be accepted; conversely, if the acceptance result of any one of the at least one signal to be accepted is failed, it means that the signal needs to be accepted twice or even multiple times. Therefore, it is necessary to control the display position of any one of the signals to be accepted on the glasses-type display screen to remain unchanged.

[0089] It should be noted that in the display list of at least one signal to be accepted, only the signal that has passed the acceptance can be adjusted to the bottom of the list, and the signal that has not passed the acceptance cannot be adjusted to the current position until the operation and maintenance personnel check that the signal transmission problem can be correctly occurred. After the entire interval acceptance is completed, the master station personnel will archive the commissioning order of the accepted interval from the dispatching automation master station system.

[0090] Optionally, the method also includes: determining a target page to be currently displayed on the glasses-type display screen; generating digital labels for different controls included in the target page through automated verification software; displaying the target page on the glasses-type display screen, and displaying digital labels on the target page.

[0091] Specifically, the above-mentioned target page can be used to represent any interface to be displayed after logging into the automated verification software, wherein different interfaces have different corresponding elements and list items. Therefore, it is necessary to generate digital labels for different spaces contained in the target page after determining the target page.

[0092] The above-mentioned different controls can be used to represent the sub-elements contained in the automation UI tree, which include but are not limited to menus, buttons, toolbars, and list boxes.

[0093] The above digital labels can be used to represent the labels for digitally marking each of the above sub-elements. It should be noted that different sub-elements should be marked with different labels. The same sub-element cannot be marked with multiple digital labels or the same digital label cannot correspond to multiple sub-elements.

[0094] In an optional embodiment, before using digital labels to trigger voice control of corresponding buttons in the automated verification software, it is necessary to determine the target page currently to be displayed on the glasses-like display screen, and then generate digital labels for different controls contained in the target page based on different sub-elements contained in different target pages, and then display the target page on the glasses-like display screen while displaying the digital labels corresponding to different controls on the target page.

[0095] Specifically, the digital labels can be drawn in the menu coordinate system on the automated UI tree. Specifically, the system analyzes the application UI and draws the digital labels in the corresponding UI menu coordinate system; caches and sorts the commands according to the number of analyzed voice commands; binds UI events to their corresponding voice commands; and forms an imperative voice menu to obtain digital labels for different controls contained in the target page.

[0096] Optionally, the method further includes: in response to the microphone sensor collecting a second voice signal, determining a target control selected on the target page based on the second voice signal; executing the target control to obtain an execution result; and displaying the execution result on a glasses-type display screen.

[0097] Specifically, the second voice signal mentioned above can be used to represent the signal sent by the substation operation and maintenance personnel based on the button operation that needs to be performed in the next step.

[0098] The target control mentioned above can be used to represent the control corresponding to the button that needs to be executed in the next step.

[0099] In an optional embodiment, after the substation operation and maintenance personnel have completed the acceptance of the current signal to be accepted, if it is necessary to accept the next signal to be accepted in the signal acceptance and debugging list, a second voice signal can be collected through the microphone sensor in the head-mounted intelligent voice control device, wherein the second voice signal carries the signal sent by the substation operation and maintenance personnel based on the button operation that needs to be performed in the next step, and then the target control selected on the target page is determined based on the second voice signal, and the execution result can be obtained by executing the target control, which is used to indicate whether the current signal to be accepted is accepted successfully, and then the execution result is displayed on the eye-type display screen.

[0100] For example, when the substation operation and maintenance personnel says "2", the head-mounted intelligent voice control device will understand that the substation operation and maintenance personnel needs to click the button on the digital label "2", and then the head-mounted intelligent voice control device will perform the corresponding operation to accept the current signal to be accepted.

[0101] Optionally, determining a target control selected on a target page based on a second voice signal includes: converting the second voice signal into a second sound signal in electronic form; identifying the second sound signal to obtain a target digital label; and determining that a control corresponding to the target digital label is the target control.

[0102] Specifically, the second sound signal mentioned above can be used to represent a voice signal in the form of an electronic sound wave obtained by converting the second voice signal.

