Railway signal drawings and spare equipment management system and method based on big data

Abstract

The present invention discloses a railway signal drawing and spare equipment management system and method based on big data, and relates to the field of management technology. The system includes: a data acquisition unit, used to obtain equipment data and drawing data; a drawing and equipment association unit, used to establish an association relationship between each device and the drawing to form an equipment-drawing chain; a damage estimation model construction unit, used to construct a damage estimation model; a damage determination unit, used to determine the current state of the equipment; a parsing unit, used to parse the equipment-drawing chain, and generate the required spare equipment data information; a notification unit, used to compare the received required spare equipment data information with the inventory information, and generate a replenishment notification when the inventory is insufficient. The system and method provided by the present invention improve the efficiency of replacing damaged equipment to a certain extent.

Description

Technical Field

[0001] The present invention relates to the technical field of management data systems, and in particular to a railway signal drawing and spare equipment management system and method based on big data. Background Art

[0002] With the development of the railway transportation industry, the railway signal system plays a vital role in ensuring train safety and improving transportation efficiency. The operation of the railway signal system involves a large number of key links such as drawing management, equipment operation data monitoring and spare equipment supply.

[0003] In the related art, the drawing information and equipment status data of the signal system are often stored in a scattered manner, and there is a lack of correlation between various types of data, resulting in low management efficiency. In addition, there are a large number of railway signal equipment, and multiple devices are interconnected, involving a large number of connection consumables. When a certain device is damaged and needs to be replaced, the staff not only needs to check the inventory information of the device, but also needs to find the drawings related to the device, determine the consumables connected to the device, and then count the inventory information of the consumables. This process is time-consuming and labor-intensive, and is very prone to errors. Therefore, it is necessary to improve one or more problems existing in the above-mentioned related technical solutions.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The purpose of the present invention is to provide a railway signal drawing and spare equipment management system and method based on big data to improve the efficiency of replacing damaged equipment.

[0006] The present invention first provides a railway signal drawing and spare equipment management system based on big data, the system comprising:

[0007] A data acquisition unit, used to acquire device data and drawing data, wherein the device data includes device identification information and real-time operating parameters, and the drawing data includes electronic drawings and index information corresponding to the electronic drawings, wherein the index information includes number, name, version and creation date;

[0008] A drawing and equipment association unit, electrically connected to the data acquisition unit, is used to assign a unique identifier to each device according to the device identification information, and to establish an association relationship between each device and the drawing based on the unique identifier and the drawing data to form a device-drawing chain;

[0009] The damage estimation model construction unit is used to construct a ternary damage estimation model consisting of a weight factor, an overvoltage number, and an overcurrent number. The ternary damage estimation model is used to calculate the damage equivalent of the device, and the calculation formula is:

[0010] ;

[0011] in, represents the damage equivalent, represents the weight factor of the current factor, represents the weight factor of the voltage factor, Indicates the maximum number of overcurrent times allowed under the standard level. Indicates the number of overcurrents during operation of the device. Indicates the maximum number of overvoltages allowed under the standard level. Indicates the number of overvoltages during operation of the equipment;

[0012] a damage determination unit, electrically connected to the data acquisition unit and the damage estimation model construction unit, respectively, for substituting the received real-time operating parameters of the device into the ternary damage estimation model, calculating the damage equivalent of the device, and determining the current state of the device according to the damage equivalent, wherein the current state includes a normal state, a critical damage state, and a damage state;

[0013] A parsing unit, electrically connected to the damage determination unit and the drawing and equipment association unit, is used to call the equipment-drawing chain when the current state of the received equipment is a critical damage state or a damage state, and generate the required spare equipment data information by parsing the equipment-drawing chain;

[0014] The notification unit is electrically connected to the analysis unit and is used to compare the received required spare equipment data information with the inventory information and generate a replenishment notification when the inventory is insufficient.

