Industrial internet data acquisition system

Abstract

The invention discloses an industrial internet data acquisition system which comprises a data acquisition terminal, a multi-protocol adaptive conversion module, a real-time data processing engine, a distributed redundancy storage module, a data transmission module, a central control module, a modular expansion interface, an anti-interference optimization module and a power management module. According to the invention, the anti-interference optimization module and the anti-interference design of each module effectively reduce the influence of electromagnetic, vibration, temperature and other interferences on the system in the industrial environment, so that the system can stably operate in the complex industrial environment, the data acquisition is more accurate and reliable, and the system is more suitable for the actual industrial use scene; the distributed redundancy storage module adopts a multi-node storage architecture to ensure redundancy storage of data, and data transmission adopts a 5G + wired dual-transmission mode, so that the reliability of data transmission and storage is improved, and the risk of data loss and errors is reduced.

Description

TECHNICAL FIELD

[0001] The application relates to an industrial internet data acquisition system, in particular to an industrial internet data acquisition system, and belongs to the technical field of digital data processing. BACKGROUND

[0002] A large amount of data is generated in the industrial production process, and if the current production state is directly understood by using the data, a large amount of effort needs to be spent, and the industrial internet data acquisition system as the core basis of the industrial digital transformation facilitates timely processing of information.

[0003] Through retrieval, the Chinese patent No. CN118152869A discloses an industrial internet data acquisition system, which comprises a multi-source data acquisition module, a high-speed big data processing module, a data storage module and a user interface module. By compressing and fusing a large amount of raw data collected, key information can be effectively extracted as the final acquisition result, and the efficiency of mastering the industrial production state is improved. However, the above-mentioned patent product does not consider the label mislabeling caused by electromagnetic interference and vibration. In actual use, industrial environment interference is a key challenge affecting data acquisition, transmission and processing. If the data is disturbed by the industrial environment, the false positive rate of the key information of the data will be greatly increased, causing unnecessary loss. SUMMARY

[0004] The purpose of the present application is to provide an industrial internet data acquisition system to solve the above problems.

[0005] The present application achieves the above-mentioned purpose by the following technical scheme, an industrial internet data acquisition system, comprising a data acquisition terminal, a multi-protocol adaptive conversion module, a real-time data processing engine, a distributed redundant storage module, a data transmission module, a central control module, a modular expansion interface, an anti-interference optimization module and a power management module.

[0006] The data acquisition terminal is used for collecting various types of data in the industrial field and sending them to the multi-protocol adaptive conversion module. The data acquisition terminal comprises a sensor group and an intelligent instrument. The sensor group is used for collecting physical quantity data in the industrial field, and the intelligent instrument is used for collecting operating parameter data of industrial equipment.

[0007] The multi-protocol adaptive conversion module is used for converting data collected by multiple data acquisition terminals in different protocol formats into a unified format and transmitting them to the real-time data processing engine. The multi-protocol adaptive conversion module comprises a protocol identification unit, a protocol conversion unit and a protocol updating unit.

[0008] The real-time data processing engine is used to quickly process and analyze the received real-time data. After analysis and processing, the real-time data processing engine transmits the processed data to the distributed redundant storage module. The real-time data processing engine adopts FPGA+ARM architecture;

[0009] The distributed redundant storage module is used to perform redundant storage on data to ensure data reliability;

[0010] The data transmission module is used to realize data transmission between modules;

[0011] The central control module is used to control and manage the entire system;

[0012] The modular expansion interface is used to implement system expansion;

[0013] The anti-interference optimization module is used to reduce the impact of industrial environment interference on the system. The anti-interference optimization module includes an environment monitoring unit and an interference suppression unit. The environment monitoring unit is used to monitor electromagnetic intensity, vibration frequency, temperature and other parameters in the industrial environment in real time. The environment monitoring unit includes an electromagnetic sensor, a vibration sensor, and a temperature sensor. The interference suppression unit automatically adjusts the operating parameters of each module of the system according to the monitoring results of the environment monitoring unit to suppress interference. The interference suppression unit includes an adaptive filter and a dynamic frequency adjustment circuit;

[0014] The power management module is connected to each module in the system respectively, and is used to provide stable power supply for each module.

[0015] Preferably, the data acquisition terminal is connected to the multi-protocol adaptive conversion module, the multi-protocol adaptive conversion module is respectively connected to the data acquisition terminal and the real-time data processing engine, the real-time data processing engine is respectively connected to the multi-protocol adaptive conversion module and the distributed redundant storage module, the distributed redundant storage module is respectively connected to the real-time data processing engine and the data transmission module, the data transmission module is respectively connected to the distributed redundant storage module and the central control module, the central control module is respectively connected to the data transmission module and the modular expansion interface, the modular expansion interface is connected to the central control module, and the anti-interference optimization module is respectively connected to each module in the system.

[0016] Preferably, the protocol identification unit is used to identify the protocol type of data sent by the data acquisition terminal, the protocol conversion unit is used to convert data in different protocol formats into a unified format, and the protocol update unit is used to update the supported protocol types through remote upgrading.

[0017] Preferably, the FPGA is used to implement rapid pre-processing and real-time response of data, and the ARM is used to implement complex data processing and analysis algorithms.

[0018] Preferably, the distributed redundant storage module adopts a multi-node storage architecture, and optical fibers are used to transmit data between the nodes of the distributed redundant storage module.

[0019] Preferably, the modular expansion interface includes a hardware expansion interface and a software expansion interface, the hardware expansion interface is used to connect to newly added hardware devices, and the software expansion interface is used to access new applications and functional modules.

[0020] Preferably, the power management module is respectively connected to the data acquisition terminal, the multi-protocol adaptive conversion module, the real-time data processing engine, the distributed redundant storage module, the data transmission module, the central control module, the modular expansion interface and the anti-interference optimization module, and the power management module is used to provide stable power supply for each module and realize intelligent management and energy-saving control of power supply.

