CN115144098A - Ray nondestructive testing method for armored temperature sensor - Google Patents
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- CN115144098A CN115144098A CN202210761032.8A CN202210761032A CN115144098A CN 115144098 A CN115144098 A CN 115144098A CN 202210761032 A CN202210761032 A CN 202210761032A CN 115144098 A CN115144098 A CN 115144098A
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- G01—MEASURING; TESTING
- G01K—MEASURING TEMPERATURE; MEASURING QUANTITY OF HEAT; THERMALLY-SENSITIVE ELEMENTS NOT OTHERWISE PROVIDED FOR
- G01K15/00—Testing or calibrating of thermometers
- G01K15/007—Testing
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
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- Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
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- Y02E30/30—Nuclear fission reactors
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Abstract
The invention relates to a ray nondestructive testing method of an armored temperature sensor, which comprises the following steps of S1, establishing a standard image database of the armored temperature sensor; s2, acquiring to-be-detected image data of an armored temperature sensor to be detected; and S3, comparing and analyzing the image data to be detected with the standard image database to obtain a detection result. The invention can be applied to different-stage detection of the armored temperature sensor, wherein the different-stage detection comprises detection before manufacturing, detection after welding or assembling, finished product detection and the like; if the method is applied to detection before manufacturing, components with hidden quality troubles or defects can be eliminated, and the subsequent product rate is improved; if the method is applied to welding or detection after assembly, the method can be used for evaluating the welding process and the structural process effect; if the device is applied to finished product detection, the device can completely detect the internal components of the armored temperature sensor, and the possible quality weak points and potential quality hidden dangers are found, and the risks brought by equipment in the operation process of the nuclear power station are reduced.
Description
Technical Field
The invention relates to the technical field of ray nondestructive testing, in particular to a ray nondestructive testing method for an armored temperature sensor.
Background
A sheathed temperature sensor is a temperature-sensitive device consisting of one or more temperature-sensing elements (often in the form of a wire wrap) housed within a sheath, an inner lead and an external terminal for connection to an electrical measuring instrument, the temperature sensing device mainly comprises a temperature sensing element, an inner lead, a signal lead, an insulating material, an inner protection tube, a temperature sensing sleeve and the like, wherein the temperature sensing element, the inner lead and the signal lead are connected through welding. With the rapid development of nuclear power engineering in China, a large number of armored temperature sensors are used in engineering application, and the quality and performance stability of the armored temperature sensors are related to the safe operation of a nuclear power station. Because the application environment is harsh, the factors such as irradiation, vibration, high temperature and the like exist, the armored temperature sensor adopted by nuclear power is extremely difficult to replace after failure, the design life of the armored temperature sensor is as long as more than 20 years, and therefore hidden danger troubleshooting and quality detection of the armored temperature sensor before use are particularly important.
Generally, a complete qualified armored temperature sensor for nuclear power needs to be processed and manufactured through 100 steps and quality inspection procedures, and the quality control is strict. However, the current technical scheme still has potential quality weaknesses and hidden dangers of internal components, the internal components mainly comprise temperature sensing elements, inner leads, signal leads, insulating materials and the like, and the detection rate of the weaknesses and the hidden dangers is very low or even cannot be detected. The main performance is as follows: 1. in the wire-wound coil pressing process of the temperature sensing element, overstretching, turn-to-turn wire winding overlapping or wrinkling is carried out; 2. the temperature sensing element is in cold joint/cold joint with the inner lead and the signal lead; 3. overstretching the inner lead during the filling and drawing of the insulating material; 4. material defects of the temperature sensing element body, and the like. The problems of overcurrent open circuit and turn-to-turn short circuit of the armored temperature sensor in the application process can be caused by the hidden troubles or the defects.
Disclosure of Invention
The invention aims to solve the technical problem of providing a ray nondestructive testing method of an armored temperature sensor, which is convenient to detect and aims at least one defect in the prior art.
The technical scheme adopted by the invention for solving the technical problems is as follows: a ray nondestructive testing method for constructing an armored temperature sensor comprises the following steps:
s1, establishing a standard image database of an armored temperature sensor;
s2, acquiring to-be-detected image data of an armored temperature sensor to be detected;
and S3, comparing and analyzing the image data to be detected with the standard image database to obtain a detection result.
