Adaptive fault early warning method and device of CT equipment

Abstract

The present application relates to the technical field of medical equipment maintenance, and particularly relates to a CT device self-adaptive fault early warning method and device. Historical operation records of a target CT device and anode temperature cycle records of an X-ray tube are acquired; a scan task timing sequence is obtained, the scan task timing sequence comprising a plurality of scan tasks, each scan task having a scan task type identifier; according to the scan task timing sequence, anode temperature change data segments corresponding to each scan task are extracted and time sequence processing is performed, obtaining an anode temperature cycle characteristic sequence; the anode temperature cycle characteristic sequence is processed, obtaining an anode cumulative fatigue damage degree of the X-ray tube; a fatigue damage degree self-adaptive threshold value of the X-ray tube is acquired, and when the anode cumulative fatigue damage degree is greater than or equal to the fatigue damage degree threshold value, X-ray tube fault early warning information is generated and output to a maintenance management system. The present application can accurately quantify the anode cumulative fatigue damage degree, and timely issue a fault early warning based on the self-adaptive threshold value.

Description

Technical Field

[0001] This invention relates to the field of medical equipment maintenance technology, and in particular to an adaptive fault early warning method and device for CT equipment. Background Technology

[0002] As a core piece of modern medical diagnostic equipment, the stable and reliable operation of CT scanners directly impacts the accuracy of medical diagnoses and patient safety. The X-ray tube, a critical component of CT equipment, plays a vital role in generating X-rays, and its operational status directly affects image quality and equipment availability. During CT scans, the X-ray tube anode must withstand high voltage and high current surges, generating significant heat. Prolonged operation can lead to anode fatigue damage, ultimately causing equipment failure and downtime. Current CT equipment X-ray tube early warning systems primarily rely on instantaneous temperature monitoring, which cannot accurately assess the cumulative fatigue damage to the tungsten anode target under repeated thermal cycling, resulting in delayed warnings and a high risk of sudden failure. Summary of the Invention

[0003] This invention addresses the technical problem in the prior art that it is impossible to accurately assess the cumulative fatigue damage of the tungsten anode target under repeated thermal cycling, by providing an adaptive fault early warning method and device for CT equipment.

[0004] The technical solution of the present invention to solve the above-mentioned technical problems is as follows:

[0005] In a first aspect, the present invention provides an adaptive fault early warning method for CT equipment, comprising: establishing a communication connection with a target CT equipment, acquiring historical operation records of the target CT equipment and cyclic records of the anode temperature of the X-ray tube in the target CT equipment; classifying the historical operation records based on the scanning location information in the historical operation records to obtain a scanning task sequence, wherein the scanning task sequence includes multiple scanning tasks, each of the scanning tasks having a scanning task type identifier; extracting anode temperature change data segments corresponding to each scanning task from the cyclic records of the X-ray tube according to the scanning task sequence and performing time-series processing to obtain an anode temperature cycle feature sequence; establishing an anode fatigue damage evaluator based on the scanning task type identifier in the scanning task sequence, processing the anode temperature cycle feature sequence, and outputting the cumulative fatigue damage degree of the X-ray tube; acquiring an adaptive threshold for the fatigue damage degree of the X-ray tube, and when the cumulative fatigue damage degree of the anode is greater than or equal to the fatigue damage degree threshold, generating X-ray tube fault early warning information and outputting it to a maintenance management system.

[0006] Optionally, the historical operation records are classified and divided based on the scan site information in the historical operation records to obtain a scan task sequence. The scan task sequence includes multiple scan tasks, each scan task having a scan task type identifier, including: extracting the scan site information of each scan task from the historical operation records; assigning a corresponding scan task type identifier to each scan task according to the scan site information, the scan task type identifier including head scan type, chest scan type, and abdomen scan type; arranging the scan tasks assigned scan task type identifiers in chronological order to form the scan task sequence.

[0007] Optionally, based on the scanning task timing, the anode temperature change data segments corresponding to each scanning task are extracted from the anode temperature cycle record of the X-ray tube and subjected to timing processing to obtain the anode temperature cycle feature sequence, including: locating the anode temperature change data segments corresponding to each scanning task in the anode temperature cycle record based on the time information of each scanning task in the scanning task timing; extracting the temperature peak value, temperature valley value, heating time, and cooling time from each anode temperature change data segment to construct the temperature cycle feature parameters corresponding to each scanning task; and arranging the temperature cycle feature parameters corresponding to each scanning task according to the time order of the scanning task timing to form the anode temperature cycle feature sequence.

[0008] Optionally, an anode fatigue damage evaluator is established based on the scan task type identifier in the scan task timeline to process the anode temperature cycle feature sequence and output the anode cumulative fatigue damage degree of the X-ray tube. This includes: constructing multiple fatigue damage evaluation units based on the scan task type identifier; constructing the anode fatigue damage evaluator based on the scan task timeline and the multiple fatigue damage evaluation units; inputting the anode temperature cycle feature sequence into the anode fatigue damage evaluator, performing chain processing on the anode temperature cycle feature sequence, and outputting the anode cumulative fatigue damage degree of the X-ray tube.

[0009] The process involves constructing multiple fatigue damage assessment units based on the scanning task type identifier, including: determining a target scanning task type identifier from the scanning task type identifiers; retrieving and obtaining X-ray tube operation records based on the target scanning task type identifier, and extracting multiple X-ray tube sample operation data from the X-ray tube operation records, whereby each X-ray tube sample operation data includes sample temperature cycle characteristic parameters, initial fatigue damage degree, and final fatigue damage degree; training and generating a target fatigue damage assessment unit corresponding to the target scanning task type identifier using the initial fatigue damage degree and sample temperature cycle characteristic parameters as input, and using the final fatigue damage degree as a supervision label; and training and generating fatigue damage assessment units corresponding to other scanning task type identifiers in the same manner as training and generating the target fatigue damage assessment unit corresponding to the target scanning task type identifier, thereby obtaining multiple fatigue damage assessment units.

[0010] The anode fatigue damage evaluator is constructed based on the scanning task timing and multiple fatigue damage assessment units, including: determining a first scanning task from the scanning task timing in chronological order and obtaining the corresponding first scanning task type; determining a first fatigue damage assessment unit from the multiple fatigue damage assessment units according to the first scanning task type; continuing to determine a second scanning task from the scanning task timing in chronological order and obtaining the corresponding second scanning task type; determining a second fatigue damage assessment unit from the multiple fatigue damage assessment units according to the second scanning task type; until the Nth scanning task is determined from the scanning task timing in chronological order and obtaining the corresponding Nth scanning task type; determining the Nth fatigue damage assessment unit from the multiple fatigue damage assessment units according to the Nth scanning task type, where N is the total number of scanning tasks in the scanning task timing; and connecting the first fatigue damage assessment unit to the Nth fatigue damage assessment unit sequentially in chronological order to form the anode fatigue damage evaluator.