[0021] Preferably, the data transmission module adopts a 5G+wired dual transmission mode to improve the reliability of data transmission while ensuring the data transmission speed; the wired transmission adopts a shielded twisted pair cable, and the 5G antenna is arranged in an anti-interference housing.

[0022] Preferably, the electromagnetic sensor, the vibration sensor and the temperature sensor are used to monitor the electromagnetic intensity, vibration frequency and temperature respectively, the adaptive filter is used to filter the data signal, and the dynamic frequency adjustment circuit is used to adjust the operating frequency of the system to avoid interference frequency.

[0023] Preferably, the casing of the sensor group and the smart meter is made of electromagnetic shielding material, the internal circuits of the sensor group and the smart meter are provided with a filtering circuit, the multi-protocol adaptive conversion module is packaged in a metal shielding box, a grounding protection circuit is provided inside the multi-protocol adaptive conversion module, and the circuit board of the real-time data processing engine adopts a multi-layer board design.

[0024] The present invention has the following beneficial effects:

[0025] 1. The multi-protocol adaptive conversion module can identify and convert data in multiple protocol formats and supports expansion of protocol types through remote upgrades, enabling the system to adapt to equipment in different industrial sites and improving system compatibility;

[0026] 2. The real-time data processing engine adopts FPGA+ARM architecture. FPGA realizes fast pre-processing and real-time response, while ARM performs complex processing and analysis, which greatly improves the data processing speed and meets the real-time requirements of industrial control.

[0027] 3. The distributed redundant storage module adopts a multi-node storage architecture to ensure redundant storage of data. Data transmission adopts 5G+ wired dual transmission mode, which improves the reliability of data transmission and storage and reduces the risk of data loss and errors.

[0028] 4. Modular expansion interfaces include hardware and software expansion interfaces, which facilitate the addition of new devices and functional modules without the need for large-scale system modifications, thus reducing expansion costs and cycles;

[0029] 5. By optimizing hardware design, adopting universal components, and realizing intelligent power management, the system's hardware cost, energy consumption cost, and maintenance cost are reduced, which is conducive to its promotion and application in small and medium-sized industrial enterprises;

[0030] 6. The anti-interference optimization module and the anti-interference design of each module effectively reduce the impact of electromagnetic, vibration, temperature and other interferences in the industrial environment on the system, enabling the system to operate stably in complex industrial environments, and data collection is more accurate and reliable, more in line with actual industrial usage scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is an overall system flow chart of an industrial Internet data acquisition system proposed by the present invention;

[0032] Figure 2 This is a comparison chart of the anti-interference effect of the industrial Internet data acquisition system proposed by the present invention;

[0033] Figure 3 This is a comparison chart of data transmission reliability of an industrial Internet data acquisition system proposed by the present invention. DETAILED DESCRIPTION

[0034] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0035] Example 1:

[0036] Reference Figure 1 , an industrial Internet data acquisition system, including a data acquisition terminal, a multi-protocol adaptive conversion module, a real-time data processing engine, a distributed redundant storage module, a data transmission module, a central control module, a modular expansion interface, an anti-interference optimization module and a power management module;

[0037] The data acquisition terminal is used to collect various types of data from the industrial site and send them to the multi-protocol adaptive conversion module. The data acquisition terminal includes a sensor group and an intelligent instrument. The sensor group is used to collect physical quantity data from the industrial site, and the intelligent instrument is used to collect operating parameter data of industrial equipment.

[0038] The multi-protocol adaptive conversion module is used to convert data in different protocol formats collected by multiple data acquisition terminals into a unified format and transmit it to the real-time data processing engine. The multi-protocol adaptive conversion module includes a protocol identification unit, a protocol conversion unit and a protocol update unit;

[0039] The real-time data processing engine is used to quickly process and analyze the received real-time data. After analysis and processing, the real-time data processing engine transmits the processed data to the distributed redundant storage module. The real-time data processing engine adopts FPGA+ARM architecture;

[0040] The distributed redundant storage module is used to redundantly store data to ensure data reliability; the data transmission module is used to realize data transmission between modules; the central control module is used to control and manage the entire system; and the modular expansion interface is used to realize system expansion.

[0041] The anti-interference optimization module is used to reduce the impact of industrial environment interference on the system. The anti-interference optimization module includes an environmental monitoring unit and an interference suppression unit. The environmental monitoring unit is used to monitor the electromagnetic intensity, vibration frequency, temperature and other parameters in the industrial environment in real time. The environmental monitoring unit includes an electromagnetic sensor, a vibration sensor, and a temperature sensor. The interference suppression unit automatically adjusts the working parameters of each module of the system according to the monitoring results of the environmental monitoring unit to suppress interference. The interference suppression unit includes an adaptive filter and a dynamic frequency adjustment circuit; the power management module is connected to each module in the system respectively, and the power management module is used to provide stable power supply for each module.

[0042] In this embodiment, it should be noted that:

[0043] The workflow of this industrial Internet data acquisition system is as follows:

[0044] Data acquisition: Multiple sensor groups and smart meters are installed at the industrial site. The sensor groups and smart meters in the data acquisition terminal collect physical quantity data and equipment operating parameter data at the industrial site, and the collected data is sent to the multi-protocol adaptive conversion module;

[0045] Protocol conversion: The metal shielding box and grounding protection circuit of the multi-protocol adaptive conversion module resist interference. The protocol identification unit of the multi-protocol adaptive conversion module identifies the protocol type of the received data and converts data in different protocol formats into a unified format. If new protocol types need to be supported, remote upgrades can be performed through the protocol update unit.