Preferably, the sheathed temperature sensor comprises a plurality of types of sheathed temperature sensors; the step S1 includes:
s11, acquiring corresponding ray energy value data according to parameters of the various armored temperature sensors;
s12, acquiring standard image data of the armored temperature sensor corresponding to the ray energy value data according to the ray energy value data;
s13, establishing the standard image database according to the parameters of the armored temperature sensors of various types, the corresponding ray energy value data and the standard image data.
Preferably, the parameters of the armored temperature sensor of multiple types comprise the model of the armored temperature sensor, the detection position and the wall thickness parameter of each detection position.
Preferably, the step S2 includes:
s21, carrying out digital image acquisition on the armored temperature sensor to be detected through the ray detection system to obtain an acquired image;
s22, preprocessing the collected image to obtain the image data to be detected.
Preferably, the step S21 includes:
s211, setting a corresponding ray energy value according to the model, the detection position and the wall thickness parameter of the armored temperature sensor to be detected;
s212, the armored temperature sensors to be detected are driven to move, the detection positions are moved to the irradiation center of the ray transillumination field one by one, and then the image data to be detected of the detection positions are obtained.
Preferably, the detection position comprises a first detection point arranged at a temperature sensing element of the armored temperature sensor, a second detection point arranged at an inner welding point of the armored temperature sensor, a third detection point arranged at an inner lead of the armored temperature sensor and/or a fourth detection point arranged at a signal lead and a welding point of the armored temperature sensor.
Preferably, the step S3 includes:
s31, calling corresponding standard image data in the standard image database according to the image data to be detected;
and S32, comparing and analyzing the image data to be detected and the corresponding standard image data.
Preferably, the method further comprises:
and S4, constructing a computer neural network data set to train and test the standard image database.
Preferably, the step S4 specifically includes constructing a computer neural network data set based on a convolutional neural network algorithm, and performing normalization processing on standard image data of the various types of armored temperature sensors to train and test the standard image data base.
Preferably, the expression of the characteristic diagram of the convolutional neural network is as follows:
wherein b is the deviation amount, Z l And Z l+1 Respectively representing the convolution input and output of the l +1 th layer, K being the number of channels, s 0 F is the convolution step length, f is the convolution kernel size, and p is the number of filling layers.
The implementation of the invention has the following beneficial effects: the invention can be applied to different-stage detection of the armored temperature sensor, wherein the different-stage detection comprises detection before manufacturing, detection after welding or assembling, finished product detection and the like; if the method is applied to detection before manufacturing, components with hidden quality troubles or defects can be eliminated, and the subsequent product rate is improved; if the method is applied to detection after welding or assembly, the method can be used for evaluating the welding process and the structural process effect; if the method is applied to finished product detection, the complete detection of the internal components of the armored temperature sensor can be realized, possible quality weaknesses and potential quality hidden dangers can be found, and the risks brought by equipment in the operation process of the nuclear power station can be reduced.
Drawings
The invention will be further described with reference to the following drawings and examples, in which:
FIG. 1 is a flow chart of a method of nondestructive radiographic testing of an armored temperature sensor of the present invention;
FIG. 2 is a flow chart of the present invention for the method step S1 of nondestructive testing of the radiation of the armored temperature sensor;
FIG. 3 is a flow chart of the present invention for the method step S2 of nondestructive testing of the radiation of the armored temperature sensor;
FIG. 4 is a flow chart of a nondestructive radiographic testing method step S21 of the armored temperature sensor of the present invention;
FIG. 5 is a flow chart of step S3 of the nondestructive testing method for rays of the armored temperature sensor of the present invention;
FIG. 6 is a schematic view of the method of nondestructive inspection of the armored temperature sensor of the present invention;
FIG. 7 is a block flow diagram of one embodiment of a method for nondestructive inspection of armored temperature sensors of the present invention;
FIG. 8 is an imaging of a qualified armored temperature sensor of the present invention;
FIG. 9 is an imaging of a sheathed temperature sensor of the present invention showing an indication fluctuation problem;
FIG. 10 is an imaging view of a sheathed temperature sensor of the present invention with a circuit break problem;
FIG. 11 is an imaging of the armored temperature sensor of the present invention with the problem of inter-turn overlap of the resistance wire;
fig. 12 is an imaging of a sheathed temperature sensor of the present invention that has metal poisoning issues.