[0011] The process of chaining the anode temperature cycle feature sequence to output the cumulative fatigue damage degree of the X-ray tube includes: setting the initial fatigue damage degree to 0 and extracting the first temperature cycle feature parameter corresponding to the first scan task from the anode temperature cycle feature sequence; inputting the initial fatigue damage degree and the first temperature cycle feature parameter into the first fatigue damage assessment unit and outputting the first fatigue damage degree; extracting the second temperature cycle feature parameter corresponding to the second scan task from the anode temperature cycle feature sequence, inputting the first fatigue damage degree and the second temperature cycle feature parameter into the second fatigue damage assessment unit and outputting the second fatigue damage degree; and so on until the Nth scan task is reached, inputting the (N-1)th fatigue damage degree and the Nth temperature cycle feature parameter into the Nth fatigue damage assessment unit and outputting the Nth fatigue damage degree as the cumulative fatigue damage degree of the X-ray tube.

[0012] The process includes: obtaining an adaptive threshold for fatigue damage of the X-ray tube; generating an X-ray tube fault warning and outputting it to the maintenance management system when the cumulative fatigue damage of the anode is greater than or equal to the fatigue damage threshold; obtaining the current service time of the X-ray tube; searching for the corresponding adaptive threshold for fatigue damage in a preset service time-threshold mapping table based on the current service time; comparing the cumulative fatigue damage of the anode with the adaptive threshold for fatigue damage; constructing an X-ray tube fault warning message containing fatigue damage assessment results when the cumulative fatigue damage of the anode is greater than or equal to the adaptive threshold for fatigue damage; and sending the X-ray tube fault warning message to the maintenance management system via a communication interface.

[0013] Optionally, the method further includes: when the cumulative fatigue damage of the anode is less than the fatigue damage adaptive threshold, generating X-ray tube status information based on the cumulative fatigue damage of the anode and the fatigue damage adaptive threshold; and sending the X-ray tube status information to the maintenance management system through a communication interface.

[0014] Secondly, the present invention provides an adaptive fault early warning device for CT equipment, comprising:

[0015] The operation record data acquisition module is used to establish a communication connection with the target CT device and acquire the historical operation record of the target CT device and the anolyte temperature cycle record of the X-ray tube in the target CT device.

[0016] The scanning task timing acquisition module is used to classify and divide the historical operation records based on the scanning part information in the historical operation records to obtain the scanning task timing. The scanning task timing includes multiple scanning tasks, and each scanning task has a scanning task type identifier.

[0017] The anode temperature cycle feature acquisition module is used to extract the anode temperature change data segment corresponding to each scanning task from the anode temperature cycle record of the X-ray tube according to the scanning task timing and perform timing processing to obtain the anode temperature cycle feature sequence.

[0018] The anode fatigue damage assessment module is used to establish an anode fatigue damage assessor based on the scanning task type identifier in the scanning task time sequence, process the anode temperature cycle characteristic sequence, and output the anode cumulative fatigue damage degree of the X-ray tube.

[0019] The fault warning information generation module is used to obtain the fatigue damage degree adaptive threshold of the X-ray tube. When the cumulative fatigue damage degree of the anode is greater than or equal to the fatigue damage degree threshold, the module generates X-ray tube fault warning information and outputs it to the maintenance management system.

[0020] By implementing this invention, a communication connection can be established with the target CT device, and the historical operation records of the target CT device and the anodic temperature cycle records of the X-ray tube in the target CT device can be obtained, providing sufficient data support for subsequent in-depth analysis of the fatigue damage of the X-ray tube and ensuring the reliability of the subsequent analysis results.

[0021] By implementing this invention, the historical operation records can be classified and divided based on the scanning location information in the historical operation records to obtain the scanning task sequence. The scanning task sequence includes multiple scanning tasks, and each scanning task has a scanning task type identifier. This lays the foundation for subsequent fatigue damage analysis of X-ray tubes under different working conditions, because the scanning parameters and load on the X-ray tube are different for different scanning locations.

[0022] By implementing this invention, it is possible to extract the anode temperature change data segments corresponding to each scanning task from the anode temperature cycle record of the X-ray tube according to the scanning task time sequence and perform time sequence processing to obtain the anode temperature cycle feature sequence. Temperature data irrelevant to a specific scanning task is eliminated, focusing on the key temperature change information corresponding to each scanning task. This reduces the interference of irrelevant data on subsequent analysis and improves analysis efficiency. In addition, the extracted characteristic parameters such as temperature peaks, valleys, heating time, and cooling time intuitively reflect the temperature change law of the anode under each scanning task, providing a clear and key analytical basis for subsequent evaluation of anode fatigue damage.

[0023] By implementing this invention, an anode fatigue damage evaluator can be established based on the scanning task type identifier in the scanning task time sequence, the anode temperature cycle characteristic sequence can be processed, and the cumulative fatigue damage degree of the anode of the X-ray tube can be output. The influence of different working conditions on anode fatigue damage is fully considered, making the evaluation results more in line with the actual situation and avoiding the inaccuracy caused by using a uniform standard for evaluation.

[0024] By implementing this invention, an adaptive threshold for the fatigue damage degree of the X-ray tube can be obtained. When the cumulative fatigue damage degree of the anode is greater than or equal to the fatigue damage degree threshold, an X-ray tube fault warning information is generated and output to the maintenance management system. The adaptive threshold can be dynamically adjusted according to factors such as the actual service condition of the X-ray tube, avoiding the problem of false alarms or missed alarms that are prone to occur under different use stages and operating conditions of the equipment when the fixed threshold is used, thus improving the accuracy of the warning.

[0025] In summary, by implementing this invention, the impact of different scanning conditions of CT equipment on the X-ray tube anode can be fully considered, the cumulative fatigue damage of the anode can be accurately quantified, and a fault warning can be issued in a timely manner based on an adaptive threshold. This effectively solves the problems of delayed warning, high risk of sudden failure, and many false alarms and missed alarms in the traditional X-ray tube warning method of CT equipment. Attached Figure Description

[0026] Figure 1 A flowchart illustrating an adaptive fault early warning method for CT equipment provided by the present invention;

[0027] Figure 2 This is a schematic diagram of the structure of an adaptive fault early warning device for CT equipment provided by the present invention.

[0028] In the attached diagram, the components represented by each number are as follows:

[0029] The module includes: 11 for acquiring running record data, 12 for acquiring scanning task timing, 13 for acquiring anode temperature cycle characteristics, 14 for assessing anode fatigue damage, and 15 for generating fault warning information. Detailed Implementation

[0030] 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.

