Industrial non-intrusive measurement data transmission method and system based on wavelet transform compression

Abstract

The invention discloses an industrial non-intrusive measurement data transmission method and system based on wavelet transform compression. The method comprises the following steps: designing a data transmission protocol for I format information; the power system collects the equipment type, the operation mode, the real-time power, the real-time current, the transient power and the transient current on the production line, and uniquely encodes the equipment type and the operation mode; the power system monitors the start-stop state of electric equipment on the production line; transmitting a remote measurement value and a remote signaling value to a monitoring system; directly transmitting real-time power and real-time current through a network; the transient power and the transient current are compressed and then transmitted; the start-stop state of the electric equipment is directly transmitted through a network; data encryption is carried out before transmission; and the monitoring system carries out data decryption, verification and error processing on the received data. According to the invention, effective compression transmission of transient power and transient current data is realized, and high requirements of a modern industrial automation system on real-time performance and accuracy are met.

Description

Technical Field

[0001] The present invention belongs to the technical field of industrial automation and power system data transmission, and relates to an industrial non-intrusive measurement data transmission method and system based on wavelet transform compression. Background Art

[0002] In modern industrial automation systems, real-time monitoring and data collection of equipment are critical. These systems often need to collect and analyze large amounts of data to ensure optimal operation and maintenance of equipment. Previous data transmission methods often relied on intrusive connections, which meant that each electrical device needed to be equipped with instruments with communication capabilities. This approach not only increased the cost of deploying and maintaining measurement instruments, but also could affect the safety and stability of the equipment.

[0003] In order to solve the above problems, a non-invasive load monitoring method has been proposed. This method only requires the installation of a measuring instrument at the user entrance of the power grid, and the collected power consumption information is analyzed through an algorithm to monitor the power consumption status of each power-consuming device under it. For large-scale deployment scenarios, non-invasive load monitoring systems can significantly reduce installation complexity and reduce maintenance costs. However, existing non-invasive load monitoring methods have limitations in data transmission and processing. For example, the calculation method is relatively complex, and it is impossible to make accurate and effective judgments based on the actual power consumption of the target user, resulting in the inability to complete load decomposition in real time or near real time.

[0004] In addition, with the development of Industry 4.0 and intelligent manufacturing, the real-time and accuracy requirements for data transmission are getting higher and higher. In the power system, especially for the fault transient data of high-voltage transmission lines, a data compression method with a high compression ratio is required for compressing and recording fault transient data. Summary of the invention

[0005] In order to solve the deficiencies in the prior art, the present invention provides an industrial non-intrusive measurement data transmission method and system based on wavelet transform compression. By optimizing the discrete wavelet transform of the wavelet basis, effective compression transmission of transient power and transient current data is achieved, which not only improves the efficiency of data transmission, but also reduces the reconstruction error. It is suitable for the compression and recording of transient data of power system faults, and meets the high requirements of modern industrial automation systems for real-time and accuracy.

[0006] The present invention adopts the following technical solution.

[0007] The first aspect of the present invention provides an industrial non-intrusive measurement data transmission method based on wavelet transform compression, comprising:

[0008] Design a data transmission protocol for I-format information;

[0009] The power system collects telemetry values, including equipment type, operation mode, real-time power, real-time current, transient power and transient current on the production line, and uniquely encodes the equipment type and operation mode; at the same time, the power system monitors telesignal values, including the start and stop status of electrical equipment on the production line;

[0010] The telemetry value and telesignal value are transmitted to the monitoring system based on the data transmission protocol. The specific transmission method is as follows:

[0011] (1) directly transmitting the real-time power and real-time current through a network;

[0012] (2) compressing the transient power and transient current by wavelet transform and transmitting them;

[0013] (3) directly transmitting the start and stop status of the electrical equipment through the network;

[0014] The above (1)-(3) data are encrypted before transmission;

[0015] The monitoring system performs data decryption, verification and error processing on the received data based on the data transmission protocol.

[0016] Preferably, the data transmission protocol designed for I format information defines the data format, transmission rate, error detection and correction mechanism based on hash check and packet redundancy, and data security transmission mechanism based on double-layer encryption.

[0017] Preferably, the format of the data includes:

[0018] Header, including source address, destination address, and sequence number information;

[0019] Load, including telemetry value and telesignaling value;

[0020] The tail part includes the CRC checksum;

[0021] The extended field is used to identify whether each data packet has been hash-checked and redundancy-processed and to record related parameters;

[0022] Reserved field, used to transmit error statistics and retransmission request information fed back by the receiving end.

[0023] Preferably, the error detection and correction mechanism based on hash check and packet redundancy is applied to the entire process of data transmission, including:

[0024] Hash check part: The sender groups the data to be transmitted according to a fixed length, calculates the hash value of each group of data, obtains the hash code, and attaches the hash code to the end of the corresponding data group for transmission; after receiving the data, the receiver splits the data in the same grouping method, extracts the hash code at the end of each group of data, and recalculates the hash value of the group of data, and compares the calculated hash value with the received hash code bit by bit. If the two are completely consistent, it is considered that there is no error in the transmission of the group of data; if they are inconsistent, it indicates that there is an error in the group of data and further error correction is required;

[0025] Packet redundancy part: At the sending end, the data to be transmitted is grouped according to a fixed length. For each group of data, an additional redundant packet is generated, and the original data packet and the corresponding redundant packet are transmitted in sequence. At the receiving end, if an error is found in a group of data through hash verification, the receiving end uses the received redundant packet to correct the error.

