An intelligent fault diagnosis method for subway signal power supply

Abstract

The application discloses an intelligent fault diagnosis method for a subway signal power supply and relates to the technical field of fault diagnosis. The method comprises the following steps: acquiring line connection information of a target signal power supply, obtaining a target connection set, and obtaining a target connection item composed of at least one connection line; acquiring type identification data stored by the target signal power supply, obtaining an identification information item, and identifying information items including rated voltage, cycle times and aging information; and creating a first feedback formula based on the identification information item. According to the application, the decline amplitude of the rated voltage is obtained according to a comprehensive influence formula, and the decline amplitude is combined with different connection lines, so that the intelligent diagnosis effect of different branches according to the actual use data of the target signal power supply is realized, and the situation that the actual feedback data of the line under different discharge voltages cannot be detected due to the fluctuation of the discharge voltage is avoided.

Description

Technical Field

[0001] This invention relates to the field of fault diagnosis technology, specifically to an intelligent fault diagnosis method for subway signal power supplies. Background Technology

[0002] Subway signal power supplies are specialized power supply devices that provide stable power to the subway signaling system. They ensure the continuous and normal operation of signaling equipment such as signals, turnout controllers, and communication equipment, guaranteeing the safety and punctuality of train operations. During the use of subway signal power supplies, fault diagnosis is crucial. The normal operation of the signal power supply is the foundation of the signaling system's safety, ensuring that trains run on time and correctly, avoiding collisions or mis-entries. Furthermore, power supply failures can paralyze the signaling system, causing operational interruptions and affecting passenger safety and traffic efficiency.

[0003] The power supply fault detection method, apparatus, device, and storage medium disclosed in patent publication number CN117149493A, if a power supply fault is detected, acquires the power controller status. When the power controller is in a Stby state, it sends a first working request to the CPLD and, based on the first working result received from the CPLD, sends a first communication command to the analog converter. Then, based on the first communication completion result received from the analog converter, it sends status register information to the BMC. Finally, the BMC analyzes the power supply fault information to obtain the address information and cause of the faulty power supply and sends it to the user's terminal device. This method enables the BMC to acquire server fault information even when the power controller is in a Stby state, thereby accurately analyzing and locating the fault, enhancing operability.

[0004] In the process of using the above and similar technical solutions, when the subway signal power supply discharges, it needs to release electrical energy to different lines according to the specific electrical equipment connected. Therefore, it is necessary to diagnose the status of each line separately. However, when the power supply discharges, the magnitude of the discharge voltage will fluctuate to a certain extent under the influence of many factors such as different temperatures, humidity, vibration, and aging. Therefore, when using a fixed diagnostic voltage to diagnose different lines, it is impossible to detect the actual feedback data of the line under different discharge voltages, resulting in inaccurate diagnostic results. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent fault diagnosis method for subway signal power supplies to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: an intelligent fault diagnosis method for subway signal power supplies, comprising:

[0007] Obtain the line connection information of the target signal power supply to obtain the target connection set. The target connection set includes at least one target connection item consisting of a connection line.

[0008] Obtain the type identification data stored in the target signal power supply to obtain identification information items, which include rated voltage, number of cycles, and aging information.

[0009] Based on the identification information item, a first feedback formula is created. The first feedback formula is used to represent the first influence feedback data of the target signal power supply output voltage, and the first influence item is obtained.

[0010] The environmental information data of the target signal power source is obtained to obtain environmental information items. A second feedback formula is created based on the environmental information items. The second feedback formula is used to represent the second influence feedback data of the output voltage of the target signal power source to obtain the second influence item. Based on the combination result of the first influence item and the second influence item, the comprehensive influence formula of the target signal power source is obtained.

[0011] The limit voltage data of the target signal power supply is obtained based on the comprehensive influence formula, and the limit voltage term is obtained. The target connection term and the rated voltage data of the target signal power supply are obtained based on the identification information term, and the branch voltage term and the rated total voltage term are obtained.

[0012] The voltage span value is obtained by taking the drop of the limit voltage term based on the rated total voltage term. Based on the voltage span value, the predicted voltage data of each target connection term is obtained to obtain the connection prediction term.

