Loom operation and maintenance data encryption system and loom equipment with same

Abstract

The invention relates to the technical field of loom equipment data encryption protection. The invention provides a loom operation and maintenance data encryption system and loom equipment with the system, and the system comprises a data collection module which collects operation and maintenance data of the loom equipment, associates the operation and maintenance data with a process knowledge base, and distributes a process sensitivity weight for each piece of operation and maintenance data based on the predefined process knowledge base; the multi-stage encryption module is used for selecting a corresponding high-strength encryption algorithm or low-overhead encryption algorithm according to the process sensitivity weight of the operation and maintenance data; generating a fault diagnosis key segment based on the association between the operation and maintenance data and a process knowledge base, and binding the fault diagnosis key segment with a state sensor of a physical component in the loom equipment; and the secret key triggering module is used for authorizing a fault diagnosis secret key fragment to a specified maintenance terminal according to the state signal generated by the loom equipment and the real-time state sensor data of the physical component when the state signal and the real-time state sensor data meet release conditions, and carrying out local decryption on the operation and maintenance data.

Description

Technical Field

[0001] The embodiments of the present invention generally relate to the field of data encryption and protection technology for loom equipment, and particularly to a loom operation and maintenance data encryption system and a loom equipment having the system. Background Technology

[0002] As core equipment supporting efficient production in the textile industry, looms collect and generate massive amounts of operational data in real time during continuous operation. This data includes not only core equipment operation indicators such as spindle speed, weft density control parameters, and weft insertion tension, but also crucial information such as pattern design documents and process parameter configurations that directly determine product quality. From an industry value perspective, this data is not only the core data support for real-time monitoring of equipment operation status, fault early warning, and precise optimization of production processes, but also a carrier of core intellectual property rights and trade secrets that embody a company's exclusive production technology and market competitive advantage, possessing extremely high economic and technological protection value. However, in current practice, loom data security protection systems generally suffer from insufficient refinement of protection strategies, with most companies still using a single encryption strength algorithm to homogenize the encryption of all operational data. This lack of differentiated protection model fails to fully meet the core needs of data value hierarchy classification. On the one hand, it leads to excessive use of encryption computing resources for non-core operation and maintenance data, resulting in ineffective consumption of system computing resources. On the other hand, for high-value core process data, the lack of targeted design of encryption schemes makes it difficult to form a protection strength that meets its security requirements. Ultimately, it is difficult to effectively build a dynamic balance between data security and production efficiency.

[0003] To address these contradictions, existing technologies have explored various optimizations. For example, they have developed differentiated encryption algorithms based on data classification and grading results, dynamically adjusting encryption strength to achieve precise resource allocation; or introduced key fragmentation management technology, splitting and storing core keys across different security nodes to enhance the keys' resistance to attacks. These technological improvements have, to some extent, compensated for the shortcomings of traditional protection models, effectively improving the flexibility and overall reliability of data protection. However, existing solutions still have significant limitations. The core issue is that most solutions only optimize strategies at the software logic layer. Key generation mechanisms, storage architectures, access control, and dynamic release processes fail to establish deep correlation and coordinated control with the real-time physical operating status of the loom, such as equipment operating mode, fault level, and maintenance authorization status. This design flaw directly leads to real-world challenges in operation and maintenance scenarios: when a loom experiences a sudden malfunction and requires urgent retrieval of historical data for fault diagnosis, either the cumbersome key authorization process and lengthy approval chain delay the best repair opportunity, affecting production continuity; or, to simplify the repair operation process, a backdoor key with permanent permissions is pre-set, and if such a key is mismanaged, it can easily become a major security vulnerability in the data security system, ultimately making it difficult to achieve an organic unity between data security protection and operation and maintenance efficiency. Summary of the Invention

[0004] To address the above issues, this invention intelligently assesses data value through a process knowledge base and performs adaptive hierarchical encryption, effectively overcoming the resource waste and insufficient protection caused by traditional single encryption methods, and ensuring that security investment is precisely matched to the importance of the data.

[0005] According to an embodiment of the present invention, a loom maintenance data encryption system and a loom device having the system are provided.

[0006] In a first aspect of the present invention, a loom maintenance data encryption system is provided. The system includes: Data acquisition module: Collects operation and maintenance data of loom equipment and associates it with the process knowledge base, and assigns process sensitivity weights to each piece of operation and maintenance data based on the predefined process knowledge base; Multi-level encryption module: Selects the corresponding high-strength encryption algorithm or low-overhead encryption algorithm according to the process sensitivity weight of the operation and maintenance data; generates fault diagnosis key fragments based on the association between operation and maintenance data and process knowledge base, and binds the fault diagnosis key fragments to the status sensors of physical components in the loom equipment; Key triggering module: Based on the status signals generated by the loom equipment and the real-time status sensor data of the physical components, when both meet the release conditions, the fault diagnosis key fragment is authorized to the designated maintenance terminal to partially decrypt the operation and maintenance data.

[0007] Furthermore, the operation and maintenance data mentioned in the data acquisition module includes: Motion parameters: real-time spindle speed measured by the spindle encoder, and real-time weft density measured by the fabric density sensor; Mechanical parameters: Real-time tension values ​​of warp and weft yarns measured by pressure sensors; Electrical parameters: Real-time operating current of the main motor acquired through a current sensor; Process parameters: The core process recipe code being run, read directly from the controller.

[0008] Furthermore, the process knowledge base in the multi-level encryption module is used to store the mapping relationship between different operation and maintenance data items and the core process parameters and health status of the loom. The process knowledge base provides a mapping relationship for each operation and maintenance data item. Calculate a process sensitivity weight with a value between 0 and 1. , is represented as: , in, The mapping function represents the relationship between maintenance data items and core process parameters, and between maintenance data items and equipment health status. The process knowledge base defines the qualitative and quantitative relationships between different maintenance data and the core process parameters and health status of the loom. The specific rules are as follows: Mapping of core process parameters: used to define the relationship between operation and maintenance data items and key process outputs; Device health status mapping: used to define the association between maintenance data items and device operating status.

