Voice-controlled lamp operation data intelligent analysis system

Abstract

The present invention relates to an intelligent analysis system for operation data of a voice-controlled lamp, comprising: a parameter analysis device for analyzing the predicted value of the power consumption value and the predicted value of the number of light-on times of the voice-controlled lamp in the future time interval based on the self-extinguishing time of the voice-controlled lamp, various related information of the voice-controlled lamp, the corresponding power consumption values ​​of the voice-controlled lamp in various historical time intervals, and the corresponding number of light-on times of the voice-controlled lamp using a single-layer neural network model; a wireless reporting device for wirelessly reporting the analyzed predicted value to a big data management network element. Through the present invention, a single-layer neural network model with a customized structure can be cited to simultaneously analyze the predicted value of the power consumption value and the predicted value of the number of light-on times of the voice-controlled lamp in the future time interval based on various basic information selected in a targeted manner, thereby providing valuable reference information for subsequent energy consumption management and life prediction.

Description

Technical Field

[0001] The present invention relates to the field of electricity consumption monitoring, and in particular to an intelligent analysis system for operation data of a voice-controlled lamp. Background Art

[0002] The voice-controlled lamp is a voice-controlled electronic lighting device, which is composed of an audio amplifier, a frequency selection circuit, a delay opening circuit and a thyristor circuit. It provides a voice-controlled lamp that is easy to operate, flexible, has strong anti-interference ability and is sensitive to control. It uses a control signal sound of about 1 second from the human mouth to conveniently and timely open and close the voice-controlled lighting device, and has an automatic delay closing function to prevent false triggering. Some of them are equipped with manual switches, making their application more convenient. The voice-controlled lamp is composed of a microphone, an audio amplifier, a frequency selection circuit, a voltage doubler rectifier circuit, an amplitude detection circuit, a constant voltage source circuit, a delay opening circuit, a controllable delay switch circuit and a thyristor circuit.

[0003] For voice-controlled lights, the number of times they are turned on and the power consumption data are difficult to predict, resulting in a lack of key reference data for the power distribution management and service life analysis of voice-controlled lights. At the same time, there is no analysis mechanism that can predict the number of times voice-controlled lights are turned on and the power consumption data. Summary of the invention

[0004] In order to solve the technical problems in the related fields, the present invention provides a voice-controlled lamp operation data intelligent analysis system, which refers to a sequential training mechanism for sequentially performing multiple training operations on a single-layer neural network to obtain a single-layer neural network after completing the multiple training operations, and outputs the single-layer neural network after completing the multiple training operations as a single-layer neural network model. The number of training operations performed by the single-layer neural network is positively correlated with the lighting duration of the voice-controlled lamp, thereby providing a customized structure artificial intelligence model for the subsequent intelligent analysis of the power consumption value and the number of times the voice-controlled lamp is turned on in the future time interval, and refers to the self-extinguishing time of the voice-controlled lamp, various related information of the voice-controlled lamp, and the corresponding power consumption values ​​of the voice-controlled lamp in each historical time interval and the corresponding number of times the voice-controlled lamp is turned on as various basic information participating in the intelligent analysis. Specifically, the various related information of the voice-controlled lamp is the lighting duration, rated power and voice control amplitude of the voice-controlled lamp. The lighting duration of the voice-controlled lamp is the interval between the moment of turning on the lamp and the moment of outputting stable brightness of the voice-controlled lamp, thereby ensuring the reliability and stability of the intelligent analysis results.

[0005] According to the present invention, a sound-controlled lamp operation data intelligent analysis system is provided, the system comprising:

[0006] A sequential training mechanism, used for sequentially performing multiple training operations on a single-layer neural network to obtain a single-layer neural network after completing the multiple training operations, and outputting the single-layer neural network after completing the multiple training operations as a single-layer neural network model;

[0007] A lamp body collecting mechanism is used to collect various related information of the voice-controlled lamp body located in the corridor to obtain various related information of the voice-controlled lamp body, wherein the various related information of the voice-controlled lamp body is the lighting time, rated power and voice control amplitude of the voice-controlled lamp body;

[0008] An information acquisition mechanism, used for acquiring the respective power consumption values ​​and the respective light-on times corresponding to the voice-controlled lamp body in each historical time interval;