Detailed Description
For a more clear understanding of the technical features, objects, and effects of the present invention, embodiments of the present invention will now be described in detail with reference to the accompanying drawings. In the following description, it is to be understood that the orientations and positional relationships indicated by "front", "rear", "upper", "lower", "left", "right", "longitudinal", "lateral", "vertical", "horizontal", "top", "bottom", "inner", "outer", "leading", "trailing", and the like are configured and operated in specific orientations based on the orientations and positional relationships shown in the drawings, and are only for convenience of describing the present invention, and do not indicate that the device or element referred to must have a specific orientation, and thus, are not to be construed as limiting the present invention.
It is also noted that, unless expressly stated or limited otherwise, the terms "mounted," "connected," "secured," "disposed," and the like are intended to be inclusive and mean, for example, that they may be fixedly connected, detachably connected, or integrally formed; can be mechanically or electrically connected; either directly or indirectly through intervening media, either internally or in any other relationship. When an element is referred to as being "on" or "under" another element, it can be "directly" or "indirectly" on the other element or intervening elements may also be present. The terms "first", "second", "third", etc. are merely for convenience in describing the present technical solution and are not to be construed as indicating or implying any relative importance or implicitly indicating the number of technical features indicated, whereby the features defined as "first", "second", "third", etc. may explicitly or implicitly include one or more of such features. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
Referring to fig. 1 to 7, a nondestructive testing method for radiation of a sheathed temperature sensor according to the present invention is shown, in the present embodiment, nondestructive testing is performed by taking X-ray as an example, and it is understood that other types of radiation can be used for testing. The ray nondestructive testing method of the armored temperature sensor comprises the following steps:
s1, establishing a standard image database of an armored temperature sensor according to standard image data; specifically, a standard image database of the armored temperature sensors is established according to parameters of various armored temperature sensors to be detected; the armored temperature sensor comprises a plurality of types of armored temperature sensors; as shown in fig. 2, further, step S1 includes:
s11, acquiring corresponding ray energy value data according to parameters of various armored temperature sensors; the parameters of the various types of armored temperature sensors comprise the types and the detection positions of the armored temperature sensors and the wall thickness parameters of the detection positions, and the ray energy value data of the various types of armored temperature sensors are obtained according to the parameters. Wherein the detection position of each type of sheathed temperature sensor can be a preset detection position.
S12, acquiring standard image data of the corresponding armored temperature sensor according to the ray energy value data;
and S13, establishing a standard image database according to the parameters of the various types of armored temperature sensors, the corresponding ray energy value data and the standard image data.
Because the armored platinum thermal resistance temperature sensor is formed by compositely processing different metal structures, the energy of X-ray photon is required to be adjusted according to the thickness and the density of different metal materials, the thickness and density of each metal material, corresponding to one ray energy level, otherwise, the transmission effect cannot be realized; i.e., one for each type of armor temperature sensor. Therefore, the standard image database comprises parameters of all armored temperature sensors needing to be detected, the parameters of each armored temperature sensor comprise the model of the armored platinum thermal resistor temperature sensor, wall thickness parameters of all parts, ideal standard images and the like, ray energy value data of the armored temperature sensor are obtained, and finally ray energy value data of various armored temperature sensors are obtained in a summarizing mode so as to establish the standard image database.
S2, acquiring to-be-detected image data of an armored temperature sensor to be detected; as shown in fig. 3, further, step S2 includes:
s21, carrying out digital image acquisition on an armored temperature sensor to be detected through a ray detection system to obtain an acquired image; specifically, an X-ray detection system can be used for carrying out image acquisition on an armored temperature sensor to be detected to obtain an acquired image; an X-ray detection system, also known as an X-ray constant frequency emission and imaging system; before detection, related parameter setting is carried out on the system, including presetting the detection position of a temperature sensor, and the ray energy value and related parameters corresponding to the X-ray detection system are adjusted according to the preset detection position of the temperature sensor;
as shown in fig. 4, specifically, step S21 includes:
step S211, setting corresponding ray energy values according to the model, the detection position and the wall thickness parameters of the armored temperature sensor to be detected; more specifically, image acquisition is carried out according to the model of the armored temperature sensor to be detected and the detection position corresponding to the armored temperature sensor of the model, namely, the X-ray detection system can adjust the corresponding parameters of the system according to the model of the armored temperature sensor to be detected currently and the detection position corresponding to the armored temperature sensor of the model, and the X-ray detection system can quickly and accurately acquire the detection position of the armored temperature sensor to be detected currently to obtain a corresponding acquired image;
s212, driving the armored temperature sensor to be detected to move, moving the detection positions to the irradiation center of the radiographic field one by one, and further acquiring image data to be detected of the detection positions; furthermore, according to the identification requirement of the ray detection system, a sliding submission device can be arranged in the ray detection system, a proper sliding track is specifically arranged according to the preset detection position of the armored temperature sensor, the armored temperature sensor to be detected is conveyed to the identifiable range of the ray detection system through the sliding submission device, and the detection range is in a square detection window of an operation platform of the ray detection system; preferably, each preset detection position of the armored temperature sensor is positioned in the center below the radiolucent field.
