An early warning system based on cable fault data analysis

Abstract

This invention relates to the field of cable fault monitoring technology, specifically to an early warning system based on cable fault data analysis. The system includes a quantum encryption unit, a data acquisition and transmission unit, and a fault analysis and early warning unit. In this invention, the quantum encryption unit utilizes a quantum entanglement enhancement mechanism to design quantum gate operation sequences to control quantum bit pairs and implements adaptive noise-resistant quantum coding. It adjusts the coding method and performs verification and error correction based on noise levels to ensure secure and reliable data encryption. The data acquisition and transmission unit collects various types of cable operation data, encrypts it using different methods according to a multi-source data hierarchical encryption architecture, and then transmits it to the fault analysis and early warning unit. Upon receiving the data, this unit first decrypts and verifies it, uses a quantum hash function to ensure data integrity, and then uses a preset neural network model and thresholds to determine the cable fault risk, issuing timely early warnings. This effectively solves the problems of secure transmission and accurate analysis of cable fault data, improving the safety and reliability of cable operation and maintenance in power systems.

Description

Technical Field

[0001] This invention relates to the field of cable fault monitoring technology, and more specifically, to an early warning system based on cable fault data analysis. Background Technology

[0002] Cable fault monitoring is an important technology. In the field of cable fault monitoring and early warning, the secure and reliable transmission and accurate analysis of data are key to ensuring the stable operation of the power system. Traditional cable fault data analysis and early warning systems have exposed many serious problems when facing complex power environments and increasing security threats.

[0003] In the past, conventional encryption methods were mostly used to process cable fault data. However, with the development of quantum computing technology, these traditional encryption methods face a huge risk of being cracked. In the actual data transmission process, the key operating data of cables, including real-time current and voltage abnormal fluctuation data, as well as data reflecting changes in insulation performance, are important indicators for the safe and stable operation of the power system. Once this data is leaked due to the cracking of traditional encryption, hackers can use this information to precisely plan attacks on the power system, thereby causing great negative impacts on social and economic order and people's lives. In order to solve this technical problem, we provide an early warning system based on cable fault data analysis. Summary of the Invention

[0004] The purpose of this invention is to provide an early warning system based on cable fault data analysis to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, an early warning system based on cable fault data analysis is provided, including a quantum encryption unit, a data acquisition and transmission unit, and a fault analysis and early warning unit;

[0006] The quantum encryption unit uses a quantum encryption algorithm to encrypt cable fault-related data. By employing a quantum bit entanglement enhancement mechanism, a quantum gate operation sequence is designed to control the entanglement of the quantum bit pairs used to generate the key. At the same time, adaptive noise-resistant quantum coding is implemented. Based on the real-time monitored noise level of the cable transmission environment, the encoding method of the quantum bits is adjusted. Quantum error correction codes and noise perception algorithms are combined to perform redundant coding and error verification of the quantum bits.

[0007] The data acquisition and transmission unit collects various operating data of the cable, encrypts them using a quantum encryption unit, and transmits them to the fault analysis and early warning unit. Furthermore, the multi-source data layered encryption architecture in the quantum encryption unit is used to encrypt different data.

[0008] The fault analysis and early warning unit receives data encrypted by the quantum encryption unit, first decrypts and verifies the integrity of the data. The verification process uses a data integrity identifier based on a quantum hash function generated during quantum encryption. By verifying the correctness of the quantum tag, the decrypted data is analyzed and processed. Based on a preset fault diagnosis model and threshold, it determines whether there is a fault risk in the cable. When a fault risk is detected, an early warning signal is issued.

[0009] As a further improvement to this technical solution, the quantum encryption unit includes an entanglement control module. The specific algorithm for the entanglement control module to design quantum gate operation sequence pairs for entanglement control of the quantum bit pairs used to generate the key using a quantum bit entanglement enhancement mechanism is as follows:

[0010] The initial state of the qubit pair is determined and a set of quantum gates is selected, including CONT gates, H gates and rotation gates;

[0011] First, an H-gate operation is applied to the first qubit to obtain the primary quantum state. Then, a CONT-gate operation is applied to the two qubits to obtain the intermediate quantum state and initially construct the entangled state. Then, a rotation gate is used to rotate the second qubit to obtain the advanced quantum state. The rotation angle is determined according to the preset entanglement enhancement coefficient.

[0012] By repeating the sequence of H-gate, CNOT gate, and rotating gate with a specific angle a preset number of times, the quantum states after each operation are combined into a set of quantum states, ultimately resulting in entangled qubit pairs, which are used to generate a key.