[0009] A parameter analysis device is connected to the sequential training mechanism, the lamp collection mechanism and the information capture mechanism respectively, and is used to use the self-extinguishing time of the voice-controlled lamp, various associated information of the voice-controlled lamp, various power consumption values ​​corresponding to the voice-controlled lamp in various historical time intervals, and various corresponding light-on times as various input contents of the single-layer neural network model, so as to run the single-layer neural network model and obtain the predicted value of the power consumption value and the predicted value of the light-on times of the voice-controlled lamp in the future time interval output by the single-layer neural network model;

[0010] A wireless reporting device, connected to the parameter analysis device, for wirelessly reporting the predicted value of the power consumption value and the predicted value of the number of times the voice-controlled lamp is turned on in a future time interval to a remote big data management network element;

[0011] The sequential training mechanism is used to sequentially perform multiple training operations on the single-layer neural network to obtain the single-layer neural network after completing the multiple training operations, and output the single-layer neural network after completing the multiple training operations as a single-layer neural network model, including: the number of training operations performed by the single-layer neural network is positively correlated with the lighting time of the voice-controlled lamp body;

[0012] Among them, the lamp body collection mechanism is used to collect various related information of the voice-controlled lamp body located in the corridor to obtain various related information of the voice-controlled lamp body. The various related information of the voice-controlled lamp body are the lighting duration of the voice-controlled lamp body, the rated power and the voice control amplitude, including: the lighting duration of the voice-controlled lamp body is the interval between the moment the voice-controlled lamp body is turned on and the moment the stable brightness is output.

[0013] It can be seen that the present invention has at least the following three important inventive features:

[0014] Firstly: a sequential training mechanism is used to sequentially perform multiple training operations on a single-layer neural network to obtain a single-layer neural network after completing multiple training operations, and the single-layer neural network after completing multiple training operations is output as a single-layer neural network model, and the number of training operations performed by the single-layer neural network is positively correlated with the lighting duration of the voice-controlled lamp, thereby providing a customized artificial intelligence model for intelligent analysis of the power consumption value and the number of times the voice-controlled lamp is turned on in the future time interval;

[0015] Secondly, the self-extinguishing time of the voice-controlled lamp, various related information of the voice-controlled lamp, the corresponding power consumption values ​​of the voice-controlled lamp in each historical time interval, and the corresponding number of times the lamp is turned on are used as the basic information for intelligent analysis;

[0016] Finally, specifically, the various related information of the voice-controlled lamp body is the lighting duration of the voice-controlled lamp body, the rated power and the voice control amplitude. The lighting duration of the voice-controlled lamp body is the interval between the moment the voice-controlled lamp body is turned on and the moment the stable brightness is output, thereby ensuring the reliability and stability of the intelligent analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The embodiments of the present invention will be described below with reference to the accompanying drawings, wherein:

[0018] Figure 1 It is a structural block diagram of a sound-controlled lamp operation data intelligent analysis system according to implementation scheme A of the present invention.

[0019] Figure 2 It is a structural block diagram of a sound-controlled lamp operation data intelligent analysis system according to implementation scheme B of the present invention.

[0020] Figure 3 It is a structural block diagram of a sound-controlled lamp operation data intelligent analysis system according to implementation scheme C of the present invention. DETAILED DESCRIPTION

[0021] The implementation scheme of the sound-controlled lamp operation data intelligent analysis system of the present invention will be described in detail below with reference to the accompanying drawings.

[0022] Figure 1 The structure block diagram of the intelligent analysis system of the operation data of the voice-controlled lamp body according to the embodiment A of the present invention is shown, and the system comprises:

[0023] A sequential training mechanism, used for sequentially performing multiple training operations on a single-layer neural network to obtain a single-layer neural network after completing the multiple training operations, and outputting the single-layer neural network after completing the multiple training operations as a single-layer neural network model;

[0024] A lamp body collecting mechanism is used to collect various related information of the voice-controlled lamp body located in the corridor to obtain various related information of the voice-controlled lamp body, wherein the various related information of the voice-controlled lamp body is the lighting time, rated power and voice control amplitude of the voice-controlled lamp body;

[0025] For example, the lamp body collection mechanism is used to collect various related information of the voice-controlled lamp body located in the corridor to obtain various related information of the voice-controlled lamp body, wherein the various related information of the voice-controlled lamp body is the lighting time, rated power and voice control amplitude of the voice-controlled lamp body, including: the voice-controlled lamp body has a built-in sound sensor and a main controller;

[0026] An information acquisition mechanism, used for acquiring the respective power consumption values ​​and the respective light-on times corresponding to the voice-controlled lamp body in each historical time interval;

