Electromechanical equipment automation control system based on Internet of Things

Abstract

The invention discloses an electromechanical equipment automation control system based on the Internet of Things, and relates to the technical field of automation control of the Internet of Things. The system comprises an electromechanical equipment data acquisition module, an electromechanical equipment data processing module, an electromechanical equipment data analysis module, an electromechanical equipment automation control system early warning module and an electromechanical equipment automation control system Internet of Things module, the electromechanical equipment real-time monitoring module is used for collecting electromechanical equipment real-time current data, electromechanical equipment environment humidity data and electromechanical equipment real-time voltage data, and the automatic control monitoring module is used for constructing an automatic control monitoring model by utilizing a neural network algorithm. The problems that the electromechanical equipment cannot work normally due to power failure, the circuit is short-circuited and the service life of the electromechanical equipment is affected due to over-high humidity, and the electromechanical equipment breaks down due to unstable voltage are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of automated control of the Internet of Things, and particularly relates to an automated control system for electromechanical equipment based on the Internet of Things. Background Art

[0002] The background technology of the automated control system for electromechanical equipment based on the Internet of Things integrates a number of high technologies and is widely used in the field of automation. As the core, the Internet of Things technology closely combines sensors, automatic control systems, and wireless communication technologies to achieve real-time information interaction and transmission; sensors are responsible for collecting data related to electromechanical equipment, the automatic control system adjusts related activities of electromechanical equipment according to preset algorithms, the computer is used for data processing and analysis, and the wireless communication technology is responsible for real-time data transmission and remote management. The comprehensive application of these technologies has promoted the steady development of the automated control system for electromechanical equipment based on the Internet of Things;

[0003] Although the existing technology has made great progress in the direction of automated control of the Internet of Things, there are still some problems to be optimized. First of all, the normal operation of electromechanical equipment has certain requirements for the environment. In the case of power failure, the normally operating electromechanical equipment will stop running accordingly, affecting the normal operation of the equipment. In the case of too high humidity, it will cause short circuits inside the electromechanical equipment and rust of metal parts, affecting the life of the electromechanical equipment; secondly, for electromechanical equipment with a relatively long service life, unstable voltage during operation is likely to cause equipment failures, shutdowns, and affect production. Summary of the Invention

[0004] To achieve the above objectives, the present invention is realized through the following technical solutions: An automated control system for electromechanical equipment based on the Internet of Things, including an electromechanical equipment data collection module, an electromechanical equipment data processing module, an automated control monitoring module, an early warning module for the automated control system of electromechanical equipment, and an Internet of Things module for the automated control system of electromechanical equipment;

[0005] The electromechanical equipment data collection module uses collection equipment to collect real-time current data of electromechanical equipment, environmental humidity data of electromechanical equipment, and real-time voltage data of electromechanical equipment, providing data support for the work of subsequent modules;

[0006] The electromechanical equipment data processing module is divided into a preprocessing unit, a current unit, a humidity unit, and a voltage unit. Among them, the preprocessing unit is used for preprocessing the collected data; the current unit is used to obtain the degree of influence of the real-time current data of electromechanical equipment on the automated control process; the humidity unit is used to obtain the degree of interference of the environmental humidity data of electromechanical equipment on the automated control process; the voltage unit obtains the degree of influence of the real-time voltage data of electromechanical equipment on the automated control process;

[0007] The automated control and monitoring module constructs an automated control and monitoring model using neural network algorithms;

[0008] The early warning module of the electromechanical equipment automated control system evaluates the automated control process of the electromechanical equipment in combination with the automated control and monitoring model and sends corresponding signals to the client through wireless transmission;

[0009] The Internet of Things module of the electromechanical equipment automated control system realizes data interaction, instruction reception and sending of each module of the system.

[0010] A further improvement of the technical solution of the present invention lies in that the process of the electromechanical equipment data acquisition module using the acquisition device to acquire the real-time current data of the electromechanical equipment and the real-time voltage data of the electromechanical equipment includes:

[0011] The acquisition device includes a current sensor, a capacitive humidity sensor and a voltage sensor;

[0012] The current sensor is used to acquire the real-time current data of the electromechanical equipment to obtain the real-time current data of the electromechanical equipment;

[0013] The voltage sensor uses the principle of resistance voltage division, selects an appropriate resistance ratio, connects to this resistance, knowing the value of this resistance, and calculates the measured voltage value through the resistance voltage division of the connected resistance to obtain the real-time voltage data of the electromechanical equipment.

[0014] A further improvement of the technical solution of the present invention lies in that the process of the electromechanical equipment data acquisition module acquiring the environmental humidity data of the electromechanical equipment includes:

[0015] The capacitive humidity sensor measures the humidity in the air using the correlation between capacitance and dielectric. When the humidity in the air changes, the dielectric constant of the dielectric changes, changing the capacitance of the capacitor. The changing capacitance of the capacitor is obtained through the capacitive humidity sensor, and the humidity data in the air is calculated to obtain the environmental humidity data of the electromechanical equipment.

