Internet of Things-based kiln control system

Abstract

This invention discloses an Internet of Things (IoT)-based kiln control system, relating to the field of industrial kiln technology. It includes a monitoring sensor group, a monitoring and analysis module, a controller, an airflow regulation module, and a temperature analysis module. Each kiln is equipped with a corresponding monitoring sensor group to monitor its internal environmental data. The monitoring and analysis module preprocesses the received internal environmental data, performs ventilation coefficient analysis on the preprocessed data, and determines the airflow threshold FL for the corresponding ventilation device based on the ventilation coefficient TF. The monitoring and analysis module transmits the airflow threshold FL to the airflow regulation module via the controller to adjust the airflow of the ventilation device, thereby achieving automatic adjustment of the gas-air ratio to achieve optimal energy consumption and improve kiln efficiency. The temperature analysis module analyzes temperature changes within the kiln to determine if the kiln's thermal state is abnormal, improving kiln operational safety.

Description

Technical Field

[0001] This invention relates to the field of industrial kiln technology, specifically to a kiln control system based on the Internet of Things (IoT). Background Technology

[0002] Industrial kilns often use fuel gas as a heat source, and the ratio of fuel gas to air during combustion directly affects energy consumption. If there is too little air, combustion is incomplete, and the incomplete combustion products contain a large number of pollutants that pollute the environment, while also wasting energy; on the other hand, if there is too much air, the excess air will carry away a large amount of heat when it is discharged, increasing heat loss.

[0003] With technological advancements, kiln structures are becoming increasingly longer. In production process management, relying solely on manual monitoring of the kiln system's operation is proving increasingly inadequate. Operators need to inspect the kilns on-site, sometimes walking 500 to 600 meters or more for a single large kiln. Sometimes, one person has to manage several kilns simultaneously. During on-site inspections, operators cannot keep track of most of the kiln's operational status information in the control room, making it impossible to make timely adjustments to various kiln conditions, which seriously affects the firing quality of the kilns. Based on these shortcomings, this invention proposes a kiln control system based on the Internet of Things (IoT). Summary of the Invention

[0004] This invention aims to solve at least one of the technical problems existing in the prior art. To this end, this invention proposes a kiln control system based on the Internet of Things (IoT).

[0005] To achieve the above objectives, an Internet of Things-based kiln control system is proposed according to an embodiment of the first aspect of the present invention, including a monitoring sensor group, a monitoring and analysis module, a controller, a database, an air volume regulation module, and a temperature analysis module;

[0006] Each kiln is equipped with a corresponding set of monitoring sensors to monitor the internal environmental data of its corresponding kiln and send the monitored internal environmental data to the monitoring and analysis module; the internal environmental data includes air pressure information, temperature information and gas composition information.

[0007] The monitoring and analysis module is used to preprocess the received internal environmental data, analyze the ventilation coefficient of the preprocessed data, and determine the air volume threshold FL of the corresponding ventilation device based on the ventilation coefficient TF; the monitoring and analysis module is used to transmit the air volume threshold FL to the air volume adjustment module via the controller to adjust the air volume of the ventilation device.

[0008] The temperature analysis module is used to analyze the temperature changes inside the kiln and determine whether the kiln's thermal state is abnormal; the specific analysis steps are as follows:

[0009] Establish a curve of the temperature difference WT between the top and bottom as a function of time; compare WT with a preset temperature difference threshold; if WT ≥ preset temperature difference threshold, extract the corresponding curve segment from the corresponding curve and mark it as the abnormal heat curve segment.

[0010] The heat deviation RL is evaluated based on the occurrence of abnormal heat curve segments; if RL ≥ deviation threshold, the kiln heat state is determined to be abnormal, and an early warning signal is generated.

[0011] Furthermore, the specific analysis steps of the monitoring and analysis module are as follows:

[0012] After obtaining the preprocessed data, the gas pressure information inside the kiln is marked as Y1, the temperature information at the top of the kiln is marked as T1, the temperature information at the bottom of the kiln is marked as T2, the CH4 gas content information is marked as N1, and the O2 gas content information is marked as N2.

[0013] The ventilation coefficient TF is calculated using the formula TF=Y1×b1+(T1-T2) / (T0-T1)×b2+N1 / N2×b3, where b1, b2, and b3 are coefficient factors; T0 represents the preset maximum temperature inside the furnace.

[0014] Furthermore, the database stores a mapping table between the ventilation coefficient range and the air volume threshold; the preprocessing involves removing obviously erroneous or useless data.