[0013] As a further improvement to this technical solution, the quantum encryption unit includes an encoding adjustment module. The specific implementation steps of the adaptive noise-resistance quantum encoding module, which adjusts the encoding method of the qubits based on the real-time monitored noise level of the cable transmission environment, are as follows:

[0014] A fixed time interval is set, and ambient noise intensity values ​​are collected by noise sensors arranged on the cable. Three noise level ranges are set: low noise range, medium noise range, and high noise range.

[0015] When the acquired noise intensity is in the low noise range, a single-qubit direct encoding method is used. If the noise intensity is in the medium noise range, a two-qubit encoding method is used, that is, it is divided into two binary bits. When the noise intensity is in the high noise range, a three-qubit repetitive encoding method is used.

[0016] As a further improvement to this technical solution, the quantum encryption unit includes an encoding verification module. The specific method for redundancy encoding and error verification of the qubits in the encoding verification module, combining quantum error correction codes and noise sensing algorithms, is as follows:

[0017] A preset quantum error correction code is selected for redundancy encoding. For the quantum bit information to be encoded, the encoding operation is performed according to the generator matrix of the preset quantum error correction code to generate the encoded quantum bit sequence.

[0018] For noise perception, a noise monitoring cycle is set. In each cycle, the noise situation is perceived by measuring the decoherence time of the qubit. When noise interference is detected, the check matrix of the preset quantum error correction code is used to calculate the check quantum and a pre-established error mode mapping table is constructed. The corresponding error location and error type are found in the mapping table according to the value of the check quantum. Then, the erroneous qubit is corrected to restore the original correct qubit information.

[0019] As a further improvement to this technical solution, the specific operation of encrypting different data using the multi-source data layered encryption architecture in the quantum encryption unit in the data acquisition and transmission unit is as follows:

[0020] Cable operation data is categorized according to its frequency of change into critical real-time data, routine inspection data, and auxiliary reference data.

[0021] For critical real-time data, a multi-layered encryption approach is adopted, using a quantum bit entanglement enhancement mechanism to generate a strong key, and then the data is redundantly encoded based on quantum error correction codes to obtain the encoded data.

[0022] For routine inspection data, adaptive noise resistance quantum coding is first applied to it, and the coding method is selected according to the current environmental noise level to obtain the coded data.

[0023] For auxiliary reference data, a lightweight key generated by qubit entanglement is used for direct XOR encryption.

[0024] As a further improvement to this technical solution, the data acquisition and transmission unit employs a multi-layered encryption approach for critical real-time data, as detailed below:

[0025] For critical real-time data, after generating a strong key K1 using a quantum bit entanglement enhancement mechanism, redundant encoding is performed using a [9, 6] quantum error-correcting code.

[0026] Let the key real-time data be D1, which is divided into 6 qubit information blocks, x1, x2, x3, x4, x5, x6. Encoding is performed according to the [9, 6] quantum error-correcting code generator matrix G1 to generate the encoded qubit sequence:

[0027] X1=[x'1,x'2,...,x'9]=G1·[x1,x2,x3,x4,x5,x6] T ;

[0028] Then, the encoded data X1 is XORed and encrypted using a strong key K1, resulting in the encrypted data.

[0029] As a further improvement to this technical solution, the fault analysis and early warning unit includes a decryption and verification module. The specific steps for decrypting and verifying the integrity of the data in the decryption and verification module are as follows:

[0030] Upon receiving encrypted data, the corresponding decryption key is first extracted. The decryption key is generated synchronously and securely stored during the encryption process of the quantum encryption unit. Different types of data correspond to different decryption keys.

[0031] For the received encrypted data D' i Where i = 1, 2, 3 correspond to different data types, and the corresponding decryption key K is used. i Perform an XOR decryption operation to obtain the decrypted data.

[0032] While decrypting, obtain the data integrity identifier H generated during the quantum encryption process based on the quantum hash function. q (D i For the decrypted data D i Recalculate its quantum hash function value H' q (D i );

[0033] Comparison H' q (D i ) and the original identifier H stored q (D i If the two are equal, the data is determined to be complete and untampered; if they are not equal, the data is determined to have encountered a problem during transmission, a data integrity error alarm is issued, and the corresponding data is requested to be resent.

[0034] As a further improvement to this technical solution, the fault analysis and early warning unit includes a risk judgment module. The specific algorithm in the risk judgment module for determining whether the cable has a fault risk based on a preset fault diagnosis model and threshold is as follows:

[0035] The preset fault diagnosis model adopts a neural network model, which is a three-layer neural network structure including an input layer, a hidden layer and an output layer. The number of nodes in the input layer is determined according to the number of selected cable fault features, the number of nodes in the hidden layer is set according to the number of nodes in the input layer, the activation function is the ReLU function, and the number of nodes in the output layer is 1, which is used to output the fault probability value.