[0016] A further improvement of the technical solution of the present invention lies in that the process of the preprocessing unit preprocessing the acquired data includes:

[0017] Perform data cleaning on the acquired real-time current data of the electromechanical equipment, the real-time voltage data of the electromechanical equipment and the environmental humidity data of the electromechanical equipment to remove outliers and duplicate values;

[0018] According to the data mean formula and the standard deviation formula, calculate the mean and standard deviation of the real-time current data of the electromechanical equipment respectively. The mean and standard deviation of the real-time current data of the electromechanical equipment are represented by µ and β respectively.

[0019] A further improvement of the technical solution of the present invention lies in that: the process of the current unit obtaining the influence degree of the real-time current data of the electromechanical equipment on the automatic control process includes:

[0020] Using the mean and standard deviation of the real-time current data of the electromechanical equipment, set [µ - kβ, µ + kβ] as the normal working current range of the electromechanical equipment, where k is a constant;

[0021] According to the normal working current range of the electromechanical equipment, count the number of real-time current data located within the normal working current range of the electromechanical equipment, and calculate the proportion of the number of real-time current data located within the normal working current range of the electromechanical equipment in the total number of all real-time current data of the electromechanical equipment;

[0022] When the proportion of the number of real-time current data within the normal working current range of the electromechanical equipment in the total number of all real-time current data of the electromechanical equipment is greater than 90%, the real-time current data of the electromechanical equipment has a low influence degree on the automatic control process; when the proportion of the number of real-time current data within the normal working current range of the electromechanical equipment in the total number of all real-time current data of the electromechanical equipment is between 70% and 90%, the real-time current data of the electromechanical equipment has a medium influence degree on the automatic control process; when the proportion of the number of real-time current data within the normal working current range of the electromechanical equipment in the total number of all real-time current data of the electromechanical equipment is less than 70%, the real-time current data of the electromechanical equipment has a high influence degree on the automatic control process.

[0023] A further improvement of the technical solution of the present invention lies in that: the process of the humidity unit obtaining the interference degree of the environmental humidity data of the electromechanical equipment on the automatic control process includes:

[0024] According to the environment where the electromechanical equipment is located, set the lower threshold and upper threshold of the environmental humidity data of the electromechanical equipment. By referring to the electromechanical equipment manual, obtain the small - amplitude humidity fluctuation value and large - amplitude humidity fluctuation value of the environment of the electromechanical equipment, and use 、 、 and to represent the lower threshold, upper threshold, small - amplitude humidity fluctuation value and large - amplitude humidity fluctuation value of the environmental humidity data of the electromechanical equipment respectively;

[0025] When the environmental humidity data of the electromechanical equipment is within , , the environmental humidity data of the electromechanical equipment has a low interference degree on the automatic control process; when the environmental humidity data of the electromechanical equipment is within , , the environmental humidity data of the electromechanical equipment has a medium interference degree on the automatic control process; when the environmental humidity data of the electromechanical equipment is within , When it is between [specific range], the environmental humidity data of the electromechanical equipment has a high degree of interference on the automation control process.

[0026] A further improvement of the technical solution of the present invention lies in that: the process of the voltage unit obtaining the influence degree of the real-time voltage data of the electromechanical equipment on the automation control process includes:

[0027] It is set that the normal fluctuation range of the working voltage of the electromechanical equipment is 198v - 238v. When the real-time voltage data of the electromechanical equipment is within the normal fluctuation range of the working voltage of the electromechanical equipment, the real-time voltage data of the electromechanical equipment has a low influence degree on the automation control process; when the real-time voltage data of the electromechanical equipment exceeds 2% - 5% of the normal fluctuation range of the working voltage of the electromechanical equipment, the real-time voltage data of the electromechanical equipment has a medium influence degree on the automation control process; when it exceeds 5% of the normal fluctuation range of the working voltage of the electromechanical equipment, the real-time voltage data of the electromechanical equipment has a high influence degree on the automation control process.

[0028] A further improvement of the technical solution of the present invention lies in that: the process of the automation control monitoring module constructing an automation control monitoring model by using the neural network algorithm includes:

[0029] Using the neural network algorithm to construct a neural network model, taking the real-time current data of the electromechanical equipment and its influence degree on the automation control process, the environmental humidity data of the electromechanical equipment and its interference degree on the automation control process, and the real-time voltage data of the electromechanical equipment and its influence degree on the automation control process as a data set, dividing it into a training set and a test set according to a ratio of 7:3, selecting MLP as the neural network structure, the input layer includes three neurons, receiving the real-time current data of the electromechanical equipment, the environmental humidity data of the electromechanical equipment, and the real-time voltage data of the electromechanical equipment, the hidden layer is configured with the MSE function, and the output layer includes three neurons, outputting the influence degree of the real-time current data of the electromechanical equipment on the automation control process, the interference degree of the environmental humidity data of the electromechanical equipment on the automation control process, and the influence degree of the real-time voltage data of the electromechanical equipment on the automation control process;