[0013] The system acquires real-time voltage data of the target connection item, obtains the real-time connection item, compares the predicted connection item with the real-time connection item, diagnoses the target connection item, obtains the target connection item with early warning, and obtains the diagnosed connection item. This achieves intelligent diagnosis of different branches based on the actual usage data of the target signal power supply.

[0014] Furthermore, the first feedback formula includes a reference discharge module, a cycle aging module, and a calendar aging module, and the method for creating the first feedback formula includes:

[0015] ;

[0016] in As the first influencing factor, As a reference discharge module, For cyclic aging module, For calendar aging module;

[0017] ;

[0018] in Rated voltage, Let Euler's constant be 1. Discharge time, For internal resistance, For capacity;

[0019] ;

[0020] in The cyclic decay rate, The number of charge / discharge cycles. This represents the total number of cycles in the user's lifetime.

[0021] ;

[0022] in The time decay coefficient, This refers to the end of lifespan. This refers to the discharge time.

[0023] Furthermore, the environmental information items include temperature, humidity, and vibration items, and the method for creating the second feedback formula includes:

[0024] ;

[0025] in As the second influencing factor, For temperature, For humidity, It is a vibration term;

[0026] ;

[0027] in For temperature coefficient, For ambient temperature, The reference ambient temperature;

[0028] ;

[0029] in Humidity coefficient Relative humidity, Humidity index;

[0030] ;

[0031] in As a mechanical degradation factor, The amplitude of vibration. The vibration frequency, For duration.

[0032] Furthermore, the target signal power supply stores connection signal data, and the method for obtaining the target connection set includes:

[0033] Based on the connection signal data, obtain the activity information of the connection with the target signal power supply to obtain the activity information item;

[0034] Based on the active information items, obtain the actual number of connected branches and connected node information to obtain the target connection set and node information set. Based on the matching results of the target connection set and the node information set, obtain the target connection set.

[0035] Furthermore, the target signal power supply also stores identification data, and the method for obtaining the identification information items includes:

[0036] Based on the type recognition data, the rated output voltage information, charge and discharge cycle information, and power-on time information of the target signal power supply are obtained to obtain the first information item;

[0037] Based on the identification data, the internal resistance data, capacity data, factory life cycle period, and factory life duration of the target signal power supply are obtained to obtain the second information item. The first information item and the second information item are combined to obtain the identification information item.

[0038] Furthermore, the environmental information data includes temperature data, humidity data, and vibration data, and the methods for obtaining the environmental information items include:

[0039] The location information of the target signal power source is obtained to obtain the target location item. An acquisition range is set based on the target location item. At least two first acquisition modules are set based on the acquisition range. The first acquisition module includes a temperature acquisition device and a humidity acquisition device. The average temperature data and humidity data of the target location item are obtained based on the first acquisition module.

[0040] At least one second acquisition module is set based on the target location item. The second acquisition module includes a vibration sensor, sets a judgment threshold, which is a vibration amplitude threshold, acquires the vibration amplitude of the target signal power supply based on the second acquisition module, acquires the amplitude value and duration corresponding to the vibration amplitude reaching the amplitude threshold, obtains the average amplitude item, and combines the average amplitude item, average temperature data and humidity data to obtain the environmental information item.

[0041] Furthermore, the method for obtaining the branch voltage term includes:

[0042] Based on the target connection item, obtain the feature information of the line connection information, including the electrical equipment code information;

[0043] Based on the feature information, the reference voltage information of the target electrical equipment is obtained to obtain the initial voltage term. The branch voltage term is obtained by matching the initial voltage term.

[0044] Furthermore, the method for obtaining the connection prediction term includes:

[0045] Based on the branch voltage term, the combination result of the voltage span value and the branch voltage term is obtained to obtain the branch span term, and the branch span term corresponds to the branch voltage term respectively;

[0046] Using the branch span term as the predicted voltage data for the target connection term, the connection prediction term is obtained.

[0047] Furthermore, the method for obtaining the diagnostic connectivity items includes:

[0048] Obtain the difference information between the real-time connectivity term and the predicted connectivity term to obtain the connectivity difference term;

[0049] Set a splitting threshold, which is a quantity threshold. Based on the splitting threshold, split the connection difference item to obtain the split difference item.