[0009] Furthermore, the selection of the high-strength encryption algorithm or the low-overhead encryption algorithm in the multi-level encryption module is based on a decision function, with a preset configurable weight threshold. For each piece of operational data The encryption process is determined by the assigned process sensitivity weights. The decision is based on this definition of the decision function, expressed as: , in, Indicates the first The ciphertext obtained after encrypting the operation and maintenance data; and These represent the symmetric keys corresponding to high-strength encryption algorithms and low-overhead encryption algorithms, respectively, and are securely generated and rotated by the key management service. and These represent high-strength encryption algorithms and low-overhead encryption algorithms, respectively. This indicates the preset weight threshold.

[0010] Furthermore, the step of generating the fault diagnosis key fragment in the multi-level encryption module is as follows: In a finite field Above is the operation and maintenance data. The encrypted ciphertext generates a master secret. The master secret is conceptually equivalent to the decryption key itself, or a master key strongly associated with the decryption key; Build a A polynomial of degree n is expressed as: , in, Represents a polynomial function; Represents the coefficients of a polynomial; This represents the constant term, which is also the master secret that needs to be split. ,Right now ; The independent variable of a function is represented by giving... Different values ​​are assigned to generate different key fragments; This represents the threshold value, which indicates the required threshold value. The master secret is recovered from the key fragments, and the degree of the polynomial is designed to be... That is, to uniquely determine one A polynomial of degree at least requires One point; This means that all operations are performed modulo 1. Performed on a finite field, It is a large prime number; The fault diagnosis key fragment and the master key fragment are generated based on the polynomial function. There is one fault diagnosis key fragment, and the number of master key fragments is determined according to the threshold value.

[0011] Furthermore, the fault diagnosis key fragment is bound to the status sensor of the physical component through a secure binding tuple. The secure binding tuple stores complete binding information, namely: a unique identifier for the fault diagnosis key fragment; a globally unique identifier for the status sensor on the physical component; and a cryptographic commitment for the hiding, binding, and verification mechanism.

[0012] Furthermore, the status signal generated by the loom equipment in the key triggering module is a global fault status signal collected by the loom control sensor. The physical component's state sensor data outputs a physical state signal, and the release condition is a logical composite function, expressed as: , in, Real-time data from sensors indicating the status of physical components; Indicating targeting The exception handling function, when Return when the exception condition is met. According to the aforementioned logical composition function, if and only if for When this occurs, initiate the fault diagnosis key fragment authorization process; The authorization process is as follows: Send the master key fragment to the designated maintenance terminal via a secure link; Send an authorization request to the multi-level encryption module to request the release of the fault diagnosis key fragment; The multi-level encryption module queries the secure binding tuple, performs release verification through the cryptographic commitment, and after verification, authorizes the fault diagnosis key fragment to the designated maintenance terminal. The maintenance terminal reconstructs the complete master secret using Lagrange interpolation based on the fault diagnosis key fragment and the master key fragment, and finally uses the reconstructed master secret for decryption. In a second aspect of the invention, a weaving machine is provided. The weaving machine includes: The machine includes a frame, support components, a weft insertion assembly, a needle bed assembly, a warp feed assembly, a dust removal assembly, a control cabinet assembly, and a process sensing assembly. The weft insertion assembly, the needle bed assembly, the warp feed assembly, and the dust removal assembly are fixedly installed inside the frame. The weft insertion assembly is installed above the needle bed assembly. The process sensing assembly is fixedly installed on the top of the weft insertion assembly. The warp feed assembly is installed in front of the needle bed assembly. The dust removal assembly is installed above the warp feed assembly. Four support components are installed at the four corners of the frame. The control cabinet assembly is fixedly installed on one side of the frame. The control cabinet assembly integrates electrical sensing components, a controller, and the loom operation and maintenance data encryption system. The process sensing component includes a fabric density sensor, a fabric defect sensor, and a fabric width sensor, and the process sensing component is connected to the control cabinet component. The feeding assembly includes a feeding table, a groove, a mounting bracket, and a motion sensing component. The groove is located at the upper end of the feeding table and is evenly distributed along its direction at the upper end of the feeding table. The mounting bracket is fixedly installed above the rear end of the feeding table. The motion sensing component is fixedly installed on the top of the mounting bracket, and its lower end is arc-shaped. The motion sensing component includes a displacement sensor, a pressure sensor, and a Hall sensor, and is connected to the control cabinet assembly.

[0013] Further, the dust removal assembly includes a horizontal plate, an ion fan, a first connecting pipe, a nozzle, a dust collection box, an exhaust fan, a second connecting pipe, a first cavity, a second cavity, and a perforated mesh plate. The first cavity is disposed inside the horizontal plate. The nozzle is fixedly installed below the horizontal plate and communicates with the first cavity. The nozzles are evenly distributed along the direction below the horizontal plate and are inclined. The ion fan is fixedly installed on one side of the frame. The first connecting pipe is installed between the ion fan and the horizontal plate. The second cavity is disposed inside the horizontal plate and is parallel to the first cavity. The perforated mesh plate is fixedly installed at the lower end of the horizontal plate and at the bottom of the second cavity. The dust collection box and the exhaust fan are fixedly installed on one side of the frame and communicate with each other. The second connecting pipe is installed between the dust collection box and the horizontal plate. The ion fan and the exhaust fan are electrically connected to the control cabinet assembly.

[0014] Furthermore, the support assembly includes a connecting column, a rubber seat, a nut, and a telescopic cavity. The upper end of the connecting column is fixedly connected to the frame, the nut is fixedly installed on the upper end of the rubber seat, and the telescopic cavity is provided at the center of the upper end of the rubber seat. The inner diameter of the telescopic cavity is larger than the diameter of the connecting column, and the connecting column and the nut are connected by a through thread.