And S22, preprocessing the collected image to obtain image data to be detected. Specifically, in step S22, the acquired image obtained in step S1 is subjected to image processing methods such as image filtering and image denoising to obtain image data to be detected.
Furthermore, the present embodiment includes four preset detection positions, the diameter of which is 8.4mm, the initial X-ray tube voltage is 130-150 KV, the voltage changes with the diameter of the standard part, and the voltage increases by 10KV every 1mm increase in diameter on the basis of 130 KV; the exposure time was set to 333ms, the resolution was 2000 x 1500, the radiation angle was perpendicular to 90 ℃, and the focus was automatically adjusted. As shown in fig. 6, the X-ray detection system specifically includes an X-ray machine 100, and emits X-ray beams through a radiation source such as the X-ray machine 100, the radiation passes through a relay and is attenuated, the transmitted radiation is converted into analog signals and digital signals by a radiation receiving and converting device, and then the detection result image is visually displayed on a display screen by means of a transmission technology of semiconductor materials and a processing and information technology of digital images. Under the precondition that the performance of the temperature sensor is not influenced or damaged, the images of the internal structure of the object on the film 101 can be distinguished due to different photosensitive degrees of all parts of the object, and the internal defects can be visually displayed. In the detection process of the embodiment, four detection points are mainly selected as preset detection positions for detection, and the preset detection positions of the armored temperature sensor comprise a first detection point 1 arranged at a temperature sensing element of the armored temperature sensor, a second detection point 2 arranged at an internal welding point of the armored temperature sensor, a third detection point 3 arranged at an internal lead of the armored temperature sensor and a fourth detection point 4 arranged at a signal lead welding position of the armored temperature sensor.
The first detection point 1 mainly detects a temperature sensing element, and can discriminate the following quality and hidden danger problems:
(1) The platinum coil overlaps the shadow and the wrinkle, and the inter-turn distance of the platinum coil is not uniform, as shown in fig. 11. The problem causes poor measurement precision of the temperature sensor and fluctuation of measured values;
(2) The platinum coil lead break point is open. This problem results in the temperature sensor not measuring properly.
The second detection point 2, the third detection point 3 and the fourth detection point 4 are mainly used for detecting internal leads and welding points thereof, and the following quality and hidden danger problems can be identified:
(1) The lead and the welding point thereof are in false welding, which causes the fluctuation of the measured value of the temperature sensor, low insulation and the like;
(2) The wire and its bonding pads will be whisker, impurity, etc. causing temperature sensor metal poisoning, as shown in fig. 12, which in turn causes measurement value fluctuation, low insulation, open circuit, etc.
And S3, comparing and analyzing the image data to be detected with a standard image database to obtain a detection result. As shown in fig. 5, specifically, step S3 includes:
s31, calling corresponding standard image data in a standard image database according to the image data to be detected; for example, the model of the current temperature sensor to be detected is obtained according to the image data to be detected, and the standard image data corresponding to the temperature sensor of the model is called; if the specific model of the current temperature sensor to be detected cannot be accurately obtained, calling standard image data of the temperature sensor with the similar model;
s32, comparing and analyzing the image data to be detected and the corresponding standard image data; specifically, when a collected image of the armored temperature sensor to be detected currently is obtained, or after image data to be detected is obtained through image processing, standard image data corresponding to the armored temperature sensor to be detected currently is called from a standard image database, and the current image data to be detected and the standard image data are compared and analyzed to obtain a detection result. Further, the standard image data corresponding to the currently-to-be-detected armored temperature sensor may be standard image data corresponding to the model of the currently-to-be-detected armored temperature sensor, or standard image data corresponding to the shape of the currently-to-be-detected armored temperature sensor, or standard image data corresponding to the related parameter of the currently-to-be-detected armored temperature sensor; the standard image data can comprise one or more groups, and preferably a group of standard image data corresponding to the type of the armored temperature sensor to be detected is called for comparative analysis; however, when the model of the currently-to-be-detected armored temperature sensor cannot be obtained, one or more groups of standard image data similar to the shape or related parameters of the currently-to-be-detected armored temperature sensor can be taken into consideration for comparison and analysis.