[0050] Based on the combined results of splitting the difference term and connecting the real-time term, the target connection term is diagnosed separately, and the feedback information of the target connection term is obtained to obtain the feedback information set;

[0051] A fluctuation threshold is set. When the feedback information exceeds the fluctuation threshold, the corresponding target connection item is determined to be a diagnostic connection item.

[0052] Compared with the prior art, the beneficial effects of the present invention are:

[0053] This intelligent fault diagnosis method for subway signal power supplies acquires line connection information with the target signal power supply and simultaneously obtains the actual state of the target signal power supply under different discharge times, charge / discharge cycles, temperatures, humidity, vibration amplitudes, etc. It then creates a first feedback formula and a second feedback formula, ultimately deriving a comprehensive influence formula. This formula fully considers the influence of the power supply's own characteristics and environmental factors on the output voltage, significantly improving the accuracy of voltage data prediction. Based on the comprehensive influence formula, it obtains the rated voltage drop and combines the drop with different connection lines, achieving intelligent diagnosis of different branches based on the actual usage data of the target signal power supply. This avoids the situation where actual feedback data of the line under different discharge voltages cannot be detected due to fluctuations in discharge voltage. Attached Figure Description

[0054] Figure 1 This is a schematic diagram of the overall process of the present invention;

[0055] Figure 2 This is a schematic diagram illustrating the acquisition of identification information items according to the present invention;

[0056] Figure 3 This is a schematic diagram showing the target location and acquisition range of the present invention;

[0057] Figure 4 This is a schematic diagram of the vibration amplitude trend of the present invention;

[0058] Figure 5 This is a schematic diagram of the vibration frequency trend of the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. 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.

[0060] Traditional methods for diagnosing the discharge status of subway signal power supplies often use a fixed voltage value as a benchmark to diagnose each connected line. The drawback of this method is that it ignores the fact that the discharge voltage is not constant. During the discharge process, multiple factors affect the magnitude of the discharge voltage, causing it to fluctuate. First, environmental factors cannot be ignored. Temperature changes affect the rate of chemical reactions inside the battery, thus altering the discharge voltage. In high-temperature environments, the battery's internal resistance decreases, and the discharge voltage may increase; conversely, in low-temperature environments, the battery's internal resistance increases, and the discharge voltage may decrease. Humidity also affects battery performance. In high-humidity environments, electrode materials may corrode, affecting discharge capacity and voltage. Second, mechanical vibration also affects the battery's discharge process. With increasing service life, the battery's internal materials gradually degrade, and electrolyte leakage may occur, all of which lead to increased battery internal resistance and decreased discharge voltage. The interaction of these factors causes the voltage of the subway signal power supply to exhibit complex nonlinear changes during discharge. Under these circumstances, using a fixed diagnostic voltage to diagnose different lines is ineffective. The inability to accurately reflect actual feedback data under different discharge voltages, coupled with the inability of fixed diagnostic voltages to adapt to dynamic changes in discharge voltage, leads to discrepancies between diagnostic results and actual conditions. This can result in misjudgments or omissions of potential problems, threatening the safe and reliable operation of the subway signaling system. This application provides an intelligent fault diagnosis method for subway signaling power supplies. By acquiring line connection information with the target signaling power supply and simultaneously obtaining the actual state of the target signaling power supply under different discharge times, charge / discharge cycles, temperatures, humidity, vibration amplitudes, etc., a first feedback formula and a second feedback formula are created, leading to a comprehensive influence formula. This formula fully considers the influence of the power supply's own characteristics and environmental factors on the output voltage, significantly improving the accuracy of voltage data prediction. The method obtains the rated voltage drop based on the comprehensive influence formula and combines the drop with different connected lines, achieving intelligent diagnosis of different branches based on the actual usage data of the target signaling power supply. This avoids the situation where actual feedback data under different discharge voltages cannot be detected due to discharge voltage fluctuations. Figure 1As shown, it includes steps S100-S900.