[0031] In the description of this invention, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0032] In the description of this invention, the term "for example" is used to mean "used as an example, illustration, or description." Any embodiment described as "for example" in this invention is not necessarily to be construed as being more preferred or advantageous than other embodiments. The following description is provided to enable any person skilled in the art to make and use the invention. Details are set forth in the following description for purposes of explanation. It should be understood that those skilled in the art will recognize that the invention can be made without using these specific details. In other instances, well-known structures and processes will not be described in detail to avoid obscuring the description of the invention with unnecessary detail. Therefore, the invention is not intended to be limited to the embodiments shown, but is consistent with the broadest scope of the principles and features disclosed herein.

[0033] Example 1, as Figure 1 As shown, this embodiment of the invention provides an adaptive fault early warning method for CT equipment, including:

[0034] S100: Establish a communication connection with the target CT device and obtain the historical operation record of the target CT device and the anode temperature cycle record of the X-ray tube in the target CT device;

[0035] S200: Based on the scanning location information in the historical operation record, the historical operation record is classified and divided to obtain the scanning task sequence. The scanning task sequence includes multiple scanning tasks, and each scanning task has a scanning task type identifier.

[0036] S300: Based on the scanning task timing, extract the anode temperature change data segment corresponding to each scanning task from the anode temperature cycle record of the X-ray tube and perform timing processing to obtain the anode temperature cycle feature sequence.

[0037] S400: Based on the scanning task type identifier in the scanning task time sequence, an anode fatigue damage evaluator is established, the anode temperature cycle characteristic sequence is processed, and the cumulative fatigue damage degree of the anode of the X-ray tube is output.

[0038] S500: Obtain the adaptive threshold for fatigue damage of the X-ray tube. When the cumulative fatigue damage of the anode is greater than or equal to the fatigue damage threshold, generate an X-ray tube fault warning and output it to the maintenance management system.

[0039] In step S100 of this application embodiment, it is necessary to establish a communication connection with the target CT device and obtain the historical operation record of the target CT device and the anode temperature cycle record of the X-ray tube in the target CT device.

[0040] First, a communication connection needs to be established with the target CT equipment according to communication protocols such as HL7FHIR and Industrial Ethernet. After the communication connection is stable, a historical operation record retrieval command is sent to the CT equipment's control system through the early warning system. The command clearly specifies the time range and data type of the required data. The time range is such as the past month or the past three months, and the data type is such as scan time, scan area, tube voltage, and tube current parameters.

[0041] Next, the cyclic record of the X-ray tube's anode temperature needs to be retrieved via command. This cyclic record can be obtained from the temperature data storage module of the target CT equipment. Simply send a request for anode temperature data within a specified time range, receive and parse the anode temperature data at each time point, forming a continuous cyclic record of the anode temperature. This record is then stored in association with historical operation records for subsequent analysis and matching.

[0042] In step S200 of this application embodiment, the historical operation record is classified and divided based on the scanning part information in the historical operation record to obtain the scanning task sequence. The scanning task sequence includes multiple scanning tasks, and each scanning task has a scanning task type identifier, including:

[0043] Extract the scan area information for each scan task from the historical operation records;

[0044] Based on the scanned area information, a corresponding scan task type identifier is assigned to each scan task. The scan task type identifier includes head scan type, chest scan type, and abdominal scan type.

[0045] Each scan task, which has been assigned a scan task type identifier, is arranged in chronological order to form the scan task sequence.

[0046] In this embodiment of the application, the purpose of step S200 is to transform the messy historical operation records into a structured and ordered scanning task sequence, laying the foundation for subsequent analysis of the impact of different scanning conditions on the X-ray tube anode.

[0047] First, it is necessary to extract the scan site information for each scan task from the historical operation records. That is, to parse the metadata of each scan task from the historical operation records and filter out information containing the scan site field, such as the ScanBodyPart field defined in the CT equipment protocol.

[0048] Information about specific body parts, such as head, chest, and abdomen, is extracted using regular expression matching and keyword recognition. Synonyms are also processed, such as classifying the thoracic cavity as chest.

[0049] Next, based on the scanned area information, a corresponding scan task type identifier needs to be assigned to each scan task. The scan task type identifier includes head scan type, chest scan type, and abdominal scan type.

[0050] Specifically, a mapping rule base for scanning sites and type identifiers needs to be established, such as mapping the head to the head scan type, the chest / thoracic cavity to the chest scan type, and the abdomen / pelvis to the abdomen scan type. Then, for each extracted scanning site information, the corresponding type in the mapping rule base is automatically matched to give the scanning task a unique identifier, such as using code 001 to represent the head, 002 to represent the chest, and 003 to represent the abdomen, forming a structured task attribute.

[0051] Finally, the scan tasks assigned with scan task type identifiers need to be arranged in chronological order to form the scan task sequence.

[0052] This involves reading the timestamp information of each scan task, such as the scan start time, and sorting all scan tasks with type identifiers in chronological order. The sorted task sequence is then stored as a time-series data structure, with each node containing information such as task start / end time, type identifier, and associated parameters, ultimately forming a complete scan task time sequence.

[0053] In step S300 of this embodiment, based on the scanning task timing, the anode temperature change data segment corresponding to each scanning task is extracted from the anode temperature cycle record of the X-ray tube and subjected to timing processing to obtain the anode temperature cycle feature sequence, including:

[0054] Based on the time information of each scanning task in the scanning task time sequence, locate the anode temperature change data segment corresponding to each scanning task in the anode temperature cycle record;

[0055] Extract the temperature peak, temperature valley, heating time, and cooling time from each of the anode temperature change data segments to construct the temperature cycle characteristic parameters corresponding to each scanning task;

[0056] The temperature cycle characteristic parameters corresponding to each scanning task are arranged in chronological order according to the scanning task sequence to form the anode temperature cycle characteristic sequence.

[0057] In this embodiment, the core purpose of step S300 is to transform the original anode temperature cycle record into characteristic time-series data directly related to the scanning task, providing accurate quantitative basis for subsequent evaluation of X-ray tube anode fatigue damage.

[0058] To achieve the above objectives, the first step is to locate the anode temperature change data segment corresponding to each scanning task in the anode temperature cycle record based on the time information of each scanning task in the scanning task time sequence.

[0059] Specifically, it is necessary to read the start and end timestamps of each task in the scanning task sequence as the time boundary for temperature data extraction;

[0060] Then, the anode temperature cycle records are traversed, and all anode temperature data within each scanning task time period are extracted by time interval matching to form a unique anode temperature change data segment for that task.

[0061] Next, the integrity of the anode temperature change data segment is checked. If there is a time gap, the missing data is supplemented by an interpolation algorithm to ensure that the anode temperature curve of each task is continuous and complete.

