Intelligent quality inspection method and platform for home textile products

Abstract

The invention discloses an intelligent quality inspection method and platform for home textile products, and relates to the related technical field of intelligent detection, and the method comprises the steps: obtaining an elastic material center of an elastic home textile product; a central infrared spectrum is obtained through the infrared transmitter and the infrared receiver. And reading a neighbor node strategy, and obtaining a neighbor node of the center node corresponding to the center of the elastic material according to the neighbor node strategy. Cooperative infrared detection is carried out on neighbor nodes through an infrared transmitter and an infrared receiver, and a neighbor infrared spectrum is obtained. Reading a spectrum feedback strategy, and analyzing the neighbor infrared spectrum and the center infrared spectrum according to the spectrum feedback strategy to obtain a target infrared spectrum. And comparing and analyzing the target infrared spectrum and a preset infrared spectrum to obtain the target aging degree of the elastic home textile product. The technical problems that in the prior art, a home textile product quality inspection method is high in quality inspection cost and low in quality inspection efficiency, and the quality condition of the whole home textile product cannot be comprehensively and accurately reflected are solved.

Description

Technical Field

[0001] The present application relates to the technical field related to intelligent detection, and specifically to an intelligent quality inspection method and platform for home textile products. Background Art

[0002] Home textile products are the most common products in daily life, and their performance directly affects the comfort of users. Traditional home textile product quality inspection methods mostly use manual inspection, visual inspection and local inspection, which have the problems of high quality inspection cost, low quality inspection efficiency, and failure to fully and accurately reflect the quality status of the entire home textile product.

[0003] Therefore, the quality inspection method for home textile products in the prior art has the technical problems of high quality inspection cost, low quality inspection efficiency, and failure to fully and accurately reflect the quality status of the entire home textile product. Summary of the invention

[0004] This application provides an intelligent quality inspection method and platform for home textile products, which solves the technical problems of high quality inspection cost, low quality inspection efficiency, and inability to fully and accurately reflect the quality status of the entire home textile product in the existing technology. Through infrared spectrum detection and polymerization analysis, the quality characteristics of home textile products can be fully detected, and the aging of products can be effectively evaluated by calculating the aging degree, realizing intelligent and comprehensive quality inspection, thereby fully and accurately reflecting the quality status of the entire home textile product, while improving the quality inspection efficiency and reducing the quality inspection cost.

[0005] The present application provides an intelligent quality inspection method for home textile products, the method comprising: obtaining the elastic material center of an elastic home textile product. Transmitting an infrared signal to the elastic material center through an infrared transmitter, and receiving the infrared signal through an infrared receiver to obtain a central infrared spectrum. Reading a neighbor node strategy, and obtaining a neighbor node of a central node corresponding to the elastic material center according to the neighbor node strategy. Performing collaborative infrared detection on the neighbor nodes through the infrared transmitter and the infrared receiver to obtain a neighbor infrared spectrum. Reading a spectral feedback strategy, and analyzing the neighbor infrared spectrum and the central infrared spectrum according to the spectral feedback strategy to obtain a target infrared spectrum. Comparing and analyzing the target infrared spectrum with a predetermined infrared spectrum to obtain a target aging degree of the elastic home textile product.

[0006] In an implementation, the first-level neighbor node of the central node is obtained according to the neighbor node strategy, wherein the first-level neighbor node includes multiple first-level nodes. A target first-level node is randomly extracted from the multiple first-level nodes, and a target first-level neighbor node of the target first-level node is obtained according to the neighbor node strategy. A second-level neighbor node is formed based on the target first-level neighbor node, wherein the second-level neighbor node includes multiple second-level nodes. The multiple first-level nodes and the multiple second-level nodes form the neighbor node.

[0007] In an implementation, the center coordinate of the center node is obtained. A first arbitrary coordinate of the elastic home textile product is randomly obtained, and the first arbitrary coordinate corresponds to a first arbitrary node. A first arbitrary distance is calculated based on the center coordinate and the first arbitrary coordinate. It is determined whether the first arbitrary distance is less than a first distance threshold. If it is less than, the first arbitrary node is added to the first-level neighbor node.

[0008] In an implementation, a second arbitrary coordinate of the elastic home textile product is randomly obtained, and the second arbitrary coordinate corresponds to a second arbitrary node. A second arbitrary distance is calculated according to the center coordinate and the second arbitrary coordinate. It is determined whether the second arbitrary distance is less than the first distance threshold. If it is less than, the first node spacing is calculated according to the second arbitrary coordinate and the first arbitrary coordinate. When the first node spacing is greater than the second distance threshold, the second arbitrary node is added to the first-level neighbor node.