[0061] Step S100: Obtain the line connection information of the target signal power supply to obtain the target connection set.

[0062] It should be noted that the target connection set includes at least one target connection item consisting of a connection line. The target signal power supply stores connection signal data. The method for obtaining the target connection set includes: based on the connection signal data, obtaining the active information connected to the target signal power supply to obtain the active information item; based on the active information item, obtaining the actual number of connection branches and connection node information to obtain the target connection set and node information set; and based on the matching result of the target connection set and the node information set, obtaining the target connection set.

[0063] Specifically, since the signal power supply module includes a signal power supply panel with a modular design, and provides different voltage outputs through a high-frequency switching power supply module, the active information connected to the target signal power supply can be obtained through the signal power supply panel connected to the target signal power supply, i.e., active users. For example, when the electrical equipment connected to the target signal power supply is a track circuit, a signal, or a router, the active information displayed on the signal power supply panel will be three items: track circuit, signal, and router, respectively. Thus, the active information item is obtained. At this time, the actual connected branch information and node information are obtained through the active information item, resulting in the target connection set and node information set. The signal power supply panel will display the connection lines and node positions between the track circuit, signal, router, and the target signal power supply. The connection lines and node lines are set in the line box connected to the target signal power supply, thus obtaining the target connection set.

[0064] Step S200: Obtain the type identification data stored in the target signal power supply to obtain the identification information item.

[0065] It is important to note that, such as Figure 2 As shown, the identification information items include rated voltage, number of cycles, and aging information. The target signal power supply also stores identification data. The method for obtaining the identification information items includes: based on the type identification data, obtaining the rated output voltage information, charge / discharge cycle information, and power-on time information of the target signal power supply to obtain the first information item; based on the identification data, obtaining the internal resistance data, capacity data, factory life cycle period, and factory life duration of the target signal power supply to obtain the second information item; and combining the first information item and the second information item to obtain the identification information item.

[0066] Specifically, the target signal power supply stores type identification data and identification data. The type identification data is the usage scenario data of the target signal power supply, such as rated output voltage information, charge and discharge cycle information during use, and power-on time information. The power-on time information can be used to obtain the single power-on usage duration of the target signal power supply. The identification data is the parameter information of the target signal power supply, including internal resistance, rated capacity, limited charge and discharge cycle limit information marked at the factory, and service life. The identification information items are obtained by combining the above information.

[0067] Step S300: Based on the identification information item, create a first feedback formula. The first feedback formula is used to represent the first influence feedback data of the target signal power supply output voltage, and the first influence item is obtained.

[0068] It should be noted that the first feedback formula includes the reference discharge module, the cycle aging module, and the calendar aging module. The methods for creating the first feedback formula include:

[0069] ;

[0070] in As the first influencing factor, As a reference discharge module, For cyclic aging module, For calendar aging module;

[0071] ;

[0072] in Rated voltage, Let Euler's constant be 1. Discharge time, For internal resistance, For capacity;

[0073] ;

[0074] in The cyclic decay rate, The number of charge / discharge cycles. This represents the total number of cycles in the user's lifetime.

[0075] ;

[0076] in The time decay coefficient, This refers to the end of lifespan. Discharge time;

[0077] By acquiring the identification information items, the relevant parameters of the target signal power supply can be obtained, and then the reference discharge module, cycle aging module and calendar aging module can be calculated based on the relevant parameters.

[0078] Example 1

[0079] In the specific implementation process, the target signal power source was identified as lithium battery A. The battery's type identification data showed a rated output voltage of 60V, 500 charge / discharge cycles, and a power-on time of 3600s (meaning a discharge time of 3600s). A day is 86400s. Further identification data revealed the battery's internal resistance to be 0.05 ohms, capacity of 144kF, factory cycle life of 2000 cycles, and a factory lifespan of 8 years (2920 days). The lithium battery's cycle degradation rate was 0.0004, and its time degradation coefficient was 3×10⁻⁶. -6 / day, at this point according to the formula:

[0080] ;

[0081] The calculation shows that:

[0082] ;

[0083] Then, according to the formula:

[0084] ;

[0085] The calculation shows that:

[0086] ;

[0087] Then, according to the formula:

[0088] ;

[0089] The calculation shows that:

[0090] ;

[0091] At this point, according to the formula:

[0092] ;

[0093] The calculation shows that:

[0094] ;

[0095] That is, the first influence term is 32.75V.

