Power plant solenoid valve coil life prediction system

Abstract

The embodiment of the invention provides a power plant solenoid valve coil life prediction system, and relates to the technical field of power plant equipment maintenance, and the system comprises a data collection module which is used for monitoring the current and voltage of a solenoid valve coil and the temperature data of the coil in real time; the data transmission module is used for packing and uploading the collected data to a cloud server in a wireless communication mode; the data processing and analysis module analyzes the resistance change rate and the aging factor of the coil based on the uploaded data to generate an analysis result; the early warning decision support module predicts the residual life of the coil based on the analysis result and a preset life prediction model, and provides decision suggestions based on a prediction value; according to the method, the current, voltage and temperature data of the solenoid valve coil are comprehensively collected, the data are analyzed and processed at the cloud to accurately predict the residual life of the coil, effective decision suggestions are provided according to the prediction result, and the problems of incomplete data collection and inaccurate life prediction in the prior art are solved.

Description

Technical Field

[0001] The invention relates to the technical field of power plant equipment maintenance, and in particular to a power plant solenoid valve coil life prediction system. Background Art

[0002] In the early stages of power plant development, equipment monitoring mainly relied on manual inspections. Technicians regularly inspected the equipment and determined whether there were any problems with the equipment by observing its appearance and listening to the sound of its operation. This method is inefficient, and it is difficult to detect some potential faults in a timely manner. For example, the aging problem of the solenoid valve coil may not have obvious appearance characteristics or abnormal sounds in the early stages, but in fact its performance has begun to decline; and with the development of sensor technology, power plants began to install various sensors on the equipment. For solenoid valve coils, sensors for measuring current and voltage began to be used. These sensors can obtain the operating parameters of the equipment in real time, allowing technicians to remotely monitor the operating status of the equipment. However, simply obtaining parameters is not enough to fully understand the health of the equipment, and there is still a lack of effective methods for analyzing these parameters and predicting the remaining life of the equipment;

[0003] Therefore, how to provide a power plant solenoid valve coil life prediction system has become a technical problem that technicians in this field are eager to solve. Summary of the invention

[0004] The present invention provides a power plant solenoid valve coil life prediction system, which comprehensively collects the current, voltage and temperature data of the solenoid valve coil and establishes a life prediction model that comprehensively considers multiple aging factors to solve the problems existing in the above-mentioned prior art.

[0005] The present invention provides a power plant solenoid valve coil life prediction system, comprising:

[0006] A data acquisition module, which is used to monitor the current, voltage and temperature data of the solenoid valve coil in real time;

[0007] A data transmission module, which is connected to the data acquisition module and is used to package and upload the collected data to a cloud server via wireless communication;

[0008] A data processing and analysis module is provided in the cloud server and connected to the data transmission module, and analyzes the resistance change rate and aging factor of the coil based on the uploaded data to generate an analysis result;

[0009] The early warning decision support module is arranged in the cloud server and connected to the data processing and analysis module. It predicts the remaining life of the coil based on the analysis results and a preset life prediction model, and provides decision suggestions based on the predicted value.

[0010] According to a power plant solenoid valve coil life prediction system provided by the present invention, the data acquisition module includes:

[0011] A current sensor unit, which is used to measure the current value flowing through the solenoid valve coil;

[0012] A voltage sensor unit, which is used to measure the voltage value supplied to the solenoid valve coil;

[0013] A coil temperature sensor unit, which is used to measure the temperature value of the solenoid valve coil itself;

[0014] A data identification unit is connected to the current sensor unit, the voltage sensor unit and the coil temperature sensor unit, and inserts corresponding coil identification codes and timestamps into various parameters based on the electromagnetic valve coils corresponding to each sensor unit and the measurement time.

[0015] According to a power plant solenoid valve coil life prediction system provided by the present invention, the current sensor unit adopts a Hall effect sensor, the voltage sensor unit adopts a resistor voltage divider circuit, and the ambient temperature sensor unit and the coil temperature sensor unit are connected using a thermistor.