[0009] In an implementation, a target first-level neighbor region of the target first-level node is obtained. A unit slice length is read, and the target first-level neighbor region is sliced ​​in combination with the unit slice length to obtain a target slice set, wherein the target slice set includes a plurality of slices. A first slice coordinate in a first slice is obtained, wherein the first slice coordinate corresponds to a first slice node. The target first-level neighbor node of the target first-level node is formed based on the first slice node.

[0010] In an implementation, a plurality of infrared spectra of the target first-level neighbor nodes are aggregated to obtain a first aggregate spectrum. The first aggregate spectrum is fused with the infrared spectrum of the target first-level node to obtain a target first-level node spectrum. The target first-level node spectrum is aggregated to obtain a central aggregate spectrum of the elastic material center. The central aggregate spectrum is used as the neighbor infrared spectrum.

[0011] In the implementation, according to the spectral feedback strategy, the first neighbor absorption peak of the neighbor infrared spectrum at the first time and the first central absorption peak of the central infrared spectrum are obtained in sequence. The first average absorption peak of the first neighbor absorption peak and the first central absorption peak is taken as the first target absorption peak at the first time. The target infrared spectrum is obtained by combining the first mapping relationship between the first time and the first target absorption peak.

[0012] In an implementation, a first absorption peak difference is obtained, where the first absorption peak difference refers to the difference between a first target absorption peak in the target infrared spectrum and a first predetermined absorption peak in the predetermined infrared spectrum. A first ratio of the first absorption peak difference to the first predetermined absorption peak is normalized to obtain a first aging degree. The first aging degrees are arranged in descending order to obtain an aging degree descending list, and the top aging degree in the aging degree descending list is used as the target aging degree.

[0013] This application also provides an intelligent quality inspection platform for home textile products, including:

[0014] The center extraction module is used to obtain the elastic material center of elastic home textile products.

[0015] The infrared spectrum acquisition module is used to transmit an infrared signal to the center of the elastic material through an infrared transmitter, and receive the infrared signal through an infrared receiver to obtain a central infrared spectrum.

[0016] The neighbor node acquisition module is used to read the neighbor node strategy and acquire the neighbor nodes of the center node corresponding to the center of the elastic material according to the neighbor node strategy.

[0017] The neighbor infrared spectrum acquisition module is used to perform cooperative infrared detection on the neighbor node through the infrared transmitter and the infrared receiver to obtain the neighbor infrared spectrum.

[0018] The target infrared spectrum acquisition module is used to read the spectrum feedback strategy, and analyze the neighbor infrared spectrum and the central infrared spectrum according to the spectrum feedback strategy to obtain the target infrared spectrum.

[0019] The aging degree acquisition module is used to compare and analyze the target infrared spectrum with a predetermined infrared spectrum to obtain a target aging degree of the elastic home textile product.

[0020] The present application proposes an intelligent quality inspection method and platform for home textile products, by obtaining the elastic material center of the elastic home textile product. An infrared transmitter transmits an infrared signal to the elastic material center, and an infrared receiver receives the infrared signal to obtain a central infrared spectrum. The neighbor node strategy is read, and the neighbor nodes of the elastic material center corresponding to the central node are obtained according to the neighbor node strategy. The neighbor nodes are subjected to coordinated infrared detection by the infrared transmitter and the infrared receiver to obtain a neighbor infrared spectrum. The spectrum feedback strategy is read, and the neighbor infrared spectrum and the central infrared spectrum are analyzed according to the spectrum feedback strategy to obtain a target infrared spectrum. The target infrared spectrum is compared and analyzed with the predetermined infrared spectrum to obtain the target aging degree of the elastic home textile product. The technical problems of the quality inspection method for home textile products in the prior art, such as high quality inspection cost, low quality inspection efficiency, and inability to comprehensively and accurately reflect the quality status of the entire home textile product, are solved. Through infrared spectroscopy detection and polymerization analysis, the quality characteristics of home textile products can be comprehensively tested, and the aging of products can be effectively evaluated by calculating the aging degree, realizing intelligent and comprehensive quality inspection, thereby comprehensively and accurately reflecting the quality status of the entire home textile products, while improving quality inspection efficiency and reducing quality inspection costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solution of the embodiment of the present disclosure, the accompanying drawings of the embodiment of the present disclosure are briefly introduced below. A flow chart is used in the present application to illustrate the operations performed by the platform according to the embodiment of the present application. It should be understood that the previous or following operations are not necessarily performed precisely in order. On the contrary, various steps can be processed in reverse order or simultaneously as needed. At the same time, other operations can also be added to these processes, or one or more operations can be removed from these processes.