[0015] This invention intelligently assesses the value of data through a process knowledge base and performs adaptive hierarchical encryption, effectively overcoming the resource waste and insufficient protection caused by traditional single encryption methods, and ensuring that security investment is precisely matched with the importance of the data.

[0016] It should be understood that the description in the Summary of the Invention is not intended to limit the key or essential features of the embodiments of the present invention, nor is it intended to restrict the scope of the invention. Other features of the invention will become readily apparent from the following description.

[0017] The beneficial effects of this invention are: 1. The loom maintenance data encryption system of the present invention can achieve reliable encryption protection of maintenance data. By intelligently evaluating the value of data through a process knowledge base and completing adaptive hierarchical encryption, it effectively overcomes the resource waste and insufficient protection caused by traditional single encryption methods, allowing security investment to accurately match the importance of data. At the same time, the system binds fault diagnosis key fragments to the sensor status of physical components, making key release dependent on the actual physical status of the equipment. This not only prevents malicious triggering that pure software logic may encounter, but also enables rapid authorization in the event of a real equipment failure, balancing security and maintenance efficiency. With the dual verification mechanism of loom equipment status signals and physical component sensor data, it ensures that specific maintenance data is only temporarily accessed when the equipment experiences a specific, verifiable fault, achieving the security goal of "strict prevention under normal conditions and controllable faults." This fundamentally solves the contradiction between security and maintenance convenience, and the master key fragment can be sent to a designated maintenance terminal through a secure link, further ensuring data security and reliability.

[0018] 2. This invention, through the coordinated arrangement of motion sensing components, process sensing components, and control cabinet components, can comprehensively collect multi-dimensional operational data such as yarn movement distance, tension, conveying speed, fabric density, surface defects, width, and loom motor speed, temperature, current, and voltage. The control cabinet component, as the control core, accurately analyzes, processes, and adjusts the loom's operating parameters based on this data, enabling each component to work efficiently under its unified coordination, ensuring a stable and controllable weaving process. Simultaneously, the dust removal component generates an ionized airflow through an ion fan, which is blown onto the yarn through an inclined nozzle, effectively removing dust adhering to the yarn and eliminating static electricity. Combined with an exhaust fan, the dust-laden air is sucked into the dust collection box, effectively maintaining a clean operating environment for the equipment and reducing the impact of impurities and static electricity on weaving quality. Attached Figure Description

[0019] The above and other features, advantages, and aspects of the various embodiments of the present invention will become more apparent from the accompanying drawings and the following detailed description. Wherein: Figure 1 A schematic diagram of a loom maintenance data encryption system according to Embodiment 1 of the present invention is shown; Figure 2 A schematic diagram of a data acquisition module according to Embodiment 1 of the present invention is shown; Figure 3 A schematic diagram of a multi-level encryption module according to Embodiment 1 of the present invention is shown; Figure 4 A schematic diagram of the structure of a loom according to Embodiment 2 of the present invention is shown; Figure 5 A schematic diagram of the weft insertion assembly structure according to Embodiment 2 of the present invention is shown; Figure 6 A schematic diagram of the needle bed assembly structure according to Embodiment 2 of the present invention is shown; Figure 7 A schematic diagram showing the connection relationship between the motion sensing component and the feeding table according to Embodiment 2 of the present invention is shown; Figure 8 A schematic diagram showing the connection relationship between the horizontal plate, the ion fan, and the exhaust fan according to Embodiment 2 of the present invention is shown. Figure 9 A schematic diagram showing the connection relationship between the nozzle and the perforated mesh plate and the horizontal plate according to Embodiment 2 of the present invention is shown; Figure 10 A schematic diagram showing the connection relationship between the connecting column and the rubber seat according to Embodiment 2 of the present invention is shown. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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.

[0021] According to an embodiment of the present invention, a loom operation and maintenance data encryption system and a loom equipped with the system are proposed. The system intelligently evaluates the value of data through a process knowledge base and performs adaptive hierarchical encryption, effectively overcoming the resource waste and insufficient protection caused by traditional single encryption methods, and ensuring that security investment is precisely matched with the importance of data.

[0022] The principles and spirit of the present invention will be explained in detail below with reference to several representative embodiments.

[0023] Figure 1 This is a schematic diagram of a loom maintenance data encryption system according to an embodiment of the present invention. The system includes: Data acquisition module: Collects operation and maintenance data of loom equipment and associates it with the process knowledge base, and assigns process sensitivity weights to each piece of operation and maintenance data based on the predefined process knowledge base; Multi-level encryption module: Selects the corresponding high-strength encryption algorithm or low-overhead encryption algorithm according to the process sensitivity weight of the operation and maintenance data; generates fault diagnosis key fragments based on the association between operation and maintenance data and process knowledge base, and binds the fault diagnosis key fragments to the status sensors of physical components in the loom equipment; Key triggering module: Based on the status signals generated by the loom equipment and the real-time status sensor data of the physical components, when both meet the release conditions, the fault diagnosis key fragment is authorized to the designated maintenance terminal to partially decrypt the operation and maintenance data.

[0024] It should be noted that although the operation of the method of the present invention has been described in a specific order in the above embodiments and figures, this does not require or imply that the operations must be performed in that specific order, or that all the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0025] To provide a clearer explanation of the above-mentioned loom maintenance data encryption system, two specific embodiments are described below. However, it is worth noting that these embodiments are only for better illustrating the present invention and do not constitute an improper limitation of the present invention.

[0026] The following two specific examples will further illustrate the loom maintenance data encryption system and the loom equipment equipped with this system in more detail: Example 1: This embodiment discloses a loom maintenance data encryption system, which includes: Data acquisition module: Collects operation and maintenance data of the loom equipment and associates it with the process knowledge base, and assigns a process sensitivity weight to each piece of operation and maintenance data based on the predefined process knowledge base. For example... Figure 2 As shown.