[0016] According to a power plant solenoid valve coil life prediction system provided by the present invention, the data transmission module includes:

[0017] A data packaging unit connected to the data identification unit, for summarizing the various parameters detected in a data set corresponding to the coil identification code according to the coil identification code, and arranging the parameters in each data set in chronological order according to the timestamps of the various parameters;

[0018] A wireless communication unit, connected to the data packaging unit, for uploading the data set to the cloud server via a wireless network;

[0019] A data cache unit is connected to the wireless communication unit and is used to temporarily store the data set when the data set cannot be uploaded immediately.

[0020] According to a power plant solenoid valve coil life prediction system provided by the present invention, the wireless communication unit adopts LoRa or NB-IOT technology.

[0021] According to a power plant solenoid valve coil life prediction system provided by the present invention, the data processing and analysis module includes:

[0022] A preprocessing unit connected to the wireless communication unit and used to identify and clean the uploaded data set so that various parameters can be quickly applied to the analysis process;

[0023] A resistance change analysis unit connected to the preprocessing unit analyzes the change of the coil resistance over time and temperature based on a pre-established resistance change model, and calculates a predicted resistance value of the coil at a future time;

[0024] An aging factor analysis unit, which is connected to the preprocessing unit, analyzes the influence of the current on the aging of the coil based on a pre-established aging factor model, and calculates the aging factor parameter value of the coil at a future time;

[0025] A result summarizing unit is connected to the resistance change analyzing unit and the aging factor analyzing unit, and is used to summarize the resistance prediction value and the aging factor parameter value, and insert the corresponding coil identification code.

[0026] According to a power plant solenoid valve coil life prediction system provided by the present invention, the resistance value change model is:

[0027] R (t) =R0*e -αt +βT (t)

[0028] Among them, R (t) is the predicted resistance value of the coil at the future time t, R0 is the resistance value of the coil at the initial time, and the initial time is the time corresponding to the new installation or maintenance; α is the time attenuation coefficient, which is used to reflect the aging speed of the coil material over time. The larger α is, the faster the coil ages. It is estimated by long-term tracking tests of coils of the same type; T (t) is the average temperature value of the coil, representing the average temperature of each coil in the historical time; β is the temperature influence coefficient, which is used to reflect the influence of coil temperature on resistance, and is obtained through the physical properties of the material and resistance tests at different temperatures under laboratory conditions.

[0029] According to a power plant solenoid valve coil life prediction system provided by the present invention, the aging factor model is:

[0030]

[0031] Among them, A (t) is the aging factor parameter value of the coil at the future time t, representing the aging degree of the coil at the time t; γ is the related constant of the coil material, representing the influence of the square of the current on the coil life, determined based on experiments; I(s) is the function of the change of the current flowing through the coil with time, determined based on the actual current pattern; is the time integral of the square of the current flowing through the coil since the initial working state, representing the accumulated power loss.

[0032] According to a power plant solenoid valve coil life prediction system provided by the present invention, the early warning decision support module includes:

[0033] The life prediction unit is connected to the result summary unit and is used to calculate the remaining life prediction value of the coil according to the summarized resistance prediction value and aging factor parameter value; the calculation formula is:

[0034]

[0035] Wherein, L is the predicted value of the remaining life of the coil; is the expected reduction in life due to natural aging calculated from the change in resistance; A is the correction term after considering the temperature effect, which represents the process of accelerating coil aging after the temperature rises; (t) is the above aging factor parameter value, representing the additional aging effect caused by current;

[0036] an alarm triggering unit, which is connected to the life prediction unit, pre-sets a life threshold, generates a warning signal based on a comparison result between the remaining life prediction value L and the life threshold, and triggers a corresponding alarm signal;

[0037] A decision support unit is connected to the alarm trigger unit and provides a corresponding maintenance plan suggestion to the user based on the type of the alarm signal; wherein a plurality of maintenance plan suggestions are pre-set and bound to different types of alarm signals.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] 1. The data acquisition module of this system covers the current, voltage and temperature data of the solenoid valve coil; unlike the existing technology which usually only focuses on a single parameter, this comprehensive data acquisition provides a richer information basis for accurately evaluating the coil status;

[0040] 2. The system is equipped with a data cache unit, which can be used for temporary storage when the network is poor and data cannot be uploaded immediately, thus avoiding data loss and further improving the reliability of data transmission;