[0015] Furthermore, the drawing and equipment association unit includes:

[0016] A unique identifier assigning module, used to assign a unique identifier to each device according to the device identification information;

[0017] The optimization module is used to filter out index information with the same name but different versions, and retain only the index information with the latest creation date and the electronic drawing corresponding to the index information according to the order of creation dates, so as to obtain the optimized first drawing data;

[0018] a hierarchy construction module, used for parsing the first drawing data, and constructing a hierarchy of the first drawing data using a resource description framework model, wherein the hierarchy of the first drawing data includes an exclusive layer and a shared layer, wherein the exclusive layer is first drawing data dedicated to a device, and the shared layer is first drawing data shared by multiple devices;

[0019] A feature extraction module is used to extract the type feature of the first drawing data in the exclusive layer to obtain the sub-component specification information of the device; extract the type feature of the first drawing data in the shared layer to obtain other devices associated with the device, and obtain the specification information of the connection consumables according to the connection mode between the devices;

[0020] The chain generation module is used to generate a device-drawing chain including a unique identifier, sub-component specification information, and connection consumable specification information from the chain head to the chain tail.

[0021] Furthermore, the unique identifier is an MD5 value.

[0022] Furthermore, the hierarchical building blocks include:

[0023] A classification processing submodule, used for parsing the first drawing data and classifying the first drawing data, wherein the classification includes circuit classification, structure classification, construction classification, wiring classification and structural layout classification;

[0024] A model expression submodule, used to express the hierarchy of the first drawing data in the form of a resource description framework according to the classification of the first drawing data;

[0025] Among them, the hierarchical expression of the first drawing data is:

[0026] ;

[0027] ;

[0028] ;

[0029] ;

[0030] ;

[0031] In the above expression, A hierarchical model representing the first drawing data, Indicates the specific level of the first drawing data, j indicates the level number, Denotes the exclusive layer, represents the shared layer, Indicates the classification of the first drawing data, Represents the circuit class, Represents the circuit class, Indicates the construction class. Indicates the construction class. Represents the structure layout class, It indicates the semantic relationship of inclusion, and i indicates the sequence number.

[0032] Furthermore, the damage determination unit includes a calculation module and a determination module;

[0033] The calculation module is used to substitute the received real-time operating parameters of the equipment into the calculation formula of the ternary damage estimation model to calculate the damage equivalent of the equipment;

[0034] The judgment module is used to judge the current state of the device according to the damage equivalent:

[0035] when 1. Make sure the device is in normal status;

[0036] when 1. Determine that the equipment is in a critical damage state;

[0037] when 1. Determine whether the device is in a damaged state.

[0038] Furthermore, the parsing unit includes:

[0039] A reading module, used for reading the data on the device-drawing chain and sending it to the statistics module;

[0040] The statistical module is used to count the names, models and quantities of the required sub-components, as well as the names, models and quantities of the required connecting consumables, and then generate the required spare equipment data information.

[0041] Further, the notification unit includes:

[0042] The demand verification module is used to verify the received data information of the required spare equipment to ensure that the name and model of the required spare equipment are consistent with the inventory information;

[0043] The inventory comparison module is used to compare the verified data information of the required spare equipment with the existing inventory information to determine whether the current inventory can meet the demand. When the inventory is sufficient, the outbound information that meets the demand is generated; when the inventory is insufficient, the name, model and quantity of the insufficient spare equipment are counted to generate replenishment information;

[0044] A replenishment notification generation module is used to generate a replenishment instruction based on the replenishment information, wherein the replenishment instruction includes a replenishment priority level, wherein the priority level of the spare parts required for the equipment currently in a damaged state is higher than the priority level of the spare parts required for the equipment currently in a critical damaged state.

[0045] Furthermore, the management system also includes:

[0046] The inventory updating unit is electrically connected to the notification unit and is used to update the inventory information of the spare equipment in real time according to the outbound information and the replenishment information.