[0046] Real-time processing: The converted unified format data is transmitted to the real-time data processing engine. Its multi-layer board design reduces interference. The FPGA quickly pre-processes the data and responds in real time. The ARM performs complex processing and analysis on the data. The processed results are transmitted to the distributed redundant storage module.

[0047] Data storage: Distributed redundant storage modules transmit data via optical fibers. Node devices are housed in shock-proof cabinets to reduce vibration interference. A multi-node storage architecture is used to redundantly store processed data, ensuring data reliability and security.

[0048] Data transmission: The data transmission module adopts 5G+wired dual transmission mode to transmit the stored data to the central control module and realize data interaction between modules.

[0049] System control and expansion: The central control module controls and manages the operation of the entire system. The locking device of the hardware expansion interface ensures stable connection. When new equipment or functions need to be added, expansion can be carried out through the modular expansion interface.

[0050] Anti-interference optimization: The environmental monitoring unit of the anti-interference optimization module monitors industrial environmental parameters in real time. The interference suppression unit suppresses interference through adaptive filters and dynamic frequency adjustment circuits based on the monitoring results. The power management module provides stable power supply for each module and realizes energy-saving control. Its surge protection circuit and electromagnetic compatibility filter further enhance the system's anti-interference capability.

[0051] Example 2:

[0052] The difference from the first embodiment is that, referring to Figure 1-3 This embodiment also has the following further contents: the protocol identification unit is used to identify the protocol type of the data sent by the data acquisition terminal, the protocol conversion unit is used to convert data in different protocol formats into a unified format, and the protocol update unit is used to update the supported protocol types through remote upgrading.

[0053] FPGA is used to achieve rapid data preprocessing and real-time response, ARM is used to implement complex data processing and analysis algorithms, and the distributed redundant storage module adopts a multi-node storage architecture. Fiber optics are used to transmit data between the nodes of the distributed redundant storage module.

[0054] The modular expansion interface includes a hardware expansion interface and a software expansion interface. The hardware expansion interface is used to connect new hardware devices, and the software expansion interface is used to access new applications and functional modules. The power management module is connected to the data acquisition terminal, multi-protocol adaptive conversion module, real-time data processing engine, distributed redundant storage module, data transmission module, central control module, modular expansion interface and anti-interference optimization module respectively. The power management module is used to provide stable power supply for each module and realize intelligent power management and energy-saving control.

[0055] The data transmission module adopts 5G+wired dual transmission mode, which improves the reliability of data transmission while ensuring data transmission speed; wired transmission uses shielded twisted pair cable, and the 5G antenna is set in the anti-interference casing.

[0056] The outer shell of the sensor group and the smart meter is made of electromagnetic shielding material, the internal circuit of the sensor group and the smart meter is equipped with a filtering circuit, the multi-protocol adaptive conversion module is packaged in a metal shielding box, the multi-protocol adaptive conversion module is internally provided with a grounding protection circuit, and the circuit board of the real-time data processing engine adopts a multi-layer board design.

[0057] In this embodiment, it should be noted that:

[0058] The sensor group is used to collect physical quantity data at the industrial site, such as temperature, pressure, flow, etc.; the smart instrument is used to collect operating parameter data of industrial equipment, such as voltage, current, power, etc.

[0059] The casing of the sensor group and the intelligent instrument is made of electromagnetic shielding material, which can effectively block the interference of electromagnetic signals in the industrial environment. The filtering circuit is set in the internal circuit to filter out the noise components in the signal and improve the accuracy of the collected data.

[0060] The protocol identification unit identifies the protocol type of data sent by the data acquisition terminal by analyzing the data frame structure and characteristic fields. The protocol conversion unit converts data in different protocol formats into a unified format using preset conversion rules and algorithms. The protocol update unit updates supported protocol types through remote upgrades, facilitating system adaptation to new protocol standards. The module is packaged in a metal shielding box that effectively shields against external electromagnetic interference. An internal grounding protection circuit directs interference currents to the ground, ensuring stable operation.

[0061] The real-time data processing engine adopts FPGA+ARM architecture. The FPGA has strong parallel processing capability and high speed, and is used to realize fast pre-processing and real-time response of data, such as data filtering, abnormal value detection, etc. The ARM has strong computing capability and flexibility, and is used to realize complex data processing and analysis algorithms, such as data statistical analysis, trend prediction, etc. In order to reduce the influence of industrial environment interference, the circuit board of the engine adopts multi-layer board design, increases the ground layer and the power supply layer, the ground layer can absorb and shield the interference signal, and the power supply layer can provide stable power supply, reducing the interference of power supply noise to the circuit.

[0062] The FPGA adopts sliding window filtering algorithm, amplitude limiting filtering algorithm and fast Fourier transform (FFT) algorithm.

[0063] 1. The formula of the sliding window filtering algorithm is: let the window length be N, the filtering result of the i-th data be Y i , and the original data be X j (j from i-N+1 to i), then

[0064] For example, in a certain chemical production workshop, the temperature sensor collects data every second. Due to the interference of equipment running vibration, the data fluctuates greatly. After adopting the sliding window filtering algorithm with window length of 5, the data can be quickly smoothed.

[0065] For example, the continuously collected temperature data are 25℃, 28℃, 26℃, 30℃, 27℃, 29℃, when i=5, The instantaneous fluctuation is effectively eliminated, providing stable data basis for subsequent temperature control.

[0066] 2. The formula of the amplitude limiting filtering algorithm is: let the maximum deviation value be Δ, the last processed data be Y i-1 , and the current original data be X i . If |X i -Y i-1 |≤Δ, then Y i =X i ; otherwise, Y i =Y i-1 .