[0026] Preferably, the redundant grouping is generated as follows:

[0027] The original data group is LDPC encoded. Through the LDPC encoding algorithm, check bits are generated according to the information bits in the original data group. The check bits and the original data bits together form a redundant group.

[0028] Preferably, the error correction strategy is as follows:

[0029] Error statistics and feedback: At the receiving end, the error situation of each group of data is counted, the number of erroneous data packets and the error type are recorded, and the error statistics information is regularly fed back to the sending end so that the sending end can understand the quality of data transmission and take corresponding measures;

[0030] Retransmission mechanism: If some data packets cannot be restored to correct state after error correction at the receiving end, the retransmission mechanism is started: the receiving end sends a retransmission request to the sending end, requesting the sending end to retransmit the erroneous data packets. After receiving the retransmission request, the sending end resends the corresponding data packets, and the receiving end performs error detection and correction again until all data packets are received correctly.

[0031] Preferably, the data security transmission mechanism based on double-layer encryption uses symmetric encryption and asymmetric encryption to encrypt and transmit data.

[0032] Preferably, (2) the transient power and the transient current are compressed and transmitted after wavelet transformation, comprising:

[0033] 1) Taking the transient power and transient current as the signals to be compressed, selecting the wavelet basis according to the characteristics of the signal to be compressed f(t) and performing discrete wavelet transform on the signal to be compressed to obtain a series of approximation coefficients cA with different decomposition scales j j and detail coefficient cD j ,cD j-1 ,…,cD1; the formula is as follows:

[0034] DWT(f(t))={cA j ,cD j ,cD j-1 ,…,cD1}

[0035] 2) Set the compression threshold according to the detail coefficient:

[0036]

[0037] Where M is the number of decomposition scales, α and β are adjustable parameters, std(cD j ) represents the detail coefficient cD j The standard deviation of

[0038] 3) All the values ​​less than the compression threshold η s The detail coefficient is set to zero to obtain the compressed detail coefficient:

[0039]

[0040] 4) Use the approximation coefficient and the compressed detail coefficient to perform inverse discrete wavelet transform to obtain the reconstructed signal:

[0041] f ′ (t) = IDWT({cA j ,cD j ′ ,cD j ′ -1 ,…,cD1 ′})

[0042] Preferably, the wavelet basis is selected as follows:

[0043] For transient signals with high-order singularities, a wavelet basis with a fairly vanishing moment is selected;

[0044] For weak transient signals detected in low-frequency carriers, a wavelet basis with a high center frequency is selected;

[0045] For transient signals extracted from narrowband interference, a high-order wavelet with narrow transition band and good frequency division capability is selected.

[0046] The second aspect of the present invention provides an industrial non-intrusive measurement data transmission system based on wavelet transform compression, comprising:

[0047] A transmission protocol design module, used to design a data transmission protocol for I format information;

[0048] The data acquisition module is used for the power system to collect telemetry values, including the equipment type, operation mode, real-time power, real-time current, transient power and transient current on the production line, and uniquely encode the equipment type and operation mode; the power system monitors the telemetering value, including the start and stop status of the electrical equipment on the production line;

[0049] A data transmission module is used to transmit the telemetry value and telesignaling value to the monitoring system based on the data transmission protocol, specifically to directly transmit the real-time power and real-time current through the network; to compress the transient power and transient current after wavelet transformation and transmit them; to directly transmit the start and stop status of the electric equipment through the network; and to encrypt the data before the transmission;

[0050] The data receiving module is used to monitor the system based on the data transmission protocol and perform data decryption, verification and error processing on the received data.

[0051] A third aspect of the present invention provides a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0052] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0053] Compared with the prior art, the beneficial effects of the present invention include at least:

[0054] The present invention can realize real-time monitoring of equipment status in industrial automation systems. Through discrete wavelet transform of wavelet basis, effective compression transmission of transient power and transient current data is realized, reducing the impact on equipment, improving the efficiency and security of data transmission, and reducing reconstruction errors. It is suitable for compression and recording of transient data of power system faults, meeting the high requirements of modern industrial automation systems for real-time performance and accuracy, and is suitable for various industrial automation systems.

[0055] The present invention can effectively transmit the real-time data and transient data of the equipment, while reducing the loss and delay in the data transmission process. It also provides a series of steps such as corresponding data transmission protocol design, telemetry value establishment, data encryption and decryption, error detection and processing, etc., to ensure the security and reliability of data transmission.

[0056] When the present invention performs wavelet transform compression, the wavelet basis is not selected based solely on a single signal feature, but rather the multi-dimensional characteristics of transient signals such as singularity, frequency, and interference environment are comprehensively considered. The wavelet basis is selected according to the characteristics of the signal, which can ensure the best time and frequency resolution and achieve the best signal decomposition and feature extraction.

[0057] When the present invention performs wavelet transform compression, the compression threshold is set according to the detail coefficient, specifically according to the average value and standard deviation of the detail coefficient, and the threshold can be dynamically adjusted according to the overall distribution characteristics of the signal. When the signal fluctuates greatly, the weight of the standard deviation part is increased, so that the threshold can better adapt to the signal change and avoid the loss of important information caused by excessive compression; when the signal is relatively stable, the average value part is dominant, and the signal details are reasonably retained, thereby improving the stability and accuracy of the compression effect.

[0058] When setting the compression threshold according to the detail coefficient, the present invention introduces adjustable parameters α and β, so that the threshold setting can be adaptively optimized according to different industrial scenarios and signal characteristics. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a flow chart of the industrial non-intrusive measurement data transmission method based on wavelet transform compression of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical scheme and advantages of the present invention clearer, the technical scheme of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. The embodiments described in this application are only part of the embodiments of the present invention, not all of them. Based on the spirit of the present invention, other embodiments obtained by ordinary technicians in this field without creative work are all within the scope of protection of the present invention.