[0041] 3. The pre-processing unit of this system identifies and cleans the uploaded data set, optimizes the data quality and makes subsequent analysis more accurate;

[0042] 4. The resistance change analysis unit of this system analyzes the coil resistance change based on the resistance change model that comprehensively considers the influence of time and temperature, and the aging factor analysis unit analyzes based on the aging factor model that considers the influence of current on coil aging. Compared with the incomplete model in the prior art, the model of this system can more accurately reflect the actual situation of coil aging, thereby improving the accuracy of life prediction;

[0043] 5. The life prediction unit of the early warning decision support module of this system calculates the predicted value of the remaining life of the coil according to a formula that comprehensively considers the predicted value of resistance and the parameter value of the aging factor; compared with the inaccurate prediction model in the prior art, this system can more accurately predict the remaining life of the coil.

[0044] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0045] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0047] Figure 1 It is a structural schematic diagram of a power plant solenoid valve coil life prediction system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0049] Embodiment 1:

[0050] This embodiment provides a power plant solenoid valve coil life prediction system, see Figure 1 ,include:

[0051] A data acquisition module, which is used to monitor the current, voltage and temperature data of the solenoid valve coil in real time;

[0052] A data transmission module, which is connected to the data acquisition module and is used to package and upload the collected data to the cloud server via wireless communication;

[0053] A data processing and analysis module is provided in the cloud server and connected to the data transmission module, and analyzes the resistance change rate and aging factors of the coil based on the uploaded data to generate analysis results;

[0054] The early warning decision support module is set in the cloud server and connected to the data processing and analysis module. It predicts the remaining life of the coil based on the analysis results and the preset life prediction model, and provides decision suggestions based on the predicted value.

[0055] The principle of the above embodiment is: the data acquisition module obtains the current, voltage and temperature data of the solenoid valve coil in real time through the corresponding sensors; these data are the basis for subsequent analysis and prediction; for example, the current and voltage data can reflect the working state of the coil, and the temperature data is crucial for analyzing the aging of the coil, because the temperature will affect the resistance and aging speed of the coil; the data transmission module packages the collected data and uploads it to the cloud server through wireless communication; the packaging process can ensure the integrity and orderliness of the data, and the wireless communication method facilitates the remote transmission of the data, so that the equipment can be monitored at different locations; the data processing and analysis module in the cloud server first pre-processes the uploaded data, such as identifying and cleaning the data, to improve the data quality; then, according to the resistance change model, the change of the coil resistance with time and temperature is analyzed, and the resistance prediction value at the future time is calculated; at the same time, the influence of the current on the aging of the coil is analyzed, and the aging factor parameter value at the future time is calculated; finally, these results are summarized; the early warning decision support module calculates the remaining life prediction value of the coil according to the summarized results and the preset life prediction model; if the remaining life prediction value is lower than the preset threshold, an alarm is triggered, and corresponding decision suggestions are provided according to the alarm type, such as maintenance plan suggestions.

[0056] The beneficial effects of the above embodiments are: it can collect current, voltage and temperature data at the same time, and compared with the system that only collects single data, it can have a more comprehensive understanding of the working status and aging of the coil, providing a more sufficient basis for accurately predicting the life; the use of wireless communication to upload data facilitates remote monitoring, and through data packaging and possible data caching, the reliability of data transmission is guaranteed, and the risk of data loss is reduced; data processing and analysis are performed in the cloud server, with sufficient computing resources and advanced algorithms; by preprocessing the data and using resistance changes and aging factors that comprehensively consider multiple factors, the resistance change rate and aging factors of the coil can be more accurately analyzed, thereby improving the accuracy of life prediction; it can trigger alarms in time and provide effective decision-making suggestions based on accurate life prediction results, which helps power plant maintenance personnel take timely measures to avoid equipment shutdowns caused by coil failures and other problems, thereby improving the reliability and safety of power plant equipment operation.