[0096] Step S400: Obtain environmental information data of the target signal power source to obtain environmental information items.

[0097] It should be noted that the environmental information data includes temperature data, humidity data, and vibration data. The method for acquiring environmental information items includes: acquiring the location information of the target signal power source to obtain the target location item; setting an acquisition range based on the target location item; setting at least two first acquisition modules based on the acquisition range, the first acquisition modules including a temperature acquisition device and a humidity acquisition device, wherein the temperature acquisition module is a temperature sensor and the humidity acquisition module is a humidity sensor; acquiring the average temperature data and humidity data of the target location item based on the first acquisition modules; setting at least one second acquisition module based on the target location item, the second acquisition module including a vibration sensor; setting a judgment threshold, the judgment threshold being a vibration amplitude threshold of 0.1 mm; acquiring the vibration amplitude of the target signal power source based on the second acquisition module; acquiring the amplitude value and duration corresponding to the vibration amplitude reaching the amplitude threshold to obtain the average amplitude item; and combining the average amplitude item, average temperature data, and humidity data to obtain the environmental information item.

[0098] Example 2

[0099] In the specific implementation process, such as Figures 3-5As shown, after obtaining the location information of the target signal power supply B located in the subway tunnel, an acquisition range of 5m is set. Within this range, three first acquisition modules (a, b, and c) are set up. Each first acquisition module includes a temperature acquisition device and a humidity acquisition device. Module a acquires temperature and humidity data of 40℃ and 85%, respectively; module b acquires temperature and humidity data of 40.2℃ and 85.1%, respectively; and module c acquires temperature and humidity data of 39.8℃ and 84.9%, respectively. The average temperature and humidity data are then obtained as 40℃ and 85%. A second acquisition module (d) is then set up to acquire the vibration amplitude of the target signal power supply B. As the train passes, the vibration amplitude of the target signal power supply B gradually increases and then gradually decreases. According to the set judgment threshold, at 10 seconds, the vibration amplitude of the target signal power supply B reaches the judgment threshold, which is 0.1mm, with a vibration frequency of 28Hz. At 11 seconds, the vibration amplitude is... The vibration amplitude was 0.2 mm at 12 seconds, with a vibration frequency of 31 Hz. At 12 seconds, the vibration amplitude was 0.3 mm, with a vibration frequency of 34 Hz. At 13 seconds, the vibration amplitude was 0.4 mm, with a vibration frequency of 37 Hz. At 14 seconds, the vibration amplitude was 0.5 mm, with a vibration frequency of 40 Hz. At 15 seconds, the vibration amplitude was 0.5 mm, with a vibration frequency of 40 Hz. At 16 seconds, the vibration amplitude was 0.4 mm, with a vibration frequency of 37 Hz. At 17 seconds, the vibration amplitude was 0. The vibration amplitude was 0.3 mm at 18s and the vibration frequency was 34 Hz. At 18s, the vibration amplitude was 0.2 mm and the vibration frequency was 31 Hz. At 19s, the vibration amplitude was 0.1 mm and the vibration frequency was 28 Hz. At 20s, the vibration amplitude of the target signal power supply B decreased to below the judgment threshold. After that, the train passed the target signal power supply B. At this time, the average vibration amplitude of the target signal power supply B was 0.3 mm, the duration was 10s, and the average vibration frequency was 30 Hz. Thus, the environmental information item was obtained.

[0100] Step S500: Create a second feedback formula based on the environmental information item. The second feedback formula is used to represent the second influence feedback data of the target signal power supply output voltage, and the second influence item is obtained.

[0101] It should be noted that the environmental information items include temperature, humidity, and vibration. The methods for creating the second feedback formula include:

[0102] ;

[0103] in As the second influencing factor, For temperature, For humidity, It is a vibration term;

[0104] ;

[0105] in For temperature coefficient, For ambient temperature, The reference ambient temperature;

[0106] ;

[0107] in Humidity coefficient Relative humidity, Humidity index;

[0108] ;

[0109] in As a mechanical degradation factor, The amplitude of vibration. The vibration frequency, For duration.