[0061] Embodiment 1 of the present invention provides an industrial non-intrusive measurement data transmission method based on wavelet transform compression, such as Figure 1 As shown, the following steps are included:

[0062] Step 1: Design a data transmission protocol for I format information;

[0063] Further preferably, this step involves creating a standardized data transmission protocol, which is specially designed for I format information to ensure data standardization and compatibility.

[0064] The data transmission protocol will define the data format, transmission rate, error detection and correction mechanism based on hash check and packet redundancy, and data security transmission mechanism based on double-layer encryption.

[0065] Assume that in a steel manufacturing enterprise, it is necessary to monitor the operating status of various equipment on the production line in real time and to efficiently transmit transient data of the power system. In this embodiment, the protocol defines the structure of the data packet as follows:

[0066] Header: Contains information such as source address, destination address, and sequence number.

[0067] Load: Contains actual data such as telemetry values ​​and telesignaling values.

[0068] Tail: contains CRC check code;

[0069] The extended field is used to identify whether each data packet has been hash-checked and redundancy-processed, and to record related parameters;

[0070] Reserved field, used to transmit error statistics and retransmission request information fed back by the receiving end.

[0071] Error detection and correction mechanism based on hash check and packet redundancy:

[0072] 1. Overall idea:

[0073] Combining the characteristics of hash functions with the idea of ​​group redundancy, efficient and reliable error detection and correction can be achieved during data transmission, ensuring the integrity and accuracy of data, and meeting the special needs of industrial non-intrusive measurement data transmission.

[0074] 2. Specific design:

[0075] (I) Hash verification part:

[0076] Hash function selection and data grouping:

[0077] Select a hash function with good collision resistance and avalanche effect: SHA-256 (Secure Hash Algorithm 256-bit). At the sending end, the data to be transmitted is grouped according to a fixed length, with each group consisting of 1024 bytes.

[0078] For each set of data, calculate its SHA-256 hash value to obtain a 256-bit hash code, which is then attached to the end of the corresponding data packet for transmission.

[0079] Receiver verification:

[0080] After receiving the data, the receiving end splits the data in the same grouping method. For each group of data, the hash code at the end is extracted and the SHA-256 hash value of the group of data is recalculated.

[0081] The calculated hash value is compared bit by bit with the received hash code. If the two are completely consistent, it is considered that there is no error in the transmission of the group of data; if they are inconsistent, it indicates that there is an error in the group of data and further error correction is required.

[0082] (II) Packet redundancy part:

[0083] Data grouping and redundancy generation:

[0084] The data is grouped according to the fixed length of 1024 bytes. For each group of data, an additional redundant group is generated. The redundant group is generated as follows:

[0085] The original data packets are subjected to specific encoding operations, using low-density parity check (LDPC) encoding. Through the LDPC encoding algorithm, a certain number of check bits are generated according to the information bits in the original data packets, and these check bits and the original data bits together form redundant packets. Assuming that the original data packet is D, after LDPC encoding, the redundant packet R is obtained. The length of R will be slightly longer than D. The specific length depends on the parameter setting of LDPC encoding: the number of check bits is 1 / 4 of the number of original data bits.

[0086] Redundant packet transmission and error correction:

[0087] The original data packets and the corresponding redundant packets are transmitted in sequence. At the receiving end, if a certain group of data is found to have errors through hash verification, the receiving end uses the received redundant packets to correct the errors.

[0088] The LDPC decoding algorithm is used to jointly process the original data packets containing errors and the redundant packets. The LDPC decoding algorithm corrects the error bits in the data packets through iterative calculations based on the relationship between the check bits and the information bits. During the iteration process, the estimation of the error bits is continuously updated until certain convergence conditions are met (such as reaching a preset number of iterations or the bit error rate is lower than a certain threshold), thereby recovering the correct original data packets.

[0089] (III) Error handling strategy:

[0090] Error statistics and feedback:

[0091] At the receiving end, the error situation of each group of data is counted. The number of data packets with errors and the error type (such as hash check failure, error correction failure, etc.) are recorded. These error statistics are regularly fed back to the sending end so that the sending end can understand the quality of data transmission and take corresponding measures (such as adjusting transmission parameters, checking device status, etc.).

[0092] Retransmission mechanism:

[0093] If some data packets cannot be restored to correctness after error correction at the receiving end (for example, the error correction failure rate exceeds a certain threshold of 5%), the retransmission mechanism is started. The receiving end sends a retransmission request to the sending end, requesting the sending end to retransmit these erroneous data packets. After receiving the retransmission request, the sending end resends the corresponding data packets, and the receiving end performs error detection and correction again until all data packets are received correctly.

[0094] (IV) Integration with data transmission protocols:

[0095] Protocol field extension:

[0096] In the data transmission protocol, the corresponding fields are extended to support the error detection and correction mechanism. A field is added to identify whether each data packet has been hash-checked and redundancy-processed, and to record related parameters (such as hash function type, redundant packet generation method, etc.).

[0097] In addition, the reserved field is used to transmit control information such as error statistics and retransmission requests fed back by the receiving end, ensuring that the sending and receiving ends can correctly parse and process this information related to error detection and correction.

[0098] Data processing flow adjustment:

[0099] The processing steps of this error detection and correction mechanism are inserted into the entire process of data transmission. At the sending end, before data grouping and transmission, hash calculation, redundant group generation and other operations are performed first; at the receiving end, after receiving the data, hash verification, error correction and other processing are performed first, and then the correct data is passed to the subsequent processing module.