[0057] In order to further optimize the above embodiment, the data acquisition module includes:

[0058] A current sensor unit, which is used to measure the current value flowing through the solenoid valve coil;

[0059] A voltage sensor unit, which is used to measure the voltage value supplied to the solenoid valve coil;

[0060] A coil temperature sensor unit, which is used to measure the temperature value of the solenoid valve coil itself;

[0061] A data identification unit connected to the current sensor unit, the voltage sensor unit, and the coil temperature sensor unit, inserts a corresponding coil identification code and a timestamp into various parameters based on the solenoid valve coil and the measurement time corresponding to each sensor unit;

[0062] Among them, the current sensor unit adopts a Hall effect sensor, the voltage sensor unit adopts a resistor voltage divider circuit, and the ambient temperature sensor unit and the coil temperature sensor unit are connected by a thermistor.

[0063] It should be noted that the Hall effect sensor has the advantages of high precision, high sensitivity, and non-contact measurement; it can accurately measure current and will not interfere with the circuit being measured; its working principle is based on the Hall effect. When current passes through a conductor placed in a magnetic field, a potential difference will be generated on both sides of the conductor. This potential difference is proportional to the current; therefore, by measuring this potential difference, the value of the current can be obtained; the resistor voltage divider circuit is a simple and effective voltage measurement method; it connects a known resistor in series with the voltage source being measured, and then measures the voltage divider on the known resistor. According to the voltage divider principle, the value of the measured voltage can be calculated; this circuit has a simple structure and low cost, and the appropriate resistance value can be selected as needed to achieve voltage measurement of different ranges; thermistor A resistor is a resistive element that is very sensitive to temperature changes; its resistance value will decrease (negative temperature coefficient thermistor) or increase (positive temperature coefficient thermistor) as the temperature increases; the temperature value can be indirectly measured by measuring the change in the resistance value of the thermistor; thermistors have the advantages of small size, fast response speed, and high accuracy, and are very suitable for measuring the temperature of the coil; the coil identification code can distinguish different solenoid valve coils, so that the data of each coil can be accurately identified in subsequent data processing and analysis; the timestamp records the measurement time, which is very important for analyzing the relationship between the performance change trend of the coil and time; for example, the aging process of the coil can be observed by comparing data at different time points, and the specific time when a certain abnormal situation occurs can be determined.

[0064] In order to further optimize the above embodiment, the data transmission module includes:

[0065] A data packaging unit, which is connected to the data identification unit, is used to summarize the various parameters detected in a data set corresponding to the coil identification code according to the coil identification code, and arrange the parameters in each data set in chronological order according to the timestamps of the various parameters;

[0066] A wireless communication unit, which is connected to the data packaging unit and is used to upload the data set to the cloud server via a wireless network;

[0067] a data cache unit connected to the wireless communication unit and used for temporarily storing the data set when the data set cannot be uploaded immediately;

[0068] Among them, the wireless communication unit adopts LoRa or NB-IOT technology.

[0069] It should be noted that the data packaging unit is connected to the data identification unit; its main function is to sort and organize the collected data for subsequent transmission and processing;

[0070] According to the coil identification code, it summarizes the various parameters detected in the data set corresponding to the coil identification code; this is like establishing an exclusive "data file" for each solenoid valve coil, so that the data of different coils can be clearly distinguished; at the same time, according to the timestamps of various parameters, it arranges the parameters in each data set in chronological order; the advantage of this is that when analyzing the performance changes of the coil in the subsequent period, the change trend of the parameters can be accurately observed in chronological order, for example, it can clearly see how the current, voltage, temperature and other parameters change over time, so as to better understand the aging process of the coil;

[0071] The wireless communication unit is connected to the data packaging unit, and its core function is to upload the packaged data to the cloud server via the wireless network;

[0072] LoRa technology has the characteristics of long-distance transmission, low power consumption, and strong anti-interference ability. It can achieve stable data transmission over a long distance, which is suitable for some large power plants where solenoid valve coils may be distributed over a long distance. Moreover, its low power consumption allows sensor equipment to run for a long time without frequent battery replacement, reducing maintenance costs. NB-IOT technology is a narrowband Internet of Things technology with the advantages of wide coverage, large number of connections, and low cost. In some complex industrial environments, there may be a large number of solenoid valve coils that need to be monitored. NB-IOT technology can well meet the needs of connecting a large number of devices and ensure the stability and reliability of data transmission.