[0047] The present invention also provides a railway signal drawing and spare equipment management method based on big data, which is applied to any of the railway signal drawing and spare equipment management systems based on big data described above, and the method comprises the following steps:

[0048] Acquire device data and drawing data, wherein the device data includes device identification information and real-time operating parameters, and the drawing data includes electronic drawings and index information corresponding to the electronic drawings, wherein the index information includes number, name, version, and creation date;

[0049] Assigning a unique identifier to each device according to the device identification information, and establishing an association relationship between each device and the drawing based on the unique identifier and the drawing data to form a device-drawing chain;

[0050] A ternary damage estimation model consisting of a weight factor, overvoltage times, and overcurrent times is constructed. The ternary damage estimation model is used to calculate the damage equivalent of the equipment. The calculation formula is:

[0051] ;

[0052] in, represents the damage equivalent, represents the weight factor of the current factor, represents the weight factor of the voltage factor, Indicates the maximum number of overcurrent times allowed under the standard level. Indicates the number of overcurrents during operation of the device. Indicates the maximum number of overvoltages allowed under the standard level. Indicates the number of overvoltages during operation of the equipment;

[0053] Substituting the received real-time operating parameters of the equipment into the ternary damage estimation model, calculating the damage equivalent of the equipment, and judging and determining the current state of the equipment according to the damage equivalent, wherein the current state includes a normal state, a critical damage state, and a damage state;

[0054] When the current state of the equipment is a critical damage state or a damage state, the equipment-drawing chain is called, and the required spare equipment data information is generated by parsing the equipment-drawing chain;

[0055] Compare the required spare equipment data information with the inventory information and generate a replenishment notification when the inventory is insufficient.

[0056] The technical solution provided by the present invention may include the following beneficial effects:

[0057] The railway signal drawing and spare equipment management system based on big data provided by the present invention highly correlates equipment data and drawing data to form an equipment-drawing chain, and can determine whether the equipment is damaged through the real-time operating parameters of the equipment. When the equipment is damaged or in a critical damage state, the equipment-drawing chain will be called to directly generate data information of the spare equipment that needs to be replaced. In this way, the process of comparing drawings by staff is omitted, and the efficiency of replacing damaged equipment is improved to a certain extent.

[0058] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] The accompanying drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present invention, and together with the specification are used to explain the principles of the present invention. Obviously, the accompanying drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without creative work.

[0060] Figure 1 A block diagram showing the composition of a railway signal drawing and spare equipment management system based on big data in an exemplary embodiment of the present invention;

[0061] Figure 2 A schematic diagram showing the steps of a railway signal drawing and spare equipment management method based on big data in an exemplary embodiment of the present invention. DETAILED DESCRIPTION

[0062] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the present invention will be more comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0063] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0064] This example implementation provides a railway signal drawing and spare equipment management system based on big data, referring to Figure 1 As shown, the system includes a data acquisition unit, a drawing and equipment association unit, a damage estimation model construction unit, a damage determination unit, a parsing unit and a notification unit.

[0065] The data acquisition unit is used to obtain device data and drawing data, wherein the device data includes device identification information and real-time operating parameters, and the drawing data includes electronic drawings and index information corresponding to the electronic drawings, wherein the index information includes number, name, version and creation date.

[0066] The drawing and equipment association unit is electrically connected to the data acquisition unit, and is used to assign a unique identifier to each device according to the device identification information, and to establish an association relationship between each device and the drawing based on the unique identifier and the drawing data to form a device-drawing chain.

[0067] The damage estimation model construction unit is used to construct a ternary damage estimation model consisting of a weight factor, an overvoltage number, and an overcurrent number. The ternary damage estimation model is used to calculate the damage equivalent of the device, and the calculation formula is:

[0068] ;

[0069] in, represents the damage equivalent, represents the weight factor of the current factor, represents the weight factor of the voltage factor, Indicates the maximum number of overcurrent times allowed under the standard level. Indicates the number of overcurrents during operation of the device. Indicates the maximum number of overvoltages allowed under the standard level. Indicates the number of overvoltages during operation of the equipment;

[0070] The damage determination unit is electrically connected to the data acquisition unit and the damage estimation model construction unit, respectively, and is used to substitute the received real-time operating parameters of the equipment into the ternary damage estimation model, calculate the damage equivalent of the equipment, and determine the current state of the equipment based on the damage equivalent, wherein the current state includes a normal state, a critical damage state and a damage state.