[0027] Operation and maintenance data refers to data closely related to the production process, operating parameters, and technological operation of looms. This data reflects the working status and operating efficiency of the looms. Specifically, operation and maintenance data includes the following categories: Motion parameters: real-time spindle speed measured by the spindle encoder, and real-time weft density measured by the fabric density sensor; Mechanical parameters: Real-time tension values ​​of warp and weft yarns measured by pressure sensors; Electrical parameters: Real-time operating current of the main motor acquired through a current sensor; Process parameters: Core process recipe codes that are currently in operation, read directly from the controller, such as pattern files, density preset sequences, etc.

[0028] The raw data streams collected typically contain noise and outliers, which can affect the accuracy of subsequent analysis if used directly. Therefore, a data preprocessing workflow is required, specifically: 1. Data cleaning: Employ threshold-based filtering algorithms to identify and remove physically impossible outliers; 2. Format standardization: Data from different data sources with different units and sampling frequencies are uniformly converted into an internally defined standardized format and units, and timestamps are synchronized to ensure that all data can be correlated and analyzed under a unified time base.

[0029] The process knowledge base stores the mapping relationship between different operation and maintenance data items and the core process parameters and health status of the loom. Each piece of operation and maintenance data after preprocessing is sent to the predefined process knowledge base for evaluation to determine the process sensitivity weight. This weight is a value between 0 and 1, which quantifies the degree of process coreness and commercial value contained in the operation and maintenance data.

[0030] In this embodiment, the process knowledge base is an expert system containing a series of IF-THEN rules or a classification model trained on historical operation and maintenance data. The knowledge system is constructed based on the experience of textile process experts and a large amount of historical operation and maintenance data. The process knowledge base clearly defines the qualitative and quantitative relationships between different operation and maintenance data and the core process parameters of the loom and the health status of the equipment. The specific rules are as follows: Mapping of core process parameters: Defines the relationship between operation and maintenance data items and key process outputs. For example, the weft density data item of motion parameters is mapped to the core process parameters that directly affect product quality, and the pattern file code data item of process parameters is mapped to the core process parameters that determine the fabric pattern. Equipment health status mapping: Defines the association between maintenance data items and equipment operating status. For example, the main motor current characteristic data item of electrical parameters is mapped to an equipment health status index that reflects the wear degree of motor bearings.

[0031] Based on the above mapping relationship, the process knowledge base provides each piece of operation and maintenance data. Calculate a process sensitivity weight This weight is a value between 0 and 1, and the calculation logic strictly follows the importance of the above mapping, expressed as: , in, The mapping function represents the relationship between maintenance data items and core process parameters, and between maintenance data items and equipment health status. In this embodiment, maintenance data directly corresponds to core process parameters, and its disclosure could lead to the replication of core processes. Given high weight Such as pattern file code and precise weft density settings.

[0032] Ultimately, the data acquisition module outputs structured data tuples with precise process sensitivity weights, providing a core basis for subsequent modules to execute differentiated security strategies.

[0033] Multi-level encryption module: Based on the process sensitivity weight of the operation and maintenance data, selects the corresponding high-strength encryption algorithm or low-overhead encryption algorithm; based on the association between the operation and maintenance data and the process knowledge base, generates fault diagnosis key fragments, and binds the fault diagnosis key fragments to the status sensors of physical components in the loom equipment. For example... Figure 3 As shown.

[0034] This module is the core of implementing hierarchical data security protection and controllable fault diagnosis. It receives operation and maintenance data tuples with process sensitivity weights from the data acquisition module and performs two levels of security processing: weight-based adaptive encryption, and key segmentation and physical binding for core data.

[0035] High-strength encryption algorithm High computational strength, resistant to side-channel and quantum attacks, such as those based on AES-256-GCM mode; low-overhead encryption algorithms. Suitable for resource-constrained environments while maintaining a certain level of security, such as PRESENT-80.

[0036] The choice between high-strength and low-overhead encryption algorithms is based on a decision function with a preset configurable weight threshold. For each piece of operational data The encryption process is determined by the assigned process sensitivity weights. The decision is based on this definition of the decision function, expressed as: , in, Indicates the first The ciphertext obtained after encrypting the operation and maintenance data; and These represent the symmetric keys corresponding to high-strength encryption algorithms and low-overhead encryption algorithms, respectively, and are securely generated and rotated by the key management service. and These represent high-strength encryption algorithms and low-overhead encryption algorithms, respectively. This indicates the preset weight threshold.

[0037] The decision function achieves security performance optimization at the cryptographic level. By precisely matching encryption strength with data value, it ensures that high-value operation and maintenance data enjoys the highest level of confidentiality protection, while effectively maintaining the computational efficiency of the entire system at the edge and avoiding resource waste.

[0038] In the encryption process, in addition to the regular encryption operations, the multi-level encryption module also needs to generate fault diagnosis key fragments for specific operation and maintenance data. The generation of these key fragments is to enable maintenance personnel to decrypt relevant key operation and maintenance data for fault diagnosis when a loom equipment malfunctions.

[0039] Targeting the satisfaction Furthermore, the process knowledge base contains operation and maintenance data directly related to the core process parameters of the loom. The enhanced security protocol is initiated, generating a fault diagnosis key fragment; this protocol is based on the Shamir secret sharing scheme and operates within a finite domain. Above, one Threshold secret sharing scheme through a The secret is partitioned using a polynomial of degree 1. The specific generation process is as follows: 1. In a finite field Above is the operation and maintenance data. The encrypted ciphertext generates a master secret. The master secret is conceptually equivalent to the decryption key itself, or a master key strongly associated with the decryption key; 2. Build a A polynomial of degree n is expressed as: , in, Represents a polynomial function; The coefficients of a polynomial are numbers randomly selected when the polynomial is created. This represents the constant term, which is also the master secret that needs to be split. ,Right now This means that the secret itself is hidden in the intercept of this polynomial; The independent variable of a function is represented by giving... Different values ​​are assigned to generate different key fragments; This represents the threshold value, which indicates the required threshold value. It takes several key fragments to recover the master secret, and the degree of the polynomial is designed to be... This means that to uniquely identify one A polynomial of degree at least requires One point; This means that all operations are performed modulo 1. Performed on a finite field, It is a large prime number, which guarantees that all calculation results are integers and fall within a fixed range, which is crucial for computer processing and cryptographic security; 3. Generate a fault diagnosis key fragment and a master key fragment based on a polynomial function. There is one fault diagnosis key fragment, and the number of master key fragments is determined according to the threshold value.