The standard image database comprises image data of different measuring positions of various armored temperature sensors, so that when contrastive analysis is performed, the X-ray detection system can respectively compare the image data of different measuring positions of the armored temperature sensor to be detected with corresponding standard image data according to the image data of different measuring positions of the armored temperature sensor to be detected currently, for example, if the model of the armored temperature sensor to be detected currently is A, the X-ray detection system obtains the image data to be detected of a first detection point of the armored temperature sensor to be detected currently, then the system can quickly screen out the standard image data corresponding to the temperature sensor with the model of A according to the model of the armored temperature sensor to compare the standard image data, and more specifically, the X-ray detection system can directly contrastively analyze the image data to be detected of the first detection point of the temperature sensor with the model of A stored in the standard image database in advance, so that high-efficiency quick detection is realized, and the workload of system contrastive analysis is reduced. As shown in fig. 7, in an embodiment, the X-ray detection system includes an X-ray generator, the detection position of the armored platinum thermistor temperature sensor to be detected is subjected to X-ray imaging by the X-ray generator, imaging acquisition and processing are performed, and quality screening of the sensor is completed by the visual contrast system.
In some embodiments, the nondestructive radiographic testing method for armored temperature sensors further comprises step S4 of constructing a computer neural network data set to train and test a standard image database.
Specifically, step S4 includes building based on a convolutional neural network algorithm, and the convolution kernel parameter sharing and sparsity of interlayer connection within the hidden layer of the convolutional neural network may enable the deep features of the input data to be automatically learned. Firstly, the normalization processing of standard images of various armored platinum thermal resistance temperature sensors is completed, two channels (black and white) are arranged, and a standard image is arranged to obtain standard image data. The characteristic diagram expression of the convolutional neural network is as follows:
wherein b is the deviation amount, Z l And Z l+1 Respectively representing convolution input and output of the l +1 th layer, K being the number of channels, s 0 F and p are convolution layer parameters, s 0 F is the convolution step length, f is the convolution kernel size, and p is the number of filling layers. Specifically, the number of K channels was set to 3, the number of p-filled layers was 2, the size of the convolution kernel was set to 5 × 5,s 0 The convolution step size is set to 4.
Pooling layer the Lp pooling model was used:
s 0 and pixel (i, j) is the same as the above convolutional layer parameter set, with p pre-specified parameter being 1.
According to the ray nondestructive detection method of the armored temperature sensor, the following conditions can be distinguished through contrast analysis:
1) Overlapping shadows and folds of the platinum wire ring;
2) The platinum coil has uneven turn-to-turn distance, as shown in FIG. 11;
3) The platinum coil, the signal lead or the armored platinum thermal resistor with the broken point open circuit of the welding spot.
The detection results of platinum wire resistance coils of different armored temperature sensors are as follows:
(1) As shown in fig. 8, the internal platinum coil of the qualified temperature sensor is clearly intact without overlapping or wrinkling.
(2) As shown in fig. 9, the internal platinum coil of the temperature sensor probe with fluctuating indication value has overlapping shadow and wrinkle phenomena, and the platinum coil may have turn-to-turn short circuit under tiny field vibration, which may cause short-time drop of the resistance value of the probe, thereby causing the temperature display to fluctuate for a short time. The reason for this is a defect in the manufacturing quality of the element of the sensor or excessive stretching during the manufacturing process of the sensor body.
(3) As shown in fig. 10, the platinum coil of the open-circuit temperature sensor also has overlapping shadows and wrinkles, which are obviously stretched, and easily causes excessive current density (electrical stress concentration) at the damaged portion, causing the resistance wire to be burned out and fused at the portion.