[0062] The second step is to extract the temperature peak, temperature valley, heating time, and cooling time from each of the anode temperature change data segments to construct the temperature cycle characteristic parameters corresponding to each scanning task.

[0063] That is, curve analysis is performed on each segment of anode temperature change data, and the temperature peak (highest temperature) and temperature valley (lowest temperature) are identified by the extreme value search algorithm.

[0064] Calculate the heating time and cooling time, where the heating time is the time difference from the valley temperature to the peak temperature, and the cooling time is the time difference from the peak temperature to the next valley temperature.

[0065] The four parameters—temperature peak, temperature valley, heating time, and cooling time—are packaged to form a temperature cycle feature parameter set corresponding to the scanning task, such as: {Temperature peak: 2100K, Temperature valley: 1500K, Heating time: 12s, Cooling time: 45s}.

[0066] The third step is to arrange the temperature cycle characteristic parameters corresponding to each scanning task according to the time sequence of the scanning task to form the anode temperature cycle characteristic sequence.

[0067] First, the temperature cycle feature parameter sets corresponding to each task are arranged sequentially according to the time sequence of the scanning tasks.

[0068] Then, structured anode temperature cycle feature sequence data is constructed, such as an array or list, where each element in the sequence corresponds to a feature parameter of a scan task, while retaining the association with the scan task type identifier;

[0069] Finally, the anode temperature cycle characteristic sequence is stored in a time-series database format, supporting fast querying and retrieval by time sequence or task type.

[0070] In step S400 of this embodiment, an anode fatigue damage evaluator is established based on the scan task type identifier in the scan task timing, the anode temperature cycle characteristic sequence is processed, and the cumulative fatigue damage degree of the X-ray tube is output, including:

[0071] Based on the scanning task type identifier, multiple fatigue damage assessment units are constructed;

[0072] Based on the scanning task timing and multiple fatigue damage assessment units, the anode fatigue damage evaluator is constructed;

[0073] The anode temperature cycle characteristic sequence is input into the anode fatigue damage evaluator, the anode temperature cycle characteristic sequence is processed in a chain, and the cumulative fatigue damage degree of the anode of the X-ray tube is output.

[0074] In this embodiment of the application, the purpose of step S400 is to construct a fatigue damage assessment system that fits the actual scanning conditions of CT equipment, accurately quantify the cumulative fatigue damage of the X-ray tube anode under multiple scanning tasks, and solve the technical problem that traditional methods cannot take into account both the differences in working conditions and the cumulative effect.

[0075] To achieve the above objectives, it is first necessary to construct multiple fatigue damage assessment units based on the scanning task type identifier.

[0076] In step S400 of this application embodiment, multiple fatigue damage assessment units are constructed according to the scanning task type identifier, including:

[0077] Determine the target scan task type identifier from the scan task type identifier;

[0078] Based on the target scanning task type identifier, the X-ray tube operation record is retrieved, and multiple X-ray tube sample operation data are extracted from the X-ray tube operation record. Each X-ray tube sample operation data includes sample temperature cycle characteristic parameters, initial fatigue damage degree of the sample, and final fatigue damage degree of the sample.

[0079] Using the initial fatigue damage degree and temperature cycle characteristic parameters of the sample as inputs, and the final fatigue damage degree of the sample as a supervision label, a target fatigue damage assessment unit corresponding to the target scanning task type identifier is trained and generated.

[0080] Following the method of training and generating target fatigue damage assessment units corresponding to the target scanning task type identifier, fatigue damage assessment units corresponding to the other scanning task type identifiers are trained and generated, resulting in multiple fatigue damage assessment units.

[0081] First, it is necessary to determine the target scanning task type identifier from the scanning task type identifiers. That is, select one of the scanning task type identifiers obtained in step S200 as the target type to be trained. For example, select the head scanning type first to clarify the boundary of the training object.

[0082] Then, it is necessary to retrieve the X-ray tube operation record based on the target scanning task type identifier, and extract multiple X-ray tube sample operation data according to the X-ray tube operation record. Each X-ray tube sample operation data includes sample temperature cycle characteristic parameters, sample initial fatigue damage degree, and sample final fatigue damage degree.

[0083] The initial fatigue damage degree of the sample is the fatigue damage degree of the X-ray tube anode recorded at the beginning of the scanning task. The initial fatigue damage degree of the sample is 0 when a new X-ray tube is scanned for the first time, and subsequent scans can use the previous evaluation results or test records. The final fatigue damage degree of the sample is the anode fatigue damage degree determined by professional testing or equipment failure analysis after the completion of the scanning task. Specifically, it can be determined by combining the actual test conditions, life decay curves, etc.

[0084] Furthermore, using the initial fatigue damage degree and temperature cycle characteristic parameters of the sample as input, and the final fatigue damage degree of the sample as the supervision label, a target fatigue damage assessment unit corresponding to the target scanning task type identifier needs to be trained and generated. The training sample size for each target scanning task type identifier is no less than 500 sets.

[0085] Considering the task type of the target fatigue damage assessment unit, an improved model based on Miner's linear cumulative damage theory can be used to construct the target fatigue damage assessment unit. The core of this method is to optimize the traditional Miner theory by introducing a temperature correction coefficient, so that it can accurately reflect the fatigue damage accumulation law under different temperature cycling characteristics, which is consistent with the physical characteristics of fatigue damage caused by repeated heat loads on X-ray tube anodes.

[0086] In the construction of the fatigue damage assessment unit, the temperature correction factor is calculated based on the ratio of the peak temperature to the material's fatigue limit temperature, using the formula: Temperature Correction Factor = Peak Temperature ÷ Material Fatigue Limit Temperature. The time correction factor is determined by the ratio of the heating time to the cooling time, using the formula: Time Correction Factor = Heating Time ÷ (Heating Time + Cooling Time)

[0087] The single-cycle damage increment is calculated based on Miner's theory, combined with temperature correction coefficients and time correction coefficients. The formula is: Single-cycle damage increment = (temperature correction coefficient × time correction coefficient) ÷ total fatigue life cycles corresponding to this type of scan.

[0088] For example, the fatigue limit temperature of the material can be set according to the physical properties of the X-ray tube anode material, such as 2200K. The total fatigue life cycles corresponding to this type of scan can be set according to the physical properties of the X-ray tube anode material and the model of the CT equipment. For example, the total fatigue life cycles for a head scan are 8000; for a chest scan, 6000; and for an abdominal scan, 5000.

[0089] In training the fatigue damage assessment unit, 30 rounds of iterative training were adopted, with all sample data used in each round. The accuracy of the model output was optimized by continuously adjusting the calculation weights of the temperature correction coefficient and the time correction coefficient.