[0030] Input the training set data into the neural network model, set the learning rate to 0.01, and the number of iterative training times to 1000. The training process includes forward propagation and backward propagation. Among them, forward propagation is used to calculate the predicted output data, and backward propagation is used to update the weights and biases of the model. By repeating the iterative training, learn the non-linear relationships between the real-time current data of the electromechanical device and the degree of influence of the real-time current data of the electromechanical device on the automation control process, between the signal fading amplitude and the degree of multi-path fading of the signal fading amplitude on the channel, between the environmental humidity data of the electromechanical device and the degree of interference of the environmental humidity data of the electromechanical device on the automation control process, and between the real-time voltage data of the electromechanical device and the degree of influence of the real-time voltage data of the electromechanical device on the automation control process, until the set number of iterative training times is reached, and obtain the trained neural network model;

[0031] Input the test set data into the trained neural network model, use the MSE function to evaluate the error between the output value and the actual value of the neural network model, adjust the parameters of the neural network model according to the evaluation results, optimize the performance of the neural network model, and obtain the automation control monitoring model.

[0032] A further improvement of the technical solution of the present invention lies in: the warning module of the electromechanical device automation control system, in combination with the automation control monitoring model, the process of evaluating the automation control process of the electromechanical device and sending corresponding signals to the client through wireless transmission includes:

[0033] Input the real-time current data of the electromechanical device, the environmental humidity data of the electromechanical device, and the real-time voltage data of the electromechanical device into the automation control monitoring model respectively, and obtain the degree of influence of the real-time current data of the electromechanical device on the automation control process, the degree of interference of the environmental humidity data of the electromechanical device on the automation control process, and the degree of influence of the real-time voltage data of the electromechanical device on the automation control process;

[0034] When the real-time current data of the electromechanical device has a low degree of influence on the automation control process, it indicates that the automation control process is little affected by the real-time current of the electromechanical device; when the real-time current data of the electromechanical device has a medium degree of influence on the automation control process, send an early warning signal of the real-time current of the electromechanical device to the client through wireless transmission; when the real-time current data of the electromechanical device has a high degree of influence on the automation control process, send an abnormal signal of the real-time current of the electromechanical device to the client through wireless transmission;

[0035] When the environmental humidity data of the electromechanical equipment has a low interference level on the automation control process, it indicates that the automation control process is less affected by the environmental humidity of the electromechanical equipment; when the environmental humidity data of the electromechanical equipment has a medium interference level on the automation control process, an early warning signal of the environmental humidity of the electromechanical equipment is sent to the client through wireless transmission; when the environmental humidity data of the electromechanical equipment has a high interference level on the automation control process, an abnormal signal of the environmental humidity of the electromechanical equipment is sent to the client through wireless transmission;

[0036] When the real-time voltage data of the electromechanical equipment has a low impact level on the automation control process, it indicates that the automation control process is less affected by the real-time voltage of the electromechanical equipment; when the real-time voltage data of the electromechanical equipment has a medium impact level on the automation control process, an early warning signal of the real-time voltage of the electromechanical equipment is sent to the client through wireless transmission; when the real-time voltage data of the electromechanical equipment has a high impact level on the automation control process, an abnormal signal of the real-time voltage of the electromechanical equipment is sent to the client through wireless transmission.

[0037] A further improvement of the technical solution of the present invention lies in that: the Internet of Things module of the electromechanical equipment automation control system, the process of realizing data interaction, instruction reception and sending of each module of the system includes:

[0038] According to the remote control requirements of the electromechanical equipment automation control system, select the WIFI wireless transmission module, configure the IP address, subnet mask, default gateway, WIFI network name and password of the Internet of Things module of the electromechanical equipment automation control system. The Internet of Things device establishes a connection with each module through the WIFI wireless transmission module. The connection involves the processes of device discovery, authentication and connection establishment. After the connection is established, the Internet of Things device performs data interaction, instruction reception and sending with other modules through the WIFI wireless transmission module.

[0039] The beneficial effects of the present invention are: The present invention combines the electromechanical equipment data acquisition module, electromechanical equipment data processing module, automation control monitoring module, electromechanical equipment automation control system early warning module and electromechanical equipment automation control system Internet of Things module of the automation control system, and realizes data interaction and instruction transmission through wireless transmission. Compared with the traditional automation control system of electromechanical equipment, the present invention implements more strict real-time monitoring of the current, voltage data of the electromechanical equipment during operation and the humidity data of its working environment, solves the problems that the electromechanical equipment cannot work properly due to power failure, short circuit caused by too high humidity and affects the service life of the electromechanical equipment, and the electromechanical equipment fails due to unstable voltage, and further promotes the normal operation of the automation control system to control the electromechanical equipment and its troubleshooting work. Description of the Drawings

[0040] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the accompanying drawings required in the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments recorded in the present invention. For those of ordinary skill in the art, other accompanying drawings can also be obtained based on these drawings.