[0040] In this embodiment, a threshold is set. Then the degree of the polynomial is 1, which is a straight line, and the master secret needs to be divided. As Randomly select another coefficient Constructing a polynomial, expressed as: Generate a master key fragment stored by the system. and fault diagnosis key fragment ,in, ,set up ,but , ,set up ,but ; Subsequently, the master key fragment and the fault diagnosis key fragment are distributed, and the polynomial itself is completely destroyed. When fault diagnosis is needed later, the master secret can be reconstructed using the master key fragment and the fault diagnosis key fragment through Lagrange interpolation. This means that the master key fragment and the fault diagnosis key fragment must be held at the same time to recover the decryption key, which is used to decrypt specific operation and maintenance data for diagnosis.

[0041] The generated fault diagnosis key fragment is not stored in plaintext. Instead, it is logically bound to the state sensor of a pre-defined key physical component. The goal of this physical binding process is to create a mandatory and tamper-proof association, ensuring that the validity of the fault diagnosis key fragment is not merely a digital credential, but deeply coupled with the state of a specific, measurable physical world. The specific steps are as follows: 1. Generate a secure binding tuple, which stores complete binding information, namely: a unique identifier for the fault diagnosis key fragment, used to index the corresponding key fragment in subsequent processes; a globally unique identifier for the status sensor on the preset physical component, which is hard-coded or securely configured during initialization; and a cryptographic commitment with built-in hiding, binding, and verification mechanisms. Hiding means not exposing any information of the fault diagnosis key fragment; binding means uniquely and non-repudially locking the two identifiers together; and verification means that it can be used to verify the authenticity and integrity of the provided key fragment when the key is released later.

[0042] 2. The generated secure binding tuple is securely stored in the protected memory area of ​​the encryption module, while the corresponding master key fragment is transferred to the higher-security key triggering module for independent and higher-security management.

[0043] By separating key fragments and centralizing binding information, even if an attacker obtains the stored secure binding tuple, they cannot pose a threat because they lack the plaintext of the master key fragment and the fault diagnosis key fragment. Furthermore, the logical relationship of the physical binding is well maintained within the encryption module, providing a basis for conditional judgment.

[0044] The final logic of the binding is reflected in the release condition judgment of the key triggering module. When it is necessary to decide whether to release, the operation performed is actually to verify a composite logical condition. Only when this composite logical condition is true will the key triggering module send a request to the encryption module. The multi-level encryption module then uses the cryptographic commitment in the secure binding tuple to verify the correctness of the key fragment to be released. Only then is the security policy set by the entire physical binding fully implemented.

[0045] Through the above methods, the multi-level encryption module not only achieves adaptive allocation of data encryption strength, but also creates an innovative security paradigm by deeply coupling cryptographic secrets with the state of the physical world. That is, access to core data is forcibly subject to a physical precondition, which greatly improves overall security and provides a feasible technical path for secure remote fault diagnosis.

[0046] Key triggering module: Based on the status signals generated by the loom equipment and combined with real-time status sensor data of physical components, when both meet the release conditions, it authorizes a fault diagnosis key fragment to the designated maintenance terminal for partial decryption of the maintenance data. For example... Figure 4 As shown.

[0047] This module is the final arbitration and enforcement unit for the security policy. It is responsible for authorizing temporary access to specific operation and maintenance data under strictly controlled conditions to achieve secure fault diagnosis. As the last checkpoint in the double-lock mechanism, it ensures that the fault diagnosis key fragment will only be released when a real and specific physical fault occurs in the loom equipment.

[0048] This module continuously monitors two types of input signals: the status signals of the loom equipment and the physical status signals of the physical components.

[0049] The status signals generated by the loom equipment are global fault status signals collected by the loom control sensors. This is a Boolean value. When the control sensor detects a global fault such as a system emergency stop, a serious deviation in key process parameters, or a failure of a critical logic unit, Set as Status signal detection, such as system emergency stop, serious deviation of major process parameters, or failure of key logic units, is set at the factory.

[0050] The physical status signal comes from the real-time data of the status sensors of key physical components that are bound to the fault diagnosis key fragment. In this embodiment, when the fault diagnosis key fragment is bound to the vibration sensor of the jacquard machine head, the real-time data is the vibration acceleration value collected in real time. If it is bound to the main motor current sensor, the real-time data is the current waveform or characteristic value.

[0051] This module pre-defines release conditions for specific fault scenarios. This condition is a strictly logical compound function that ensures authorization is triggered only when both logical and physical anomalies occur simultaneously, expressed as: , in, Real-time data from sensors indicating the status of physical components; Indicating targeting The exception handling function, when Return when the exception condition is met. .

[0052] In this embodiment, the anomaly detection function is defined as follows: when (Vibration value) >5 hour, return ;when When the total harmonic distortion (THD) of the current is >15%, return .

[0053] According to the logical composition function, if and only if for Only when the key release process is initiated will the subsequent key release process be started. This dual verification mechanism effectively prevents the key from being maliciously triggered due to a single false alarm, greatly enhancing security.

[0054] The specific steps for authorizing a fault diagnosis key fragment to a designated maintenance terminal are as follows: Send the master key fragment to the designated maintenance terminal via a secure link; Send an authorization request to the multi-level encryption module to request the release of the fault diagnosis key fragment; The multi-level encryption module queries the secure binding tuple, performs release verification through cryptographic commitment, and authorizes the fault diagnosis key fragment to the designated maintenance terminal after verification. The maintenance terminal reconstructs the complete master secret using the fault diagnosis key fragment and the master key fragment, and finally uses the reconstructed master secret for decryption.