[0022] Figure 1 A schematic diagram of a process flow of an intelligent quality inspection method for home textile products provided in an embodiment of the present application;

[0023] Figure 2 A schematic diagram of the structure of an intelligent quality inspection platform for home textile products provided in an embodiment of the present application.

[0024] Explanation of the reference numerals: center extraction module 11 , infrared spectrum acquisition module 12 , neighbor node acquisition module 13 , neighbor infrared spectrum acquisition module 14 , target infrared spectrum acquisition module 15 , aging degree acquisition module 16 . DETAILED DESCRIPTION

[0025] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0026] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0027] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, platform, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0028] The present application embodiment provides a method and platform for intelligent quality inspection of home textile products, such as Figure 1 As shown, the method includes:

[0029] The elastic material center of the elastic home textile product is obtained. An infrared transmitter transmits an infrared signal to the elastic material center, and an infrared receiver receives the infrared signal to obtain a central infrared spectrum. A neighbor node strategy is read, and a neighbor node of the elastic material center corresponding to the central node is obtained according to the neighbor node strategy.

[0030] The elastic material center of the elastic home textile product is obtained, and the elastic material center is the center position of the elastic material with elastic properties in the home textile product, such as the center position of latex or sponge. In general, the failure of elastic materials is uneven, and the elasticity of the middle part of the elastic material is more likely to fail. A pair of infrared transmitters and receivers are used to emit infrared light of a specific wavelength range to the center position of the elastic material. After the infrared light passes through or reflects the elastic material, the receiver captures the signal and generates infrared spectrum data to obtain the central infrared spectrum, which can represent the physical and chemical properties of the material at this position. Subsequently, the neighbor node strategy is read, and the neighbor node strategy is a distance-based node selection, which expands outward from the center node according to a preset distance interval such as 5cm, 10cm, and selects adjacent detection points. According to the neighbor node strategy, the neighbor node corresponding to the center node of the elastic material center is obtained. Exemplarily, at the elastic material center of the bedding, the neighbor node strategy spacing is set to 30cm, and several neighbor nodes will be automatically generated around the elastic material center of the bedding, such as 8 nodes may be selected around the center, and the coordinates of each node are determined based on the coordinate origin and physical size of the elastic material center of the bedding.

[0031] The method provided by the embodiment of the present application also includes: obtaining the first-level neighbor node of the central node according to the neighbor node strategy, wherein the first-level neighbor node includes multiple first-level nodes. Randomly extracting a target first-level node from the multiple first-level nodes, and obtaining the target first-level neighbor node of the target first-level node according to the neighbor node strategy. Based on the target first-level neighbor node, a second-level neighbor node is formed, wherein the second-level neighbor node includes multiple second-level nodes. The multiple first-level nodes and the multiple second-level nodes form the neighbor node.

[0032] The first-level neighbor nodes of the central node are obtained according to the neighbor node strategy, wherein the first-level neighbor nodes include multiple first-level nodes. Further, a target first-level node is randomly selected from the multiple first-level nodes, and then based on the neighbor node strategy, the target first-level node is used as the central node to determine the neighbor nodes of the target first-level node. Second-level neighbor nodes are formed based on the target first-level neighbor nodes, wherein the second-level neighbor nodes include multiple second-level nodes. Finally, the multiple first-level nodes and the multiple second-level nodes form the neighbor nodes. After obtaining the neighbor nodes, data will be obtained from these nodes to comprehensively test the overall performance of the material. By analyzing the entire node network, the system can identify whether there are quality problems in the mattress, such as aging or uneven materials.

[0033] The method provided in the embodiment of the present application also includes: obtaining the center coordinates of the center node. Randomly obtaining the first arbitrary coordinates of the elastic home textile product, the first arbitrary coordinates corresponding to the first arbitrary node. Calculating the first arbitrary distance according to the center coordinates and the first arbitrary coordinates. Determining whether the first arbitrary distance is less than a first distance threshold value. If less than, adding the first arbitrary node to the first-level neighbor node.