[0015] Furthermore, the monitoring sensor group includes a pressure sensor, a temperature sensor, and a gas composition sensor. The pressure sensor is used to monitor the gas pressure information inside the kiln in real time; the temperature sensor is used to monitor the temperature information at the top and bottom of the kiln in real time; and the gas composition sensor is used to monitor the gas composition information inside the kiln in real time, including CH4 gas content information and O2 gas content information.

[0016] Furthermore, the ventilation device is equipped with an air volume regulating valve; the air volume regulating module is used to control the valve opening of the air volume regulating valve to regulate the air volume.

[0017] Furthermore, the temperature analysis module also includes:

[0018] The temperature information T1 at the top of the kiln and T2 at the bottom of the kiln are obtained. The temperature difference WT between the top and bottom is calculated using the formula WT = T1 - T2. If T1 is greater than T0 and the duration exceeds the first preset duration, the kiln's thermal state is determined to be abnormal, and an early warning signal is generated.

[0019] Furthermore, the specific evaluation process for the heat bias RL is as follows:

[0020] Within a preset time period, the number of abnormal heat curve segments is counted as C1. All abnormal temperature rise curve segments are integrated over time to obtain the abnormal heat temperature reference energy E1. The heat deviation value RL of the kiln is calculated using the formula RL=C1×g1+E1×g2, where g1 and g2 are coefficient factors.

[0021] Furthermore, the temperature analysis module is used to transmit the early warning signal to the controller; after receiving the early warning signal, the controller controls the alarm module to issue an alarm and automatically cuts off the kiln circuit.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] 1. In this invention, the monitoring and analysis module is used to preprocess the received internal environmental data and perform ventilation coefficient analysis on the preprocessed data; combining the gas pressure information, top temperature information, bottom temperature information, CH4 gas content information, and O2 gas content information in the kiln, the ventilation coefficient TF is calculated; based on the ventilation coefficient TF, the air volume threshold FL of the corresponding ventilation device is determined; the air volume adjustment module is used to control the valve opening of the air volume adjustment valve to adjust the air volume; to realize the automatic adjustment of the gas and air ratio, achieve optimal energy consumption, and thus improve the working efficiency of the kiln;

[0024] 2. In this invention, the temperature analysis module is used to analyze the temperature changes inside the kiln and determine whether the kiln's thermal state is abnormal. The top-to-bottom temperature difference WT is calculated using the formula WT = T1 - T2. If T1 is greater than T0 and the duration exceeds a first preset duration, the kiln's thermal state is determined to be abnormal, and an early warning signal is generated. Otherwise, a curve of the top-to-bottom temperature difference WT changing over time is established. Combining the number of abnormal heat curve segments C1 and the abnormal heat temperature reference energy E1, the kiln's thermal deviation value RL is calculated. If RL ≥ the deviation threshold, the kiln's thermal state is determined to be abnormal, and an early warning signal is generated. After receiving the early warning signal, the controller controls the alarm module to issue an alarm and automatically cuts off the kiln circuit to provide protection. Attached Figure Description

[0025] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0026] Figure 1 This is a system block diagram of the Internet of Things-based kiln control system of the present invention. Detailed Implementation

[0027] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0028] like Figure 1 As shown, the IoT-based kiln control system includes a monitoring sensor group, a monitoring and analysis module, a controller, an air volume regulation module, a database, a temperature analysis module, and an alarm module.

[0029] In this embodiment, each kiln is equipped with a corresponding monitoring sensor group, and the monitoring sensor group and the monitoring and analysis module are connected in a distributed manner through Internet of Things nodes; the monitoring sensor group includes a pressure sensor, a temperature sensor, and a gas composition sensor, which are used to monitor the internal environmental data of the corresponding kiln and send the monitored internal environmental data to the monitoring and analysis module; the internal environmental data includes pressure information, temperature information, and gas composition information;

[0030] Among them, the pressure sensor is used to monitor the air pressure information inside the kiln in real time; the temperature sensor is used to monitor the temperature information at the top and bottom of the kiln in real time; the gas composition sensor is used to monitor the gas composition information inside the kiln in real time, which mainly includes CH4 gas content and O2 gas content information. Since the ratio of fuel gas to air during combustion directly affects energy consumption, insufficient air leads to incomplete combustion, and incomplete combustion products contain a large number of pollutants, while also wasting energy.