[0027] A parameter analysis device is connected to the sequential training mechanism, the lamp collection mechanism and the information capture mechanism respectively, and is used to use the self-extinguishing time of the voice-controlled lamp, various associated information of the voice-controlled lamp, various power consumption values ​​corresponding to the voice-controlled lamp in various historical time intervals, and various corresponding light-on times as various input contents of the single-layer neural network model, so as to run the single-layer neural network model and obtain the predicted value of the power consumption value and the predicted value of the light-on times of the voice-controlled lamp in the future time interval output by the single-layer neural network model;

[0028] A wireless reporting device, connected to the parameter analysis device, for wirelessly reporting the predicted value of the power consumption value and the predicted value of the number of times the voice-controlled lamp is turned on in a future time interval to a remote big data management network element;

[0029] The sequential training mechanism is used to sequentially perform multiple training operations on the single-layer neural network to obtain the single-layer neural network after completing the multiple training operations, and output the single-layer neural network after completing the multiple training operations as a single-layer neural network model, including: the number of training operations performed by the single-layer neural network is positively correlated with the lighting time of the voice-controlled lamp body;

[0030] The lamp collection mechanism is used to collect various related information of the voice-controlled lamp located in the corridor to obtain various related information of the voice-controlled lamp, wherein the various related information of the voice-controlled lamp is the lighting duration, rated power and voice control amplitude of the voice-controlled lamp, including: the lighting duration of the voice-controlled lamp is the interval between the moment of turning on the lamp and the moment of stable brightness output of the voice-controlled lamp;

[0031] The lamp collection mechanism is used to collect various related information of the voice-controlled lamp located in the corridor to obtain various related information of the voice-controlled lamp, wherein the various related information of the voice-controlled lamp is the lighting duration, rated power and voice control amplitude of the voice-controlled lamp, including: the voice control amplitude of the voice-controlled lamp is the sound amplitude that triggers the voice-controlled lamp to turn on the lamp;

[0032] Among them, the self-extinguishing time of the voice-controlled lamp, various associated information of the voice-controlled lamp, various power consumption values ​​corresponding to the voice-controlled lamp in various historical time intervals, and various corresponding light-on times are used as various input contents of the single-layer neural network model to run the single-layer neural network model, and obtain the predicted value of the power consumption value and the predicted value of the light-on times of the voice-controlled lamp in the future time interval output by the single-layer neural network model, including: the self-extinguishing time of the voice-controlled lamp is the interval time between the light-on moment and the light-off moment of the voice-controlled lamp;

[0033] And wherein, the self-extinguishing time of the voice-controlled lamp, various related information of the voice-controlled lamp, the corresponding power consumption values ​​of the voice-controlled lamp in each historical time interval and the corresponding number of times the lamp is turned on are used as various input contents of the single-layer neural network model to run the single-layer neural network model, and obtain the predicted value of the power consumption value and the predicted value of the number of times the voice-controlled lamp is turned on in the future time interval output by the single-layer neural network model, which also includes: the various historical time intervals and the future time intervals form a complete time segment on the time axis and the duration of each time interval is equal.

[0034] Figure 2 It is a structural block diagram of a sound-controlled lamp operation data intelligent analysis system according to implementation scheme B of the present invention.

[0035] Compared with the implementation scheme A, the intelligent analysis system for voice-controlled lamp operation data shown in the implementation scheme B of the present invention may also include:

[0036] A voltage measuring mechanism, connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, respectively, for measuring the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism respectively;

[0037] Wherein, the voltage measuring mechanism is respectively connected with the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, and is used to respectively measure the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, including: the voltage measuring mechanism includes a plurality of voltage measuring units, which are respectively connected with the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, so as to complete the measurement of the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism;

[0038] Wherein, the voltage measurement mechanism includes a plurality of voltage measurement units, which are used to be respectively connected with the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism to complete the measurement of the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism respectively, including: the plurality of voltage measurement units are a plurality of voltage sensing circuits, which are used to be respectively connected with the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism to complete the measurement of the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism respectively;

[0039] Wherein, the multiple voltage measurement units are multiple voltage sensing circuits, which are used to be connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism respectively, so as to complete the measurement of the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism respectively, including: the structures of the multiple voltage sensing circuits are the same;

[0040] And wherein, the multiple voltage measurement units are multiple voltage sensing circuits, which are used to be respectively connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism to complete the respective measurements of the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, and also include: the multiple voltage sensing circuits have the same voltage measurement upper limit value and voltage measurement lower limit value.