[0036] The neural network model is trained using historical cable operation data. The input feature data is normalized and then input into the neural network. The output fault probability value is compared with the actual fault label, and the weight parameters of the neural network are adjusted through the backpropagation algorithm.

[0037] For the real-time decrypted and verified cable data to be judged, the corresponding feature data is extracted, normalized and input into the trained neural network model to obtain the output fault probability value. A fault risk threshold is set and compared with the fault probability value. Based on the comparison result, it is determined whether the cable has a fault risk.

[0038] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0039] In an early warning system based on cable fault data analysis, a quantum encryption unit employs a quantum bit entanglement enhancement mechanism. It designs an operation sequence including CNOT gates, H gates, and rotation gates to perform multiple entanglement manipulations on the quantum bit pairs generating the key, enhancing key security and enabling it to resist threats such as quantum computing attacks, thus ensuring data confidentiality. Simultaneously, based on the noise level of the cable transmission environment, an adaptive noise-resistance quantum coding is implemented through an encoding adjustment module. Single, double, and triple quantum bit coding methods are used in different noise ranges. Combined with an encoding verification module, quantum error correction codes and noise sensing algorithms are used to perform redundant encoding and error verification of the quantum bits, ensuring accurate data transmission in complex environments. Attached Figure Description

[0040] Figure 1 This is an overall block diagram of the present invention.

[0041] The meanings of the labels in the diagram are as follows:

[0042] 1. Quantum encryption unit; 11. Entanglement control module; 12. Encoding adjustment module; 13. Encoding verification module; 2. Data acquisition and transmission unit; 3. Fault analysis and early warning unit; 31. Decryption verification module; 32. Risk judgment module. Detailed Implementation

[0043] 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.

[0044] This invention provides an early warning system based on cable fault data analysis. Please refer to [link / reference]. Figure 1 As shown, it includes a quantum encryption unit 1, a data acquisition and transmission unit 2, and a fault analysis and early warning unit 3;

[0045] Quantum encryption unit 1 uses quantum encryption algorithms to encrypt cable fault-related data. By employing a quantum bit entanglement enhancement mechanism, a quantum gate operation sequence is designed to control the entanglement of the quantum bit pairs used to generate the key. At the same time, adaptive noise-resistant quantum coding is implemented. Based on the real-time monitored noise level of the cable transmission environment, the encoding method of the quantum bits is adjusted. Quantum error correction codes and noise sensing algorithms are combined to perform redundant coding and error verification of the quantum bits.

[0046] Quantum encryption unit 1 includes entanglement control module 11. The specific algorithm of entanglement control module 11, which uses a quantum bit entanglement enhancement mechanism to design quantum gate operation sequence pairs for entanglement control of quantum bit pairs used to generate the key, is as follows:

[0047] First, determine the initial state of the qubit pair as follows: The initial state is selected from a set of quantum gates including the CONT gate, H gate, and rotation gate R. This initial state is chosen because the |00> state is a basic and simple quantum state, facilitating the gradual construction of entangled states through various quantum gate operations. The process is easy to operate and understand. These quantum gates are selected because they are commonly used and fundamental operational units in quantum information processing. The CNOT gate can achieve entanglement between qubits, the H gate can prepare qubits into a superposition state, creating conditions for entanglement, and the rotation gate can be used for fine-tuning of quantum states. Their combined use can effectively achieve entanglement control of qubit pairs, meeting the high randomness and high security requirements for key generation.

[0048] Applying an H-gate operation to the first qubit, the transformation matrix of the H-gate... After this operation, the quantum state becomes Where I is the identity matrix, and the H gate can transform it from a deterministic state into a superposition state, so that subsequent operations can be based on this superposition state to construct more complex quantum states, laying the foundation for the subsequent construction of entangled states.

[0049] Next, a CNOT gate operation is applied to the two qubits, resulting in the following quantum state: The purpose of applying the CNOT gate is to utilize its properties to achieve entanglement between two qubits, making the states of the two qubits correlated, thus initially constructing an entangled state and laying the groundwork for further enhancing the degree of entanglement.

[0050] Then, a rotation gate R is used to rotate the second qubit. The rotation angle θ is determined based on a preset entanglement enhancement coefficient λ. The matrix form of the rotation gate is as follows: The expression for the quantum state after this operation is: The reason for using the rotating gate operation is that it can finely control the state of the qubits by changing the rotation angle based on the existing entangled state, thereby adjusting the degree of entanglement and meeting the requirements of entanglement strength under different security levels or different application scenarios, so that the generated key has higher randomness and non-cloning properties.