[0071] The parsing unit is electrically connected to the damage determination unit and the drawing and equipment association unit, and is used to call the equipment-drawing chain when the current state of the received equipment is a critical damage state or a damage state, and generate the required spare equipment data information by parsing the equipment-drawing chain.

[0072] The notification unit is electrically connected to the analysis unit and is used to compare the received required spare equipment data information with the inventory information and generate a replenishment notification when the inventory is insufficient.

[0073] The railway signal drawing and spare equipment management system based on big data provided by the present invention highly correlates equipment data and drawing data to form an equipment-drawing chain, and can determine whether the equipment is damaged through the real-time operating parameters of the equipment. When the equipment is damaged or in a critical damage state, the equipment-drawing chain will be called to directly generate data information of the spare equipment that needs to be replaced. In this way, the process of staff searching and comparing drawings according to damaged equipment is omitted, thereby improving the efficiency of replacing damaged equipment to a certain extent.

[0074] Below, each component of the above system in this example implementation will be described in more detail.

[0075] It can be understood that the railway signal drawing and spare equipment management system based on big data provided by the present invention belongs to a small system in the entire railway equipment management system. The system is provided with a data transmission interface, which can realize data transmission with other systems.

[0076] In this system, the equipment data acquired by the data acquisition unit usually comes from the equipment detection system, and the drawing data comes from the drawing management system. Of course, the above equipment data and drawing data can also come from the collection of local data or the transmission based on other data transmission devices.

[0077] The above-mentioned drawing and equipment association unit includes a unique identifier assignment module, an optimization module, a hierarchy construction module, a feature extraction module and a chain generation module.

[0078] Among them, the unique identifier assignment module is used to assign a unique identifier to each device according to the device identification information in the device data. Specifically, the unique identifier is the fifth-generation message digest algorithm value (Message-Digest Algorithm, MD5). MD5 is a cryptographic hash function that can generate a 128-bit hash value, which is suitable for assigning a unique value to a large number of railway signal devices. Moreover, the computer can also quickly locate the relevant equipment through this value, which is convenient for the subsequent generation of the equipment-drawing chain. In addition, since the MD5 value is long and not easy to tamper with, it also improves the security of the system to a certain extent.

[0079] It is understandable that with the change of technology, the drawings owned by a device are constantly increasing. For example, the same device may have multiple versions of circuit diagrams, but in fact, the device may currently use only the latest version of the circuit diagram, and the remaining versions of the circuit diagram are useless in this system. Therefore, the optimization module is required to filter the collected drawing data and only retain the drawing data of the version currently being used by the device to reduce the amount of calculation in the subsequent device-drawing chain generation process. Specifically, the optimization module first filters out the index information corresponding to the electronic drawings with the same name but different versions, and according to the order of the creation date, only retains the index information under the latest creation date and the electronic drawings corresponding to the index information, and then obtains the optimized first drawing data.

[0080] Furthermore, the optimized first drawing data is parsed by the hierarchical construction module to further stratify the first drawing data using the resource description framework model. According to the characteristics of the railway signal equipment, it can be divided into an exclusive layer and a shared layer. The exclusive layer is the first drawing data dedicated to one device, while the shared layer is the first drawing data shared by multiple devices.

[0081] Specifically, the above-mentioned hierarchical construction module includes a classification processing submodule and a model expression submodule.

[0082] The classification processing submodule is used to parse the first drawing data and classify the first drawing data into: circuit class, structure class, construction class, wiring class and structure layout class. Among them, the first drawing data of the circuit class and the structure class are usually dedicated to the device, while the first drawing data of the construction class, wiring class and structure layout class usually also include other devices and connection consumables connected to other devices. The model expression submodule is used to express the hierarchy of the first drawing data according to the above classification and in the form of a resource description framework.