[0110] Example 3

[0111] In the specific implementation process, the target signal power source was identified as lithium battery C. Average temperature and humidity data were obtained as 40℃ and 85%, respectively. At this point, the temperature coefficient of lithium battery C was 0.004, which is the median temperature coefficient for lithium batteries. The baseline ambient temperature was set at 25℃, the humidity coefficient was 0.003, and the humidity index was 1.5, representing the humidity parameters for the underground environment. The average vibration amplitude was 0.3 mm, the duration was 10 seconds, the average vibration frequency was 30 Hz, and the mechanical degradation factor was 5 × 10⁻⁶. -6 At this point, according to the formula:

[0112] ;

[0113] The calculation shows that:

[0114] ;

[0115] According to the formula:

[0116] ;

[0117] The calculation shows that:

[0118] ;

[0119] Then, according to the formula:

[0120] ;

[0121] The calculation shows that:

[0122] ;

[0123] At this point, according to the formula:

[0124] ;

[0125] The calculation shows that:

[0126] ;

[0127] That is, the second influence term is 0.7182.

[0128] Step S600: Based on the combined results of the first and second influence terms, the comprehensive influence formula of the target signal power supply is obtained.

[0129] It is important to note the first influencing factor: The second influencing factor: The formula for the overall impact at this time is:

[0130] .

[0131] Example 4

[0132] In the specific implementation process, the target signal power source was identified as lithium battery D. The battery's type identification data showed a rated output voltage of 60V, 500 charge / discharge cycles, and a power-on time of 3600s (meaning a discharge time of 3600s). A day is 86400s. Further identification data revealed an internal resistance of 0.05 ohms, a capacity of 144kF, a factory-set cycle life of 2000 cycles, and a factory-set lifespan of 8 years (2920 days). The lithium battery's cycle degradation rate was 0.0004, and its time degradation coefficient was 3×10⁻⁶. -6 / day, the average temperature and average humidity data of lithium battery D were simultaneously acquired at 40℃ and 85%, respectively. At this time, the temperature coefficient of lithium battery D was 0.004, the baseline ambient temperature was a set 25℃, the humidity coefficient was 0.003, the humidity index was 1.5, the average vibration amplitude was 0.3mm, the duration was 10s, the average vibration frequency was 30Hz, and the mechanical degradation factor was 5×10⁻⁶. -6 At this point, the calculation is performed according to the formula:

[0133] ;

[0134] ;

[0135] ;

[0136] ;

[0137] ;

[0138] ;

[0139] The calculation result is:

[0140] .

[0141] Step S700: Obtain the limit voltage data of the target signal power supply based on the comprehensive influence formula to obtain the limit voltage term; obtain the target connection term and the rated voltage data of the target signal power supply based on the identification information term to obtain the branch voltage term and the rated total voltage term.

[0142] It should be noted that the method for obtaining the branch voltage term includes: based on the target connection term, obtaining the feature information of the line connection information, including the electrical equipment code information; based on the feature information, obtaining the reference voltage information of the target electrical equipment to obtain the initial voltage term; and using the initial voltage term as a match to obtain the branch voltage term.

[0143] Specifically, different numbers of target connection items require different voltages. For example, if there are four target connection items, the voltage allocated to the four target connection items is 25% of the rated voltage. When the rated output voltage is 60V, the initial voltage of the four target connection items is 15V. Therefore, based on the characteristic information of the line connection information, the reference voltage information of the target connection items is obtained, and then the branch voltage is obtained.

[0144] Step S800: Obtain the voltage span value based on the decrease of the limit voltage term and the rated total voltage term. Based on the voltage span value, obtain the predicted voltage data of each target connection term to obtain the connection prediction term.