[0090] When the average error between the model output sample final state fatigue damage degree and the actual sample final state fatigue damage degree is less than 3% in 5 consecutive training rounds, the model training is considered to have converged, training is stopped, and the current model parameters are saved as the final parameters of the target fatigue damage assessment unit.

[0091] Following the steps described above, process the remaining scanning task type identifiers in sequence, such as chest scan type, abdominal scan type, etc.

[0092] That is, for each type, the corresponding sample running data is retrieved again; the same model framework is used or the model parameters are adjusted according to the characteristics of the type for training; finally, multiple fatigue damage assessment units corresponding to all scanning task types are obtained.

[0093] In step S400 of this application embodiment, the anode fatigue damage evaluator is constructed based on the scanning task timing and multiple fatigue damage evaluation units, including:

[0094] The first scanning task is determined from the scanning task sequence according to the time order, and the corresponding first scanning task type is obtained. The first fatigue damage assessment unit is determined from the plurality of fatigue damage assessment units according to the first scanning task type.

[0095] Continue to determine the second scanning task from the scanning task sequence according to the time order, and obtain the corresponding second scanning task type. Then, determine the second fatigue damage assessment unit from the multiple fatigue damage assessment units according to the second scanning task type.

[0096] Until the Nth scan task is determined from the scan task sequence in chronological order, and the corresponding Nth scan task type is obtained, the Nth fatigue damage assessment unit is determined from the multiple fatigue damage assessment units according to the Nth scan task type, where N is the total number of scan tasks in the scan task sequence;

[0097] The first fatigue damage assessment unit to the Nth fatigue damage assessment unit are connected sequentially in chronological order to form the anode fatigue damage assessor.

[0098] In this embodiment of the application, the core purpose of the above-mentioned subdivision steps in step S400 is to connect the corresponding types of fatigue damage assessment units into a complete anode fatigue damage assessor according to the actual execution order of the scanning task, so as to realize the dynamic tracking and calculation of the accumulated fatigue damage of the X-ray tube anode during continuous scanning.

[0099] The first step is to determine the first scanning task from the scanning task sequence according to the time order, obtain the corresponding first scanning task type, and determine the first fatigue damage assessment unit from the multiple fatigue damage assessment units according to the first scanning task type.

[0100] First, extract the first scan task in chronological order from the scan task sequence, that is, the earliest scan task executed.

[0101] Then, obtain the scan task type identifier of the first scan task, such as head scan type, chest scan type, or abdominal scan type.

[0102] Finally, based on the type identifier, the matching evaluation unit is called from among the multiple fatigue damage evaluation units that have been constructed, and it is identified as the first fatigue damage evaluation unit.

[0103] The second step involves continuing to determine the second scanning task from the scanning task sequence in chronological order, obtaining the corresponding second scanning task type, and determining the second fatigue damage assessment unit from the plurality of fatigue damage assessment units based on the second scanning task type, until the Nth scanning task is determined from the scanning task sequence in chronological order, and the corresponding Nth scanning task type is obtained, and the Nth fatigue damage assessment unit is determined from the plurality of fatigue damage assessment units based on the Nth scanning task type.

[0104] First, in chronological order, extract the second scan task, the third scan task, and so on up to the Nth scan task from the scan task time sequence, where N is the total number of all scan tasks in the scan task time sequence.

[0105] Then, obtain the scanning task type identifier corresponding to each task, such as head scan type, chest scan type, or abdominal scan type.

[0106] Next, for each task type identifier, a matching fatigue damage assessment unit is found from multiple fatigue damage assessment units and sequentially identified as the second fatigue damage assessment unit, the third fatigue damage assessment unit, ... the Nth fatigue damage assessment unit.

[0107] The third step is to connect the first fatigue damage assessment unit to the Nth fatigue damage assessment unit in chronological order to form the anode fatigue damage assessor.

[0108] First, the first fatigue damage assessment unit, the second fatigue damage assessment unit, ... the Nth fatigue damage assessment unit are connected in series according to the time sequence of the scanning tasks.

[0109] Then, the data transfer relationship between units is established, that is, the final state fatigue damage degree of the sample output by the previous fatigue damage assessment unit is automatically used as the initial fatigue damage degree of the sample of the next fatigue damage assessment unit.

[0110] Finally, a complete chain-like evaluation structure is formed, namely the anode fatigue damage evaluator. This evaluator can receive the temperature cycle characteristic parameters corresponding to each scanning task in chronological order, perform damage calculations in sequence, and finally output the cumulative fatigue damage degree of the anode.

[0111] In step S400 of this embodiment, the anode temperature cycle characteristic sequence is processed in a chain to output the cumulative fatigue damage degree of the anode of the X-ray tube, including:

[0112] The initial fatigue damage degree is set to 0, and the first temperature cycle feature parameter corresponding to the first scanning task is extracted from the anode temperature cycle feature sequence.

[0113] The initial fatigue damage degree and the first temperature cycle characteristic parameters are input into the first fatigue damage assessment unit, and the first fatigue damage degree is output.

[0114] Extract the second temperature cycle feature parameter corresponding to the second scanning task from the anode temperature cycle feature sequence, input the first fatigue damage degree and the second temperature cycle feature parameter into the second fatigue damage assessment unit, and output the second fatigue damage degree.

[0115] The process continues until the Nth scan task is reached. The (N-1)th fatigue damage degree and the Nth temperature cycle characteristic parameter are input into the Nth fatigue damage assessment unit, and the Nth fatigue damage degree is output as the anodic cumulative fatigue damage degree of the X-ray tube.

[0116] In this embodiment of the application, the purpose of the above-mentioned subdivision steps in step S400 is to calculate the fatigue damage caused by each scanning task to the X-ray tube anode by successive accumulations through a chain processing mechanism, and finally obtain the total cumulative fatigue damage degree of the X-ray tube anode.

[0117] The first step is to set the initial fatigue damage of the X-ray tube to 0, starting the calculation from the undamaged state by default. Then, extract the first temperature cycle feature parameters corresponding to the first scanning task from the anode temperature cycle feature sequence, including temperature peak, temperature valley, heating time, and cooling time.

[0118] The second step involves inputting the initial fatigue damage degree (i.e., 0) and the first temperature cycle characteristic parameters into the first fatigue damage assessment unit. The first fatigue damage assessment unit calculates the first fatigue damage degree based on the improved model of Miner theory within it and outputs the first fatigue damage degree after the completion of the first scanning task.

[0119] The third step is to extract the second temperature cycle feature parameters corresponding to the second scanning task from the anode temperature cycle feature sequence; then, the first fatigue damage degree is used as the initial value and input together with the second temperature cycle feature parameters into the second fatigue damage assessment unit to output the second fatigue damage degree.