[0103] The above-mentioned target digital label can be used to represent the digital label corresponding to the target sub-element on the automation UI tree obtained based on the matching of the recognition result of the second sound signal.

[0104] For example, based on the recognition result of the second sound signal, it can be known that the substation operation and maintenance personnel need to trigger button "2", so it is determined that the corresponding target digital label may be a button marked with the number "2".

[0105] In an optional embodiment, in the process of determining the target control selected on the target page based on the second voice signal, the second voice signal is converted into a second sound signal in the form of an electronic sound wave, and then the second sound signal is recognized based on the voice recognition engine in the head-mounted intelligent voice control device to obtain the target digital label, and then the control corresponding to the target digital label is determined as the target control.

[0106] Optionally, the method further includes: in response to the signal acceptance that the debugging form has been accepted, storing the accepted debugging form in a database.

[0107] Specifically, after the acceptance of all the signals to be accepted in the signal acceptance and debugging list is completed, the accepted debugging list needs to be stored in the database.

[0108] It should be noted that in the process of accepting all the signals to be accepted in the signal acceptance and debugging form, since some signals to be accepted are successfully accepted once, while some signals to be accepted are successfully accepted after multiple acceptances, before storing the accepted debugging form in the database, it is necessary to record the acceptance log of each signal to be accepted, that is, the log records the acceptance time and number of acceptances of each signal to be accepted, and stores the first validity period for the signals to be accepted that are successfully accepted once, and stores the second validity period for the signals to be accepted that are successfully accepted multiple times, wherein the second validity period is greater than the first validity period, and sets the validity period storage time of the signals to be accepted that are successfully accepted multiple times to be greater than the validity period storage time of the signals to be accepted that are successfully accepted once, so that when the next operation and maintenance failure of the substation equipment occurs, the acceptance log stored in the database can be used to troubleshoot the problem of the signals to be accepted that were successfully accepted multiple times last time, thereby improving the troubleshooting efficiency of the substation equipment.

[0109] Example 2

[0110] According to an embodiment of the present invention, a signal acceptance device is provided, which can execute a signal acceptance method provided in the above-mentioned embodiment 1. The specific implementation method and preferred application scenario are the same as those of the above-mentioned embodiment 1, and will not be repeated here.

[0111] Figure 2 is a schematic diagram of a signal acceptance device according to an embodiment of the present invention. Figure 2 As shown, the device comprises:

[0112] The parsing module 202 is used for parsing the signal acceptance and debugging form in response to the head-mounted intelligent voice control device receiving the signal acceptance and debugging form to obtain at least one signal to be accepted;

[0113] A display module 204, configured to display at least one signal to be accepted on a glasses-like display screen of the head-mounted intelligent voice control device;

[0114] The acceptance module 206 is used to accept at least one signal to be accepted based on the first voice signal in response to the microphone sensor of the head-mounted intelligent voice control device collecting the first voice signal, and obtain an acceptance result of the at least one signal to be accepted.

[0115] Optionally, the acceptance module 206 includes: a conversion unit, used to convert the first voice signal into a first sound signal in electronic form; a recognition unit, used to recognize the first sound signal and obtain an acceptance instruction; and a signal acceptance unit, used to accept at least one signal to be accepted based on the acceptance instruction and obtain an acceptance result.

[0116] Optionally, the recognition unit includes: a preprocessing unit, used to preprocess the first sound signal to obtain a processed signal; a signal conversion unit, used to convert the processed signal into text data; and a data recognition unit, used to recognize the text data to obtain an acceptance instruction.

[0117] Optionally, the preprocessing unit includes: a signal preprocessing unit, configured to preprocess the first sound signal through the sound signal processing unit to obtain a processed signal, wherein the preprocessing includes at least one of the following: denoising, sound enhancement and sound analysis.

[0118] Optionally, the signal conversion unit includes: a parameter acquisition unit, used to convert the processed signal into fixed weighted parameters through a sound wave analysis algorithm; and a text data acquisition unit, used to convert the processed signal into text data based on the fixed weighted parameters through a speech recognition engine.