[0073] The data cache unit is connected to the wireless communication unit; when the data set cannot be uploaded immediately due to network failure or other reasons, it will play a role in temporarily storing the data set;

[0074] If there is no data cache unit, the collected data may be lost when a network problem occurs, which will lead to omissions in subsequent data processing and analysis, and it is impossible to accurately understand the status of the coil; with a data cache unit, once the network returns to normal, the cached data can continue to be uploaded, ensuring the integrity and continuity of the data, thereby ensuring the accuracy and reliability of the entire system's monitoring of the solenoid valve coil.

[0075] In order to further optimize the above embodiment, the data processing and analysis module includes:

[0076] A pre-processing unit, which is connected to the wireless communication unit and is used to identify and clean the uploaded data set so that various parameters can be quickly applied to the analysis process;

[0077] A resistance change analysis unit is connected to the preprocessing unit, and analyzes the change of the coil resistance with time and temperature based on a pre-established resistance change model, and calculates the predicted resistance value of the coil at a future time;

[0078] An aging factor analysis unit is connected to the preprocessing unit, and analyzes the influence of the current on the aging of the coil based on a pre-established aging factor model, and calculates the aging factor parameter value of the coil at a future time;

[0079] The result summary unit is connected to the resistance change analysis unit and the aging factor analysis unit, and is used to summarize the resistance prediction value and the aging factor parameter value, and insert the corresponding coil identification code.

[0080] Among them, the resistance change model is:

[0081] R (t) =R0*e -αt +βT (t)

[0082] Among them, R (t) is the predicted resistance value of the coil at the future time t, R0 is the resistance value of the coil at the initial time, and the initial time is the time corresponding to the new installation or maintenance; α is the time attenuation coefficient, which is used to reflect the aging rate of the coil material over time. The larger α is, the faster the coil ages. It is estimated by long-term tracking tests of coils of the same type; T (t) is the average temperature value of the coil, representing the average temperature of each coil in the historical time; β is the temperature influence coefficient, which is used to reflect the influence of coil temperature on resistance, and is obtained through the physical properties of the material and resistance tests at different temperatures under laboratory conditions.

[0083] It should be noted that the recognition operation refers to the ability to distinguish different types of parameters in the data set, such as accurately identifying which are current values, which are voltage values, which are temperature values, etc.; the cleaning operation is to remove erroneous data, duplicate data or abnormal values ​​that may exist in the data set; for example, if a sensor fails, some unreasonable data may be collected, and the cleaning operation can remove these data to ensure the quality of the data used for subsequent analysis;

[0084] R in the formula (t)is the predicted value of the coil resistance at a future time; R0 is the resistance value of the coil at the initial time, which corresponds to the time after new installation or maintenance, and is a reference value;

[0085] α is the time decay coefficient, which reflects the aging rate of the coil material over time; the larger the α, the faster the coil ages; this coefficient is estimated by long-term tracking tests on coils of the same type; for example, if a batch of solenoid valve coils of the same type are monitored for many years and their resistance changes are observed, the value of α can be determined based on these data;

[0086] T (t) is the average temperature value of the coil, which represents the average temperature of each coil in the historical time; the temperature has an impact on the resistance of the coil, and different temperatures will cause the resistance to change;

[0087] β is the temperature influence coefficient, which is used to reflect the influence of coil temperature on resistance. This coefficient is obtained through the physical properties of the material and resistance tests at different temperatures under laboratory conditions. For example, in the laboratory, the resistance of the material used to make the coil is tested at different temperatures, and the value is determined based on the test results.

[0088] Among them, the aging factor model is:

[0089]

[0090] Among them, A (t) is the aging factor parameter value of the coil at the future time t, representing the aging degree of the coil at the time t; γ is the related constant of the coil material, representing the influence of the square of the current on the coil life, determined based on experiments; I(s) is the function of the change of the current flowing through the coil with time, determined based on the actual current pattern; is the time integral of the square of the current flowing through the coil since the initial working state, representing the accumulated power loss.