[0034] The center coordinates of the central node are obtained, wherein the center coordinates are the origin of the coordinates, and if the center nodes of the detection object are in the same plane, the center coordinates are two-dimensional coordinates. If the center nodes of the detection object are not in the same plane, the center coordinates are three-dimensional coordinates. The first arbitrary coordinates of the elastic home textile product are randomly obtained, and the first arbitrary coordinates are randomly selected to specify a detection point in the detection area of ​​the product, and the first arbitrary coordinates correspond to the first arbitrary node. Further, after the center coordinates and the first arbitrary coordinates are determined, the distance between the two is calculated by the distance calculation formula to obtain the first arbitrary distance, and the first arbitrary distance is the straight-line distance from the center coordinate to the first arbitrary coordinate. Further, it is determined whether the first arbitrary distance is less than the first distance threshold value, that is, the calculated first arbitrary distance is compared with the first distance threshold value, and the first distance threshold value is a preset distance limit value. When it is less than the distance, the corresponding first arbitrary node has a strong correlation with the center coordinate and is within the effective range of quality inspection. Exemplarily, in the above example, the first arbitrary distance obtained by calculation is 15.8cm. If the set first distance threshold value is 20cm, the system will determine that the distance is less than the threshold value. Therefore, the first arbitrary node is considered to be within the valid range. If it is less than, the first arbitrary node is added to the first-level neighbor node. In this way, the acquisition of the first-level neighbor node is random and is not affected by the neighbor node strategy, which further ensures the randomness of the acquisition of the detection point position.

[0035] The method provided in the embodiment of the present application also includes: randomly obtaining a second arbitrary coordinate of the elastic home textile product, the second arbitrary coordinate corresponding to a second arbitrary node. Calculating a second arbitrary distance based on the center coordinate and the second arbitrary coordinate. Determining whether the second arbitrary distance is less than the first distance threshold. If less than, calculating the first node spacing based on the second arbitrary coordinate and the first arbitrary coordinate. When the first node spacing is greater than the second distance threshold, adding the second arbitrary node to the first-level neighbor node.

[0036] Randomly obtain the second arbitrary coordinate of the elastic home textile product, the second arbitrary coordinate corresponds to the second arbitrary node. According to the center coordinate and the second arbitrary coordinate, calculate the second arbitrary distance. Further, determine whether the second arbitrary distance is less than the first distance threshold. If it is less than, calculate the first node spacing according to the second arbitrary coordinate and the first arbitrary coordinate, that is, obtain the node spacing between the second arbitrary coordinate and the first arbitrary coordinate through the distance calculation formula. When the first node spacing is greater than the second distance threshold, wherein the second distance threshold is the minimum value of the spacing between the pre-set nodes, when it is greater than the second distance threshold, the corresponding node distance meets the collection requirements, and the second arbitrary node is added to the first-level neighbor node. In this way, the acquisition of the first-level neighbor node is random and is not affected by the neighbor node strategy, which further ensures the randomness of the acquisition of the detection point position.

[0037] The method provided in the embodiment of the present application also includes: obtaining a target first-level neighbor region of the target first-level node. Reading a unit slice length, and slicing the target first-level neighbor region in combination with the unit slice length to obtain a target slice set, wherein the target slice set includes a plurality of slices. Obtaining a first slice coordinate in a first slice, wherein the first slice coordinate corresponds to a first slice node. The target first-level neighbor node of the target first-level node is formed based on the first slice node.

[0038] The target first-level neighbor area of ​​the target first-level node is obtained. The target first-level neighbor area of ​​the target first-level node refers to the area within a certain range around the node. The unit slice length is read. The unit slice length refers to the fixed length used when the target neighbor area is gridded. The entire target area is sliced ​​equidistantly according to this fixed length to form multiple small areas. The unit slice length can be set to an appropriate slice length according to the detection accuracy requirements of the product. For example, the unit slice length can be set to 5cm, indicating that the target neighbor area is divided into a 5cm grid. The target first-level neighbor area is sliced ​​in combination with the unit slice length to obtain a target slice set, and the target slice set includes multiple cut blocks. The first cut block coordinates in the first cut block are obtained. The first cut block refers to a cut block randomly selected from the cut block set. Each cut block has a center or representative point as the cut block coordinate. The first cut block coordinate is the center or representative point of the first cut block. The first cut block coordinate corresponds to the first cut block node. The target first-level neighbor node of the target first-level node is formed based on the first cut block node.