[0051] Repeat the above sequence of H-gate, CNOT-gate, and rotation gate operations at a specific angle n times, and denote the quantum states after each operation as follows: These quantum states are grouped into a quantum state set. A single operation may only build a certain degree of entanglement. By repeating the operation multiple times, the entanglement effect can be continuously strengthened, making the entanglement between the quantum bit pairs more stable and reaching the desired high-intensity entanglement level to meet the requirements of high-quality key generation. It can gradually accumulate entanglement characteristics, further improve the security of the key, and ensure that the final generated key can still maintain its confidentiality and reliability when facing various potential attacks or noise interference.

[0052] The quantum encryption unit 1 includes an encoding adjustment module 12. The specific implementation steps of the adaptive noise-resistance quantum encoding in the encoding adjustment module 12, which adjusts the encoding method of the qubits based on the real-time monitored ambient noise level of the cable transmission environment, are as follows:

[0053] A fixed time interval ΔT = 0.1s was set. This time interval was chosen to ensure timely detection of changes in environmental noise during cable transmission, while avoiding excessive data collection that could waste system resources or overburden data processing. The environmental noise intensity value N was collected using high-precision noise sensors deployed around the cable.

[0054] Three noise level ranges are defined: low noise range [0, N1), medium noise range [N1, N2), and high noise range [N2, +∞). N1 and N2 are thresholds determined based on statistical analysis of the actual operating environment of the cable. This precise division of the ranges is to flexibly select the most suitable quantum bit encoding method according to different noise intensities, so as to achieve the best noise reduction effect and ensure accurate data transmission.

[0055] When the collected noise intensity N is in the low noise range [0, N1), a single-qubit direct encoding method is adopted. That is, for the data D to be encoded, if D = 0, the corresponding qubit is encoded as |0>, and if D = 1, it is encoded as |1>. This encoding method is the simplest and most efficient in low noise environment. The reason is that under low noise conditions, qubits are less affected by external interference and do not need complex encoding structures to resist noise. This can reduce system processing time and computational resource consumption, and also reduce the probability of errors introduced by the encoding process itself, ensuring the timeliness and accuracy of data transmission.

[0056] If the noise intensity N is in the medium noise range [N1, N2), two-qubit encoding is used. For the data, it is divided into two binary bits, i.e., D=0 corresponds to |00>, and D=1 corresponds to |01>. In medium noise environments, single-qubit encoding is insufficient in noise resistance, while two-qubit encoding utilizes the superposition and entanglement properties of qubits to resist a certain degree of noise interference. Compared to single-qubit encoding, it can carry information through more quantum state combinations, and under noise interference, the correlation between these quantum states can correct errors to some extent, improving the reliability of the encoding and making the data more stable during transmission.

[0057] When the noise intensity N is in the high noise range [N2, +∞), three-qubit repetitive encoding is enabled. If D = 0, the encoding is |000>; if D = 1, the encoding is |111>. In high noise environments, noise has a great impact on qubits, and ordinary encoding methods are prone to data errors. Three-qubit repetitive encoding combats strong noise environments by adding redundant information. It has a strong noise resistance capability and can ensure that cable fault data can still be transmitted accurately under harsh noise conditions, providing a reliable data foundation for subsequent fault analysis and early warning.

[0058] Quantum encryption unit 1 includes encoding and verification module 13. The specific method for redundant encoding and error verification of qubits in encoding and verification module 13, which combines quantum error correction code and noise sensing algorithm, is as follows:

[0059] First, a [7,4] quantum error-correcting code is used for redundancy encoding. For the qubit information to be encoded, x1, x2, x3, x4, the encoding operation is performed according to the generator matrix G of the [7,4] quantum error-correcting code. Then, the proportion of qubits after encoding is X = [x'1, x'2, ..., x'7] = G·[x1, x2, x3, x4]. T By adding redundant information, the information of the original 4 qubits is expanded to 7 qubits, which improves the fault tolerance capability. Even if some qubits are corrupted during transmission, they can be recovered by error correction codes, thus enhancing the reliability of data transmission in quantum channels.

[0060] For noise perception, set the noise monitoring period T. s =0.2s, noise is sensed by measuring the decoherence time of the qubit in each cycle, and the average decoherence time of the qubit is t. d Set the decoherence time threshold t d0 When t d ≤t d0When noise interference is detected, causing errors in the qubits, a monitoring cycle is set to detect noise interference in a timely manner, preventing error accumulation. This allows for early processing of errors, reducing their impact on the data and ensuring the system's sensitivity to noise and timely response.