The invention solves the technical problems that potential quality weaknesses and hidden quality troubles of partial components are difficult to detect when the armored temperature sensor is manufactured by the existing process and quality control processing. The nuclear-grade temperature sensor has harsh working environment conditions and high quality requirements, and in the running process of the nuclear power station, because of the influence of harsh running conditions such as high temperature, irradiation, vibration and the like, the temperature sensor with quality weak points and potential quality hidden dangers develops into quality defects, and faults such as temperature sensor signal output fluctuation, open circuit and insulation resistance value lower than an acceptance value occur, so that internal running events (IOE) of the nuclear power station are caused. The invention aims to add X-ray nondestructive inspection detection and visual discrimination processes to the key process quality control or finished parts of the armored temperature sensor, detect the internal structure and quality hidden danger of an armored body under the condition of not damaging a metal structure, and control the quality hidden danger of the products before the temperature sensor leaves a factory. The invention can be applied to different-stage detection of the armored temperature sensor, wherein the different-stage detection comprises detection before manufacturing, detection after welding or assembling, finished product detection and the like; if the method is applied to detection before manufacturing, components with hidden quality troubles or defects can be eliminated, and the subsequent product rate is improved; if the method is applied to welding or detection after assembly, the method can be used for evaluating the welding process and the structural process effect; if the method is applied to finished product detection, the complete detection of the internal components of the armored temperature sensor can be realized, possible quality weaknesses and potential quality hidden dangers can be found, and the risks brought by equipment in the operation process of the nuclear power station can be reduced.
It should be understood that the above examples only represent the preferred embodiments of the present invention, and the description is specific and detailed, but not construed as limiting the scope of the present invention; it should be noted that, for those skilled in the art, the above technical features can be freely combined, and several changes and modifications can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention; therefore, all equivalent changes and modifications made within the scope of the claims of the present invention should be covered by the claims of the present invention.
Claims (10)
1. A ray nondestructive testing method of an armored temperature sensor, the method is characterized by comprising the following steps:
s1, establishing a standard image database of an armored temperature sensor;
s2, acquiring to-be-detected image data of an armored temperature sensor to be detected;
and S3, comparing and analyzing the image data to be detected with the standard image database to obtain a detection result.
2. The method for nondestructive radiographic testing of armored temperature sensors of claim 1 wherein said armored temperature sensors comprise a plurality of types of armored temperature sensors; the step S1 includes:
s11, acquiring corresponding ray energy value data according to parameters of the various armored temperature sensors;
s12, acquiring standard image data of the armored temperature sensor corresponding to the ray energy value data according to the ray energy value data;
s13, establishing the standard image database according to the parameters of the armored temperature sensors of various types, the corresponding ray energy value data and the standard image data.
3. The method for nondestructive radiographic testing of armored temperature sensors according to claim 2, wherein the parameters of the armored temperature sensors of the plurality of types include the model number of armored temperature sensors, the testing positions, and the wall thickness parameters of each of the testing positions.
4. The method for nondestructive radiographic testing of armored temperature sensors of claim 1 wherein said step S2 comprises:
s21, carrying out digital image acquisition on the armored temperature sensor to be detected through the ray detection system to obtain an acquired image;
s22, preprocessing the acquired image to obtain the image data to be detected.
5. The nondestructive radiographic testing method for armored temperature sensors of claim 4, wherein said step S21 comprises:
s211, setting a corresponding ray energy value according to the model, the detection position and the wall thickness parameter of the armored temperature sensor to be detected;
s212, the armored temperature sensors to be detected are driven to move, the detection positions are moved to the irradiation center of the ray transillumination field one by one, and then the image data to be detected of the detection positions are obtained.
6. The nondestructive radiographic inspection method for an armored temperature sensor according to claim 5, wherein the inspection positions include a first inspection point provided at a thermosensor of the armored temperature sensor, a second inspection point provided at an internal bonding site of the armored temperature sensor, a third inspection point provided at an internal lead of the armored temperature sensor, and/or a fourth inspection point provided at a signal lead and a bonding site of the armored temperature sensor.
7. The method for nondestructive radiographic testing of armored temperature sensors of claim 1 wherein said step S3 comprises:
s31, calling corresponding standard image data in the standard image database according to the image data to be detected;
and S32, comparing and analyzing the image data to be detected and the corresponding standard image data.
8. The method of nondestructive radiographic testing of an armored temperature sensor of claim 1, further comprising:
and S4, constructing a computer neural network data set to train and test the standard image database.
9. The method for nondestructive radiographic testing of armored temperature sensors of claim 8, wherein said step S4 specifically comprises constructing a computer neural network data set based on a convolutional neural network algorithm, and normalizing standard image data of various types of armored temperature sensors to train and test the standard image data set.
10. The radiation nondestructive testing method for armored temperature sensors of claim 9, wherein the characteristic diagram expression of the convolutional neural network is as follows:
(i,j)∈{0,1,…L l+1 }；
wherein b is the deviation amount, Z l And Z l+1 Respectively representing the convolution input and output of the l +1 th layer, K being the number of channels, s 0 F is the convolution step length, f is the convolution kernel size, and p is the number of filling layers.
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