[0145] It should be noted that the method for obtaining the connection prediction term includes: based on the branch voltage term, obtaining the combination result of the voltage span value and the branch voltage term to obtain the branch span term. When the rated output voltage is 60V, the limit voltage data of the target signal power supply is calculated to be 30V. At this time, the drop of the limit voltage term based on the rated total voltage term is 50%, and the voltage span value is 50%. At this time, the combination result of the voltage span value and the branch voltage term is the branch span term. When the branch voltage term is 15V, the branch span term is 7.5V. The branch span term corresponds to the branch voltage term respectively. Using the branch span term as the predicted voltage data of the target connection term, the connection prediction term is obtained.

[0146] Step S900: Obtain the real-time voltage data of the target connection item to obtain the real-time connection item. Compare the predicted connection item with the real-time connection item to diagnose the target connection item, obtain the target connection item for early warning, and obtain the diagnosed connection item.

[0147] It is important to note that the method for obtaining diagnostic connection items includes: obtaining the difference information between the real-time connection item and the predicted connection item to obtain the connection difference item; setting a splitting threshold, which is a quantity threshold of 5, and splitting the connection difference item based on the splitting threshold to obtain the split difference item; diagnosing the target connection item based on the combination result of the split difference item and the real-time connection item, obtaining the feedback information of the target connection item to obtain the feedback information set; setting a fluctuation threshold of 5±5%, and determining the corresponding target connection item as a diagnostic connection item when there is a fluctuation threshold in the feedback information set, thus realizing intelligent diagnosis of different branches based on the actual usage data of the target signal power supply.

[0148] Specifically, when the branch span is 12.5V and the real-time connection is 7.5V, the connection difference is 5V. Based on the set splitting threshold, the connection difference is split into five 1V values, which are then combined with the real-time connection. The combined values ​​are 8.5V, 9.5V, 10.5V, 11.5V, and 12.5V. These five combinations are used to diagnose the target connection. If the feedback fluctuation of the target connection exceeds the set fluctuation threshold ±5%, the target connection is determined to be a diagnostic connection. For example, when diagnosing line A, if the initial diagnostic value is 8.5V, the feedback is 8.3V, which does not exceed the fluctuation threshold; if the initial diagnostic value is 9.5V, the feedback is 9.4V, which also does not exceed the fluctuation threshold; if the initial diagnostic value is 10.5V, the feedback is 10.1V, which exceeds the fluctuation threshold. In this case, line A is determined to be a diagnostic connection, thus achieving intelligent diagnosis of different branches based on the actual usage data of the target signal power supply.

[0149] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended embodiments and their equivalents.

Claims

1. An intelligent fault diagnosis method for a subway signal power supply, comprising: obtaining line connection information of a target signal power supply to obtain a target connection set, the target connection set including at least a target connection item formed by one connection line; obtaining type identification data stored by the target signal power supply to obtain an identification information item, the identification information item including rated voltage, cycle number, and aging information; characterized in that: based on the identification information item, a first feedback formula is created, the first feedback formula is used to represent first influence feedback data of an output voltage of the target signal power supply to obtain a first influence item; environmental information data of the target signal power supply is obtained to obtain an environmental information item, a second feedback formula is created based on the environmental information item, the second feedback formula is used to represent second influence feedback data of the output voltage of the target signal power supply to obtain a second influence item, and a comprehensive influence formula of the target signal power supply is obtained based on a combination result of the first influence item and the second influence item; based on the comprehensive influence formula, limit voltage data of the target signal power supply is obtained to obtain a limit voltage item, and based on the identification information item, rated voltage data of the target signal power supply and the target connection item are obtained to obtain a branch voltage item and a rated total voltage item; a voltage span value is obtained based on a drop amplitude of the limit voltage item based on the rated total voltage item, and based on the voltage span value, predicted voltage data of each target connection item is obtained to obtain a connection prediction item; real-time voltage data of the target connection item is obtained to obtain a connection real-time item, the connection prediction item is compared with the connection real-time item, the target connection item is diagnosed, a target connection item for early warning is obtained to obtain a diagnosed connection item, and intelligent diagnosis of different branches according to actual use data of the target signal power supply is realized; the first feedback formula includes a reference discharge module, a cycle aging module, and a calendar aging module, and the creation method of the first feedback formula includes: ； wherein is a first influence term, is a baseline discharge module, is a cycle aging module, is a calendar aging module; ； wherein is the rated voltage, is the Euler constant, is the discharge time, is the internal resistance, is the capacity; ； wherein is the cycle decay rate, is the number of charge and discharge cycles, is the total number of cycles to life; ； wherein is a time decay coefficient, is a life termination time, is a discharge time; the environmental information item includes a temperature item, a humidity item, and a vibration item, and the creation method of the second feedback formula includes: ； wherein is a second influence term, is a temperature term, is a humidity term, is a vibration term; ； wherein is the temperature coefficient, is the ambient temperature, is the reference ambient temperature; ； wherein is the humidity coefficient, is the relative humidity, is the humidity index; ； wherein is a mechanical deterioration factor, is a vibration amplitude, is a vibration frequency, is a duration.