[0061] When an error is detected, the check matrix H of the [7,4] quantum error correction code is used to calculate the checksum S = H·X. The checksum S is a three-dimensional vector, and its different values ​​correspond to different error modes. An error mode mapping table is pre-established. The corresponding error location and error type are found in the mapping table according to the value of S. Then, the erroneous qubit is corrected to restore the original correct qubit information. By using the check matrix and the error mode mapping table, errors can be accurately located and corrected, which improves the accuracy and efficiency of error correction, ensures the consistency between the final received data and the original data, and guarantees the integrity and accuracy of the data.

[0062] The data acquisition and transmission unit 2 collects various operating data of the cable, and transmits them to the fault analysis and early warning unit 3 after encryption by the quantum encryption unit 1. The multi-source data layered encryption architecture in the quantum encryption unit 1 is used to encrypt different data.

[0063] In data acquisition and transmission unit 2, the specific operation of encrypting different data using the multi-source data layered encryption architecture in quantum encryption unit 1 is as follows:

[0064] Determine the initial state of the qubit pair as Select a set of quantum gates, apply an H-gate operation to the first qubit, and the quantum state becomes... Introducing qubits into a superposition state prepares for subsequent entanglement, adds a basis for the randomness of key generation, and improves key security. Then, a CNOT gate operation is applied to the two qubits, resulting in the following quantum state: An entangled state was initially constructed. Then, a rotation gate was used to rotate the second qubit. The rotation angle was determined based on a preset entanglement enhancement coefficient. The resulting quantum state was... Repeat the above sequence of H-gate, CNOT-gate, and rotation gate operations at a specific angle n times, and denote the quantum states after each operation as follows: The resulting highly entangled quantum bit pairs are used to generate the strong key K1.

[0065] Next, the key real-time data is subjected to redundant encoding based on quantum error correction codes. A [7,4] quantum error correction code is selected for redundant encoding. For the qubit information to be encoded, x1, x2, x3, x4, the encoding operation is performed according to the generator matrix G of the [7,4] quantum error correction code, generating the encoded qubit sequence X = [x'1, x'2, ..., x'7] = G·[x1, x2, x3, x4]. T This increases information redundancy and improves fault tolerance. Even if some qubits are corrupted during transmission, they can be recovered using error correction codes, thus enhancing the reliability of critical real-time data during transmission.

[0066] Finally, the encoded data X is XOR-encrypted using the generated strong key K1. Let the qubit sequence of the encoded data X be [x'1, x'2, ..., x'7], the qubit sequence of the strong key K1 be [k1, k2, ..., k7], and the qubit sequence of the encrypted data D1' be [d'1, d'2, ..., d'7]. Encrypting data with a key ensures data confidentiality and provides a simple and efficient encryption operation, preventing critical real-time data from being stolen or tampered with during transmission.

[0067] At fixed time intervals ΔT = 0.1s, ambient noise intensity values ​​are collected by noise sensors placed around the cable. Three noise level ranges are defined: low noise range [0, N1), medium noise range [N1, N2), and high noise range [N2, +∞). N1 and N2 are thresholds determined based on statistical analysis of the cable's actual operating environment. When the collected noise intensity N is in the low noise range [0, N1), a single-qubit direct encoding method is used, i.e., for the data D to be encoded... If D = 0, the corresponding quantum bit is encoded as |0>; if D = 1, it is encoded as |1>. If the noise intensity N is in the medium noise range [N1, N2), two-qubit encoding is used. For the data, it is divided into two binary bits, i.e., D = 0 corresponds to the encoding as |00>, and D = 1 corresponds to the encoding as |01>. When the noise intensity N is in the high noise range [N2, +∞), three-qubit repetition encoding is enabled. If D = 0, it is encoded as |000>; if D = 1, it is encoded as |111>.

[0068] Let the encoded data obtained after adaptive noise-resistant quantum coding be D2. Using a common key K2 generated by qubit entanglement, simple XOR encryption is performed, resulting in the encrypted data as follows: The principle of XOR encryption is the same as the XOR operation in critical real-time data encryption, ensuring data confidentiality and further protecting data security on the basis of encoding, preventing the illegal acquisition of routine inspection data.