[0041] Figure 1 It is a block diagram of an automated control system for electromechanical equipment based on the Internet of Things according to the present invention. Specific embodiments

[0042] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0043] As Figure 1 shown, the present invention provides an automated control system for electromechanical equipment based on the Internet of Things, including an electromechanical equipment data acquisition module, an electromechanical equipment data processing module, an automated control monitoring module, an early warning module for the electromechanical equipment automated control system, and an Internet of Things module for the electromechanical equipment automated control system;

[0044] The electromechanical equipment data acquisition module uses acquisition devices to collect the real-time current data of electromechanical equipment, the environmental humidity data of electromechanical equipment, and the real-time voltage data of electromechanical equipment, providing data support for the work of subsequent modules;

[0045] The electromechanical equipment data processing module is divided into a preprocessing unit, a current unit, a humidity unit, and a voltage unit. Among them, the preprocessing unit is used to preprocess the collected data; the current unit is used to obtain the influence degree of the real-time current data of electromechanical equipment on the automated control process; the humidity unit is used to obtain the interference degree of the environmental humidity data of electromechanical equipment on the automated control process; the voltage unit obtains the influence degree of the real-time voltage data of electromechanical equipment on the automated control process;

[0046] The automated control monitoring module uses a neural network algorithm to construct an automated control monitoring model;

[0047] The early warning module for the electromechanical equipment automated control system combines the automated control monitoring model to evaluate the automated control process of electromechanical equipment and sends corresponding signals to the client through wireless transmission;

[0048] The Internet of Things module of the electromechanical equipment automation control system realizes data interaction, instruction reception, and transmission among various system modules.

[0049] Preferably, the process of the electromechanical equipment data acquisition module using the acquisition device to acquire the real-time current data of the electromechanical equipment and the real-time voltage data of the electromechanical equipment includes:

[0050] Among them, the acquisition device includes a current sensor, a capacitive humidity sensor, and a voltage sensor;

[0051] Use the current sensor to acquire the real-time current data of the electromechanical equipment and obtain the real-time current data of the electromechanical equipment;

[0052] The voltage sensor uses the principle of resistance voltage division, selects an appropriate resistance ratio, connects to this resistance, knowing the resistance value, and calculates the voltage value to be measured through the resistance voltage division of the connected resistance to obtain the real-time voltage data of the electromechanical equipment.

[0053] Preferably, the process of the electromechanical equipment data acquisition module acquiring the environmental humidity data of the electromechanical equipment includes:

[0054] The capacitive humidity sensor uses the correlation between capacitance and dielectric to measure the humidity in the air. When the humidity in the air changes, the dielectric constant of the dielectric changes, changing the capacitance of the capacitor. Obtain the changed capacitance of the capacitor through the capacitive humidity sensor, calculate the humidity data in the air, and obtain the environmental humidity data of the electromechanical equipment.

[0055] Preferably, the process of the preprocessing unit preprocessing the acquired data includes:

[0056] Perform data cleaning on the acquired real-time current data of the electromechanical equipment, the real-time voltage data of the electromechanical equipment, and the environmental humidity data of the electromechanical equipment to remove outliers and duplicate values;

[0057] According to the data mean formula and the standard deviation formula, calculate the mean and standard deviation of the real-time current data of the electromechanical equipment respectively. The mean and standard deviation of the real-time current data of the electromechanical equipment are represented by µ and β respectively.

[0058] Preferably, the process of the current unit obtaining the influence degree of the real-time current data of the electromechanical equipment on the automation control process includes:

[0059] Use the mean and standard deviation of the real-time current data of the electromechanical equipment to set [µ - kβ, µ + kβ] as the normal working current range of the electromechanical equipment, where k is a constant;

[0060] According to the normal operating current range of the electromechanical equipment, count the number of real-time current data within the normal operating current range of the electromechanical equipment, and calculate the proportion of the number of real-time current data within the normal operating current range of the electromechanical equipment in the total number of real-time current data of all electromechanical equipment;

[0061] When the proportion of the number of real-time current data within the normal operating current range of the electromechanical equipment in the total number of real-time current data of all electromechanical equipment is greater than 90%, the real-time current data of the electromechanical equipment has a low impact on the automation control process; when the proportion of the number of real-time current data within the normal operating current range of the electromechanical equipment in the total number of real-time current data of all electromechanical equipment is between 70% and 90%, the real-time current data of the electromechanical equipment has a medium impact on the automation control process; when the proportion of the number of real-time current data within the normal operating current range of the electromechanical equipment in the total number of real-time current data of all electromechanical equipment is less than 70%, the real-time current data of the electromechanical equipment has a high impact on the automation control process.