2. The intelligent fault diagnosis method for the subway signal power supply according to claim 1, characterized in that: the target signal power supply stores connection signal data, and the obtaining method of the target connection set includes: based on the connection signal data, active information connected with the target signal power supply is obtained to obtain an active information item; based on the active information item, actual connection branch number information and connection node information are obtained to obtain the target connection set and a node information set, and the target connection set is obtained based on a matching result of the target connection set and the node information set.

3. The intelligent fault diagnosis method for metro signal power supply according to claim 1, characterized in that: the target signal power supply also stores identification recognition data, and the obtaining method of the identification information item includes: based on the type identification data, rated output voltage information, charge and discharge number information, and boot time information of the target signal power supply are obtained to obtain a first information item; based on the identification recognition data, internal resistance data, capacity data, factory life cycle limit, and factory life time limit of the target signal power supply are obtained to obtain a second information item, and the first information item and the second information item are combined to obtain the identification information item.

4. The intelligent fault diagnosis method for the subway signal power supply according to claim 1, characterized in that: the environmental information data includes temperature data, humidity data, and vibration data, and the obtaining method of the environmental information item includes: The position information of the target signal power supply is acquired to obtain a target position item, an acquisition range is set based on the target position item, at least two first acquisition modules are set based on the acquisition range, the first acquisition module includes a temperature acquisition device and a humidity acquisition device, average temperature data and humidity data of the target position item are acquired based on the first acquisition module; At least one second acquisition module is set based on the target position item, the second acquisition module includes a vibration sensor, a judgment threshold value is set, the judgment threshold value is a vibration amplitude threshold value, the vibration amplitude of the target signal power supply is acquired based on the second acquisition module, the amplitude value and the duration corresponding to the amplitude threshold value are acquired when the vibration amplitude reaches the amplitude threshold value, an average amplitude item is obtained, the environment information item is obtained by combining the average amplitude item, the average temperature data and the humidity data.

5. The intelligent fault diagnosis method for metro signal power supply according to claim 1, characterized in that: The acquisition method of the branch voltage item includes: Based on the target connection item, the feature information of the line connection information is acquired, and the feature information includes the electric equipment code information; Based on the feature information, the reference voltage information of the target electric equipment is acquired to obtain an initial voltage item, and the initial voltage item is matched to obtain the branch voltage item.

6. The intelligent fault diagnosis method for a subway signal power supply according to claim 1, characterized in that: The acquisition method of the connection prediction item includes: Based on the branch voltage item, the combination result of the voltage span value and the branch voltage item is acquired to obtain a branch span item, and the branch span item corresponds to the branch voltage item respectively; The branch span item is taken as the prediction voltage data of the target connection item to obtain the connection prediction item.

7. The intelligent fault diagnosis method for a subway signal power supply according to claim 1, characterized in that: The acquisition method of the diagnosis connection item includes: The difference information of the connection real-time item and the connection prediction item is acquired to obtain a connection difference item; A split threshold value is set, the split threshold value is a quantity threshold value, the connection difference item is split based on the split threshold value to obtain a split difference item; Based on the combination result of the split difference item and the connection real-time item, the target connection item is diagnosed respectively to acquire the feedback information of the target connection item, and a feedback information set is obtained; A fluctuation threshold value is set, when the feedback information set exceeds the fluctuation threshold value, the corresponding target connection item is determined as the diagnosis connection item.

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