[0067] For example, in the pressure collection process of a mechanical processing workshop, the maximum deviation value Δ is set to 5 Pa. The last processed pressure data is 100 Pa, and the currently collected pressure data is 108 Pa, |108-100| = 8 > 5, so the processing result Y i is 100 Pa; if the next collected data is 103 Pa, |103-100| = 3 < 5, then Y i= 103 Pa. The algorithm can quickly eliminate abnormal pressure values caused by instantaneous impact of the pipeline, etc., to ensure the stable operation of the pressure monitoring system.

[0068] 3. The formula of the Fast Fourier Transform (FFT) algorithm is: for a discrete sequence x(n) (n = 0, 1,..., N-1), the FFT result is where j is the imaginary unit.

[0069] For example: in the motor operating state monitoring, the vibration signal of the motor is collected. Through the FFT algorithm for spectral analysis of the signal, the vibration component of a specific frequency can be identified. If the analysis finds that the vibration amplitude of 100 Hz frequency abnormally increases, it can be judged that the motor bearing may be worn out, and a timely warning can be sent to facilitate maintenance personnel to overhaul in advance and avoid motor failure downtime.

[0070] ARM uses a decision tree-based anomaly detection algorithm, a time series prediction algorithm (ARIMA model), and a K-means clustering algorithm.

[0071] 1. The principle formula of the decision tree-based anomaly detection algorithm is: by constructing a decision tree, each internal node corresponds to an attribute test, and according to the attribute value, it is determined to enter the left or right subtree, and the leaf node is the classification result (normal or abnormal). The core is to select the optimal split attribute through indicators such as information gain, and the information gain formula is where is the information entropy of the data set D, A is the attribute, V is the number of values of attribute A, D v is the sample subset of attribute A taking the vth value, pk is the probability that the sample belongs to the kth class.

[0072] For example: in the monitoring of the operating parameters of a car production line, a large amount of historical data is collected to construct a decision tree. Taking the current, temperature, and speed of the device as attributes, when the newly collected parameters enter the decision tree, if the current exceeds 10 A, the temperature is higher than 60°C, and the speed is lower than 1000 r / min, the decision tree judges it as abnormal. The system will immediately issue an alarm, and maintenance personnel can check the equipment in time to prevent the fault from expanding.

[0073] 2. The formula of the time series prediction algorithm (ARIMA model) is: in the ARIMA(p, d, q) model, where is the d-order difference operator, c is the constant term, φ i is the autoregressive coefficient, θ j is the moving average coefficient, and ε t is a white noise sequence.

[0074] For example, a steel plant uses an ARIMA(2,1,1) model to predict blast furnace gas flow. Training the model based on the past 30 days' gas flow data allows it to predict flow trends for the next seven days. If the flow rate is predicted to fall below the minimum required for production on a given day, dispatchers can adjust the gas supply plan in advance to ensure continuous production.

[0075] 3. Formula of K-means clustering algorithm: The objective function is Where K is the number of clusters, C k is the kth cluster, μk is the center of the kth cluster, and ||x-μk|| is the Euclidean distance between sample x and cluster center μk. The algorithm iteratively updates the cluster center to minimize the objective function.

[0076] For example, a batch of chips produced by an electronics factory can be clustered using K-means, with K = 3, for various performance parameters (such as power consumption, frequency, and stability). After clustering, the chips can be divided into three categories: high-quality, qualified, and pending inspection. This facilitates subsequent classification and quality control, improving production efficiency.

[0077] The distributed redundant storage module is connected to the real-time data processing engine and the data transmission module respectively, and is used for redundantly storing data to ensure data reliability.

[0078] The distributed redundant storage module uses a multi-node storage architecture, with each node storing an identical copy of the data. This allows for distributed storage and management of data through a distributed algorithm. If one node fails, the remaining nodes continue to provide data services, ensuring data security and availability.

[0079] Taking into account the vibration and electromagnetic interference in industrial environments, optical fiber is used to transmit data between nodes. Optical fiber has the characteristics of strong anti-electromagnetic interference ability and fast transmission speed. The node equipment is installed in a shock-proof cabinet, which can reduce the impact of vibration on the equipment and ensure stable operation of the equipment.

[0080] The specific algorithm of the distributed redundant storage module is as follows:

[0081] 1. Consistent Hashing Algorithm

[0082] Map the entire hash value space into a virtual ring (hash ring) ranging from 0 to 2 32 -1. Each node is mapped to a position on the hash ring through hash calculation, and the data is also hashed to obtain its position on the hash ring. The data is then stored in the first node encountered in the clockwise direction on the hash ring.

[0083] Formula: For a node, the hash value calculation formula is Where dataKey is the unique identifier of the data, c and d are random numbers, and q is a large prime number.

[0084] For example, in a distributed redundant storage module in an automotive parts production workshop, there are three nodes with node IDs 10, 20, and 30. Assume a = 3, b = 7, and p = 97 (a large prime number). Calculate the node hash value using the formula:

[0085] The hash value of node 10 is:

[0086]

[0087] The hash value of node 20 is:

[0088]

[0089] The hash value of node 30 is:

[0090]

[0091] The positions of these three nodes on the hash ring are 0 (node ​​30), 1.63×10 9 (node ​​10), 2.95×10 9 (Node 20).

[0092] When a new batch of production data needs to be stored, the data keys are 5, 15, and 25. Assume c = 5, d = 11, and q = 101 (a large prime number). The data hash value calculation formula is as follows:

[0093] The hash value of data Key=5 is:

[0094] The hash value is between 0 and 1.63×10 9 So it is stored in node 10.

[0095] The hash value of data Key=15 is:

[0096] This hash value is greater than 2.95×10 9 , the first node found in a clockwise direction is node 30 at position 0, so it is stored at node 30.

[0097] The hash value of data Key=25 is:

[0098]

[0099] Stored to node 10.