[0039] The infrared transmitter and the infrared receiver perform cooperative infrared detection on the neighbor nodes to obtain a neighbor infrared spectrum. The spectrum feedback strategy is read, and the neighbor infrared spectrum and the center infrared spectrum are analyzed according to the spectrum feedback strategy to obtain a target infrared spectrum. The target infrared spectrum is compared and analyzed with a predetermined infrared spectrum to obtain a target aging degree of the elastic home textile product.

[0040] The infrared transmitter and the infrared receiver are used to perform coordinated infrared detection on the neighbor nodes, obtain the spectrum of each node in the neighbor nodes, and process the spectrum to obtain the neighbor infrared spectrum. Read the spectrum feedback strategy, and analyze the neighbor infrared spectrum and the central infrared spectrum according to the spectrum feedback strategy to obtain the target infrared spectrum. Finally, the target infrared spectrum is compared and analyzed with the predetermined infrared spectrum to obtain the target aging degree of the elastic home textile product, wherein the predetermined infrared spectrum is the infrared spectrum of the elastic material benchmark of the elastic home textile product, that is, the infrared spectrum of the benchmark obtained by infrared spectrum collection at multiple collection points when the qualified product leaves the factory under the standard environment. Finally, the target infrared spectrum is compared and analyzed with the predetermined infrared spectrum to obtain the target aging degree of the elastic home textile product. The technical problems of the quality inspection method of home textile products in the prior art, such as high quality inspection cost, low quality inspection efficiency, and inability to fully and accurately reflect the quality status of the entire home textile product, are solved. Through infrared spectroscopy detection and polymerization analysis, the quality characteristics of home textile products can be comprehensively tested, and the aging of products can be effectively evaluated by calculating the aging degree, realizing intelligent and comprehensive quality inspection, thereby comprehensively and accurately reflecting the quality status of the entire home textile products, while improving quality inspection efficiency and reducing quality inspection costs.

[0041] The method provided by the embodiment of the present application also includes: aggregating multiple infrared spectra of the target first-level neighbor node to obtain a first aggregate spectrum. The first aggregate spectrum is fused with the infrared spectrum of the target first-level node to obtain a target first-level node spectrum. Aggregating the target first-level node spectrum to obtain a central aggregate spectrum of the elastic material center. The central aggregate spectrum is used as the neighbor infrared spectrum.

[0042] Aggregate multiple infrared spectra of the target first-level neighbor node to obtain a first aggregated spectrum, by acquiring multiple infrared spectrum data of the target first-level neighbor node and aggregating these spectra. The purpose of aggregation is to obtain a comprehensive spectrum representing the regional characteristics of these nodes by integrating the infrared spectra of multiple adjacent detection points. When aggregating, the absorption or reflection values ​​at the same wavelength of multiple spectra are averaged to form a new spectrum by using average value aggregation. Subsequently, the absorption or reflection values ​​at the same wavelength of multiple spectra are averaged by using average value aggregation, and the first aggregated spectrum is fused with the infrared spectrum of the target first-level node to obtain the target first-level node spectrum. Further, the target first-level node spectrum is aggregated to obtain a central aggregated spectrum of the center of the elastic material. Finally, the central aggregated spectrum is used as the neighbor infrared spectrum.

[0043] The method provided in the embodiment of the present application also includes: according to the spectral feedback strategy, sequentially obtaining the first neighbor absorption peak of the neighbor infrared spectrum and the first central absorption peak of the central infrared spectrum at the first time. Taking the first average absorption peak of the first neighbor absorption peak and the first central absorption peak as the first target absorption peak at the first time. Combining the first mapping relationship between the first time and the first target absorption peak to obtain the target infrared spectrum.

[0044] According to the spectral feedback strategy, the first neighbor absorption peak of the neighbor infrared spectrum at the first time and the first central absorption peak of the central infrared spectrum are obtained in sequence. The first average absorption peak of the first neighbor absorption peak and the first central absorption peak is taken as the first target absorption peak at the first time, that is, the average of the first neighbor absorption peak and the first central absorption peak is calculated to obtain the first target absorption peak, which is used to reflect the overall absorption characteristics of the entire detection area at the first time. Finally, the target infrared spectrum is obtained by combining the first mapping relationship between the first time and the first target absorption peak.

[0045] The method provided in the embodiment of the present application also includes: obtaining a first absorption peak difference, wherein the first absorption peak difference refers to the difference between the first target absorption peak in the target infrared spectrum and the first predetermined absorption peak in the predetermined infrared spectrum. Normalizing a first ratio of the first absorption peak difference to the first predetermined absorption peak to obtain a first aging degree. Arranging the first aging degrees in descending order to obtain a descending aging degree list, and taking the top aging degree in the descending aging degree list as the target aging degree.