[0120] Following the same logic, subsequent scanning tasks are processed sequentially: extract the Kth temperature cycle feature parameters corresponding to the Kth scanning task, input the K-1th fatigue damage degree as the initial value into the Kth fatigue damage assessment unit, and output the Kth fatigue damage degree, where the value of K is from 3 to N-1.

[0121] The fourth step is to extract the Nth temperature cycle feature parameters corresponding to the Nth scan task;

[0122] The (N-1)th fatigue damage degree and the Nth temperature cycle characteristic parameter are input into the Nth fatigue damage assessment unit, and the Nth fatigue damage degree is output after calculation. The Nth fatigue damage degree is the cumulative fatigue damage degree of the X-ray tube anode after all scanning tasks are performed. It is output as the final result and used for early warning judgment in subsequent steps.

[0123] Through the above chain processing, the cumulative calculation of fatigue damage was realized, and the total damage degree of the X-ray tube anode during continuous scanning was accurately quantified.

[0124] In step S500 of this embodiment, the fatigue damage degree adaptive threshold of the X-ray tube is obtained. When the cumulative fatigue damage degree of the anode is greater than or equal to the fatigue damage threshold, X-ray tube fault early warning information is generated and output to the maintenance management system, including:

[0125] Obtain the current service time of the X-ray tube;

[0126] The corresponding fatigue damage adaptive threshold is found in the preset service time-threshold mapping table based on the current service time.

[0127] The cumulative fatigue damage of the anode is compared with the adaptive threshold of fatigue damage.

[0128] When the cumulative fatigue damage of the anode is greater than or equal to the fatigue damage adaptive threshold, an X-ray tube fault early warning information containing fatigue damage assessment results is constructed.

[0129] The X-ray tube fault warning information is sent to the maintenance management system via the communication interface.

[0130] In step S500 of the embodiments of this application, the following is also included:

[0131] When the cumulative fatigue damage of the anode is less than the adaptive threshold for fatigue damage, X-ray tube status information is generated based on the cumulative fatigue damage of the anode and the adaptive threshold for fatigue damage.

[0132] The status information of the X-ray tube is sent to the maintenance management system via the communication interface.

[0133] In this embodiment of the application, the purpose of step S500 is to achieve accurate fault warning and status feedback based on the comparison result of the cumulative fatigue damage degree of the X-ray tube anode and the adaptive threshold, so as to provide a basis for decision-making for equipment maintenance management.

[0134] First, it is necessary to obtain the current service time of the X-ray tube. The current service time can be obtained by extracting the activation time from the X-ray tube's operation record and calculating it in combination with the current system time, such as 200 days of use.

[0135] Then, based on the current service time, the corresponding adaptive threshold for cumulative fatigue damage of the anode needs to be found in a preset service time-threshold mapping table. Specifically, the preset service time-threshold mapping table can be called. This table is formulated according to the life decay law of the same type of X-ray tube. Different service time periods correspond to different thresholds. For example, the threshold is 0.7 for 0-300 days of service and 0.6 for 301-600 days of service. The corresponding adaptive threshold for fatigue damage is obtained by matching the current service time from the table.

[0136] Next, it is necessary to compare the cumulative fatigue damage of the anode with the adaptive threshold for fatigue damage.

[0137] When the cumulative fatigue damage of the anode is greater than or equal to the adaptive threshold of fatigue damage, the X-ray tube is determined to have a high risk of failure. The X-ray tube failure warning information is constructed, which includes the cumulative fatigue damage of the anode, the adaptive threshold, the current service time, and the recommended maintenance period. Then, the X-ray tube failure warning information is sent to the system through the communication interface agreed with the maintenance management system, triggering the maintenance work order generation process.

[0138] When the cumulative fatigue damage of the anode is less than the adaptive threshold for fatigue damage: the X-ray tube is determined to be in normal condition, and X-ray tube status information is generated, including the current cumulative fatigue damage of the anode, the remaining safety margin from the adaptive threshold for fatigue damage, and the equipment health level; the X-ray tube status information is sent to the maintenance management system through the same communication interface to update the equipment health record for management personnel to refer to.

[0139] In summary, by implementing the adaptive fault early warning method and apparatus for CT equipment provided in this embodiment, at least the following can be achieved:

[0140] 1. Accurately quantify the cumulative fatigue damage of the anode and issue timely fault warnings based on adaptive thresholds.

[0141] 2. Construct dedicated damage assessment units based on the scanned area to achieve differentiated and accurate calculation of anodic damage under different working conditions.

[0142] 3. By chaining damage data to achieve successive cumulative calculation, the evolution of anode damage with scanning tasks can be accurately reproduced.

[0143] Example 2, as Figure 2 As shown, based on the same inventive concept as the adaptive fault warning method for CT equipment provided in Embodiment 1, this embodiment of the invention also provides an adaptive fault warning device for CT equipment, comprising:

[0144] The operation record data acquisition module 11 is used to establish a communication connection with the target CT device and acquire the historical operation record of the target CT device and the anode temperature cycle record of the X-ray tube in the target CT device;

[0145] The scanning task timing acquisition module 12 is used to classify and divide the historical operation record based on the scanning part information in the historical operation record to obtain the scanning task timing. The scanning task timing includes multiple scanning tasks, and each scanning task has a scanning task type identifier.

[0146] The anode temperature cycle feature acquisition module 13 is used to extract the anode temperature change data segment corresponding to each scanning task from the anode temperature cycle record of the X-ray tube according to the scanning task timing and perform timing processing to obtain the anode temperature cycle feature sequence.

[0147] The anode fatigue damage assessment module 14 is used to establish an anode fatigue damage assessor based on the scanning task type identifier in the scanning task time sequence, process the anode temperature cycle characteristic sequence, and output the anode cumulative fatigue damage degree of the X-ray tube.

[0148] The fault warning information generation module 15 is used to obtain the fatigue damage degree adaptive threshold of the X-ray tube. When the cumulative fatigue damage degree of the anode is greater than or equal to the fatigue damage degree threshold, the module generates X-ray tube fault warning information and outputs it to the maintenance management system.

[0149] Furthermore, the scanning task timing acquisition module 12 includes the following execution steps:

[0150] Extract the scan area information for each scan task from the historical operation records;

[0151] Based on the scanned area information, a corresponding scan task type identifier is assigned to each scan task. The scan task type identifier includes head scan type, chest scan type, and abdominal scan type.

[0152] Each scan task, which has been assigned a scan task type identifier, is arranged in chronological order to form the scan task sequence.

[0153] Furthermore, the anode temperature cycle characteristic acquisition module 13 includes the following execution steps:

[0154] Based on the time information of each scanning task in the scanning task time sequence, locate the anode temperature change data segment corresponding to each scanning task in the anode temperature cycle record;

[0155] Extract the temperature peak, temperature valley, heating time, and cooling time from each of the anode temperature change data segments to construct the temperature cycle characteristic parameters corresponding to each scanning task;

[0156] The temperature cycle characteristic parameters corresponding to each scanning task are arranged in chronological order according to the scanning task sequence to form the anode temperature cycle characteristic sequence.