[0100] When node 10 fails due to electromagnetic interference, its position on the hash ring becomes invalid. The data originally stored on node 10 (Key=5 and Key=25) will be forwarded clockwise to the next node, node 20, and stored there. This ensures that production data is not lost and that other nodes respond to data query requests normally, ensuring the continuous storage and access of automotive parts production data.

[0101] 2. Distributed replica consensus algorithm (Raft algorithm)

[0102] Formula: Election timeout T timeout =T base +random(0,T random ), where T base is the basic timeout period, T random By setting different election timeouts for random time ranges, the probability of multiple nodes initiating elections at the same time is reduced.

[0103] 3. RAID5 algorithm

[0104] Formula: Assume that the data blocks are D1, D2, and D3, and the corresponding parity check blocks are, then P ( is the exclusive OR operator). When D2 is lost, it can be Restore D2.

[0105] For example, in a distributed redundant storage module at a steel plant, three nodes use a RAID 5 algorithm to store key parameters from the steelmaking process. A set of steelmaking data (molten steel temperature, carbon content, and furnace discharge time) is split into three data blocks: D1 (temperature 1600°C), D2 (carbon content 0.2%), and D3 (time 10:30).

[0106] According to the formula First convert the data into binary (assuming that the temperature of 1600°C corresponds to the binary 11001000000, the carbon content of 0.2% corresponds to 000000111110, and the time of 10:30 corresponds to 100111001010):

[0107] D1: 11001000000

[0108] D2: 000000111110

[0109] D3:100111001010

[0110] (To facilitate calculation, the data is padded to 12 bits: D1 is 011001000000)

[0111] Store D1 in node 1 and D2 in node Point 2, D3 is stored in node 3, and P is stored in node 1.

[0112] If node 2 is damaged and lost due to electromagnetic interference, and needs to be restored, according to the formula

[0113]

[0114] After conversion, the carbon content was 0.2%, which was consistent with the original data and was successfully restored, ensuring the integrity of the key parameter data for steelmaking.

[0115] The data transmission module adopts 5G+wired dual transmission mode, which improves the reliability of data transmission while ensuring data transmission speed. Shielded twisted pair cable is used for wired transmission, and the 5G antenna is set in the anti-interference casing.

[0116] For example, in an industrial internet data collection system at a large warehousing and logistics park, the 5G transmission module uses the Huawei ME909s-8215G module, which supports the Sub-6GHz frequency band and offers a theoretical peak download rate of 2Gbps and an upload rate of 150Mbps. This module connects to the data transmission module's main controller via a PCIe interface. The main controller, which uses an STM32H743 microprocessor, is responsible for encapsulating and decapsulating 5G transmitted data.

[0117] The 5G antenna uses a directional antenna with a gain of 8dBi and is installed on a signal tower at a commanding height in the campus. The antenna is encased in a 3mm-thick aluminum anti-interference casing. The interior of the anti-interference casing is sprayed with electromagnetic shielding paint, which provides a shielding effectiveness of over 40dB against electromagnetic signals in the 100MHz-6GHz frequency band, effectively blocking electromagnetic radiation interference generated by large equipment such as forklifts and cranes within the campus.

[0118] Wired transmission utilizes Category 5e shielded twisted-pair cable, with a 0.51mm bare copper conductor, polyethylene insulation, and a double shield structure of aluminum foil and copper braid. The aluminum foil shielding offers a shielding effectiveness of up to 30dB against high-frequency electromagnetic interference, while the copper braid (90% weave density) offers a shielding effectiveness of up to 60dB against low-frequency electromagnetic interference. The twisted-pair cable has an impedance of 100Ω ±20%, a transmission frequency of up to 100MHz, and supports the 1000BASE-T Ethernet standard, with a theoretical transmission rate of 1Gbps.

[0119] For example, in an automotive welding workshop, a wired transmission line runs from the distributed redundant storage module (located in the workshop control room) to the central control module (located in the factory monitoring center), with a total length of approximately 500 meters. This line is laid through galvanized steel pipe with a diameter of 25 mm and a wall thickness of 1.5 mm, further enhancing shielding against the strong electromagnetic interference (peak value up to 100 V / m) generated by the welding robot.

[0120] When transmitting the real-time operating parameters of the welding robot (each data item contains information such as current, voltage, welding speed, etc., about 512 bytes), the wired transmission module uses the RS485 interface to connect to the distributed redundant storage module and transmit data via the Modbus-RTU protocol. The protocol frame format is: slave address (1 byte) + function code (1 byte) + data (N bytes) + CRC check (2 bytes). In actual tests, the bit error rate of data within a transmission distance of 500m is less than 10 -6 , which is much better than unshielded twisted pair (bit error rate of about 10 -3 ).

[0121] The central control module serves as the core command center of the system. Its control and management functions for the entire system rely on the coordinated operation of multiple algorithms, as follows:

[0122] 1. Data acquisition terminal control algorithm (dynamic sampling frequency adjustment algorithm)

[0123] By analyzing the data change rate collected by the data acquisition terminal, when the data changes slowly, the sampling frequency is reduced; when the data changes drastically, the sampling frequency is increased. The calculation formula for the data change rate is where X t is the data collected at the current moment, X t-1 is the data collected at the last moment, and T is the sampling period. Set two thresholds R high and R low (R high >R high ), when R>R high When the sampling period is adjusted to T min (minimum sampling period); when R>R low When the sampling period is adjusted to T max (maximum sampling period); when R low ≤R≤R high When , the current sampling period T remains unchanged.