[0055] Specifically, when the release conditions are met, this module will establish a secure communication link with a designated authorized maintenance terminal. Before transmitting any sensitive information, the maintenance terminal will be required to perform identity authentication. The authentication mechanism can use digital certificates, two-way authentication, or a challenge and response protocol based on a pre-shared key to ensure that the recipient of the fault diagnosis key fragment is legitimate and authorized.

[0056] This module then sends a request to the multi-level encryption module to request the release of the fault diagnosis key fragment. After receiving the request, the multi-level encryption module will query the corresponding security binding tuple and use the cryptographic commitment in it to verify the correctness of releasing the fault diagnosis key fragment. After verification, the fault diagnosis key fragment will be authorized to the designated maintenance terminal.

[0057] The maintenance terminal uses fault diagnosis key fragments The master key fragment is used to reconstruct the complete master secret using Lagrange interpolation. Finally, the reconstructed decryption key is used to decrypt the ciphertext of specific maintenance data to recover the plaintext, thereby performing maintenance diagnosis. After the diagnosis is completed, the maintenance terminal destroys all key fragments and the reconstructed decryption key.

[0058] This embodiment proposes a loom maintenance data encryption system. The acquisition module assigns process sensitivity weights to maintenance data based on a process knowledge base. The multi-level encryption module implements adaptive differentiated encryption according to the weights and generates fault diagnosis key fragments bound to physical component status sensors for specific maintenance data. After the key triggering module passes dual verification of the equipment's global fault signal and physical component abnormal data, it collaboratively releases the key fragments to the authorized maintenance terminal, realizing conditional local decryption and security fault diagnosis of specific maintenance data.

[0059] Example 2: This embodiment discloses a loom equipment that includes a loom operation and maintenance data encryption system as described in Embodiment 1.

[0060] like Figures 5-6 As shown, the equipment includes: a frame 1, a support assembly 2, a weft insertion assembly 3, a needle bed assembly 4, a warp feed assembly 5, a dust removal assembly 6, a control cabinet assembly 7, and a process sensor assembly 8. The weft insertion assembly 3, the needle bed assembly 4, the warp feed assembly 5, and the dust removal assembly 6 are fixedly installed inside the frame 1. The weft insertion assembly 3 is installed above the needle bed assembly 4. The process sensor assembly 8 is fixedly installed on the top of the weft insertion assembly 3. The warp feed assembly 5 is installed in front of the needle bed assembly 4. The dust removal assembly 6 is installed above the warp feed assembly 5. The four support assemblies 2 are installed at the four corners of the frame 1. The control cabinet assembly 7 is fixedly installed on one side of the frame 1. The control cabinet assembly 7 integrates electrical sensor components, a controller, and a loom operation and maintenance data encryption system.

[0061] The warp feeder 5 is responsible for smoothly feeding the yarn onto the needle bed assembly 4. The beat-up assembly 3 operates stably inside the frame 1, performing beat-up operations on the fabric. The needle bed assembly 4, in conjunction with the beat-up assembly 3, precisely completes the movement of the needles, allowing the yarn to interweave in a predetermined manner to achieve the weaving task. During the weaving process, the dust removal assembly 6 is activated to remove dust and static electricity from the yarn being transported in the working area. The control cabinet assembly 7 serves as the control core of the entire loom equipment. Its internal electrical sensing components monitor the operating status of various parts of the equipment in real time, such as parameters like motor speed, temperature, current, and voltage. The loom maintenance data encryption system encrypts this maintenance data and sends the master key fragment to the designated maintenance terminal via a secure link. Even if the data is intercepted during transmission, unauthorized personnel cannot obtain the key information, ensuring the security and integrity of the equipment maintenance data.

[0062] The process sensing component 8 includes a fabric density sensor, a fabric defect sensor, and a fabric width sensor. The process sensing component 8 is connected to the control cabinet component 7.

[0063] When the weft insertion assembly 3 is working, the process sensing assembly 8 installed on the top detects the fabric. The fabric density sensor, fabric defect sensor and fabric width sensor detect the fabric density, surface defects and width respectively, and feed the detection results back to the control cabinet assembly 7. The control cabinet assembly 7 adjusts the working parameters of the loom according to these data to ensure that the quality of the fabric meets the requirements.

[0064] like Figure 7 As shown, the feeding assembly 5 includes a feeding table 501, a groove 502, a mounting bracket 503, and a motion sensing assembly 504. The groove 502 is located at the upper end of the feeding table 501, and the grooves 502 are evenly distributed along the direction of the upper end of the feeding table 501. The mounting bracket 503 is fixedly installed above the rear end of the feeding table 501. The motion sensing assembly 504 is fixedly installed on the top of the mounting bracket 503, and the lower end of the motion sensing assembly 504 is arc-shaped. The motion sensing assembly 504 includes a displacement sensor, a pressure sensor, and a Hall sensor, and the motion sensing assembly 504 is connected to the control cabinet assembly 7.

[0065] The yarn is pressed into the groove 502 at the upper end of the feeding table 501, which guides and limits the conveyed yarn to ensure the stability of the yarn conveying and enable the yarn to be accurately conveyed to the needle bed assembly 4. The motion sensing assembly 504 on the top of the mounting frame 503 monitors the running status of the yarn in real time. The displacement sensor can accurately sense the moving distance of the yarn and determine whether the yarn has reached the designated position. The pressure sensor can detect the tension during the yarn conveying process, and the Hall sensor can monitor information such as the speed of the yarn conveying. The monitoring results are fed back to the control cabinet assembly 7. The control cabinet assembly 7 analyzes and processes the data and adjusts the working parameters of the loom to ensure the stability and accuracy of the warp feeding process.