[0100] Double-layer encryption mechanism:

[0101] 1. Mechanism Overview:

[0102] The double-layer encryption mechanism combines the advantages of symmetric encryption and asymmetric encryption to ensure high security and confidentiality of data during transmission. In the present invention, AES (Advanced Encryption Standard) is used as the symmetric encryption algorithm and RSA (Rivest-Shamir-Adleman) is used as the asymmetric encryption algorithm.

[0103] 2. Detailed design:

[0104] 2.1 Symmetric encryption layer (AES):

[0105] Mechanism: Use the AES algorithm to encrypt data. The AES algorithm is a symmetric encryption algorithm that is efficient and secure and is suitable for encrypting large amounts of data.

[0106] step:

[0107] Generate symmetric key: Generate a random symmetric key (for example, a 256-bit AES key) on the sending end.

[0108] Data encryption: AES encrypts data using a generated symmetric key.

[0109] Key transmission: The generated symmetric key is transmitted to the receiving end through an asymmetric encryption layer.

[0110] 2.2 Asymmetric encryption layer (RSA):

[0111] Mechanism: Use the RSA algorithm to encrypt the symmetric key. The RSA algorithm is an asymmetric encryption algorithm with the characteristics of key distribution security and is suitable for key transmission.

[0112] step:

[0113] Generate public and private keys: Generate a pair of RSA public and private keys at the sender and receiver respectively.

[0114] Key encryption: Use the public key of the receiving end to perform RSA encryption on the generated symmetric key.

[0115] Key transmission: The encrypted symmetric key is transmitted to the receiving end through the network.

[0116] Key decryption: The receiving end uses its own private key to decrypt the encrypted symmetric key and recover the symmetric key.

[0117] Data decryption: Use the recovered symmetric key to perform AES decryption on the encrypted data to restore the original data.

[0118] Step 2: The power system collects telemetry values, including equipment type, operation mode, real-time power, real-time current, transient power and transient current on the production line, and uniquely encodes the equipment type and operation mode;

[0119] Power system monitoring telesignal values, including the start and stop status of electrical equipment on the production line;

[0120] Further preferably, step 2.1: establishing telemetry values, including but not limited to device type, operation mode, real-time power, real-time current, transient power and transient current;

[0121] In this step, the system will collect and establish telemetry values, including but not limited to equipment type, operation mode, real-time power, real-time current, transient power and transient current, which will provide the system with comprehensive operation status information of the equipment. For example, for a steel mill in a steel enterprise, the system will collect information such as its operation status, real-time power consumption, and current intensity.

[0122] Step 2.2: Encode the device type and mode in a pre-agreed manner;

[0123] To standardize data transmission, this step involves pre-agreed coding of device types and modes. This means assigning a unique identifier or code to each device type and mode so that it can be easily identified during data transmission.

[0124] The pre-agreed coding assigns a unique identifier or code to each equipment type and mode. For example, the following identifiers are assigned to the equipment of a steel enterprise:

[0125] Device Type Code

[0126] Rolling mill: 001

[0127] Smelting furnace: 002

[0128] Conveyor belt: 003

[0129] Motor: 004

[0130] Crusher: 005

[0131] Mode Encoding

[0132] Operation mode: 01

[0133] Maintenance mode: 02

[0134] Stop mode: 03

[0135] Step 2.3: Establish telesignal values, including the start and stop status of the equipment;

[0136] This step involves monitoring the start and stop status of the equipment and transmitting this status information as a telesignal value. This information is essential for remote monitoring and control of equipment. For example, if the start and stop status of a rolling mill at a certain moment is "start", the telesignal value is 1.

[0137] Step 3: Based on the data transmission protocol, the telemetry value and the telesignaling value are transmitted to the monitoring system. The specific transmission method is as follows:

[0138] (1) directly transmitting the real-time power and real-time current through a network;

[0139] This step involves transmitting the real-time power and real-time current data directly to the monitoring system through the network. These data will not be compressed to ensure the real-time and accuracy of the data. For example, the real-time power of the rolling mill at a certain moment is 500kW and the real-time current is 1000A. These data will be transmitted to the monitoring center in plain text.

[0140] (2) compressing the transient power and transient current by wavelet transform and transmitting them;

[0141] This step is the core of the present invention, and involves compressing transient power and transient current data using a compression algorithm based on an optimized wavelet basis. Specifically, it includes:

[0142] Data preparation: Obtain transient power and transient current data, which are usually collected by sensors, such as fault transient data from the power system; assume that sample data of transient power and transient current have been obtained from the power system. Here, a transient current signal of length N is taken as an example.

[0143] 1) Wavelet transform: Apply a fixed wavelet basis to perform discrete wavelet transform (DWT) on the above data;

[0144] Select a suitable wavelet basis to perform discrete wavelet transform (DWT) on the above data. Apply the optimally selected wavelet basis to perform discrete wavelet transform (DWT) on the above data.

[0145] The transient power and transient current are used as the signals to be compressed, and a wavelet basis is selected according to the characteristics of the signal to be compressed f(t) (which can be either a transient power signal or a transient current signal) and a discrete wavelet transform is performed on the signal to be compressed to obtain a series of approximation coefficients cA with different decomposition scales j. j and detail coefficient cD j ,cD j-1 ,…,cD1; the formula is as follows:

[0146] DWT(f(t))={cA j ,cD j ,cD j-1 ,…,cD1}

[0147] As a powerful tool for analyzing non-stationary signals, wavelet transform has demonstrated its superiority in power fault transient data compression. However, the compression ratio and reconstruction error are closely related to the selection of wavelet basis. If the wavelet basis is not selected well, the compression effect is not ideal. In the present invention, the wavelet basis is selected according to the characteristics of the signal to ensure the best time and frequency resolution and achieve the best signal decomposition and feature extraction.