[0091] It should be noted that for A (t) , which directly represents the degree of coil aging at time t. The larger this value is, the more serious the coil aging is. For γ, this constant represents the degree of influence of the square of the current on the coil life. Coils of different materials may have different γ values. For example, for a solenoid valve coil of a certain material, a series of experiments are conducted to observe the aging of the coil under different current conditions, so as to determine the γ value corresponding to the material;

[0092] As for the function I(s) of the change of the current flowing through the coil over time, it is set based on different current types; for example, if the constant current gas current value is I0, then I(s) = I0, where s represents time; if it is a sine wave current, then Among them I mis the amplitude of the sinusoidal current, ω is the angular frequency (ω=2πf, f is the frequency), is the phase; the same is true for square wave current or other types of current. The selection of specific functions is prior art and will not be elaborated on.

[0093] In order to further optimize the above embodiment, the early warning decision support module includes:

[0094] The life prediction unit is connected to the result summary unit and is used to calculate the remaining life prediction value of the coil according to the summarized resistance prediction value and aging factor parameter value; the calculation formula is:

[0095]

[0096] Wherein, L is the predicted value of the remaining life of the coil; is the expected reduction in life due to natural aging calculated from the change in resistance; A is the correction term after considering the temperature effect, which represents the process of accelerating coil aging after the temperature rises; (t) is the above aging factor parameter value, representing the additional aging effect caused by current;

[0097] An alarm triggering unit, which is connected to the life prediction unit, pre-sets a life threshold, generates a warning signal based on the comparison result of the remaining life prediction value L and the life threshold, and triggers a corresponding alarm signal;

[0098] The decision support unit is connected to the alarm trigger unit and provides the user with corresponding maintenance plan suggestions based on the type of the alarm signal; wherein a plurality of maintenance plan suggestions are preset and bound to different types of alarm signals.

[0099] It should be noted that as time goes by, the coil resistance will change due to material aging, and this change will lead to a reduction in the coil life. The life span reduced by natural aging is calculated by the change of resistance and time attenuation coefficient; temperature has an impact on coil aging. When the temperature rises, the aging speed of the coil will accelerate. The temperature influence coefficient and time attenuation coefficient are used to quantify the effect of temperature on life, and to correct the life reduction value caused by natural aging calculated previously; current also affects coil aging, and the parameter value A calculated by the aging factor model is (t) , is taken into account here in the calculation of the remaining life prediction value to more comprehensively reflect the aging condition and remaining life of the coil;

[0100] For the alarm trigger unit, if the remaining life prediction value is less than the preset life threshold, it means that the coil may be about to fail, and a warning signal will be generated and the corresponding alarm will be triggered. For example, if the set life threshold is 1000 hours, and the calculated remaining life prediction value is 800 hours, then an alarm will be triggered to remind relevant personnel to pay attention to the status of the coil.

[0101] Several maintenance plan suggestions are pre-set and bound to different types of alarm signals; for example, if it is a minor warning signal, the corresponding maintenance plan suggestion may be to regularly check the temperature and current of the coil; if it is a more serious warning signal, the corresponding maintenance plan suggestion may be to replace the coil or conduct a comprehensive overhaul of the coil; providing corresponding maintenance plan suggestions based on different alarm signals can help users maintain the solenoid valve coil more effectively and avoid equipment operation problems caused by coil failure.

[0102] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A power plant solenoid valve coil life prediction system, characterized in that: include: A data acquisition module, which is used to monitor the current, voltage and temperature data of the solenoid valve coil in real time; A data transmission module, which is connected to the data acquisition module and is used to package and upload the collected data to a cloud server via wireless communication; A data processing and analysis module is provided in the cloud server and connected to the data transmission module, and analyzes the resistance change rate and aging factor of the coil based on the uploaded data to generate an analysis result; The early warning decision support module is arranged in the cloud server and connected to the data processing and analysis module. It predicts the remaining life of the coil based on the analysis results and a preset life prediction model, and provides decision suggestions based on the predicted value.

2. A power plant solenoid valve coil life prediction system according to claim 1, characterized in that: The data acquisition module comprises: A current sensor unit, which is used to measure the current value flowing through the solenoid valve coil; A voltage sensor unit, which is used to measure the voltage value supplied to the solenoid valve coil; A coil temperature sensor unit, which is used to measure the temperature value of the solenoid valve coil itself; A data identification unit is connected to the current sensor unit, the voltage sensor unit and the coil temperature sensor unit, and inserts corresponding coil identification codes and timestamps into various parameters based on the electromagnetic valve coils corresponding to each sensor unit and the measurement time.