[0066] like Figure 8-9As shown, the dust removal assembly 6 includes a horizontal plate 601, an ion fan 602, a first connecting pipe 603, a nozzle 604, a dust collection box 605, an exhaust fan 606, a second connecting pipe 607, a first cavity 608, a second cavity 609, and a perforated mesh plate 610. The first cavity 608 is located inside the horizontal plate 601. The nozzle 604 is fixedly installed below the horizontal plate 601 and communicates with the first cavity 608. The nozzles 604 are evenly distributed along the direction of the horizontal plate 601 below it and are inclined. The ion fan 602 is fixedly installed on one side of the frame 1. The first connecting pipe... 603 is installed between the ion fan 602 and the horizontal plate 601. The second cavity 609 is located inside the horizontal plate 601 and is arranged parallel to the first cavity 608. The perforated mesh plate 610 is fixedly installed at the lower end of the horizontal plate 601 and at the bottom of the second cavity 609. The dust collection box 605 and the exhaust fan 606 are fixedly installed on one side of the frame 1 and are connected to each other. The second connecting pipe 607 is installed between the dust collection box 605 and the horizontal plate 601. The ion fan 602 and the exhaust fan 606 are electrically connected to the control cabinet assembly 7.

[0067] When the loom is working, the dust removal component 6 starts to work, turning on the ion fan 602 to generate an ionized airflow. The airflow is delivered to the first cavity 608 inside the horizontal plate 601 through the first connecting pipe 603, and then sprayed onto the conveyed yarn through the evenly arranged and inclined nozzles 604. The ionized airflow can not only blow away the dust attached to the yarn, but also eliminate the static electricity on the yarn. At the same time, the exhaust fan 606 is turned on to generate suction, which draws the dust-laden air around the yarn into the second cavity 609 inside the horizontal plate 601. The dust-laden air is collected into the dust collection box 605 through the second connecting pipe 607, which plays a role in dust removal.

[0068] like Figure 10 As shown, the support assembly 2 includes a connecting column 201, a rubber seat 202, a nut 203, and a telescopic cavity 204. The upper end of the connecting column 201 is fixedly connected to the frame 1. The nut 203 is fixedly installed on the upper end of the rubber seat 202. The telescopic cavity 204 is provided at the center of the upper end of the rubber seat 202, and the inner diameter of the telescopic cavity 204 is larger than the diameter of the connecting column 201. The connecting column 201 and the nut 203 are connected by a through thread.

[0069] The connecting column 201 of the support component 2 is threadedly connected to the nut 203. By rotating the nut 203, the position of the connecting column 201 in the telescopic cavity 204 can be adjusted, and the length of the support component 2 can be changed, thereby achieving fine adjustment of the height and level of the frame 1 and ensuring the stable operation of the loom equipment.

[0070] In summary, this invention constructs a loom data security system that integrates intelligent data classification, dynamic encryption protection, physical state binding, and condition-triggered decryption. It achieves in-depth defense from software logic to the physical world, effectively solving the industry problem of traditional solutions struggling to balance security strength, operational efficiency, and resource optimization.

[0071] While the spirit and principles of the invention have been described with reference to several specific embodiments, it should be understood that the invention is not limited to the disclosed specific embodiments, and the division of aspects does not imply that features in these aspects cannot be combined for benefit; such division is merely for ease of description. The invention is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

[0072] Regarding the limitation of the scope of protection of this invention, those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solution of this invention are still within the scope of protection of this invention.

Claims

1. A loom maintenance data encryption system, characterized in that, The method includes: Data acquisition module: Collects operation and maintenance data of loom equipment and associates it with the process knowledge base, and assigns process sensitivity weights to each piece of operation and maintenance data based on the predefined process knowledge base; Multi-level encryption module: Selects the corresponding high-strength encryption algorithm or low-overhead encryption algorithm according to the process sensitivity weight of the operation and maintenance data; generates fault diagnosis key fragments based on the association between operation and maintenance data and process knowledge base, and binds the fault diagnosis key fragments to the status sensors of physical components in the loom equipment; Key triggering module: Based on the status signals generated by the loom equipment and the real-time status sensor data of the physical components, when both meet the release conditions, the fault diagnosis key fragment is authorized to the designated maintenance terminal to partially decrypt the operation and maintenance data.

2. The loom maintenance data encryption system according to claim 1, characterized in that, The operation and maintenance data mentioned in the data acquisition module includes: Motion parameters: real-time spindle speed measured by the spindle encoder, and real-time weft density measured by the fabric density sensor; Mechanical parameters: Real-time tension values ​​of warp and weft yarns measured by pressure sensors; Electrical parameters: Real-time operating current of the main motor acquired through a current sensor; Process parameters: The core process recipe code being run, read directly from the controller.

3. The loom maintenance data encryption system according to claim 2, characterized in that, The process knowledge base mentioned in the multi-level encryption module is used to store the mapping relationship between different operation and maintenance data items and the core process parameters and health status of the loom. The process knowledge base is for each operation and maintenance data item. Calculate a process sensitivity weight with a value between 0 and 1. , is represented as: ， in, The mapping function represents the relationship between maintenance data items and core process parameters, and between maintenance data items and equipment health status. The process knowledge base defines the qualitative and quantitative relationships between different maintenance data and the core process parameters and health status of the loom. The specific rules are as follows: Mapping of core process parameters: used to define the relationship between operation and maintenance data items and key process outputs; Device health status mapping: used to define the association between maintenance data items and device operating status.

4. The loom maintenance data encryption system according to claim 1, characterized in that, The selection of high-strength encryption algorithm or low-overhead encryption algorithm in the multi-level encryption module is based on a decision function with a preset configurable weight threshold. For each piece of operational data The encryption process is determined by the assigned process sensitivity weights. The decision is based on this definition of the decision function, expressed as: ， in, Indicates the first The ciphertext obtained after encrypting the operation and maintenance data; and These represent the symmetric keys corresponding to high-strength encryption algorithms and low-overhead encryption algorithms, respectively, and are securely generated and rotated by the key management service. and These represent high-strength encryption algorithms and low-overhead encryption algorithms, respectively. This indicates the preset weight threshold.