[0046] Obtain a first absorption peak difference, which refers to the difference between the first target absorption peak in the target infrared spectrum and the first predetermined absorption peak in the predetermined infrared spectrum. The first absorption peak difference is calculated by comparing the target infrared spectrum with the predetermined infrared spectrum during the quality inspection process, and represents the difference between the actual state of the material and the ideal state. Among them, the predetermined infrared spectrum is the infrared spectrum of the elastic material benchmark of the elastic home textile product, that is, the infrared spectrum of the benchmark obtained by infrared spectrum collection of multiple collection points of qualified products under a standard environment when leaving the factory. Normalize the first ratio of the first absorption peak difference to the first predetermined absorption peak to obtain a first aging degree. Finally, the first aging degree is arranged in descending order to obtain an aging degree descending list, and the top aging degree in the aging degree descending list is used as the target aging degree, that is, the aging degree value with the highest ranking in the aging degree descending list is selected as the final target aging degree.

[0047] In the above, refer to Figure 1 A method for intelligent quality inspection of home textile products according to an embodiment of the present invention is described in detail. Figure 2 An intelligent quality inspection platform for home textile products according to an embodiment of the present invention is described. An intelligent quality inspection platform for home textile products according to an embodiment of the present invention solves the technical problems in the prior art of quality inspection methods for home textile products, such as high quality inspection cost, low quality inspection efficiency, and inability to fully and accurately reflect the quality status of the entire home textile product. Through infrared spectrum detection and aggregation analysis, the quality characteristics of home textile products can be fully detected, and the aging of the products can be effectively evaluated by calculating the aging degree, thereby realizing intelligent and comprehensive quality inspection, thereby fully and accurately reflecting the quality status of the entire home textile product, while improving the quality inspection efficiency and reducing the quality inspection cost. An intelligent quality inspection platform for home textile products includes: a center extraction module 11, an infrared spectrum acquisition module 12, a neighbor node acquisition module 13, a neighbor infrared spectrum acquisition module 14, a target infrared spectrum acquisition module 15, and an aging degree acquisition module 16.

[0048] The center extraction module 11 is used to obtain the elastic material center of the elastic home textile product.

[0049] The infrared spectrum acquisition module 12 is used to transmit an infrared signal to the center of the elastic material through an infrared transmitter, and receive the infrared signal through an infrared receiver to obtain a central infrared spectrum.

[0050] The neighbor node acquisition module 13 is used to read the neighbor node strategy and acquire the neighbor nodes of the center node corresponding to the center of the elastic material according to the neighbor node strategy.

[0051] The neighbor infrared spectrum acquisition module 14 is used to perform cooperative infrared detection on the neighbor node through the infrared transmitter and the infrared receiver to obtain the neighbor infrared spectrum.

[0052] The target infrared spectrum acquisition module 15 is used to read the spectrum feedback strategy, and analyze the neighbor infrared spectrum and the central infrared spectrum according to the spectrum feedback strategy to obtain the target infrared spectrum.

[0053] The aging degree acquisition module 16 is used to compare and analyze the target infrared spectrum with a predetermined infrared spectrum to obtain a target aging degree of the elastic home textile product.

[0054] The specific configuration of the neighbor node acquisition module 13 will be described in detail below. The neighbor node acquisition module 13 may further include: acquiring the first-level neighbor node of the central node according to the neighbor node strategy, wherein the first-level neighbor node includes multiple first-level nodes. Randomly extracting a target first-level node from the multiple first-level nodes, and acquiring the target first-level neighbor node of the target first-level node according to the neighbor node strategy. Forming a second-level neighbor node based on the target first-level neighbor node, wherein the second-level neighbor node includes multiple second-level nodes. The multiple first-level nodes and the multiple second-level nodes form the neighbor node.

[0055] The specific configuration of the neighbor node acquisition module 13 will be described in detail below. The neighbor node acquisition module 13 further includes: obtaining the center coordinates of the center node. Randomly obtaining the first arbitrary coordinates of the elastic home textile product, the first arbitrary coordinates corresponding to the first arbitrary node. According to the center coordinates and the first arbitrary coordinates, calculating the first arbitrary distance. Determine whether the first arbitrary distance is less than the first distance threshold. If less than, add the first arbitrary node to the first-level neighbor node.