[0124] For example, in a temperature collection scenario in a food processing plant, the central control module uses this algorithm for the temperature collection terminal in the cold storage. high =0.5℃ / s, R low =0.1℃ / s, Tmin = 1 s, T max = 10 s. When the refrigerator is in refrigeration operation, the temperature rapidly decreases from 25℃ to 5℃ in a short time, and the data change rate R is greater than R high , the central control module issues an instruction to adjust the sampling period to T min = 1 s to densely collect temperature data and ensure real-time monitoring of the refrigeration process; when the temperature stabilizes at about 5℃, the data change rate R is less than R low , the sampling period is automatically adjusted to T max = 10 s to reduce unnecessary data collection and reduce terminal energy consumption and data transmission volume.

[0125] 2. Module working state monitoring algorithm (abnormality detection and early warning algorithm based on threshold)

[0126] The formula is: for a parameter P of a module, if P < P min or P > P max , it is determined to be abnormal, where P min is the minimum normal threshold value of the parameter, and P max is the maximum normal threshold value of the parameter. At the same time, a continuous abnormality counting mechanism is introduced, and a warning is issued only when the parameter is abnormal for N consecutive times to avoid false positives caused by transient interference. The value of N can be set according to the characteristics of the module, generally 3-5 times.

[0127] For example: in the monitoring of the real-time data processing engine, the central control module collects its working temperature P, sets P min = 0℃, P max = 70℃, and N = 3.

[0128] When the real-time data processing engine runs for a long time under high load, the temperature gradually rises to 72℃, P = 72℃ > P max is collected for the first time, and the continuous abnormality count is 1; the second collection is still 72℃, and the count is 2; the third collection is still 72℃, and the count reaches 3, the central control module determines that it is abnormal, immediately issues a high temperature warning, and starts the heat dissipation control instruction to control the cooling fan to run faster. If the temperature continues to rise, further measures such as reducing the load will be taken to prevent the module from being damaged due to overheating.

[0129] 3. Data transmission scheduling algorithm (dynamic priority scheduling algorithm)

[0130] The scheduling order formula can be expressed as: let the priority of data D1 be P1 and the priority of data D2 be P2, if P1 > P2, then D1 is transmitted before D2; if P1 = P2 and the time T1 when D1 enters the queue is earlier than the time T2 when D2 enters the queue, then D1 is transmitted before D2.

[0131] The central control module adopts a high-performance microprocessor, which realizes functions such as controlling the data acquisition terminal, monitoring the working status of each module, and scheduling data transmission by running the preset control program.

[0132] The central control module's hardware utilizes the high-performance STM32H743 microprocessor, based on the ARM Cortex-M7 core and clocked at up to 480MHz. This processor boasts powerful computing capabilities and a rich set of peripheral interfaces, enabling efficient execution of pre-set control programs and meeting the system's requirements for real-time performance and processing power. The module also features 1MB of SRAM and 8MB of Flash memory, providing ample space for program execution and data caching. It also integrates multiple communication interfaces, including an Ethernet controller, UART, SPI, and I2C, ensuring stable connectivity with other modules.

[0133] The modular expansion interface connects to the central control module and enables system expansion. This interface includes both hardware and software expansion interfaces. The hardware expansion interface utilizes standardized interfaces, such as USB and PCIe, for connecting to new hardware devices, such as additional sensors and actuators. The software expansion interface utilizes an open API for integrating new applications and functional modules, such as data analysis software and remote monitoring software. The hardware expansion interface utilizes a locking connector to prevent vibration-induced contact and ensure connection stability.

[0134] The system also includes a power management module, which is connected to each module in the system to provide stable power and implement intelligent power management and energy-saving control. The module dynamically adjusts the supply voltage and current based on the operating status of each module, reducing system energy consumption. The module also incorporates a surge protection circuit and an electromagnetic compatibility filter. The surge protection circuit prevents damage to the modules caused by transient high voltages, while the electromagnetic compatibility filter filters out noise and interference signals in the power supply, ensuring its purity.

[0135] The anti-interference optimization module is connected with each module in the system respectively, and is used for reducing the influence of industrial environment interference on the system. The anti-interference optimization module comprises an environment monitoring unit and an interference suppression unit. The environment monitoring unit is used for monitoring parameters such as electromagnetic intensity, vibration frequency and temperature in the industrial environment in real time. The environment monitoring unit comprises an electromagnetic sensor, a vibration sensor and a temperature sensor, which are respectively used for monitoring the electromagnetic intensity, the vibration frequency and the temperature. The interference suppression unit automatically adjusts the working parameters of each module of the system according to the monitoring result of the environment monitoring unit to suppress the interference. The interference suppression unit comprises an adaptive filter and a dynamic frequency adjustment circuit. The adaptive filter is used for filtering the data signal and can automatically adjust the filtering parameter according to the change of the interference signal. The dynamic frequency adjustment circuit is used for adjusting the working frequency of the system to avoid the interference frequency and reduce the influence of the interference on the system.

[0136] The hardware of the anti-interference optimization module adopts a modular design. The core controller selects an STM32L476 microprocessor. The processor has a low-power characteristic and is suitable for long-term stable operation. Meanwhile, the processor is integrated with a 12-bit ADC converter and multiple PWM output channels, and can accurately collect environmental parameters and output control signals. The module is provided with an independent power management circuit, adopts a wide voltage input (9-36V) design, can adapt to the complex power supply environment in the industrial field, and is certified by electromagnetic compatibility (EMC). The anti-interference capability of the module itself reaches the industrial standard.

[0137] The environment monitoring unit realizes real-time monitoring of multi-dimensional parameters of the industrial environment through a distributed sensor network. The specific configuration and working mode are as follows.

[0138] The electromagnetic sensor adopts an EMC-302 three-axis electromagnetic induction sensor. The measurement range is 1mV / m-10V / m, the frequency response range is 10kHz-1GHz, and the sampling frequency is set to 1kHz. The sensor is connected to the anti-interference optimization module through a shielded cable, and is arranged at an interval of 5 meters near strong electric equipment (such as motors and transformers), thereby forming an electromagnetic interference monitoring network.