[0062] Preferably, the process of the humidity unit obtaining the interference degree of the environmental humidity data of the electromechanical equipment on the automation control process includes:

[0063] According to the environment where the electromechanical equipment is located, set the lower threshold and upper threshold of the environmental humidity data of the electromechanical equipment. By referring to the electromechanical equipment manual, obtain the small-amplitude humidity fluctuation value and large-amplitude humidity fluctuation value of the environment of the electromechanical equipment, and use 、 、 and to represent the lower threshold, upper threshold, small-amplitude humidity fluctuation value and large-amplitude humidity fluctuation value of the environmental humidity data of the electromechanical equipment respectively;

[0064] When the environmental humidity data of the electromechanical equipment is between , , the environmental humidity data of the electromechanical equipment has a low interference degree on the automation control process; when the environmental humidity data of the electromechanical equipment is between , , the environmental humidity data of the electromechanical equipment has a medium interference degree on the automation control process; when the environmental humidity data of the electromechanical equipment is between , , the environmental humidity data of the electromechanical equipment has a high interference degree on the automation control process.

[0065] Preferably, the process of the voltage unit obtaining the influence degree of the real-time voltage data of the electromechanical equipment on the automation control process includes:

[0066] The normal voltage fluctuation range of the electromechanical equipment is set to be 198V - 238V. When the real-time voltage data of the electromechanical equipment is within the normal voltage fluctuation range of the electromechanical equipment, the real-time voltage data of the electromechanical equipment has a low impact on the automation control process; when the real-time voltage data of the electromechanical equipment exceeds 2% - 5% of the normal voltage fluctuation range of the electromechanical equipment, the real-time voltage data of the electromechanical equipment has a medium impact on the automation control process; when it exceeds 5% of the normal voltage fluctuation range of the electromechanical equipment, the real-time voltage data of the electromechanical equipment has a high impact on the automation control process.

[0067] Preferably, for the automation control monitoring module, the process of constructing an automation control monitoring model using the neural network algorithm includes:

[0068] Using the neural network algorithm to construct a neural network model. Taking the real-time current data of the electromechanical equipment and its impact on the automation control process, the environmental humidity data of the electromechanical equipment and its interference on the automation control process, and the real-time voltage data of the electromechanical equipment and its impact on the automation control process as a data set, it is divided into a training set and a test set according to a ratio of 7:3. Select MLP as the neural network structure. The input layer includes three neurons, which receive the real-time current data of the electromechanical equipment, the environmental humidity data of the electromechanical equipment, and the real-time voltage data of the electromechanical equipment. The hidden layer is configured with the MSE function. The output layer includes three neurons, which output the impact of the real-time current data of the electromechanical equipment on the automation control process, the interference of the environmental humidity data of the electromechanical equipment on the automation control process, and the impact of the real-time voltage data of the electromechanical equipment on the automation control process;

[0069] Input the training set data into the neural network model, set the learning rate to 0.01, and the number of iterative training times to 1000. The training process includes forward propagation and backward propagation. Among them, forward propagation is used to calculate the predicted output data, and backward propagation is used to update the weights and biases of the model. Through repeated iterative training, learn the non-linear relationships between the real-time current data of the electromechanical equipment and its impact on the automation control process, the signal fading amplitude and its multi-path fading degree on the channel, the environmental humidity data of the electromechanical equipment and its interference on the automation control process, and the real-time voltage data of the electromechanical equipment and its impact on the automation control process until the set number of iterative training times is reached, and obtain the trained neural network model;

[0070] Input the test set data into the trained neural network model, use the MSE function to evaluate the error between the output value and the actual value of the neural network model, adjust the parameters of the neural network model according to the evaluation results, optimize the performance of the neural network model, and obtain the automation control monitoring model.

[0071] Preferably, for the warning module of the electromechanical equipment automation control system, in the process of evaluating the automation control process of the electromechanical equipment by combining with the automation control monitoring model and sending corresponding signals to the client through wireless transmission, the process includes:

[0072] Input the real-time current data of the electromechanical equipment, the environmental humidity data of the electromechanical equipment, and the real-time voltage data of the electromechanical equipment into the automation control monitoring model respectively, and obtain the influence degree of the real-time current data of the electromechanical equipment on the automation control process, the interference degree of the environmental humidity data of the electromechanical equipment on the automation control process, and the influence degree of the real-time voltage data of the electromechanical equipment on the automation control process;

[0073] When the real-time current data of the electromechanical equipment has a low influence degree on the automation control process, it indicates that the automation control process is little affected by the real-time current of the electromechanical equipment; when the real-time current data of the electromechanical equipment has a medium influence degree on the automation control process, send a real-time current warning signal of the electromechanical equipment to the client through wireless transmission; when the real-time current data of the electromechanical equipment has a high influence degree on the automation control process, send a real-time current abnormal signal of the electromechanical equipment to the client through wireless transmission;