[0031] The monitoring and analysis module is used to preprocess the received internal environmental data and perform ventilation coefficient analysis on the preprocessed data. Preprocessing involves removing obviously erroneous or useless data. The specific analysis steps are as follows:

[0032] After obtaining the preprocessed data, the gas pressure information inside the kiln is marked as Y1, the temperature information at the top of the kiln is marked as T1, the temperature information at the bottom of the kiln is marked as T2, the CH4 gas content information is marked as N1, and the O2 gas content information is marked as N2.

[0033] The ventilation coefficient TF is calculated using the formula TF=Y1×b1+(T1-T2) / (T0-T1)×b2+N1 / N2×b3, where b1, b2, and b3 are coefficient factors; T0 represents the preset maximum temperature inside the furnace, for example, 1240 degrees Celsius.

[0034] The air volume of the corresponding ventilation device is determined based on the ventilation coefficient TF; the ventilation device is equipped with an air volume regulating valve; specifically:

[0035] The database stores a mapping table between the ventilation coefficient range and the air volume threshold;

[0036] The ventilation coefficient range is determined based on the ventilation coefficient TF, and then the corresponding air volume threshold FL is determined based on the ventilation coefficient range.

[0037] The monitoring and analysis module transmits the air volume threshold FL to the air volume regulation module via the controller; the air volume regulation module controls the valve opening of the air volume regulation valve to regulate the air volume; thus realizing the automatic adjustment of the gas and air ratio to achieve optimal energy consumption and improve the working efficiency of the kiln.

[0038] In this embodiment, the highest temperature inside the furnace is 1240 degrees Celsius. Since heat rises, the temperature at the top of the kiln is higher than at the bottom. If the temperature difference is too large, the porcelain insulators will crack. Therefore, the temperature difference between the bottom and top of the kiln needs to be controlled within 5 degrees Celsius. The temperature analysis module is used to analyze the temperature changes inside the kiln and determine whether the thermal state of the kiln is abnormal. The specific analysis steps are as follows:

[0039] Obtain the temperature information T1 at the top of the kiln and the temperature information T2 at the bottom of the kiln, and calculate the temperature difference WT between the top and bottom using the formula WT=T1-T2;

[0040] If T1 is greater than T0 and the duration exceeds the first preset duration, the kiln's thermal state is determined to be abnormal, and an early warning signal is generated; otherwise, a curve of the top and bottom temperature difference WT changing over time is established.

[0041] Compare WT with the preset temperature difference threshold; if WT ≥ preset temperature difference threshold, then extract the corresponding curve segment in the corresponding curve graph and mark it as the abnormal heat curve segment.

[0042] Within a preset time period, the number of abnormal heat curve segments is counted as C1. All abnormal temperature rise curve segments are integrated over time to obtain the abnormal heat temperature reference energy E1. The heat deviation value RL of the kiln is calculated using the formula RL=C1×g1+E1×g2, where g1 and g2 are coefficient factors.

[0043] The heat deviation value RL is compared with the deviation threshold. If RL ≥ the deviation threshold, the kiln heat status is determined to be abnormal, and an early warning signal is generated.

[0044] The temperature analysis module is used to transmit the early warning signal to the controller; after receiving the early warning signal, the controller controls the alarm module to issue an alarm and automatically cuts off the kiln circuit to play a protective role.

[0045] The above formulas are all numerical calculations after removing dimensions. The formulas are obtained by software simulation based on a large amount of data and are closest to the real situation. The preset parameters and preset thresholds in the formulas are set by those skilled in the art according to the actual situation or obtained by simulation based on a large amount of data.

[0046] Working principle of the invention:

[0047] The IoT-based kiln control system employs a set of monitoring sensors in each kiln to monitor its internal environmental data. A monitoring and analysis module preprocesses the received data and performs ventilation coefficient analysis. Combining kiln pressure, top and bottom temperatures, and CH4 and O2 gas content, the ventilation coefficient TF is calculated. Based on the TF, the airflow threshold FL for the corresponding ventilation device is determined. The monitoring and analysis module transmits the airflow threshold FL to the airflow regulation module via a controller. The airflow regulation module controls the valve opening to adjust the airflow, achieving automatic adjustment of the gas-air ratio for optimal energy consumption and improved kiln efficiency.