[0148] The optimally selected wavelet basis is based on the characteristics of the signal to be transmitted, including:

[0149] For power transient signals with high-order singularities, a wavelet basis with a fairly vanishing moment is selected to better capture the mutation characteristics of the signal;

[0150] For detecting weak transients in low-frequency carriers, a wavelet basis with a higher center frequency is selected;

[0151] To extract transient signals from narrowband interference, a high-order wavelet with a narrow transition band and good frequency division capability is selected.

[0152] Further preferably, the present invention does not only select the wavelet basis based on a single signal feature, but also comprehensively considers the characteristics of the transient signal in multiple dimensions such as singularity, frequency and interference environment.

[0153] For transient signals with high-order singularities, a wavelet basis with a considerable vanishing moment is selected. This is because high-order singular signals have complex changes near the mutation point, and a wavelet basis with a considerable vanishing moment can better capture and characterize these mutations, so that the key information of the signal can be more accurately retained during the compression process, reducing signal distortion caused by compression. For example, in the transient data of power system faults, the current and power changes at the moment of the fault often have high-order singularities. A suitable wavelet basis can effectively extract fault features and provide an accurate basis for subsequent fault diagnosis.

[0154] For weak transient signals detected in low-frequency carriers, a wavelet basis with a high center frequency is selected. In industrial environments, weak transient signals in the background of low-frequency carrier signals are easily submerged. Wavelets with a high center frequency can enhance the resolution of such signals and improve the significance of their coefficients after wavelet transform, thereby better retaining these weak but potentially critical signal information during compression. This is a comprehensive optimization strategy that is difficult for technicians in the field to directly think of when facing complex industrial signal environments.

[0155] For transient signals extracted from narrowband interference, a high-order wavelet with a narrow transition band and good frequency division capability is selected. Narrowband interference will affect the extraction and analysis of transient signals. By selecting a specific wavelet basis, the present invention can effectively isolate narrowband interference during the compression process and better separate transient signals from the interference environment. At the same time, good frequency division capability helps to accurately characterize signals in different frequency bands, further improving the quality of compression and reconstruction.

[0156] 1. Transient signal with high-order singularity - power system short-circuit fault current signal

[0157] 1. Signal characteristics

[0158] When a short circuit occurs in a power system, the current will change dramatically in an instant, rising rapidly from the normal operating value to a very high value, and then there may be oscillation attenuation. This rapid change and mutation reflects high-order singularity. For example, in a simple power system model, the current is stable at around 5A during normal operation. When a short circuit occurs at a certain moment (assuming t = 0.1s), the current rises rapidly to 500A, and then oscillates and decays in the next 0.2s, which is similar to the superposition of an impulse function and an attenuated oscillation function.

[0159] 2. Wavelet basis selection and processing

[0160] For this transient current signal with high-order singularity, the db5 wavelet base among the Daubechies wavelet bases is selected. It has a higher vanishing moment (N=5) and can capture the sudden change part of the signal well.

[0161] Perform discrete wavelet transform on the collected short-circuit fault current signal i(t):

[0162] DWT db5 (i(t)) = cA j ,cD j ,cD j-1 ,…,cD1

[0163] Assume the sampling frequency is f s =20kHz, sampling points N = 4000 (corresponding to a duration of 0.2s). After wavelet transform, the detail coefficients cD3 and cD4 clearly show the peak and oscillation characteristics corresponding to the short-circuit fault moment. These coefficients accurately reflect the mutation and oscillation of the current signal. The lower-order detail coefficients (such as cD1 and cD2) mainly reflect the high-frequency noise and some fast small fluctuations of the signal. j The low-frequency trend information of the signal is contained in . Through the selection and transformation of this wavelet basis, in the subsequent data compression process, key information can be more effectively retained according to these coefficient characteristics, noise can be removed, compression ratio can be improved, and reconstruction error can be reduced.

[0164] 2. Weak transient signals detected in low-frequency carriers - equipment startup current signals under low-frequency carrier communication in power systems;

[0165] 1. Signal characteristics

[0166] In the low-frequency carrier communication environment of the power system, there is usually a carrier signal with a frequency of 50Hz or 60Hz. When the equipment starts, a relatively weak transient current signal is generated and superimposed on the carrier signal. For example, the amplitude of the weak transient current signal when the equipment starts is small, about 0.1A-1A, and its frequency components are mainly concentrated between 100Hz-300Hz, while the carrier signal amplitude is large, which may reach 5A-10A. This weak transient current signal is easily submerged by the carrier signal because of its small amplitude and frequency close to the carrier.

[0167] 2. Wavelet basis selection and processing

[0168] The coif4 wavelet basis is selected from the Coiflet wavelet basis, which has a relatively high center frequency and can better focus on the frequency band where the weak transient signal is located in the frequency domain.

[0169] Assume that the weak transient current signal is i w (t), perform discrete wavelet transform on it

[0170] DWT coif4 (i w (t)) = cA j ,cD j ,cD j-1 ,…,cD1

[0171] The sampling frequency is f s =10kHz, number of sampling points N = 2000 (corresponding to a duration of 0.2s). After wavelet transform, in detail coefficients cD2 and cD3, the characteristics of weak transient current signals are enhanced, and their coefficient amplitudes are more obvious than those under other unsuitable wavelet basis transforms, while the influence of carrier signals is relatively weakened. This enables more accurate identification and extraction of weak transient current signals in subsequent data processing, improves the accuracy of data transmission, and avoids the loss or confusion of weak transient signal information during compression and transmission.