[0119] Optionally, the signal acceptance unit includes: a target signal determination unit, used to determine a target signal among at least one signal to be accepted based on an acceptance instruction; and a target signal acceptance unit, used to accept the target signal through an automated signal verification function to obtain an acceptance result of the target signal.

[0120] Optionally, the device also includes: an adjustment module, used to adjust the display position of any one of the at least one signal to be accepted on the glasses-type display screen to a preset position in response to the acceptance result of any one of the at least one signal to be accepted being accepted, wherein the preset position is used to characterize that any one of the signals to be accepted is displayed at the bottom of at least one signal to be accepted; and a control module, used to control the display position of any one of the at least one signal to be accepted on the glasses-type display screen to remain unchanged in response to the acceptance result of any one of the at least one signal to be accepted being accepted failed.

[0121] Optionally, the device also includes: a target page determination module, used to determine the target page to be currently displayed on the glasses-type display screen; a digital label generation module, used to generate digital labels for different controls contained in the target page through automated verification software; and a display module, used to display the target page on the glasses-type display screen and display the digital label on the target page.

[0122] Optionally, the device also includes: a target control determination module, used to determine the target control selected on the target page based on the second voice signal collected by the microphone sensor in response to the second voice signal; an execution module, used to execute the target control and obtain an execution result; and a result display module, used to display the execution result on a glasses-like display screen.

[0123] Optionally, the target control determination module includes: a signal conversion unit, used to convert the second voice signal into a second sound signal in electronic form; a signal recognition unit, used to recognize the second sound signal to obtain a target digital label; and a target control determination unit, used to determine that the control corresponding to the target digital label is the target control.

[0124] Optionally, the device further comprises: a storage module, configured to store the accepted debugging form in a database in response to the signal acceptance debugging form being accepted.

[0125] Example 3

[0126] An embodiment of the present application further provides an electronic device, comprising: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of the present invention when running.

[0127] Example 4

[0128] An embodiment of the present application further provides a computer-readable storage medium, which includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the methods in various embodiments of the present invention.

[0129] Example 5

[0130] An embodiment of the present application further provides a computer program product, including a computer program, which implements the methods in various embodiments of the present invention when executed by a processor.

[0131] Example 6

[0132] An embodiment of the present application further provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium is used to store a computer program, and when the computer program is executed by a processor, the method in each embodiment of the present invention is implemented.

[0133] Example 7

[0134] The embodiments of the present application further provide a computer program, which implements the methods in the above-mentioned embodiments of the present invention when executed by a processor.

[0135] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0136] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0137] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0138] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0139] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0140] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk, etc. Various media that can store program codes.

[0141] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A signal acceptance method, characterized in that: include: In response to the head-mounted intelligent voice control device receiving the signal acceptance and debugging form, parsing the signal acceptance and debugging form to obtain at least one signal to be accepted; Displaying the at least one signal to be accepted on a glasses-like display screen of the head-mounted intelligent voice control device; In response to a microphone sensor of the head-mounted intelligent voice control device collecting a first voice signal, performing acceptance on the at least one signal to be accepted based on the first voice signal to obtain an acceptance result of the at least one signal to be accepted; Among them, the at least one signal to be accepted is displayed on the glasses-like display screen of the head-mounted intelligent voice control device, and in response to the microphone sensor of the head-mounted intelligent voice control device collecting a first voice signal, the at least one signal to be accepted is accepted based on the first voice signal, including: an automation UI tree is loaded on the glasses-like display screen of the head-mounted intelligent voice control device, and the automation UI tree displays digital labels on the interface of the automation verification signal software, wherein each digital label corresponds to a corresponding button in the automation verification signal software, and the substation operation and maintenance personnel speak the digital label corresponding to the button that needs to be clicked on the automation verification signal software through the microphone sensor to realize voice control of the button trigger, so as to realize the acceptance of the at least one signal to be accepted.

2. The signal acceptance method according to claim 1, characterized in that: Accepting the at least one signal to be accepted based on the first voice signal to obtain an acceptance result of the at least one signal to be accepted, including: converting the first speech signal into a first sound signal in electronic form; Recognizing the first sound signal to obtain an acceptance instruction; The at least one signal to be accepted is accepted based on the acceptance instruction to obtain the acceptance result.