[0157] Furthermore, the anode fatigue damage assessment module 14 includes the following execution steps:

[0158] Based on the scanning task type identifier, multiple fatigue damage assessment units are constructed;

[0159] Based on the scanning task timing and multiple fatigue damage assessment units, the anode fatigue damage evaluator is constructed;

[0160] The anode temperature cycle characteristic sequence is input into the anode fatigue damage evaluator, the anode temperature cycle characteristic sequence is processed in a chain, and the cumulative fatigue damage degree of the anode of the X-ray tube is output.

[0161] Based on the scanning task type identifier, multiple fatigue damage assessment units are constructed, including:

[0162] Determine the target scan task type identifier from the scan task type identifier;

[0163] Based on the target scanning task type identifier, the X-ray tube operation record is retrieved, and multiple X-ray tube sample operation data are extracted from the X-ray tube operation record. Each X-ray tube sample operation data includes sample temperature cycle characteristic parameters, initial fatigue damage degree of the sample, and final fatigue damage degree of the sample.

[0164] Using the initial fatigue damage degree and temperature cycle characteristic parameters of the sample as inputs, and the final fatigue damage degree of the sample as a supervision label, a target fatigue damage assessment unit corresponding to the target scanning task type identifier is trained and generated.

[0165] Following the method of training and generating target fatigue damage assessment units corresponding to the target scanning task type identifier, fatigue damage assessment units corresponding to the other scanning task type identifiers are trained and generated, resulting in multiple fatigue damage assessment units.

[0166] The anode fatigue damage evaluator is constructed based on the scanning task timing and multiple fatigue damage assessment units, including:

[0167] The first scanning task is determined from the scanning task sequence according to the time order, and the corresponding first scanning task type is obtained. The first fatigue damage assessment unit is determined from the plurality of fatigue damage assessment units according to the first scanning task type.

[0168] Continue to determine the second scanning task from the scanning task sequence according to the time order, and obtain the corresponding second scanning task type. Then, determine the second fatigue damage assessment unit from the multiple fatigue damage assessment units according to the second scanning task type.

[0169] Until the Nth scan task is determined from the scan task sequence in chronological order, and the corresponding Nth scan task type is obtained, the Nth fatigue damage assessment unit is determined from the multiple fatigue damage assessment units according to the Nth scan task type, where N is the total number of scan tasks in the scan task sequence;

[0170] The first fatigue damage assessment unit to the Nth fatigue damage assessment unit are connected sequentially in chronological order to form the anode fatigue damage assessor.

[0171] In step S400 of this embodiment, the anode temperature cycle characteristic sequence is processed in a chain to output the cumulative fatigue damage degree of the X-ray tube anode, including:

[0172] The initial fatigue damage degree is set to 0, and the first temperature cycle feature parameter corresponding to the first scanning task is extracted from the anode temperature cycle feature sequence.

[0173] The initial fatigue damage degree and the first temperature cycle characteristic parameters are input into the first fatigue damage assessment unit, and the first fatigue damage degree is output.

[0174] Extract the second temperature cycle feature parameter corresponding to the second scanning task from the anode temperature cycle feature sequence, input the first fatigue damage degree and the second temperature cycle feature parameter into the second fatigue damage assessment unit, and output the second fatigue damage degree.

[0175] The process continues until the Nth scan task is reached. The (N-1)th fatigue damage degree and the Nth temperature cycle characteristic parameter are input into the Nth fatigue damage assessment unit, and the Nth fatigue damage degree is output as the anodic cumulative fatigue damage degree of the X-ray tube.

[0176] Furthermore, the fault warning information generation module 15 includes the following execution steps:

[0177] Obtain the current service time of the X-ray tube;

[0178] The corresponding fatigue damage adaptive threshold is found in the preset service time-threshold mapping table based on the current service time.

[0179] The cumulative fatigue damage of the anode is compared with the adaptive threshold of fatigue damage.

[0180] When the cumulative fatigue damage of the anode is greater than or equal to the fatigue damage adaptive threshold, an X-ray tube fault early warning information containing fatigue damage assessment results is constructed.

[0181] The X-ray tube fault warning information is sent to the maintenance management system via the communication interface.

[0182] When the cumulative fatigue damage of the anode is less than the adaptive threshold for fatigue damage, X-ray tube status information is generated based on the cumulative fatigue damage of the anode and the adaptive threshold for fatigue damage.

[0183] The status information of the X-ray tube is sent to the maintenance management system via the communication interface.

[0184] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0185] Those skilled in the art will understand that embodiments of the present invention can provide methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0186] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0187] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0188] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0189] Although preferred embodiments of the invention have been described, those skilled in the art, once they have learned the basic inventive concept, can make other changes and modifications to these embodiments.

[0190] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of this invention and its equivalents, this invention also intends to include these modifications and variations.

Claims

1. An adaptive fault early warning method for CT equipment, characterized in that, The method includes: Establish a communication connection with the target CT device to obtain the historical operation records of the target CT device and the anode temperature cycle records of the X-ray tube in the target CT device; Based on the scanning location information in the historical operation record, the historical operation record is classified and divided to obtain the scanning task sequence. The scanning task sequence includes multiple scanning tasks, and each scanning task has a scanning task type identifier. Based on the scanning task timing, extract the anode temperature change data segment corresponding to each scanning task from the anode temperature cycle record of the X-ray tube and perform timing processing to obtain the anode temperature cycle feature sequence. An anode fatigue damage evaluator is established based on the scanning task type identifier in the scanning task time sequence. The anode temperature cycle characteristic sequence is processed to output the anode cumulative fatigue damage degree of the X-ray tube. The anode fatigue damage evaluator includes multiple fatigue damage evaluation units. The fatigue damage evaluation units are built using an improved model based on Miner's linear cumulative damage theory. The method for processing the anode temperature cycle characteristic sequence is chain processing. An adaptive threshold for fatigue damage of the X-ray tube is obtained. When the cumulative fatigue damage of the anode is greater than or equal to the fatigue damage threshold, an X-ray tube fault warning is generated and output to the maintenance management system.

2. The method according to claim 1, characterized in that, Based on the scanned area information in the historical operation records, the historical operation records are classified and divided to obtain a scan task sequence. The scan task sequence includes multiple scan tasks, and each scan task has a scan task type identifier, including: Extract the scan area information for each scan task from the historical operation records; Based on the scanned area information, a corresponding scan task type identifier is assigned to each scan task. The scan task type identifier includes head scan type, chest scan type, and abdominal scan type. Each scan task, which has been assigned a scan task type identifier, is arranged in chronological order to form the scan task sequence.