[0172] 3. Transient signals extracted from narrowband interference The transient power signal of motor speed regulation in industrial environment is affected by narrowband interference

[0173] 1. Signal characteristics

[0174] In industrial environments, transient power signals are generated during motor speed regulation, but there is also narrowband interference from other devices. For example, the frequency of transient power signals generated by motor speed regulation is mainly between 200Hz-800Hz, and the amplitude varies between 100W-1000W. However, there is a narrowband interference signal with a frequency of 450Hz-550Hz, and its amplitude may reach 50W-200W, which will interfere with the accurate monitoring and analysis of the transient power signal of the motor.

[0175] 2. Wavelet basis selection and processing

[0176] Based on the sym6 wavelet base in the Symlet wavelet base, a high-order wavelet (N=6) with a narrow transition band and good frequency division ability is used and modified.

[0177] Assume that the transient power signal of the motor speed regulation is p(t), and perform discrete wavelet transform on it

[0178] DWT sym6 (p(t)) = cA j ,cD j ,cD j-1 ,…,cD1

[0179] The sampling frequency is f s=5kHz, number of sampling points N=1000. After wavelet transform, the narrowband interference signal is mainly concentrated in the detail coefficient cD4, while the main characteristics of the motor speed regulation transient power signal are clearly reflected in coefficients such as cD2 and cD3. In this way, in the subsequent data compression and processing, the coefficients containing the transient power signal characteristics can be processed in a targeted manner, effectively removing the influence of narrowband interference, improving compression efficiency and reconstruction quality, so as to more accurately transmit and analyze the transient power signal in the motor speed regulation process, and provide reliable data support for equipment monitoring and optimized operation in industrial automation systems.

[0180] 2) Setting threshold: Determine a threshold to distinguish important signal features from noise;

[0181] After wavelet transform, a series of wavelet coefficients of different scales are obtained. Next, an adaptive threshold processing method is used to dynamically adjust the threshold according to the characteristics and importance of the signal, and a threshold is adaptively determined to more accurately distinguish signal characteristics and noise.

[0182] The selection of the threshold is based on the characteristics of the signal. For example, for the voltage drop part, a larger threshold may be selected, while for the oscillation part, a smaller threshold may be selected. This adaptive threshold selection helps to remove noise and unnecessary information while retaining the key features of the signal. The set threshold is to retain all coefficients that are greater than a certain multiple of the average absolute value.

[0183] Further preferably, the compression threshold is set according to the detail coefficient:

[0184]

[0185] Where M is the number of decomposition scales, α and β are adjustable parameters (0<α<1, 0<β<1), std(cD j ) represents the detail coefficient cD j The standard deviation of .

[0186] Specifically, according to the mean and standard deviation settings of the detail coefficient, the threshold can be dynamically adjusted according to the overall distribution characteristics of the signal. When the signal fluctuates greatly, the weight of the standard deviation part increases, so that the threshold can better adapt to the signal changes and avoid the loss of important information due to excessive compression; when the signal is relatively stable, the mean value part dominates, reasonably retaining the signal details, thereby improving the stability and accuracy of the compression effect.

[0187] The introduction of adjustable parameters allows the threshold setting to be adaptively optimized according to different industrial scenarios and signal characteristics. For example, when processing transient data of power system faults, the parameters can be adjusted according to the fault type and data importance. For key data, α can be appropriately reduced and β can be increased to improve the accuracy of data retention; for general data monitoring, the parameters can be appropriately adjusted to obtain a higher compression ratio, improve transmission efficiency while ensuring a certain data quality, and enhance the adaptability of the entire system to different application scenarios.

[0188] 3) Data compression: set detail coefficients smaller than the threshold to zero;

[0189] will be less than the threshold η s The detail coefficients are set to zero, and only those coefficients that are significantly greater than the threshold are retained. This can effectively remove noise and unnecessary information and achieve data compression. In addition, important wavelet coefficients are selectively retained through multi-scale analysis to further improve compression efficiency.

[0190] The data compression step includes multi-scale analysis based on wavelet transform, selectively retaining important wavelet coefficients to improve compression efficiency. The fewer coefficients retained, the higher the compression ratio, but at the same time, more reconstruction errors may be introduced. The compressed data is expressed as:

[0191]

[0192] 4) Data reconstruction: An inverse discrete wavelet transform (IDWT) is performed using the retained coefficients to reconstruct the original signal.

[0193] An inverse discrete wavelet transform (IDWT) is performed using the retained coefficients to reconstruct the original signal.

[0194] The formula for reconstructing the signal f′(t) is:

[0195] f ′ (t) = IDWT({cA j ,cD j ′ ,cD j ′ -1 ,…,cD1 ′})

[0196] During the reconstruction process, the compression ratio is defined as the ratio of the original data volume to the compressed data volume, and the reconstruction error is the mean square error between the original signal and the reconstructed signal.

[0197] Calculate the compression ratio r and reconstruction mean square error d to objectively evaluate the effect of data compression:

[0198]

[0199] Where f(t) is the original signal data to be compressed, and f′(t) is the reconstructed signal data.

[0200] (3) directly transmitting the start and stop status of the electrical equipment through the network;

[0201] The above (1)-(3) data are encrypted before transmission;

[0202] To ensure the security of data transmission, this step involves encryption before data transmission. Specifically, the compressed data is encrypted using a data security transmission mechanism based on double-layer encryption. After encryption, the data is transmitted to the receiving end through a secure communication interface. The receiving end then uses the same key for decryption to restore the original compressed data and finally reconstruct the data.