[0056] Below, the specific configuration of the neighbor node acquisition module 13 will be described in detail. The neighbor node acquisition module 13 may further include: randomly acquiring a second arbitrary coordinate of the elastic home textile product, the second arbitrary coordinate corresponding to a second arbitrary node. Calculate a second arbitrary distance based on the center coordinate and the second arbitrary coordinate. Determine whether the second arbitrary distance is less than the first distance threshold. If less than, calculate the first node distance based on the second arbitrary coordinate and the first arbitrary coordinate. When the first node distance is greater than the second distance threshold, add the second arbitrary node to the first-level neighbor node.

[0057] The specific configuration of the neighbor node acquisition module 13 will be described in detail below. The neighbor node acquisition module 13 further includes: obtaining a target first-level neighbor area of ​​the target first-level node. Reading a unit slice length, and slicing the target first-level neighbor area in combination with the unit slice length to obtain a target slice set, wherein the target slice set includes a plurality of slices. Obtaining a first slice coordinate in a first slice, wherein the first slice coordinate corresponds to a first slice node. Assembling the target first-level neighbor node of the target first-level node based on the first slice node.

[0058] The specific configuration of the neighbor infrared spectrum acquisition module 14 will be described in detail below. The neighbor infrared spectrum acquisition module 14 further includes: aggregating multiple infrared spectra of the target first-level neighbor node to obtain a first aggregate spectrum. The first aggregate spectrum is fused with the infrared spectrum of the target first-level node to obtain a target first-level node spectrum. Aggregating the target first-level node spectrum to obtain a central aggregate spectrum of the elastic material center. The central aggregate spectrum is used as the neighbor infrared spectrum.

[0059] The specific configuration of the neighbor infrared spectrum acquisition module 14 will be described in detail below. The neighbor infrared spectrum acquisition module 14 further includes: according to the spectrum feedback strategy, sequentially acquiring the first neighbor absorption peak of the neighbor infrared spectrum at the first time and the first central absorption peak of the central infrared spectrum. Taking the first average absorption peak of the first neighbor absorption peak and the first central absorption peak as the first target absorption peak at the first time. Combining the first mapping relationship between the first time and the first target absorption peak to obtain the target infrared spectrum.

[0060] The specific configuration of the aging degree acquisition module 16 will be described in detail below. The aging degree acquisition module 16 further includes: acquiring a first absorption peak difference, wherein the first absorption peak difference refers to the difference between the first target absorption peak in the target infrared spectrum and the first predetermined absorption peak in the predetermined infrared spectrum. Normalizing the first ratio of the first absorption peak difference to the first predetermined absorption peak to obtain a first aging degree. Arranging the first aging degrees in descending order to obtain an aging degree descending list, and taking the top aging degree in the aging degree descending list as the target aging degree.

[0061] An intelligent quality inspection platform for home textile products provided in an embodiment of the present invention can execute an intelligent quality inspection method for home textile products provided in any embodiment of the present invention, and has functional modules and beneficial effects corresponding to the execution method.

[0062] Although the present application makes various references to certain modules in the platform according to the embodiments of the present application, any number of different modules can be used and run on the user terminal and / or the server, and the various units and modules included are only divided according to functional logic, but are not limited to the above divisions, as long as the corresponding functions can be achieved. In addition, the specific names of the functional units are only for the convenience of distinguishing from each other and are not used to limit the scope of protection of the present invention.

[0063] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. An intelligent quality inspection method for home textile products, characterized in that: include: Get the Elastic Materials Center for Elastic Home Textile Products; Transmitting an infrared signal to the center of the elastic material through an infrared transmitter, and receiving the infrared signal through an infrared receiver to obtain a central infrared spectrum; Reading a neighbor node strategy, and obtaining a neighbor node of a center node corresponding to the center of the elastic material according to the neighbor node strategy; Performing cooperative infrared detection on the neighboring nodes by using the infrared transmitter and the infrared receiver to obtain a neighboring infrared spectrum; Reading a spectrum feedback strategy, and analyzing the neighbor infrared spectrum and the center infrared spectrum according to the spectrum feedback strategy to obtain a target infrared spectrum; The target infrared spectrum is compared and analyzed with a predetermined infrared spectrum to obtain a target aging degree of the elastic home textile product.