3. The method according to claim 1, characterized in that, Based on the scanning task timing, the anode temperature change data segments corresponding to each scanning task are extracted from the anode temperature cycle record of the X-ray tube and subjected to timing processing to obtain the anode temperature cycle feature sequence, including: Based on the time information of each scanning task in the scanning task time sequence, locate the anode temperature change data segment corresponding to each scanning task in the anode temperature cycle record; Extract the temperature peak, temperature valley, heating time, and cooling time from each of the anode temperature change data segments to construct the temperature cycle characteristic parameters corresponding to each scanning task; The temperature cycle characteristic parameters corresponding to each scanning task are arranged in chronological order according to the scanning task sequence to form the anode temperature cycle characteristic sequence.

4. The method according to claim 1, characterized in that, An anode fatigue damage evaluator is established based on the scan task type identifier in the scan task timeline. This evaluator processes the anode temperature cycle characteristic sequence and outputs the cumulative fatigue damage degree of the X-ray tube's anode, including: Based on the scanning task type identifier, multiple fatigue damage assessment units are constructed; Based on the scanning task timing and multiple fatigue damage assessment units, the anode fatigue damage evaluator is constructed; The anode temperature cycle characteristic sequence is input into the anode fatigue damage evaluator, the anode temperature cycle characteristic sequence is processed in a chain, and the cumulative fatigue damage degree of the anode of the X-ray tube is output.

5. The method according to claim 4, characterized in that, Based on the scanning task type identifier, multiple fatigue damage assessment units are constructed, including: Determine the target scan task type identifier from the scan task type identifier; Based on the target scanning task type identifier, the X-ray tube operation record is retrieved, and multiple X-ray tube sample operation data are extracted from the X-ray tube operation record. Each X-ray tube sample operation data includes sample temperature cycle characteristic parameters, initial fatigue damage degree of the sample, and final fatigue damage degree of the sample. Using the initial fatigue damage degree and temperature cycle characteristic parameters of the sample as inputs, and the final fatigue damage degree of the sample as a supervision label, a target fatigue damage assessment unit corresponding to the target scanning task type identifier is trained and generated. Following the method of training and generating target fatigue damage assessment units corresponding to the target scanning task type identifier, fatigue damage assessment units corresponding to the other scanning task type identifiers are trained and generated, resulting in multiple fatigue damage assessment units.

6. The method according to claim 4, characterized in that, Based on the scanning task timing and multiple fatigue damage assessment units, the anode fatigue damage evaluator is constructed, including: The first scanning task is determined from the scanning task sequence according to the time order, and the corresponding first scanning task type is obtained. The first fatigue damage assessment unit is determined from the plurality of fatigue damage assessment units according to the first scanning task type. Continue to determine the second scanning task from the scanning task sequence according to the time order, and obtain the corresponding second scanning task type. Then, determine the second fatigue damage assessment unit from the multiple fatigue damage assessment units according to the second scanning task type. Until the Nth scan task is determined from the scan task sequence in chronological order, and the corresponding Nth scan task type is obtained, the Nth fatigue damage assessment unit is determined from the multiple fatigue damage assessment units according to the Nth scan task type, where N is the total number of scan tasks in the scan task sequence; The first fatigue damage assessment unit to the Nth fatigue damage assessment unit are connected sequentially in chronological order to form the anode fatigue damage assessor.

7. The method according to claim 6, characterized in that, The anode temperature cycle characteristic sequence is chained to output the cumulative fatigue damage degree of the X-ray tube anode, including: The initial fatigue damage degree is set to 0, and the first temperature cycle feature parameter corresponding to the first scanning task is extracted from the anode temperature cycle feature sequence. The initial fatigue damage degree and the first temperature cycle characteristic parameters are input into the first fatigue damage assessment unit, and the first fatigue damage degree is output. Extract the second temperature cycle feature parameter corresponding to the second scanning task from the anode temperature cycle feature sequence, input the first fatigue damage degree and the second temperature cycle feature parameter into the second fatigue damage assessment unit, and output the second fatigue damage degree. The process continues until the Nth scan task is reached. The (N-1)th fatigue damage degree and the Nth temperature cycle characteristic parameter are input into the Nth fatigue damage assessment unit, and the Nth fatigue damage degree is output as the anodic cumulative fatigue damage degree of the X-ray tube.

8. The method according to claim 4, characterized in that, Obtain an adaptive threshold for fatigue damage of the X-ray tube. When the cumulative fatigue damage of the anode is greater than or equal to the fatigue damage threshold, generate an X-ray tube fault warning and output it to the maintenance management system, including: Obtain the current service time of the X-ray tube; The corresponding fatigue damage adaptive threshold is found in the preset service time-threshold mapping table based on the current service time. The cumulative fatigue damage of the anode is compared with the adaptive threshold of fatigue damage. When the cumulative fatigue damage of the anode is greater than or equal to the fatigue damage adaptive threshold, an X-ray tube fault early warning information containing fatigue damage assessment results is constructed. The X-ray tube fault warning information is sent to the maintenance management system via the communication interface.

9. The method according to claim 8, characterized in that, The method further includes: When the cumulative fatigue damage of the anode is less than the adaptive threshold for fatigue damage, X-ray tube status information is generated based on the cumulative fatigue damage of the anode and the adaptive threshold for fatigue damage. The status information of the X-ray tube is sent to the maintenance management system via the communication interface.

10. An adaptive fault early warning device for CT equipment, characterized in that, The device is used to implement an adaptive fault warning method for a CT device as described in any one of claims 1-9, comprising: The operation record data acquisition module is used to establish a communication connection with the target CT device and acquire the historical operation record of the target CT device and the anolyte temperature cycle record of the X-ray tube in the target CT device. The scanning task timing acquisition module is used to classify and divide the historical operation records based on the scanning part information in the historical operation records to obtain the scanning task timing. The scanning task timing includes multiple scanning tasks, and each scanning task has a scanning task type identifier. The anode temperature cycle feature acquisition module is used to extract the anode temperature change data segment corresponding to each scanning task from the anode temperature cycle record of the X-ray tube according to the scanning task timing and perform timing processing to obtain the anode temperature cycle feature sequence. The anode fatigue damage assessment module is used to establish an anode fatigue damage assessor based on the scanning task type identifier in the scanning task time sequence, process the anode temperature cycle characteristic sequence, and output the anode cumulative fatigue damage degree of the X-ray tube. The fault warning information generation module is used to obtain the fatigue damage degree adaptive threshold of the X-ray tube. When the cumulative fatigue damage degree of the anode is greater than or equal to the fatigue damage degree threshold, the module generates X-ray tube fault warning information and outputs it to the maintenance management system.

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