[0203] Step 4: The monitoring system decrypts, verifies and handles errors on the received data based on the data transmission protocol.

[0204] (1) Decryption is performed at the receiving end to ensure the security of data transmission. This can prevent data from being intercepted or tampered with during transmission.

[0205] To ensure the security of data transmission, the present invention encrypts the data before transmission and decrypts it at the receiving end.

[0206] (2) Data verification and error handling to ensure data integrity and accuracy.

[0207] This step involves checking during data transmission to ensure the integrity and accuracy of the data. If an error is detected, the system will take error handling measures, such as requesting retransmission or using error correction mechanisms.

[0208] Through the above steps, the present invention provides an effective industrial non-intrusive measurement data transmission method, which not only improves the efficiency and security of data transmission through the wavelet-based compression algorithm, but is also applicable to various industrial automation systems, such as power system monitoring and fault diagnosis in steel enterprises.

[0209] Embodiment 2 of the present invention provides an industrial non-intrusive measurement data transmission system based on wavelet transform compression, comprising:

[0210] A transmission protocol design module, used to design a data transmission protocol for I format information;

[0211] The data acquisition module is used for the power system to collect telemetry values, including the equipment type, operation mode, real-time power, real-time current, transient power and transient current on the production line, and uniquely encode the equipment type and operation mode; the power system monitors the telemetering value, including the start and stop status of the electrical equipment on the production line;

[0212] A data transmission module is used to transmit the telemetry value and telesignaling value to the monitoring system based on the data transmission protocol, specifically to directly transmit the real-time power and real-time current through the network; to compress the transient power and transient current after wavelet transformation and transmit them; to directly transmit the start and stop status of the electric equipment through the network; and to encrypt the data before the transmission;

[0213] The data receiving module is used to monitor the system based on the data transmission protocol and perform data decryption, verification and error processing on the received data.

[0214] Embodiment 3 of the present invention provides a terminal, including a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the method.

[0215] Embodiment 4 of the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the method when executed by a processor.

[0216] Compared with the prior art, the beneficial effects of the present invention include at least:

[0217] The present invention can realize real-time monitoring of equipment status in industrial automation systems. Through discrete wavelet transform of wavelet basis, effective compression transmission of transient power and transient current data is realized, reducing the impact on equipment, improving the efficiency and security of data transmission, and reducing reconstruction errors. It is suitable for compression and recording of transient data of power system faults, meeting the high requirements of modern industrial automation systems for real-time performance and accuracy, and is suitable for various industrial automation systems.

[0218] The present invention can effectively transmit the real-time data and transient data of the equipment, while reducing the loss and delay in the data transmission process. It also provides a series of steps such as corresponding data transmission protocol design, telemetry value establishment, data encryption and decryption, error detection and processing, etc., to ensure the security and reliability of data transmission.

[0219] When the present invention performs wavelet transform compression, the wavelet basis is not selected based solely on a single signal feature, but rather the multi-dimensional characteristics of transient signals such as singularity, frequency, and interference environment are comprehensively considered. The wavelet basis is selected according to the characteristics of the signal, which can ensure the best time and frequency resolution and achieve the best signal decomposition and feature extraction.

[0220] When the present invention performs wavelet transform compression, the compression threshold is set according to the detail coefficient, specifically according to the average value and standard deviation of the detail coefficient, and the threshold can be dynamically adjusted according to the overall distribution characteristics of the signal. When the signal fluctuates greatly, the weight of the standard deviation part is increased, so that the threshold can better adapt to the signal change and avoid the loss of important information caused by excessive compression; when the signal is relatively stable, the average value part is dominant, and the signal details are reasonably retained, thereby improving the stability and accuracy of the compression effect.

[0221] When setting the compression threshold according to the detail coefficient, the present invention introduces adjustable parameters α and β, so that the threshold setting can be adaptively optimized according to different industrial scenarios and signal characteristics.

[0222] The present disclosure may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present disclosure.

[0223] A computer-readable storage medium may be a tangible device that can hold and store instructions used by an instruction execution device. A computer-readable storage medium may be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples of computer-readable storage media (a non-exhaustive list) include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination of the foregoing. As used herein, a computer-readable storage medium is not to be interpreted as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through a wire.

[0224] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in the computer-readable storage medium in each computing / processing device.

[0225] The computer program instructions for performing the operation of the present disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages, such as Smalltalk, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. Computer-readable program instructions may be executed completely on a user's computer, partially on a user's computer, as an independent software package, partially on a user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), may be customized by utilizing the state information of the computer-readable program instructions, and the electronic circuit may execute the computer-readable program instructions, thereby realizing various aspects of the present disclosure.

[0226] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents, and any modifications or equivalent replacements that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An industrial non-intrusive measurement data transmission method based on wavelet transform compression, characterized in that: include: Design a data transmission protocol for I-format information; The power system collects telemetry values, including equipment type, operation mode, real-time power, real-time current, transient power and transient current on the production line, and uniquely encodes the equipment type and operation mode; at the same time, the power system monitors telesignal values, including the start and stop status of electrical equipment on the production line; The telemetry value and telesignal value are transmitted to the monitoring system based on the data transmission protocol. The specific transmission method is as follows: (1) directly transmitting the real-time power and real-time current through a network; (2) compressing the transient power and transient current by wavelet transform and transmitting them; (3) directly transmitting the start and stop status of the electrical equipment through the network; The above (1)-(3) data are encrypted before transmission; The monitoring system performs data decryption, verification and error processing on the received data based on the data transmission protocol.