[0083] The resource description framework is a data model expressed in XML syntax, which is used to describe the characteristics of resources and the relationship between resources. Here, the resource description framework can make the classification of the first drawing data clearer and the subsequent feature extraction faster.

[0084] In one embodiment, the hierarchical expression of the first drawing data is:

[0085] ;

[0086] ;

[0087] ;

[0088] ;

[0089] ;

[0090] In the above expression, A hierarchical model representing the first drawing data, Indicates the specific level of the first drawing data, j indicates the level number, Denotes the exclusive layer, represents the shared layer, Indicates the classification of the first drawing data, Represents the circuit class, Represents a structural class, Indicates the construction class. Indicates the wiring class, Represents the structure layout class, It indicates the semantic relationship of inclusion, and i indicates the sequence number.

[0091] After the above layers are constructed, the feature extraction module can quickly locate and extract the corresponding features. For example, if you need to extract the specification information of the subcomponents of a device, you need to locate the exclusive layer and extract it from the exclusive first drawing data of the device; if you need to extract the specification information of the connection consumables used by the device to connect with other devices, you need to locate the shared layer and extract it from the shared first drawing data of the device.

[0092] Finally, through the chain generation module, a device-drawing chain is generated from the head of the chain to the end of the chain, which is the unique identifier, sub-component specification information, and connection consumable specification information, so as to achieve a high degree of association between device-device sub-components and connection consumables.

[0093] The number of overcurrent and overvoltage events of railway signal equipment is correlated with the degree of damage. By using statistical analysis of historical data, a ternary damage estimation model consisting of weight factor, overvoltage number and overcurrent number is constructed to calculate the damage equivalent of the equipment.

[0094] Specifically, the damage determination unit includes a calculation module and a determination module, which are used to substitute the received real-time operating parameters of the equipment into the calculation formula of the ternary damage estimation model to calculate the damage equivalent of the equipment.

[0095] It should be noted that for different devices, the and Also different, and In the determination process, it is necessary to reasonably divide the influence weights of voltage factors and current factors on the damage degree based on the existing statistical data.

[0096] The above-mentioned judgment module is used to judge the current state of the device according to the damage equivalent:

[0097] when 1. Make sure the device is in normal status;

[0098] when 1. Determine that the equipment is in a critical damage state;

[0099] when 1. Determine whether the device is in a damaged state.

[0100] In this process, not only the equipment in the damaged state is identified, but more importantly, the equipment in the critical damage state is also identified. Usually, after the equipment is damaged, the abnormal parameter value is large and easy to find, but the critical damage state is not easy to detect. After the system knows the equipment in the critical damage state in advance, it can issue a notification to remind the staff to replace it, which can avoid the failure caused by the actual damage of the equipment and affect the normal operation of the railway.

[0101] In one embodiment, the parsing unit includes a reading module and a statistics module.

[0102] The reading module is used to read the data on the device-drawing chain and send it to the statistics module. The reading module uses the MD5 value of the device in the critical damage state or the damaged state to call the chain with the same chain header data as the above MD5 value on the device-drawing chain, and read the sub-component specification information and connection consumables specification information in the chain.

[0103] The statistical module statistically analyzes the names, models and quantities of the sub-components required in the above sub-component specification information and the connection consumables specification information, as well as the names, models and quantities of the required connection consumables, and then generates the required spare equipment data information.

[0104] In one embodiment, the notification unit includes a demand verification module, an inventory comparison module, and a replenishment notification generation module.

[0105] The demand verification module is used to verify the received required spare equipment data information to ensure that the name and model of the required spare equipment are consistent with the inventory information. In practice, since the input of warehousing data is completed by different operators, it is very likely that the same equipment will have differences in the required spare equipment data information and inventory information, such as differences in uppercase and lowercase letters of the model or format symbols. The demand verification module needs to verify the above differences to ensure that they are the same equipment.

[0106] The inventory comparison module is used to compare the verified data information of the required spare equipment with the existing inventory information to determine whether the current inventory can meet the demand. When the inventory is sufficient, it generates the delivery information that meets the demand; when the inventory is insufficient, it counts the name, model and quantity of the insufficient spare equipment and generates replenishment information.