[0074] When the environmental humidity data of the electromechanical equipment has a low interference degree on the automation control process, it indicates that the automation control process is little affected by the environmental humidity of the electromechanical equipment; when the environmental humidity data of the electromechanical equipment has a medium interference degree on the automation control process, send a warning signal of the environmental humidity of the electromechanical equipment to the client through wireless transmission; when the environmental humidity data of the electromechanical equipment has a high interference degree on the automation control process, send an abnormal signal of the environmental humidity of the electromechanical equipment to the client through wireless transmission;

[0075] When the real-time voltage data of the electromechanical equipment has a low influence degree on the automation control process, it indicates that the automation control process is little affected by the real-time voltage of the electromechanical equipment; when the real-time voltage data of the electromechanical equipment has a medium influence degree on the automation control process, send a real-time voltage warning signal of the electromechanical equipment to the client through wireless transmission; when the real-time voltage data of the electromechanical equipment has a high influence degree on the automation control process, send a real-time voltage abnormal signal of the electromechanical equipment to the client through wireless transmission.

[0076] Preferably, for the Internet of Things module of the electromechanical equipment automation control system, the process of realizing data interaction, instruction reception and sending of each module of the system includes:

[0077] According to the remote control requirements of the electromechanical equipment automation control system, a WIFI wireless transmission module is selected, and the IP address, subnet mask, default gateway, and WIFI network name and password of the Internet of Things module of the electromechanical equipment automation control system are configured. The Internet of Things device establishes connections with each module through the WIFI wireless transmission module. The connection involves device discovery, authentication, and connection establishment processes. After the connection is established, the Internet of Things device conducts data interaction, instruction reception, and transmission with other modules through the WIFI wireless transmission module.

[0078] The Internet of Things module of the electromechanical equipment automation control system is the core for wireless transmission of the electromechanical equipment data acquisition module, electromechanical equipment data processing module, automation control monitoring module, and electromechanical equipment automation control system warning module. The automation control system receives data from each module through the Internet of Things module of the electromechanical equipment automation control system. First, the real-time current data of the electromechanical equipment is collected through a current sensor, the environmental humidity data of the electromechanical equipment is collected using a capacitive humidity sensor, and the voltage value of the electromechanical equipment is collected using a voltage sensor. Secondly, the data processing module processes these data to respectively obtain the influence degree of the real-time current data of the electromechanical equipment on the automation control process, the interference degree of the environmental humidity data of the electromechanical equipment on the automation control process, and the influence degree of the real-time voltage data of the electromechanical equipment on the automation control process. Then, the automation control monitoring module uses the neural network algorithm to construct an automation control monitoring model. Finally, the electromechanical equipment automation control system warning module monitors the abnormal data in the output result of the automation control monitoring model and sends the corresponding signal to the client through wireless transmission. When the automation system receives the abnormal feedback data, it starts the built-in emergency processing of the system. When the emergency processing of the automation system cannot solve the problem, the abnormal data is fed back to the client through wireless transmission for the client to handle. Throughout the process, the Internet of Things module of the electromechanical equipment automation control system realizes data interaction, instruction reception, and transmission of each module.

[0079] As described above, this is only the specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claimed rights.

Claims

1. An electromechanical equipment automation control system based on the Internet of Things, comprising an electromechanical equipment data acquisition module, an electromechanical equipment data processing module, an automation control monitoring module, an electromechanical equipment automation control system early warning module, and an electromechanical equipment automation control system Internet of Things module, characterized in that: The electromechanical equipment data acquisition module uses an acquisition device to collect real-time current data of the electromechanical equipment, environmental humidity data of the electromechanical equipment, and real-time voltage data of the electromechanical equipment; The electromechanical equipment data processing module is divided into a preprocessing unit, a current unit, a humidity unit and a voltage unit, wherein the preprocessing unit is used to preprocess the collected data; the current unit is used to obtain the influence of the real-time current data of the electromechanical equipment on the automatic control process; the humidity unit is used to obtain the interference degree of the environmental humidity data of the electromechanical equipment on the automatic control process; the voltage unit is used to obtain the influence degree of the real-time voltage data of the electromechanical equipment on the automatic control process; The automatic control monitoring module uses a neural network algorithm to construct an automatic control monitoring model; The electromechanical equipment automation control system early warning module, in combination with the automation control monitoring model, evaluates the automation control process of the electromechanical equipment and sends a corresponding signal to the client via wireless transmission; The Internet of Things module of the electromechanical equipment automation control system realizes data interaction, command reception and transmission of various modules of the system.