[0041] Figure 3 It is a structural block diagram of a sound-controlled lamp operation data intelligent analysis system according to implementation scheme C of the present invention.

[0042] Compared with implementation scheme A, the intelligent analysis system for voice-controlled lamp operation data shown in implementation scheme C of the present invention may also include:

[0043] A field configuration interface, connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the multiple voltage sensing circuits of the information capture mechanism, respectively, for real-time configuration of the operation configuration parameters of the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism;

[0044] Wherein, the field configuration interface is respectively connected to the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, and is used to configure the operation configuration parameters of the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism in real time, including: the field configuration interface is a serial configuration interface;

[0045] And wherein, the field configuration interface is respectively connected to the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, and is used to configure the operating configuration parameters of the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism in real time, including: for the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, the field configuration interface uses different configuration addresses to configure the operating configuration parameters of the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism in real time.

[0046] In addition, in the voice-controlled lamp operation data intelligent analysis system, the self-extinguishing time of the voice-controlled lamp, the various related information of the voice-controlled lamp, the various corresponding power consumption values ​​of the voice-controlled lamp in each historical time interval, and the various corresponding light-on times are used as various input contents of the single-layer neural network model to run the single-layer neural network model to obtain the predicted value of the power consumption value of the voice-controlled lamp in the future time interval and the predicted value of the light-on times output by the single-layer neural network model. It also includes: using a numerical simulation mode to realize the test and simulation of the data processing process of using the self-extinguishing time of the voice-controlled lamp, the various related information of the voice-controlled lamp, the various corresponding power consumption values ​​of the voice-controlled lamp in each historical time interval, and the various corresponding light-on times as various input contents of the single-layer neural network model to run the single-layer neural network model to obtain the predicted value of the power consumption value of the voice-controlled lamp in the future time interval and the predicted value of the light-on times output by the single-layer neural network model.

[0047] The intelligent analysis system for the operation data of the voice-controlled lamp of the present invention is used to address the technical problem in the prior art that it is impossible to simultaneously predict the power consumption value and the number of times the voice-controlled lamp is turned on in a future time period. By referring to a single-layer neural network model with a customized structure, the predicted value of the power consumption value and the predicted value of the number of times the voice-controlled lamp is turned on in a future time period are simultaneously analyzed based on targeted selected basic information, thereby providing valuable reference information for subsequent energy consumption management and life prediction, thereby solving the above technical problem.

[0048] The preferred embodiments of the present invention have been discussed in detail so far, but these embodiments are only specific examples used to clarify the technical content of the present invention. Therefore, the present invention should not be considered to be limited to these specific examples. The spirit and scope of the present invention are limited only by the appended claims.

Claims

1. A voice-controlled lamp operation data intelligent analysis system, characterized in that: The system comprises: A sequential training mechanism, used for sequentially performing multiple training operations on a single-layer neural network to obtain a single-layer neural network after completing the multiple training operations, and outputting the single-layer neural network after completing the multiple training operations as a single-layer neural network model; A lamp body collecting mechanism is used to collect various related information of the voice-controlled lamp body located in the corridor to obtain various related information of the voice-controlled lamp body, wherein the various related information of the voice-controlled lamp body is the lighting time, rated power and voice control amplitude of the voice-controlled lamp body; An information acquisition mechanism, used to obtain the respective power consumption values ​​and the respective lighting times corresponding to the voice-controlled lamp body in each historical time interval; A parameter analysis device is connected to the sequential training mechanism, the lamp collection mechanism and the information capture mechanism respectively, and is used to use the self-extinguishing time of the voice-controlled lamp, various associated information of the voice-controlled lamp, various power consumption values ​​corresponding to the voice-controlled lamp in various historical time intervals, and various corresponding light-on times as various input contents of the single-layer neural network model, so as to run the single-layer neural network model and obtain the predicted value of the power consumption value and the predicted value of the light-on times of the voice-controlled lamp in the future time interval output by the single-layer neural network model; A wireless reporting device, connected to the parameter analysis device, for wirelessly reporting the predicted value of the power consumption value and the predicted value of the number of times the voice-controlled lamp is turned on in a future time interval to a remote big data management network element; The sequential training mechanism is used to sequentially perform multiple training operations on the single-layer neural network to obtain the single-layer neural network after completing the multiple training operations, and output the single-layer neural network after completing the multiple training operations as a single-layer neural network model, including: the number of training operations performed by the single-layer neural network is positively correlated with the lighting time of the voice-controlled lamp body; Among them, the lamp body collection mechanism is used to collect various related information of the voice-controlled lamp body located in the corridor to obtain various related information of the voice-controlled lamp body. The various related information of the voice-controlled lamp body are the lighting duration of the voice-controlled lamp body, the rated power and the voice control amplitude, including: the lighting duration of the voice-controlled lamp body is the interval between the moment the voice-controlled lamp body is turned on and the moment the stable brightness is output.