[0107] The replenishment notification generation module is used to generate a replenishment instruction according to the replenishment information, and the replenishment instruction includes a replenishment priority level. Among them, the priority level of the spare parts required by the equipment in the current damaged state is higher than the spare parts required by the equipment in the current critical damaged state.

[0108] In one embodiment, the management system further includes an inventory updating unit, which is electrically connected to the notification unit and is used to update the inventory information of the spare equipment in real time according to the outbound information and the replenishment information.

[0109] It should be noted that, although several units or modules of the system for action execution are mentioned in the above detailed description, this division is not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more modules described above can be concretized in one module. Conversely, the features and functions of a unit or module described above can be further divided into multiple units or modules for concretization. Some or all of the units or modules can be selected according to actual needs to achieve the purpose of the present invention. Those of ordinary skill in the art can understand and implement without paying creative work.

[0110] On the other hand, the present invention also provides a railway signal drawing and spare equipment management method based on big data, which is applied to the railway signal drawing and spare equipment management system based on big data described in any of the above embodiments. Figure 2 As shown, the method comprises the following steps:

[0111] Step S101: Acquire device data and drawing data, wherein the device data includes device identification information and real-time operating parameters, and the drawing data includes electronic drawings and index information corresponding to the electronic drawings, wherein the index information includes number, name, version and creation date.

[0112] Step S102: assigning a unique identifier to each device according to the device identification information, and establishing an association relationship between each device and the drawing based on the unique identifier and the drawing data to form a device-drawing chain.

[0113] Step S103: constructing a ternary damage estimation model consisting of a weight factor, the number of overvoltages, and the number of overcurrents, wherein the ternary damage estimation model is used to calculate the damage equivalent of the device.

[0114] The specific calculation formula is:

[0115] ;

[0116] in, represents the damage equivalent, represents the weight factor of the current factor, represents the weight factor of the voltage factor, Indicates the maximum number of overcurrent times allowed under the standard level. Indicates the number of overcurrents during operation of the device. Indicates the maximum number of overvoltages allowed under the standard level. Indicates the number of overvoltages during operation of the equipment;

[0117] Step S104: Substitute the received real-time operating parameters of the device into the ternary damage estimation model to calculate the damage equivalent of the device, and determine the current state of the device based on the damage equivalent, wherein the current state includes a normal state, a critical damage state, and a damage state.

[0118] Step S105: When the current state of the equipment is a critical damage state or a damage state, the equipment-drawing chain is called, and the required spare equipment data information is generated by parsing the equipment-drawing chain.

[0119] Step S106: Compare the required spare equipment data information with the inventory information, and generate a replenishment notice when the inventory is insufficient.

[0120] The detailed steps of the above steps S101-S106 can be implemented by referring to the above-mentioned implementation examples of the railway signal drawings and spare equipment management system based on big data, and will not be repeated here.

[0121] The railway signal drawing and spare equipment management system and method based on big data provided by the present invention highly correlates equipment data and drawing data to form an equipment-drawing chain, and can determine whether the equipment is damaged through the real-time operating parameters of the equipment. When the equipment is damaged or in a critical damage state, the equipment-drawing chain will be called to directly generate data information of the spare equipment that needs to be replaced. In this way, the process of comparing drawings by staff is omitted, and the efficiency of replacing damaged equipment is improved to a certain extent.

[0122] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. The present invention is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary technical means in the art that are not disclosed in the present invention.