[0139] The vibration sensor selects a VIB-201 piezoelectric acceleration sensor. The measurement range is ±50g, the frequency response is 0.5Hz-10kHz, and the sensitivity is 100mV / g. The sensor is fixed on the shell of each module through a magnetic base, and is used for monitoring the vibration of precise equipment such as the real-time data processing engine and the distributed redundant storage module.

[0140] Temperature sensor: "DS18B20" digital temperature sensor is used, the measurement range is -55℃-125℃, the accuracy is ±0.5℃, and it is connected with the anti-interference optimization module through the single bus protocol. The sensor is embedded in the key position of the circuit board of each module (such as the side of CPU, power chip), and temperature data is collected every 30 seconds. When the temperature of a certain module is detected to be higher than 60℃, the high-temperature related interference protection mechanism is started.

[0141] The interference suppression unit realizes active suppression of system interference through the synergistic effect of adaptive filtering and dynamic frequency adjustment based on the real-time data of the environment monitoring unit. The specific process and technical details are as follows:

[0142] Adaptive filter: The least mean square (LMS) algorithm is used to realize adaptive filtering, and the core formula is w(n+1)=w(n)+2μe(n)x(n), where w(n) is the filter coefficient at time n, μ is the step factor (value 0.01-0.1, dynamically adjusted according to the interference intensity), e(n)=d(n)-y(n) is the error signal (d(n) is the expected signal, y(n) is the filter output), x(n) is the input signal. The filter hardware is realized by FPGA, which supports 128 parallel filter coefficients and the processing delay is less than 10μs. It can realize real-time filtering of analog signals (such as temperature, pressure sensor signals) output by the data acquisition terminal.

[0143] Dynamic frequency adjustment circuit: composed of phase-locked loop (PLL) chip and frequency synthesizer, supporting continuous adjustable system working frequency in the range of 1MHz-100MHz, adjustment accuracy is 1kHz. The circuit receives the PWM control signal of the anti-interference optimization module controller, realizes frequency switching by changing the frequency division coefficient of PLL, and the switching time is less than 500μs. When it is detected that there is strong interference in a certain frequency band (such as electromagnetic sensor detects that the electromagnetic intensity at 50MHz frequency exceeds the threshold), the system working frequency is immediately adjusted from 50MHz to 48MHz to avoid the interference frequency band.

[0144] For example: in the application of a certain numerical control machine tool workshop, when the environment monitoring unit detects that the electromagnetic intensity reaches 1.8V / m (threshold 1.5V / m) at 200kHz frequency, the anti-interference optimization module starts the adaptive filter, adjusts the step factor μ to 0.05, and filters the vibration signal output by the data acquisition terminal. After processing, the signal-to-noise ratio of the signal is improved from 20dB to 35dB; at the same time, the dynamic frequency adjustment circuit adjusts the working frequency of the multi-protocol adaptive conversion module from 200kHz to 210kHz, and the communication error rate of the module is reduced from 10 -4 to 10 -6When the vibration sensor detects a mechanical vibration amplitude exceeding 0.5g at 100Hz, the filter automatically increases the attenuation coefficient of the low-frequency band to further suppress signal jitter caused by vibration.

[0145] Based on the above embodiments, the technical parameters of the key modules in the present invention are summarized and compared with the conventional level in the industry. The comparison results are detailed in the following table:

[0146] Table 1: Comparison of technical parameters of key modules in this invention and conventional industry standards

[0147]

[0148] Example 3:

[0149] In this embodiment, it should be noted that:

[0150] The anti-interference optimization module does not work independently, but forms a linkage protection mechanism with other modules of the system:

[0151] Cooperate with the power management module: When the grid voltage fluctuation exceeds ±10%, the voltage stabilization circuit and surge suppressor are triggered to stabilize the output voltage to within ±2% and cut off the overcurrent circuit;

[0152] Collaborate with the data transmission module: When there is strong interference in the 5G frequency band, it switches to wired transmission. When the wired line encounters 50Hz power frequency interference, differential transmission is enabled to offset the interference.

[0153] Collaborate with the central control module: transmit real-time environmental parameters and suppression measures, and the central control module determines whether to adopt advanced protection (such as load reduction and starting backup storage nodes).

[0154] The anti-interference optimization module and other modules' linkage protection mechanism are detailed in the table below:

[0155] Table 2: Schematic diagram of the protection mechanism of the anti-interference optimization module and other modules

[0156]

[0157]

[0158] Example 4:

[0159] In this industrial Internet data acquisition system, in the sensor group of the data acquisition terminal, the temperature sensor uses DS18B20, the outer shell uses a copper electromagnetic shielding shell, and an RC filter circuit is set inside; the pressure sensor uses MPX5010, the outer shell also uses a copper electromagnetic shielding shell, and an LC filter circuit is set inside; the smart instrument uses a multi-function power meter with an RS485 interface, the outer shell uses an iron electromagnetic shielding shell, and the internal circuit is equipped with a π-type filter circuit.

[0160] The multi-protocol adaptive conversion module utilizes an STM32H743 microprocessor-based hardware platform, housed in an aluminum alloy shielded box. It features an internal grounding protection circuit with a grounding resistance of less than 4Ω. The protocol identification unit analyzes data frame features such as the start, end, and parity bits to identify common industrial protocols such as Modbus, Profinet, and EtherCAT. The protocol conversion unit converts data from different protocols into a unified JSON format. The protocol update unit enables remote protocol upgrades using Over-the-Air (OTA) technology.

[0161] The real-time data processing engine utilizes a Xilinx Zynq-7000 series FPGA + ARM chip. The circuit board utilizes a four-layer design, including a ground layer and a power layer. The FPGA performs fast processing functions such as data filtering and outlier detection. The ARM component runs the Linux operating system and uses C++ to program data analysis algorithms for statistical analysis and trend prediction.