2. According to the Internet of Things-based electromechanical equipment automation control system of claim 1, it is characterized by: The electromechanical equipment data acquisition module uses an acquisition device to acquire real-time current data and real-time voltage data of the electromechanical equipment, and the process includes: The acquisition equipment includes a current sensor, a capacitive humidity sensor and a voltage sensor; Use current sensors to collect real-time current data of electromechanical equipment and obtain real-time current data of electromechanical equipment; The voltage sensor uses the principle of resistor voltage division, selects a suitable resistor ratio, connects to the resistor, and calculates the voltage value to be measured by connecting to the resistor voltage division to obtain real-time voltage data of the electromechanical equipment.

3. According to the Internet of Things-based electromechanical equipment automation control system of claim 2, it is characterized by: The electromechanical equipment data acquisition module collects the environmental humidity data of the electromechanical equipment, including: The capacitive humidity sensor uses the correlation between capacitance and medium to measure the humidity in the air. When the humidity in the air changes, the dielectric constant of the medium changes, changing the capacitance of the capacitor. The capacitive humidity sensor obtains the changed capacitance of the capacitor, calculates the humidity data in the air, and obtains the environmental humidity data of the electromechanical equipment.

4. The electromechanical equipment automation control system based on the Internet of Things according to claim 3 is characterized in that: The process of preprocessing the collected data by the preprocessing unit includes: Clean the collected real-time current data, real-time voltage data and environmental humidity data of electromechanical equipment to remove abnormal values ​​and duplicate values; According to the data mean formula and standard deviation formula, the mean and standard deviation of the real-time current data of the electromechanical equipment are calculated respectively. The mean and standard deviation of the real-time current data of the electromechanical equipment are represented by µ and β respectively.

5. The electromechanical equipment automation control system based on the Internet of Things according to claim 4 is characterized in that: The process of obtaining the influence degree of the real-time current data of the electromechanical equipment on the automation control process by the current unit includes: Using the mean and standard deviation of the real-time current data of electromechanical equipment, [µ-kβ, µ+kβ] is set as the normal operating current range of the electromechanical equipment, where k is a constant; According to the normal working current range of the electromechanical equipment, the number of real-time current data within the normal working current range of the electromechanical equipment is counted, and the proportion of the number of real-time current data within the normal working current range of the electromechanical equipment in the number of real-time current data of all electromechanical equipment is calculated; When the number of real-time current data within the normal working current range of electromechanical equipment accounts for more than 90% of the number of real-time current data of all electromechanical equipment, the real-time current data of electromechanical equipment has a low impact on the automation control process; when the number of real-time current data within the normal working current range of electromechanical equipment accounts for between 70% and 90% of the number of real-time current data of all electromechanical equipment, the real-time current data of electromechanical equipment has a medium impact on the automation control process; when the number of real-time current data within the normal working current range of electromechanical equipment accounts for less than 70% of the number of real-time current data of all electromechanical equipment, the real-time current data of electromechanical equipment has a high impact on the automation control process.

6. The electromechanical equipment automation control system based on the Internet of Things according to claim 5 is characterized in that: The process of the humidity unit obtaining the interference degree of the environmental humidity data of the electromechanical equipment on the automatic control process includes: According to the environment in which the electromechanical equipment is located, the lower and upper thresholds of the humidity data of the electromechanical equipment environment are set. By consulting the electromechanical equipment manual, the small and large humidity fluctuation values ​​of the electromechanical equipment environment are obtained, respectively. , , and Indicates the lower threshold, upper threshold, small humidity fluctuation value and large humidity fluctuation value of the environmental humidity data of electromechanical equipment; When the environmental humidity data of electromechanical equipment is located in [ , ], the environmental humidity data of electromechanical equipment has a low interference level on the automation control process; when the environmental humidity data of electromechanical equipment is between [ , ], the electromechanical equipment environmental humidity data has a medium interference level on the automation control process; when the electromechanical equipment environmental humidity data is between [ , ], the environmental humidity data of electromechanical equipment has a high interference level on the automation control process.

7. The electromechanical equipment automation control system based on the Internet of Things according to claim 6 is characterized by: The process of the voltage unit obtaining the influence of the real-time voltage data of the electromechanical equipment on the automation control process includes: The normal fluctuation range of the working voltage of the electromechanical equipment is set to 198V~238V. When the real-time voltage data of the electromechanical equipment is within the normal fluctuation range of the working voltage of the electromechanical equipment, the real-time voltage data of the electromechanical equipment has a low impact on the automation control process; when the real-time voltage data of the electromechanical equipment exceeds the normal fluctuation range of the working voltage of the electromechanical equipment by 2%~5%, the real-time voltage data of the electromechanical equipment has a medium impact on the automation control process; when it exceeds the normal fluctuation range of the working voltage of the electromechanical equipment by 5%, the real-time voltage data of the electromechanical equipment has a high impact on the automation control process.