5. The loom maintenance data encryption system according to claim 1, characterized in that, The steps for generating fault diagnosis key fragments in the multi-level encryption module are as follows: In a finite field Above is the operation and maintenance data. The encrypted ciphertext generates a master secret. The master secret is conceptually equivalent to the decryption key itself, or a master key strongly associated with the decryption key; Build a A polynomial of degree n is expressed as: ， in, Represents a polynomial function; Represents the coefficients of a polynomial; This represents the constant term, which is also the master secret that needs to be split. ,Right now ; The independent variable of a function is represented by giving... Different values ​​are assigned to generate different key fragments; This represents the threshold value, which indicates the required threshold value. The master secret is recovered from the key fragments, and the degree of the polynomial is designed to be... That is, to uniquely determine one A polynomial of degree at least requires One point; This means that all operations are performed modulo 1. Performed on a finite field, It is a large prime number; The fault diagnosis key fragment and the master key fragment are generated based on the polynomial function. There is one fault diagnosis key fragment, and the number of master key fragments is determined according to the threshold value.

6. The loom maintenance data encryption system according to claim 5, characterized in that, The fault diagnosis key fragment is bound to the status sensor of the physical component through a secure binding tuple. The secure binding tuple stores complete binding information, namely: a unique identifier for the fault diagnosis key fragment; a globally unique identifier for the status sensor on the physical component; and a cryptographic commitment for the hiding, binding, and verification mechanism.

7. The loom maintenance data encryption system according to claim 1, characterized in that, The status signal generated by the loom equipment in the key trigger module is the global fault status signal collected by the loom control sensor. The physical component's state sensor data outputs a physical state signal, and the release condition is a logical composite function, expressed as: ， in, Real-time data from sensors indicating the status of physical components; Indicating targeting The exception handling function, when Return when the exception condition is met. According to the aforementioned logical composition function, if and only if for When this occurs, initiate the fault diagnosis key fragment authorization process; The authorization process is as follows: Send the master key fragment to the designated maintenance terminal via a secure link; Send an authorization request to the multi-level encryption module to request the release of the fault diagnosis key fragment; The multi-level encryption module queries the secure binding tuple, performs release verification through the cryptographic commitment, and after verification, authorizes the fault diagnosis key fragment to the designated maintenance terminal. The maintenance terminal reconstructs the complete master secret using the fault diagnosis key fragment and the master key fragment, and finally uses the reconstructed master secret for decryption.

8. A weaving machine, characterized in that, The loom maintenance data encryption system described in any one of claims 1-7 is adopted. The loom equipment includes: a frame (1), a support assembly (2), a weft insertion assembly (3), a needle bed assembly (4), a warp feed assembly (5), a dust removal assembly (6), a control cabinet assembly (7), and a process sensing assembly (8). The weft insertion assembly (3), the needle bed assembly (4), the warp feed assembly (5), and the dust removal assembly (6) are fixedly installed on the inner side of the frame (1). The weft insertion assembly (3) is installed on the needle bed assembly (4). Above, the process sensing component (8) is fixedly installed on the top of the weft insertion component (3), and the warp feeding component (5) is installed in front of the needle bed component (4). The dust removal component (6) is installed above the warp feeding component (5). The four support components (2) are installed at the four corners of the frame (1). The control cabinet component (7) is fixedly installed on one side of the frame (1). The control cabinet component (7) integrates electrical sensing components, controllers and the loom operation and maintenance data encryption system inside. The process sensing component (8) includes a fabric density sensor, a fabric defect sensor and a fabric width sensor, and the process sensing component (8) is connected to the control cabinet component (7). The feeding assembly (5) includes a feeding table (501), a groove (502), a mounting bracket (503), and a motion sensing assembly (504). The groove (502) is located at the upper end of the feeding table (501), and the groove (502) is evenly distributed along the direction of the upper end of the feeding table (501). The mounting bracket (503) is fixedly installed above the rear end of the feeding table (501). The motion sensing assembly (504) is fixedly installed on the top of the mounting bracket (503), and the lower end of the motion sensing assembly (504) is arc-shaped. The motion sensing assembly (504) includes a displacement sensor, a pressure sensor, and a Hall sensor, and the motion sensing assembly (504) is connected to the control cabinet assembly (7).

9. A weaving machine according to claim 8, characterized in that, The dust removal assembly (6) includes a horizontal plate (601), an ion fan (602), a first connecting pipe (603), a nozzle (604), a dust collection box (605), an exhaust fan (606), a second connecting pipe (607), a first cavity (608), a second cavity (609), and a perforated mesh plate (610). The first cavity (608) is disposed inside the horizontal plate (601). The nozzle (604) is fixedly installed below the horizontal plate (601) and communicates with the first cavity (608). The nozzles (604) are evenly arranged below the horizontal plate (601) along its direction and are inclined. The ion fan (602) is fixedly installed on one side of the frame (1). The first connecting pipe (603) is installed on the... Between the ion fan (602) and the horizontal plate (601), the second cavity (609) is disposed inside the horizontal plate (601) and is arranged parallel to the first cavity (608). The perforated mesh plate (610) is fixedly installed at the lower end of the horizontal plate (601) and is installed at the bottom of the second cavity (609). The dust collection box (605) and the exhaust fan (606) are fixedly installed on one side of the frame (1) and are connected to each other. The second connecting pipe (607) is installed between the dust collection box (605) and the horizontal plate (601). The ion fan (602) and the exhaust fan (606) are electrically connected to the control cabinet assembly (7).

10. A weaving machine according to claim 8, characterized in that, The support assembly (2) includes a connecting column (201), a rubber seat (202), a nut (203), and a telescopic cavity (204). The upper end of the connecting column (201) is fixedly connected to the frame (1). The nut (203) is fixedly installed on the upper end of the rubber seat (202). The telescopic cavity (204) is provided at the center of the upper end of the rubber seat (202), and the inner diameter of the telescopic cavity (204) is larger than the diameter of the connecting column (201). The connecting column (201) and the nut (203) are connected by a through thread.

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