2. According to claim 1, a method for intelligent quality inspection of home textile products is characterized in that: include: Acquire a first-level neighbor node of the central node according to the neighbor node strategy, wherein the first-level neighbor node includes a plurality of first-level nodes; Randomly extracting a target first-level node from the multiple first-level nodes, and acquiring a target first-level neighbor node of the target first-level node according to the neighbor node strategy; Forming a second-level neighbor node based on the target first-level neighbor node, wherein the second-level neighbor node includes a plurality of second-level nodes; The plurality of primary nodes and the plurality of secondary nodes constitute the neighboring nodes.

3. According to claim 2, a method for intelligent quality inspection of home textile products is characterized in that: include: Obtaining the center coordinates of the central node; Randomly acquiring a first arbitrary coordinate of the elastic home textile product, where the first arbitrary coordinate corresponds to a first arbitrary node; Calculating a first arbitrary distance according to the center coordinates and the first arbitrary coordinates; Determining whether the first arbitrary distance is less than a first distance threshold; If it is less than, add the first arbitrary node to the first-level neighbor node.

4. According to claim 3, a smart quality inspection method for home textile products is characterized in that: include: Randomly acquiring a second arbitrary coordinate of the elastic home textile product, where the second arbitrary coordinate corresponds to a second arbitrary node; Calculating a second arbitrary distance according to the center coordinates and the second arbitrary coordinates; Determining whether the second arbitrary distance is less than the first distance threshold; If it is less than, calculating the first node distance according to the second arbitrary coordinate and the first arbitrary coordinate; When the first node distance is greater than a second distance threshold, the second arbitrary node is added to the first-level neighbor node.

5. According to claim 2, a method for intelligent quality inspection of home textile products, characterized in that: include: Obtain a target first-level neighbor area of ​​the target first-level node; Reading a unit slice length, and slicing the target first-level neighbor region in combination with the unit slice length to obtain a target slice set, wherein the target slice set includes a plurality of slices; Obtaining a first slice coordinate in a first slice, wherein the first slice coordinate corresponds to a first slice node; The target first-level neighbor node of the target first-level node is established based on the first slice node.

6. The intelligent quality inspection method for home textile products according to claim 1, characterized in that: include: Aggregating multiple infrared spectra of the target first-level neighbor node to obtain a first aggregated spectrum; The first aggregate spectrum is fused with the infrared spectrum of the target primary node to obtain a target primary node spectrum; Aggregating the target primary node spectrum to obtain a central aggregate spectrum of the elastic material center; The central aggregate spectrum is taken as the neighbor infrared spectrum.

7. The intelligent quality inspection method for home textile products according to claim 6, characterized in that: include: According to the spectral feedback strategy, sequentially obtaining a first neighbor absorption peak of the neighbor infrared spectrum and a first central absorption peak of the central infrared spectrum at a first time; Taking a first average absorption peak value of the first neighbor absorption peak value and the first center absorption peak value as a first target absorption peak value at the first time; The target infrared spectrum is obtained by combining a first mapping relationship between the first time and the first target absorption peak.

8. The intelligent quality inspection method for home textile products according to claim 1, characterized in that: include: Obtaining a first absorption peak difference, where the first absorption peak difference refers to a difference between a first target absorption peak in the target infrared spectrum and a first predetermined absorption peak in the predetermined infrared spectrum; Normalizing a first ratio of the first absorption peak difference to the first predetermined absorption peak value to obtain a first aging degree; The first aging degrees are arranged in descending order to obtain an aging degree descending list, and the top aging degree in the aging degree descending list is used as the target aging degree.

9. An intelligent quality inspection platform for home textile products, characterized in that: The platform is used to execute the method according to any one of claims 1 to 8, comprising: A center extraction module for obtaining the elastic material center of elastic home textile products; An infrared spectrum acquisition module, used for transmitting an infrared signal to the center of the elastic material through an infrared transmitter, and receiving the infrared signal through an infrared receiver to obtain a central infrared spectrum; A neighbor node acquisition module, used for reading a neighbor node strategy, and acquiring a neighbor node of a center node corresponding to the center of the elastic material according to the neighbor node strategy; A neighbor infrared spectrum acquisition module is used to perform cooperative infrared detection on the neighbor node through the infrared transmitter and the infrared receiver to obtain the neighbor infrared spectrum; A target infrared spectrum acquisition module is used to read the spectrum feedback strategy, and analyze the neighbor infrared spectrum and the center infrared spectrum according to the spectrum feedback strategy to obtain a target infrared spectrum; The aging degree acquisition module is used to compare and analyze the target infrared spectrum with a predetermined infrared spectrum to obtain a target aging degree of the elastic home textile product.

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