2. The intelligent analysis system for voice-controlled lamp operation data according to claim 1, characterized in that: The lamp body collecting mechanism is used to collect various related information of the voice-controlled lamp body located in the corridor to obtain various related information of the voice-controlled lamp body, wherein the various related information of the voice-controlled lamp body is the lighting duration, rated power and voice control amplitude of the voice-controlled lamp body, including: the voice control amplitude of the voice-controlled lamp body is the sound amplitude that triggers the voice-controlled lamp body to perform the light-on action; Among them, the self-extinguishing time of the voice-controlled lamp, various associated information of the voice-controlled lamp, various power consumption values ​​corresponding to the voice-controlled lamp in various historical time intervals, and various corresponding light-on times are used as various input contents of the single-layer neural network model to run the single-layer neural network model, and obtain the predicted value of the power consumption value and the predicted value of the light-on times of the voice-controlled lamp in the future time interval output by the single-layer neural network model, including: the self-extinguishing time of the voice-controlled lamp is the interval time between the light-on moment and the light-off moment of the voice-controlled lamp; Among them, the self-extinguishing time of the voice-controlled lamp, various related information of the voice-controlled lamp, the corresponding power consumption values ​​of the voice-controlled lamp in each historical time interval and the corresponding number of times the lamp is turned on are used as various input contents of the single-layer neural network model to run the single-layer neural network model, and obtain the predicted value of the power consumption value and the predicted value of the number of times the voice-controlled lamp is turned on in the future time interval output by the single-layer neural network model, which also includes: the various historical time intervals and the future time intervals form a complete time segment on the time axis and the duration of each time interval is equal.

3. The intelligent analysis system for voice-controlled lamp operation data according to claim 2, characterized in that: The system further comprises: A voltage measuring mechanism, connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, respectively, for measuring the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism respectively; Among them, the voltage measuring mechanism is respectively connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, and is used to respectively measure the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism. The voltage measuring mechanism includes multiple voltage measuring units, which are respectively connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism to complete the respective measurements of the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism.

4. The intelligent analysis system for voice-controlled lamp operation data according to claim 3, characterized in that: The voltage measuring mechanism includes a plurality of voltage measuring units, which are used to be respectively connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism to complete the respective measurements of the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism. The plurality of voltage measuring units are a plurality of voltage sensing circuits, which are used to be respectively connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism to complete the respective measurements of the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism.

5. The intelligent analysis system for voice-controlled lamp operation data according to claim 4, characterized in that: The multiple voltage measurement units are multiple voltage sensing circuits, which are used to be connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism respectively, so as to complete the respective measurements of the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, including: the structures of the multiple voltage sensing circuits are the same.

6. The intelligent analysis system for voice-controlled lamp operation data according to claim 5, characterized in that: The multiple voltage measurement units are multiple voltage sensing circuits, which are used to be connected to the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism respectively, so as to complete the respective measurements of the current real-time voltage values ​​of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, and also include: the multiple voltage sensing circuits have the same voltage measurement upper limit value and voltage measurement lower limit value.

7. The intelligent analysis system for voice-controlled lamp operation data according to claim 2, characterized in that: The system further comprises: The field configuration interface is respectively connected to the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, and is used for real-time configuration of the operating configuration parameters of the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism.

8. The intelligent analysis system for voice-controlled lamp operation data according to claim 7, characterized in that: The field configuration interface is respectively connected to the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, and is used for real-time configuration of the operating configuration parameters of the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, including: the field configuration interface is a serial configuration interface.

9. The intelligent analysis system for voice-controlled lamp operation data according to claim 7, characterized in that: The field configuration interface is respectively connected to the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, and is used to configure the operating configuration parameters of the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism in real time. The field configuration interface includes: for the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism, the field configuration interface uses different configuration addresses to configure the operating configuration parameters of the multiple voltage sensing circuits of the parameter analysis device, the sequential training mechanism, the lamp body acquisition mechanism and the information capture mechanism in real time.

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