[0069] A lightweight key K3 generated by entangled qubits is used for direct XOR encryption. Let the original auxiliary reference data be D3, and its qubit sequence be [d 31 d 32 , ..., d 3m The quantum bit sequence of the lightweight key K3 is [k 31 k 32 , ..., k 3n The encrypted data D3' has a qubit sequence of [d]. 31 ',d 32 ',…,d 3m '],in i = 1, 2, ..., m, j correspond to i according to the key generation rules. For auxiliary reference data with relatively low importance, a simple and fast encryption method is adopted to save computing resources and encryption time, and to a certain extent protect the security of auxiliary reference data.

[0070] The fault analysis and early warning unit 3 receives the data encrypted by the quantum encryption unit 1, first decrypts and verifies the integrity of the data. The verification process uses the data integrity identifier based on the quantum hash function generated during the quantum encryption process. By verifying the correctness of the quantum tag, the decrypted data is analyzed and processed. Based on the preset fault diagnosis model and threshold, it determines whether there is a fault risk in the cable. When a fault risk is detected, an early warning signal is issued.

[0071] The fault analysis and early warning unit 3 includes a decryption and verification module 31. The specific steps for decrypting and verifying the integrity of data in the decryption and verification module 31 are as follows:

[0072] After receiving encrypted data, the system extracts the corresponding decryption key based on the data type identifier, ensuring that only the correct key can decrypt the corresponding data, thus guaranteeing data confidentiality and security. Let the received encrypted data be D'i, where i = 1, 2, 3 correspond to key real-time data, routine inspection data, and auxiliary reference data, respectively, and its qubit sequence be [d' i1 ,d' i2 ,…,d' in The corresponding decryption key K i The sequence of qubits is [k i1 k i2 , ..., k in The decrypted data Di's quantum bit sequence [d] i1 d i2 , ..., d in Calculate using the following formula By leveraging the reversibility of the XOR operation, the original data can be quickly restored. The calculation is simple and efficient, consumes relatively few system resources, and accurately obtains the decrypted data, providing a foundation for subsequent analysis and processing.

[0073] During decryption, the system retrieves the data integrity identifier H, generated during the quantum encryption process and based on a quantum hash function, from the additional portion of the encrypted information. q (D i This identifier is obtained by performing a quantum hash calculation on the original data during the encryption phase. For the decrypted data D... i Recalculate its quantum hash function value H' q (D i Quantum hash functions use hash values ​​to verify whether data has been tampered with during transmission. Quantum hash functions can leverage quantum properties to provide stronger resistance to tampering and ensure data integrity.

[0074] The system compares the recalculated quantum hash function value H' q (D i ) and the original identifier H stored q (D i If the two are equal, the data is considered complete and untampered, allowing it to proceed to the subsequent analysis and processing flow. If the two are not equal, the data is considered to have encountered a problem during transmission, issuing a data integrity anomaly alarm and requesting the retransmission of the corresponding data. This mechanism can promptly detect data anomalies, ensuring data reliability. Through a strict verification mechanism, it prevents erroneous or tampered data from entering subsequent analysis, thereby improving the data quality and security of the entire system.

[0075] The fault analysis and early warning unit 3 includes a risk judgment module 32. The specific algorithm in the risk judgment module 32 for judging whether the cable has a fault risk based on a preset fault diagnosis model and threshold is as follows:

[0076] The preset fault diagnosis model adopts a three-layer neural network structure. The number of input layer nodes is determined according to the number of selected cable fault features, so that the neural network can receive enough key information to judge the cable status. The number of hidden layer nodes is set according to the number of input layer nodes. The ReLU function can effectively solve the gradient vanishing problem, speed up the training speed of the model, and has high computational efficiency when processing large-scale data, enabling the neural network to better learn the features and patterns of the input data.

[0077] The output layer has one node, which is used to output the fault probability value. It presents the cable fault status in the form of probability, which is convenient for subsequent comparison with the set threshold. It intuitively reflects the probability of cable faults and provides a quantitative basis for judging whether there is a fault risk in the cable.

[0078] The neural network model is trained using historical cable operation data. First, the input feature data is normalized to ensure that different features are on the same order of magnitude, preventing certain features from having an excessively large or small impact on model training. The normalized input feature data is then fed into the neural network, and the output fault probability value is compared with the actual fault label: 0 indicates no fault, and 1 indicates a fault. The weight parameters of the neural network are adjusted using the backpropagation algorithm. The basic principle of backpropagation is to calculate the gradient layer by layer based on the error of the output layer and update the weights to reduce prediction error. By continuously adjusting the weights, the neural network can better fit the training data, improving prediction accuracy. It can automatically learn complex relationships in the data, enabling the trained model to accurately determine the cable fault probability based on the input features.