2. The industrial non-intrusive measurement data transmission method based on wavelet transform compression according to claim 1 is characterized in that: The data transmission protocol designed for I format information defines the data format, transmission rate, error detection and correction mechanism based on hash check and packet redundancy, and data security transmission mechanism based on double-layer encryption.

3. The industrial non-intrusive measurement data transmission method based on wavelet transform compression according to claim 2 is characterized in that: The formats of the data include: Header, including source address, destination address, and sequence number information; Load, including telemetry value and telesignaling value; The tail part includes the CRC checksum; The extended field is used to identify whether each data packet has been hash-checked and redundancy-processed and to record related parameters; Reserved field, used to transmit error statistics and retransmission request information fed back by the receiving end.

4. The industrial non-intrusive measurement data transmission method based on wavelet transform compression according to claim 2 is characterized in that: The error detection and correction mechanism based on hash check and packet redundancy is applied to the entire process of data transmission, including: Hash check part: The sender groups the data to be transmitted according to a fixed length, calculates the hash value of each group of data, obtains the hash code, and attaches the hash code to the end of the corresponding data group for transmission; after receiving the data, the receiver splits the data in the same grouping method, extracts the hash code at the end of each group of data, and recalculates the hash value of the group of data, and compares the calculated hash value with the received hash code bit by bit. If the two are completely consistent, it is considered that there is no error in the transmission of the group of data; if they are inconsistent, it indicates that there is an error in the group of data and further error correction is required; Packet redundancy part: At the sending end, the data to be transmitted is grouped according to a fixed length. For each group of data, an additional redundant packet is generated, and the original data packet and the corresponding redundant packet are transmitted in sequence. At the receiving end, if an error is found in a group of data through hash verification, the receiving end uses the received redundant packet to correct the error.

5. The industrial non-intrusive measurement data transmission method based on wavelet transform compression according to claim 4 is characterized in that: The redundant grouping is generated as follows: The original data group is LDPC encoded. Through the LDPC encoding algorithm, check bits are generated according to the information bits in the original data group. The check bits and the original data bits together form a redundant group.

6. The industrial non-intrusive measurement data transmission method based on wavelet transform compression according to claim 4 is characterized in that: The error correction strategy is as follows: Error statistics and feedback: At the receiving end, the error situation of each group of data is counted, the number of erroneous data packets and the error type are recorded, and the error statistics information is regularly fed back to the sending end so that the sending end can understand the quality of data transmission and take corresponding measures; Retransmission mechanism: If some data packets cannot be restored to correct state after error correction at the receiving end, the retransmission mechanism is started: the receiving end sends a retransmission request to the sending end, requesting the sending end to retransmit the erroneous data packets. After receiving the retransmission request, the sending end resends the corresponding data packets, and the receiving end performs error detection and correction again until all data packets are received correctly.

7. The industrial non-intrusive measurement data transmission method based on wavelet transform compression according to claim 2 is characterized in that: The data security transmission mechanism based on double-layer encryption adopts symmetric encryption and asymmetric encryption to encrypt and transmit data.

8. The industrial non-intrusive measurement data transmission method based on wavelet transform compression according to claim 1 is characterized in that: The (2) performing wavelet transformation compression on the transient power and the transient current and then transmitting the same comprises: 1) Taking the transient power and transient current as the signals to be compressed, selecting the wavelet basis according to the characteristics of the signal to be compressed f(t) and performing discrete wavelet transform on the signal to be compressed to obtain a series of approximation coefficients cA with different decomposition scales j j and detail coefficient cD j ,cD j-1 ,…,cD1; the formula is as follows: DWT(f(t))={cA j ,cD j ,cD j-1 ,…,cD1} 2) Set the compression threshold according to the detail coefficient: Where M is the number of decomposition scales, α and β are adjustable parameters, std(cD j ) represents the detail coefficient cD j The standard deviation of 3) All the values ​​less than the compression threshold η s The detail coefficient is set to zero to obtain the compressed detail coefficient: 4) Use the approximation coefficient and the compressed detail coefficient to perform inverse discrete wavelet transform to obtain the reconstructed signal: f ′ (t)=IDWT({cA j ,cD j ′ ,cD j ′ -1 ,…,cD1 ′ })。 9. The industrial non-intrusive measurement data transmission method based on wavelet transform compression according to claim 8, characterized in that: The wavelet basis is selected as follows: For transient signals with high-order singularities, a wavelet basis with a fairly vanishing moment is selected; For weak transient signals detected in low-frequency carriers, a wavelet basis with a high center frequency is selected; For transient signals extracted from narrowband interference, a high-order wavelet with narrow transition band and good frequency division capability is selected.

10. An industrial non-intrusive measurement data transmission system based on wavelet transform compression, using the method according to any one of claims 1 to 9, characterized in that: The system comprises: A transmission protocol design module, used to design a data transmission protocol for I format information; The data acquisition module is used for the power system to collect telemetry values, including the equipment type, operation mode, real-time power, real-time current, transient power and transient current on the production line, and uniquely encode the equipment type and operation mode; the power system monitors the telemetering value, including the start and stop status of the electrical equipment on the production line; A data transmission module is used to transmit the telemetry value and telesignaling value to the monitoring system based on the data transmission protocol, specifically to directly transmit the real-time power and real-time current through the network; to compress the transient power and transient current after wavelet transformation and transmit them; to directly transmit the start and stop status of the electric equipment through the network; and to encrypt the data before the transmission; The data receiving module is used to monitor the system based on the data transmission protocol and perform data decryption, verification and error processing on the received data.

11. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1-9.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 9 are implemented.

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