Claims

1. Railway signal drawings and spare equipment management system based on big data, characterized by: include: A data acquisition unit, used to acquire device data and drawing data, wherein the device data includes device identification information and real-time operating parameters, and the drawing data includes electronic drawings and index information corresponding to the electronic drawings, wherein the index information includes number, name, version and creation date; A drawing and equipment association unit, electrically connected to the data acquisition unit, is used to assign a unique identifier to each device according to the device identification information, and to establish an association relationship between each device and the drawing based on the unique identifier and the drawing data to form a device-drawing chain; The damage estimation model construction unit is used to construct a ternary damage estimation model consisting of a weight factor, an overvoltage number, and an overcurrent number. The ternary damage estimation model is used to calculate the damage equivalent of the device, and the calculation formula is: ； in, represents the damage equivalent, represents the weight factor of the current factor, represents the weight factor of the voltage factor, Indicates the maximum number of overcurrent times allowed under the standard level. Indicates the number of overcurrents during operation of the device. Indicates the maximum number of overvoltages allowed under the standard level. Indicates the number of overvoltages during operation of the equipment; a damage determination unit, electrically connected to the data acquisition unit and the damage estimation model construction unit, respectively, for substituting the received real-time operating parameters of the device into the ternary damage estimation model, calculating the damage equivalent of the device, and determining the current state of the device according to the damage equivalent, wherein the current state includes a normal state, a critical damage state, and a damage state; A parsing unit, electrically connected to the damage determination unit and the drawing and equipment association unit, is used to call the equipment-drawing chain when the current state of the received equipment is a critical damage state or a damage state, and generate the required spare equipment data information by parsing the equipment-drawing chain; A notification unit, electrically connected to the analysis unit, for comparing the received required spare equipment data information with the inventory information, and generating a replenishment notification when the inventory is insufficient; The drawing and equipment association unit includes: A unique identifier assigning module, used to assign a unique identifier to each device according to the device identification information; The optimization module is used to filter out index information with the same name but different versions, and retain only the index information with the latest creation date and the electronic drawing corresponding to the index information according to the order of creation dates, so as to obtain the optimized first drawing data; a hierarchy construction module, used for parsing the first drawing data, and constructing a hierarchy of the first drawing data using a resource description framework model, wherein the hierarchy of the first drawing data includes an exclusive layer and a shared layer, wherein the exclusive layer is first drawing data dedicated to a device, and the shared layer is first drawing data shared by multiple devices; A feature extraction module is used to extract the type feature of the first drawing data in the exclusive layer to obtain the sub-component specification information of the device; extract the type feature of the first drawing data in the shared layer to obtain other devices associated with the device, and obtain the specification information of the connection consumables according to the connection mode between the devices; The chain generation module is used to generate a device-drawing chain including a unique identifier, subcomponent specification information, and connection consumable specification information from the chain head to the chain tail.

2. According to the railway signal drawing and spare equipment management system based on big data according to claim 1, it is characterized in that: The unique identifier is an MD5 value.

3. The railway signal drawing and spare equipment management system based on big data according to claim 1 is characterized in that: The hierarchical building blocks include: A classification processing submodule, used for parsing the first drawing data and classifying the first drawing data, wherein the classification includes circuit classification, structure classification, construction classification, wiring classification and structural layout classification; A model expression submodule, used to express the hierarchy of the first drawing data in the form of a resource description framework according to the classification of the first drawing data; Among them, the hierarchical expression of the first drawing data is: ； ； ； ； ； In the above expression, A hierarchical model representing the first drawing data, Indicates the specific level of the first drawing data, j indicates the level number, Denotes the exclusive layer, represents the shared layer, Indicates the classification of the first drawing data, Represents the circuit class, Represents a structural class, Indicates the construction class. Indicates the wiring class, Represents the structure layout class, It indicates the semantic relationship of inclusion, and i indicates the sequence number.

4. The railway signal drawing and spare equipment management system based on big data according to claim 1 is characterized in that: The damage determination unit includes a calculation module and a determination module; The calculation module is used to substitute the received real-time operating parameters of the equipment into the calculation formula of the ternary damage estimation model to calculate the damage equivalent of the equipment; The judgment module is used to judge the current state of the device according to the damage equivalent: when 1. Make sure the device is in normal status; when 1. Determine that the equipment is in a critical damage state; when 1. Determine whether the device is in a damaged state.