[0079] For the decrypted and verified cable data to be judged in real time, extract the corresponding feature data x1, x2, ..., x3. m After undergoing the same normalization process, the input is given to the trained neural network model to obtain the output fault probability value P. A fault risk threshold P is then set. th When P≥P th When P < P, the cable is deemed to have a fault risk. th When determining that the cable is currently free of fault risk, a threshold is set to clearly distinguish whether the cable is in a state of potential fault, providing a simple and intuitive judgment result, which can promptly detect potential cable faults and ensure the safe operation of the cable.

[0080] In this invention, a quantum encryption unit 1 utilizes a quantum bit entanglement enhancement mechanism to design a quantum gate operation sequence to control quantum bit pairs, and implements adaptive noise-resistant quantum coding. The coding method and error correction are adjusted according to noise levels to ensure secure and reliable data encryption. A data acquisition and transmission unit 2 collects various cable operation data, encrypts it using different methods according to a multi-source data layered encryption architecture, and then transmits it to a fault analysis and early warning unit 3. This unit receives the data, decrypts and verifies it, uses a quantum hash function to ensure data integrity, and then uses a preset neural network model and thresholds to determine cable fault risk, issuing timely warnings. This effectively solves the problem of secure transmission and accurate analysis of cable fault data, improving the safety and reliability of power system cable operation and maintenance. The above describes the basic principles, main features, and advantages of this invention. Those skilled in the art should understand that this invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made without departing from the spirit and scope of the invention, and all such changes and modifications fall within the scope of the invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. An early warning system based on cable fault data analysis, characterized in that, It includes a quantum encryption unit (1), a data acquisition and transmission unit (2), and a fault analysis and early warning unit (3); The quantum encryption unit (1) uses a quantum encryption algorithm to encrypt cable fault-related data. By using a quantum bit entanglement enhancement mechanism, a quantum gate operation sequence is designed to control the entanglement of the quantum bit pairs used to generate the key. At the same time, adaptive noise-resistant quantum coding is implemented. Based on the real-time monitored cable transmission environment noise level, the coding method of the quantum bits is adjusted. The quantum error correction code and noise perception algorithm are combined to perform redundant coding and error verification of the quantum bits. The data acquisition and transmission unit (2) acquires various operating data of the cable and transmits them to the fault analysis and early warning unit (3) after encryption by the quantum encryption unit (1). The multi-source data layered encryption architecture in the quantum encryption unit (1) is used to encrypt different data. The fault analysis and early warning unit (3) receives data encrypted by the quantum encryption unit (1), first decrypts and verifies the integrity of the data. The verification process uses the data integrity identifier based on the quantum hash function generated during the quantum encryption process. The correctness of the quantum tag is verified to analyze and process the decrypted data. Based on the preset fault diagnosis model and threshold, it judges whether there is a fault risk in the cable. When a fault risk is detected, an early warning signal is issued.

2. The early warning system based on cable fault data analysis according to claim 1, characterized in that: The quantum encryption unit (1) includes an entanglement control module (11). The entanglement control module (11) uses a quantum bit entanglement enhancement mechanism to design a quantum gate operation sequence pair for entanglement control of the quantum bit pairs used to generate the key. The specific algorithm is as follows: The initial state of the qubit pair is determined and a set of quantum gates is selected, including CONT gates, H gates and rotation gates; First, an H-gate operation is applied to the first qubit to obtain the primary quantum state. Then, a CONT-gate operation is applied to the two qubits to obtain the intermediate quantum state and initially construct the entangled state. Then, a rotation gate is used to rotate the second qubit to obtain the advanced quantum state. The rotation angle is determined according to the preset entanglement enhancement coefficient. By repeating the sequence of H-gate, CNOT gate, and rotating gate with a specific angle a preset number of times, the quantum states after each operation are combined into a set of quantum states, ultimately resulting in entangled qubit pairs, which are used to generate a key.

3. The early warning system based on cable fault data analysis according to claim 2, characterized in that: The quantum encryption unit (1) includes an encoding adjustment module (12). The specific implementation steps of the encoding adjustment module (12) for implementing adaptive noise-resistance quantum encoding and adjusting the encoding method of the quantum bits according to the real-time monitored cable transmission environmental noise level are as follows: A fixed time interval is set, and ambient noise intensity values ​​are collected by noise sensors arranged on the cable. Three noise level ranges are set: low noise range, medium noise range, and high noise range. When the acquired noise intensity is in the low noise range, a single-qubit direct encoding method is used. If the noise intensity is in the medium noise range, a two-qubit encoding method is used, that is, it is divided into two binary bits. When the noise intensity is in the high noise range, a three-qubit repetitive encoding method is used.