3. A power plant solenoid valve coil life prediction system according to claim 2, characterized in that: The current sensor unit adopts a Hall effect sensor, the voltage sensor unit adopts a resistor voltage divider circuit, and the ambient temperature sensor unit and the coil temperature sensor unit are connected by a thermistor.

4. A power plant solenoid valve coil life prediction system according to claim 3, characterized in that: The data transmission module comprises: A data packaging unit connected to the data identification unit, for summarizing the various parameters detected in a data set corresponding to the coil identification code according to the coil identification code, and arranging the parameters in each data set in chronological order according to the timestamps of the various parameters; A wireless communication unit, connected to the data packaging unit, for uploading the data set to the cloud server via a wireless network; A data cache unit is connected to the wireless communication unit and is used to temporarily store the data set when the data set cannot be uploaded immediately.

5. A power plant solenoid valve coil life prediction system according to claim 4, characterized in that: The wireless communication unit adopts LoRa or NB-IOT technology.

6. A power plant solenoid valve coil life prediction system according to claim 5, characterized in that: The data processing and analysis module includes: A preprocessing unit connected to the wireless communication unit and used to identify and clean the uploaded data set so that various parameters can be quickly applied to the analysis process; A resistance change analysis unit connected to the preprocessing unit analyzes the change of the coil resistance over time and temperature based on a pre-established resistance change model, and calculates a predicted resistance value of the coil at a future time; An aging factor analysis unit, which is connected to the preprocessing unit, analyzes the influence of the current on the aging of the coil based on a pre-established aging factor model, and calculates the aging factor parameter value of the coil at a future time; A result summarizing unit is connected to the resistance change analyzing unit and the aging factor analyzing unit, and is used to summarize the resistance prediction value and the aging factor parameter value, and insert the corresponding coil identification code.

7. A power plant solenoid valve coil life prediction system according to claim 6, characterized in that: The resistance change model is: R (t) =R0*e -αt +βT (t) Among them, R (t) is the predicted resistance value of the coil at the future time t, R0 is the resistance value of the coil at the initial time, and the initial time is the time corresponding to the new installation or maintenance; α is the time attenuation coefficient, which is used to reflect the aging speed of the coil material over time. The larger α is, the faster the coil ages. It is estimated by long-term tracking tests of coils of the same type; T (t) is the average temperature value of the coil, representing the average temperature of each coil in the historical time; β is the temperature influence coefficient, which is used to reflect the influence of coil temperature on resistance, and is obtained through the physical properties of the material and resistance tests at different temperatures under laboratory conditions.

8. A power plant solenoid valve coil life prediction system according to claim 7, characterized in that: The aging factor model is: Among them, A (t) is the aging factor parameter value of the coil at the future time t, representing the aging degree of the coil at the time t; γ is the related constant of the coil material, representing the influence of the square of the current on the coil life, determined based on experiments; I(s) is the function of the change of the current flowing through the coil with time, determined based on the actual current pattern; is the time integral of the square of the current flowing through the coil since the initial working state, representing the accumulated power loss.

9. A power plant solenoid valve coil life prediction system according to claim 8, characterized in that: The early warning decision support module includes: The life prediction unit is connected to the result summary unit and is used to calculate the remaining life prediction value of the coil according to the summarized resistance prediction value and aging factor parameter value; the calculation formula is: Wherein, L is the predicted value of the remaining life of the coil; is the expected reduction in life due to natural aging calculated from the change in resistance; A is the correction term after considering the temperature effect, which represents the process of accelerating coil aging after the temperature rises; (t) is the above aging factor parameter value, representing the additional aging effect caused by current; an alarm triggering unit, which is connected to the life prediction unit, pre-sets a life threshold, generates a warning signal based on a comparison result between the remaining life prediction value L and the life threshold, and triggers a corresponding alarm signal; A decision support unit is connected to the alarm trigger unit and provides a corresponding maintenance plan suggestion to the user based on the type of the alarm signal; wherein a plurality of maintenance plan suggestions are pre-set and bound to different types of alarm signals.

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