5. The railway signal drawing and spare equipment management system based on big data according to claim 4 is characterized in that: The parsing unit comprises: A reading module, used for reading the data on the device-drawing chain and sending it to the statistics module; The statistical module is used to count the names, models and quantities of the required sub-components, as well as the names, models and quantities of the required connecting consumables, and then generate the required spare equipment data information.

6. The railway signal drawing and spare equipment management system based on big data according to claim 5 is characterized in that: The notification unit comprises: The demand verification module is used to verify the received data information of the required spare equipment to ensure that the name and model of the required spare equipment are consistent with the inventory information; The inventory comparison module is used to compare the verified data information of the required spare equipment with the existing inventory information to determine whether the current inventory can meet the demand. When the inventory is sufficient, the outbound information that meets the demand is generated; when the inventory is insufficient, the name, model and quantity of the insufficient spare equipment are counted to generate replenishment information; A replenishment notification generation module is used to generate a replenishment instruction based on the replenishment information, wherein the replenishment instruction includes a replenishment priority level, wherein the priority level of the spare parts required for the equipment currently in a damaged state is higher than the priority level of the spare parts required for the equipment currently in a critical damaged state.

7. The railway signal drawing and spare equipment management system based on big data according to claim 6 is characterized in that: The management system also includes: The inventory updating unit is electrically connected to the notification unit and is used to update the inventory information of the spare equipment in real time according to the outbound information and the replenishment information.

8. A railway signal drawing and spare equipment management method based on big data, applied to a railway signal drawing and spare equipment management system based on big data as claimed in any one of claims 1 to 7, characterized in that: The following steps are involved: Acquire device data and drawing data, wherein the device data includes device identification information and real-time operating parameters, and the drawing data includes electronic drawings and index information corresponding to the electronic drawings, wherein the index information includes number, name, version and creation date; Assigning a unique identifier to each device according to the device identification information, and establishing an association relationship between each device and the drawing based on the unique identifier and the drawing data to form a device-drawing chain; A ternary damage estimation model consisting of a weight factor, overvoltage times, and overcurrent times is constructed. The ternary damage estimation model is used to calculate the damage equivalent of the equipment. The calculation formula is: ； in, represents the damage equivalent, represents the weight factor of the current factor, represents the weight factor of the voltage factor, Indicates the maximum number of overcurrent times allowed under the standard level. Indicates the number of overcurrents during operation of the device. Indicates the maximum number of overvoltages allowed under the standard level. Indicates the number of overvoltages during operation of the equipment; Substituting the received real-time operating parameters of the equipment into the ternary damage estimation model, calculating the damage equivalent of the equipment, and judging and determining the current state of the equipment according to the damage equivalent, wherein the current state includes a normal state, a critical damage state, and a damage state; When the current state of the equipment is a critical damage state or a damage state, the equipment-drawing chain is called, and the required spare equipment data information is generated by parsing the equipment-drawing chain; Compare the required spare equipment data information with the inventory information and generate replenishment notifications when the inventory is insufficient; The steps of assigning a unique identifier to each device according to the device identification information, and establishing an association relationship between each device and the drawing based on the unique identifier and the drawing data to form a device-drawing chain include: Assigning a unique identifier to each device according to the device identification information; Filter out index information with the same name but different versions, and retain only the index information with the latest creation date and the electronic drawing corresponding to the index information according to the order of creation dates, so as to obtain the optimized first drawing data; Parsing the first drawing data, and constructing a hierarchy of the first drawing data using a resource description framework model, wherein the hierarchy of the first drawing data includes an exclusive layer and a shared layer, wherein the exclusive layer is first drawing data dedicated to a device, and the shared layer is first drawing data shared by multiple devices; Extract the type characteristics of the first drawing data in the exclusive layer to obtain the sub-component specification information of the device; extract the type characteristics of the first drawing data in the shared layer to learn other devices associated with the device, and obtain the specification information of the connection consumables according to the connection mode between the devices; Generate a device-drawing chain with unique identifier, subcomponent specification information, and connection consumable specification information from the beginning to the end of the chain.

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