3. The signal acceptance method according to claim 2, characterized in that: Recognizing the first sound signal to obtain an acceptance instruction includes: Preprocessing the first sound signal to obtain a processed signal; converting the processed signal into text data; The text data is identified to obtain the acceptance instruction.

4. The signal acceptance method according to claim 3, characterized in that: Preprocessing the first sound signal to obtain a processed signal includes: The first sound signal is preprocessed by a sound signal processing unit to obtain the processed signal, wherein the preprocessing includes at least one of the following: denoising, sound enhancement and sound analysis.

5. The signal acceptance method according to claim 3, characterized in that: Converting the processed signal into text data includes: converting the processed signal into fixed weighted parameters by an acoustic wave analysis algorithm; The processed signal is converted into the text data based on the fixed weighting parameters by a speech recognition engine.

6. The signal acceptance method according to claim 2, characterized in that: Performing acceptance on the at least one signal to be accepted based on the acceptance instruction to obtain the acceptance result includes: Determine a target signal in the at least one signal to be accepted based on the acceptance instruction; The target signal is accepted through an automated signal checking function to obtain an acceptance result of the target signal.

7. The signal acceptance method according to claim 1, characterized in that: Also includes: In response to the acceptance result of any one of the at least one signal to be accepted being accepted, adjusting the display position of the any one of the signals to be accepted on the glasses-type display screen to a preset position, wherein the preset position is used to indicate that the any one of the signals to be accepted is displayed at the bottom of the at least one signal to be accepted; In response to the acceptance result of any one of the at least one signal to be accepted being acceptance failure, the display position of the any one signal to be accepted on the glasses-type display screen is controlled to remain unchanged.

8. The signal acceptance method according to claim 1, characterized in that: Also includes: Determining a target page to be currently displayed on the glasses-type display screen; Generate digital labels of different controls included in the target page by automated checking software; The target page is displayed on the glasses-type display screen, and the digital label is displayed on the target page.

9. The signal acceptance method according to claim 8, characterized in that: Also includes: In response to the microphone sensor collecting a second voice signal, determining a target control selected on the target page based on the second voice signal; Execute the target control to obtain an execution result; The execution result is displayed on the glasses-type display screen.

10. The signal acceptance method according to claim 9, characterized in that: Determining a selected target control on the target page based on the second voice signal includes: converting the second speech signal into a second sound signal in electronic form; Recognizing the second sound signal to obtain a target digital label; Determine that the control corresponding to the target digital label is the target control.

11. The signal acceptance method according to claim 1, characterized in that: Also includes: In response to the signal acceptance and the debugging form being accepted, the debug form after acceptance is stored in the database.

12. A signal acceptance device, characterized in that: include: An analysis module, configured to analyze the signal acceptance and debugging form in response to the head-mounted intelligent voice control device receiving the signal acceptance and debugging form, and obtain at least one signal to be accepted; A display module, configured to display the at least one signal to be accepted on a glasses-like display screen of the head-mounted intelligent voice control device; An acceptance module, configured to, in response to a microphone sensor of the head-mounted intelligent voice control device collecting a first voice signal, accept the at least one signal to be accepted based on the first voice signal to obtain an acceptance result of the at least one signal to be accepted; Among them, the display module and the acceptance module are also used to load an automated UI tree on the glasses-like display screen of the head-mounted intelligent voice control device, and the automated UI tree displays digital labels on the interface of the automated signal verification software, wherein each digital label corresponds to a corresponding button in the automated signal verification software, and the substation operation and maintenance personnel use the microphone sensor to speak the digital label corresponding to the button that needs to be clicked on the automated signal verification software to realize voice control of the button trigger, so as to realize acceptance of the at least one signal to be accepted.

13. An electronic device, characterized in that: include: A memory storing an executable program; A processor, configured to run the program, wherein the program executes the method according to any one of claims 1 to 11 when running.

14. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is executed, the device where the storage medium is located is controlled to execute the method according to any one of claims 1 to 11.

15. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 11.

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