[0048] The temperature analysis module analyzes the temperature changes inside the kiln to determine if the kiln's thermal state is abnormal. It calculates the top-to-bottom temperature difference WT using the formula WT = T1 - T2. If T1 is greater than T0 and its duration exceeds a first preset duration, the kiln's thermal state is deemed abnormal, and an early warning signal is generated. Otherwise, a curve of the top-to-bottom temperature difference WT over time is established. If WT ≥ a preset temperature difference threshold, the corresponding curve segment is extracted from the curve and marked as an abnormal thermal curve segment. Combining the number of abnormal thermal curve segments C1 and the abnormal thermal temperature reference energy E1, the kiln's thermal deviation RL is calculated. If RL ≥ the deviation threshold, the kiln's thermal state is deemed abnormal, and an early warning signal is generated. Upon receiving the early warning signal, the controller activates the alarm module to issue an alarm and automatically cuts off the kiln's circuit for protection.

[0049] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0050] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A kiln control system based on the Internet of Things, characterized in that, It includes a monitoring sensor group, a monitoring and analysis module, a controller, a database, an airflow regulation module, and a temperature analysis module; Each kiln is equipped with a corresponding set of monitoring sensors to monitor the internal environmental data of its corresponding kiln and send the monitored internal environmental data to the monitoring and analysis module; the internal environmental data includes air pressure information, temperature information and gas composition information. The monitoring and analysis module is used to preprocess the received internal environmental data, analyze the ventilation coefficient of the preprocessed data, and determine the air volume threshold FL of the corresponding ventilation device based on the ventilation coefficient TF; the monitoring and analysis module is used to transmit the air volume threshold FL to the air volume adjustment module via the controller to adjust the air volume of the ventilation device. The temperature analysis module is used to analyze the temperature changes inside the kiln and determine whether the kiln's thermal state is abnormal; the specific analysis steps are as follows: Establish a curve of the temperature difference WT between the top and bottom as a function of time; compare WT with a preset temperature difference threshold. If WT ≥ preset temperature difference threshold, the corresponding curve segment is extracted from the corresponding curve graph and marked as abnormal heat curve segment; the heat deviation RL is evaluated based on the occurrence of abnormal heat curve segment; if RL ≥ deviation threshold, the kiln heat state is determined to be abnormal and an early warning signal is generated. The temperature analysis module also includes: Obtain the temperature information T1 at the top of the kiln and the temperature information T2 at the bottom of the kiln, and calculate the temperature difference WT between the top and bottom using the formula WT=T1-T2; If T1 is greater than T0 and the duration exceeds the first preset duration, the kiln's thermal state is determined to be abnormal, and an early warning signal is generated; T0 represents the preset highest temperature inside the kiln. The specific evaluation process for the heat bias RL is as follows: Within a preset time period, the number of abnormal heat curve segments is counted as C1. All abnormal temperature rise curve segments are integrated over time to obtain the abnormal heat temperature reference energy E1. The heat deviation value RL of the kiln is calculated using the formula RL=C1×g1+E1×g2, where g1 and g2 are coefficient factors.

2. The kiln control system based on the Internet of Things according to claim 1, characterized in that, The specific analysis steps of the monitoring and analysis module are as follows: After obtaining the preprocessed data, the gas pressure information inside the kiln is marked as Y1, the temperature information at the top of the kiln is marked as T1, the temperature information at the bottom of the kiln is marked as T2, the CH4 gas content information is marked as N1, and the O2 gas content information is marked as N2. The ventilation coefficient TF is calculated using the formula TF=Y1×b1+(T1-T2) / (T0-T1)×b2+N1 / N2×b3, where b1, b2, and b3 are coefficient factors; T0 represents the preset maximum temperature inside the furnace.

3. The kiln control system based on the Internet of Things according to claim 2, characterized in that, The database stores a mapping table between ventilation coefficient ranges and air volume thresholds; the preprocessing involves removing obviously erroneous or useless data.

4. The kiln control system based on the Internet of Things according to claim 1, characterized in that, The monitoring sensor group includes a pressure sensor, a temperature sensor, and a gas composition sensor. The pressure sensor is used to monitor the gas pressure information inside the kiln in real time; the temperature sensor is used to monitor the temperature information at the top and bottom of the kiln in real time; and the gas composition sensor is used to monitor the gas composition information inside the kiln in real time, including CH4 gas content and O2 gas content.

5. The kiln control system based on the Internet of Things according to claim 1, characterized in that, The ventilation device is equipped with an air volume regulating valve; the air volume regulating module is used to control the valve opening of the air volume regulating valve to regulate the air volume.

6. The kiln control system based on the Internet of Things according to claim 1, characterized in that, The temperature analysis module is used to transmit the early warning signal to the controller; after receiving the early warning signal, the controller controls the alarm module to issue an alarm and automatically cuts off the kiln circuit to play a protective role.

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