8. The electromechanical equipment automation control system based on the Internet of Things according to claim 7 is characterized in that: The process of constructing the automatic control monitoring model by using the neural network algorithm in the automatic control monitoring module includes: A neural network model is constructed by using a neural network algorithm. The real-time current data of electromechanical equipment and its influence on the automation control process, the environmental humidity data of electromechanical equipment and its interference with the automation control process, and the real-time voltage data of electromechanical equipment and its influence on the automation control process are taken as data sets, which are divided into a training set and a test set in a ratio of 7:

3. MLP is selected as the neural network structure. The input layer includes three neurons, which receive the real-time current data of electromechanical equipment, the environmental humidity data of electromechanical equipment, and the real-time voltage data of electromechanical equipment. The hidden layer is configured with an MSE function. The output layer includes three neurons, which output the influence of the real-time current data of electromechanical equipment on the automation control process, the interference of the environmental humidity data of electromechanical equipment on the automation control process, and the influence of the real-time voltage data of electromechanical equipment on the automation control process. Input the training set data into the neural network model, set the learning rate to 0.01, and the number of iterative training times to 1000. The training process includes forward propagation and back propagation, wherein the forward propagation is used to calculate the predicted output data, and the back propagation is used to update the weights and biases of the model. Through repeated iterative training, the nonlinear relationship between the output real-time current data of the electromechanical equipment and the influence of the real-time current data of the electromechanical equipment on the automation control process, the nonlinear relationship between the signal fading amplitude and the signal fading amplitude on the multipath fading degree of the channel, the nonlinear relationship between the environmental humidity data of the electromechanical equipment and the interference degree of the environmental humidity data of the electromechanical equipment on the automation control process, and the nonlinear relationship between the real-time voltage data of the electromechanical equipment and the influence degree of the real-time voltage data of the electromechanical equipment on the automation control process are learned. The training is repeated until the set number of iterative training times is reached to obtain the trained neural network model; The test set data is input into the trained neural network model, and the MSE function is used to evaluate the error between the output value of the neural network model and the actual value. The parameters of the neural network model are adjusted according to the evaluation results, the performance of the neural network model is optimized, and the automatic control monitoring model is obtained.

9. The electromechanical equipment automation control system based on the Internet of Things according to claim 8, characterized in that: The electromechanical equipment automation control system early warning module combines the automation control monitoring model to evaluate the automation control process of the electromechanical equipment, and the process of sending the corresponding signal to the client through wireless transmission includes: The real-time current data of the electromechanical equipment, the environmental humidity data of the electromechanical equipment and the real-time voltage data of the electromechanical equipment are respectively input into the automatic control monitoring model to obtain the influence degree of the output real-time current data of the electromechanical equipment on the automatic control process, the interference degree of the environmental humidity data of the electromechanical equipment on the automatic control process and the influence degree of the real-time voltage data of the electromechanical equipment on the automatic control process; When the real-time current data of the electromechanical equipment has a low impact on the automation control process, it indicates that the automation control process is less affected by the real-time current of the electromechanical equipment; when the real-time current data of the electromechanical equipment has a medium impact on the automation control process, a real-time current warning signal of the electromechanical equipment is sent to the client through wireless transmission; when the real-time current data of the electromechanical equipment has a high impact on the automation control process, a real-time current abnormal signal of the electromechanical equipment is sent to the client through wireless transmission; When the environmental humidity data of the electromechanical equipment has a low interference degree to the automatic control process, it indicates that the automatic control process is less affected by the environmental humidity of the electromechanical equipment; when the environmental humidity data of the electromechanical equipment has a medium interference degree to the automatic control process, an early warning signal of the environmental humidity of the electromechanical equipment is sent to the client through wireless transmission; when the environmental humidity data of the electromechanical equipment has a high interference degree to the automatic control process, an abnormal signal of the environmental humidity of the electromechanical equipment is sent to the client through wireless transmission; When the real-time voltage data of the electromechanical equipment has a low impact on the automation control process, it indicates that the automation control process is less affected by the real-time voltage of the electromechanical equipment; when the real-time voltage data of the electromechanical equipment has a medium impact on the automation control process, the real-time voltage warning signal of the electromechanical equipment is sent to the client through wireless transmission; when the real-time voltage data of the electromechanical equipment has a high impact on the automation control process, the real-time voltage abnormality signal of the electromechanical equipment is sent to the client through wireless transmission.

10. The electromechanical equipment automation control system based on the Internet of Things according to claim 9, characterized in that The process of realizing data interaction, command reception and transmission of each module of the mechatronic equipment automation control system Internet of Things module includes: According to the remote control requirements of the electromechanical equipment automation control system, select the WIFI wireless transmission module, configure the IP address, subnet mask, default gateway, WIFI network name and password of the Internet of Things module of the electromechanical equipment automation control system, and the Internet of Things device establishes a connection with each module through the WIFI wireless transmission module. The connection involves device discovery, identity authentication and connection establishment processes. After the connection is established, the Internet of Things device interacts with other modules and receives and sends commands through the WIFI wireless transmission module.

Images