[0162] The distributed redundant storage module consists of three nodes, each of which uses an embedded server equipped with a 1TB solid-state drive and RAID 5 technology for redundant data storage and fault tolerance. Data is transmitted between nodes using single-mode optical fiber at a transmission rate of 10Gbps. The node equipment is installed in a steel, shock-resistant cabinet with internal shock-absorbing pads.

[0163] The 5G part of the data transmission module uses the Huawei ME909s-8215G module, and the 5G antenna is set in an aluminum anti-interference casing; the wired transmission part uses Category 5e shielded twisted pair cable with a transmission rate of 1000Mbps.

[0164] The central control module uses an STM32F429 microprocessor and runs the FreeRTOS real-time operating system.

Claims

1. An industrial Internet data acquisition system, characterized by: It includes data acquisition terminal, multi-protocol adaptive conversion module, real-time data processing engine, distributed redundant storage module, data transmission module, central control module, modular expansion interface, anti-interference optimization module and power management module; The data acquisition terminal is used to collect various types of data at the industrial site and send them to the multi-protocol adaptive conversion module. The data acquisition terminal includes a sensor group and an intelligent instrument. The sensor group is used to collect physical quantity data at the industrial site, and the intelligent instrument is used to collect operating parameter data of industrial equipment. The multi-protocol adaptive conversion module is used to convert data in different protocol formats collected by multiple data acquisition terminals into a unified format and transmit the data to the real-time data processing engine. The multi-protocol adaptive conversion module includes a protocol identification unit, a protocol conversion unit and a protocol update unit; The real-time data processing engine is used to quickly process and analyze the received real-time data. After analysis and processing, the real-time data processing engine transmits the processed data to the distributed redundant storage module. The real-time data processing engine adopts FPGA+ARM architecture; The distributed redundant storage module is used to perform redundant storage on data to ensure data reliability; The data transmission module is used to realize data transmission between modules; The central control module is used to control and manage the entire system; The modular expansion interface is used to implement system expansion; The anti-interference optimization module includes an environmental monitoring unit and an interference suppression unit. The environmental monitoring unit is used to monitor electromagnetic intensity, vibration frequency, temperature and other parameters in the industrial environment in real time. The environmental monitoring unit includes an electromagnetic sensor, a vibration sensor, and a temperature sensor. The interference suppression unit automatically adjusts the operating parameters of each module of the system to suppress interference based on the monitoring results of the environmental monitoring unit. The interference suppression unit includes an adaptive filter and a dynamic frequency adjustment circuit. The power management module is connected to each module in the system respectively, and is used to provide stable power supply for each module.

2. The industrial Internet data acquisition system according to claim 1, characterized in that: The data acquisition terminal is connected to the multi-protocol adaptive conversion module, the multi-protocol adaptive conversion module is respectively connected to the data acquisition terminal and the real-time data processing engine, the real-time data processing engine is respectively connected to the multi-protocol adaptive conversion module and the distributed redundant storage module, the distributed redundant storage module is respectively connected to the real-time data processing engine and the data transmission module, the data transmission module is respectively connected to the distributed redundant storage module and the central control module, the central control module is respectively connected to the data transmission module and the modular expansion interface, the modular expansion interface is connected to the central control module, and the anti-interference optimization module is respectively connected to each module in the system.

3. The industrial Internet data acquisition system according to claim 2, characterized in that: The protocol identification unit is used to identify the protocol type of the data sent by the data acquisition terminal, the protocol conversion unit is used to convert data in different protocol formats into a unified format, and the protocol update unit is used to update the supported protocol types through remote upgrading.

4. The industrial Internet data acquisition system according to claim 3, characterized in that: The FPGA is used to implement fast data pre-processing and real-time response, and the ARM is used to implement complex data processing and analysis algorithms.

5. The industrial Internet data acquisition system according to claim 4, characterized in that: The distributed redundant storage module adopts a multi-node storage architecture, and optical fibers are used to transmit data between the nodes of the distributed redundant storage module.

6. The industrial Internet data acquisition system according to claim 5, characterized in that: The modular expansion interface includes a hardware expansion interface and a software expansion interface. The hardware expansion interface is used to connect to newly added hardware devices, and the software expansion interface is used to access new application programs and functional modules.

7. The industrial Internet data acquisition system according to claim 6, characterized in that: The power management module is respectively connected to the data acquisition terminal, the multi-protocol adaptive conversion module, the real-time data processing engine, the distributed redundant storage module, the data transmission module, the central control module, the modular expansion interface and the anti-interference optimization module. The power management module is used to provide stable power supply for each module and realize intelligent management and energy-saving control of power supply.

8. The industrial Internet data acquisition system according to claim 7, characterized in that: The data transmission module adopts a 5G+wired dual transmission mode, which improves the reliability of data transmission while ensuring the data transmission speed; the wired transmission adopts a shielded twisted pair cable, and the 5G antenna is set in an anti-interference housing.

9. The industrial Internet data acquisition system according to claim 1, characterized in that: The electromagnetic sensor, the vibration sensor and the temperature sensor are used to monitor electromagnetic intensity, vibration frequency and temperature respectively; the adaptive filter is used to filter the data signal; and the dynamic frequency adjustment circuit is used to adjust the operating frequency of the system to avoid interference frequency.

10. The industrial Internet data acquisition system according to claim 8, characterized in that: The housings of the sensor group and the smart meter are made of electromagnetic shielding material, the internal circuits of the sensor group and the smart meter are provided with filtering circuits, the multi-protocol adaptive conversion module is packaged in a metal shielding box, a grounding protection circuit is provided inside the multi-protocol adaptive conversion module, and the circuit board of the real-time data processing engine adopts a multi-layer board design.

Images