4. The early warning system based on cable fault data analysis according to claim 3, characterized in that: The quantum encryption unit (1) includes an encoding verification module (13). The specific method for redundant encoding and error verification of qubits in the encoding verification module (13) by combining quantum error correction codes and noise perception algorithms is as follows: A preset quantum error correction code is selected for redundancy encoding. For the quantum bit information to be encoded, the encoding operation is performed according to the generator matrix of the preset quantum error correction code to generate the encoded quantum bit sequence. For noise perception, a noise monitoring cycle is set. In each cycle, the noise situation is perceived by measuring the decoherence time of the qubit. When noise interference is detected, the check matrix of the preset quantum error correction code is used to calculate the check quantum and a pre-established error mode mapping table is constructed. The corresponding error location and error type are found in the mapping table according to the value of the check quantum. Then, the erroneous qubit is corrected to restore the original correct qubit information.

5. The early warning system based on cable fault data analysis according to claim 4, characterized in that: In the data acquisition and transmission unit (2), the specific operation of encrypting different data using the multi-source data layered encryption architecture in the quantum encryption unit (1) is as follows: Cable operation data is categorized according to its frequency of change into critical real-time data, routine inspection data, and auxiliary reference data. For critical real-time data, a multi-layered encryption approach is adopted, using a quantum bit entanglement enhancement mechanism to generate a strong key, and then the data is redundantly encoded based on quantum error correction codes to obtain the encoded data. For routine inspection data, adaptive noise resistance quantum coding is first applied to it, and the coding method is selected according to the current environmental noise level to obtain the coded data. For auxiliary reference data, a lightweight key generated by qubit entanglement is used for direct XOR encryption.

6. The early warning system based on cable fault data analysis according to claim 5, characterized in that: The data acquisition and transmission unit (2) employs a multi-layered encryption method for critical real-time data, as follows: For critical real-time data, after generating a strong key K1 using a quantum bit entanglement enhancement mechanism, redundant encoding is performed using a [9, 6] quantum error-correcting code. Let the key real-time data be D1, which is divided into 6 qubit information blocks x1, x2, x3, x4, x5, x6. Encoding is performed according to the [9, 6] quantum error-correcting code generator matrix G1 to generate the encoded qubit sequence: X1=[x'1,x'2,...,x'9]=G1·[x1,x2,x3,x4,x5,x6] T ; The encoded data X1 is then XORed and encrypted using a strong key K1, resulting in the encrypted data.

7. The early warning system based on cable fault data analysis according to claim 6, characterized in that: The fault analysis and early warning unit (3) includes a decryption and verification module (31). The specific steps for decrypting and verifying the integrity of the data in the decryption and verification module (31) are as follows: After receiving encrypted data, the corresponding decryption key is first extracted. The decryption key is generated synchronously and securely stored when the quantum encryption unit (1) performs encryption. Different types of data correspond to different decryption keys. For the received encrypted data D' i Where i = 1, 2, 3 correspond to different data types, and the corresponding decryption key K is used. i Perform an XOR decryption operation to obtain the decrypted data. While decrypting, obtain the data integrity identifier H generated during the quantum encryption process based on the quantum hash function. q (D i For the decrypted data D i Recalculate its quantum hash function value H' q (D i ); Comparison H' q (D i ) and the original identifier H stored q (D i If the two are equal, the data is determined to be complete and untampered; if they are not equal, the data is determined to have encountered a problem during transmission, a data integrity error alarm is issued, and the corresponding data is requested to be resent.

8. The early warning system based on cable fault data analysis according to claim 7, characterized in that: The fault analysis and early warning unit (3) includes a risk judgment module (32). The specific algorithm for judging whether the cable has a fault risk based on the preset fault diagnosis model and threshold in the risk judgment module (32) is as follows: The preset fault diagnosis model adopts a neural network model, which is a three-layer neural network structure including an input layer, a hidden layer and an output layer. The number of nodes in the input layer is determined according to the number of selected cable fault features, the number of nodes in the hidden layer is set according to the number of nodes in the input layer, the activation function is the ReLU function, and the number of nodes in the output layer is 1, which is used to output the fault probability value. The neural network model is trained using historical cable operation data. The input feature data is normalized and then input into the neural network. The output fault probability value is compared with the actual fault label, and the weight parameters of the neural network are adjusted through the backpropagation algorithm. For the real-time decrypted and verified cable data to be judged, the corresponding feature data is extracted, normalized and input into the trained neural network model to obtain the output fault probability value. A fault risk threshold is set and compared with the fault probability value. Based on the comparison result, it is determined whether the cable has a fault risk.

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