State monitoring multi-source heterogeneous data synchronous acquisition algorithm

Abstract

The invention relates to the technical field of monitoring and diagnosis, in particular to a state monitoring multi-source heterogeneous data synchronous acquisition algorithm, which comprises the following steps of: S1, accessing a sensor into an acquisition module of an integrated collector, and performing signal acquisition, signal type judgment and automatic adaptation on the sensor through an interface adaptation module; and S2, after the adaptation is completed, the integrated collector obtains the number and type information of the accessed sensors by using a data acquisition module. According to the application, the integrated collector is adopted to replace a traditional multi-sensor multi-collector, and the integrated collector realizes that the same interface adapts to the access of different state sensors through an interface adaptation algorithm, so that the synchronism and integrity of multi-source multi-channel data collection are ensured; an intelligent prediction and optimization scheduling algorithm is provided to solve the problem of data synchronous acquisition of an access sensor, and the accuracy and timeliness of marine equipment state monitoring are realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of monitoring and diagnosis, and specifically relates to a synchronous acquisition algorithm for multi-source heterogeneous data of state monitoring. Background Art

[0002] Marine equipment, including ships, buoys, submersibles, underwater robots, etc., play an important role in marine scientific research, resource development, environmental protection and other fields. However, these equipments have been operating in harsh marine environments for a long time and are easily affected by factors such as wind and waves, corrosion, and biological adhesion, which can lead to performance degradation or even failure. Therefore, it is of great significance to monitor the status of marine equipment and discover and solve problems in time to ensure equipment safety and improve operating efficiency. At present, there are many condition monitoring sensors in the marine equipment condition monitoring industry, such as acceleration sensors, vibration sensors, displacement sensors, climate sensors, etc. The types of each sensor are different. Some are IEPE vibration type, some are voltage type, and some are current type. As a result, each condition monitoring sensor must be configured with a signal collector separately, which is a waste of resources. The data collection time of each collector is determined by its own hardware time. Often in the later analysis, only one type of sensor data can be analyzed each time, and then a comprehensive analysis is performed based on the characteristics of the data to calculate the health and structural safety of the current marine equipment, which greatly wastes time. In this regard, we propose a synchronous acquisition algorithm for multi-source heterogeneous data for condition monitoring. Summary of the invention

[0003] In view of the deficiencies in the prior art, the present invention provides a synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring to solve the above technical problems.

[0004] To achieve the above object, the present invention provides the following technical solutions: A synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring, the method steps of the synchronous acquisition algorithm are: S1. The sensor is connected to the acquisition module of the integrated collector, and the sensor signal is collected through the interface adapter module, the signal type is determined, and the signal is automatically adapted; S2. After the adaptation is completed, the integrated collector uses the data acquisition module to obtain the number and type information of the connected sensors and starts the self-test process; S3, the self-test process tests the connected sensors one by one in the order of interfaces to obtain the sensor sampling frequency; S4. After the self-test process is completed, the integrated collector arranges the acquired sampling frequencies in reverse order to form F pmaxi 、F pmax(i-1) ……F pmax(i-i+2) 、Fpmax (i-i+1) , and interrupt the collection; S5, the integrated collector calculates the total system resources, and then automatically allocates system resources according to the sensor collection frequency, collects data, and pre-processes the collected data; S6. After the preprocessing is completed, the data is stored in the integrated collector for backup and forwarding.

[0005] Preferably, the method for automatic adaptation of the interface adaptation module in step S1 is: Integrated collector acquisition module interface detection to check the status of each access port and whether the sensor is connected; The sensors connected to the integrated collector are arranged in the order of the acquisition modules, and the signal of the first sensor is collected through the interface adapter module; The signal is transmitted to the high-impedance input voltage detection unit to determine whether the signal type is voltage. If the detection signal type is voltage, the interface adapter module will process the sensor data according to the voltage signal. If the detection signal type is not voltage, the signal is transmitted to the low-impedance current detection unit to detect and determine that the signal type is current. The interface adapter module will process the sensor data according to the current signal. After the judgment is completed, the integrated collector interrupts the judgment of the first sensor and adapts the remaining sensors in sequence; When a single sensor signal line is interrupted or abnormal, a re-adaptation process will be performed for the interface.

[0006] Preferably, the detailed steps of the self-test process in step S2 are: Based on the information of the number of sensors obtained, the integrated collector controls the first acquisition module to collect data at a speed of 100KHz according to the order of interfaces, and the acquisition time is 10S; The integrated collector performs change timing on the collected data, determines the sampling frequency of the current sensor through the change timing, and obtains the data of the collection module again to verify the accuracy of this sampling frequency; If the sampling frequencies obtained by verification are consistent, the sampling frequencies of the acquisition modules of the remaining connected sensors are obtained in sequence; If the sampling frequencies obtained by verification are inconsistent, re-detection is performed until the detection sampling frequency obtained is consistent with the verification sampling frequency, and then the sampling frequencies of the acquisition modules of the remaining connected sensors are obtained in sequence.

[0007] Preferably, the calculation method for automatically allocating system resources in step S5 is: The quantity information and frequency information of the acquisition modules obtained based on the integrated collector; Based on the total number of resources of the integrated collector itself, calculate the system resources automatically allocated to the corresponding collection module; The calculation formula for automatically allocating system resources is: In the formula, f i Indicates the system resources f allocated to acquisition module i, F i represents the acquisition frequency F of acquisition module i, n represents the total number of acquisition modules, R total Indicates the total system resources, where the total system resources are calculated as follows: In the formula, represents the weight of memory usage, Indicates memory usage, which is a value between 0 and 1, indicating the percentage of memory occupied. Indicates the weight of CPU usage. Indicates the CPU usage, which is a value between 0 and 1, indicating the percentage of memory usage.

[0008] Preferably, the data preprocessing in step S5 is aimed at detecting abnormalities or errors in the collected sensor data.

[0009] Preferably, the preprocessing calculation formula for data anomalies or errors is: Where ∆MA(t,n) represents the time series difference between the previous and next values, N represents the number of data points used to calculate the moving average, n represents the total number of acquisition modules, t represents the current time point, and x(i) represents the original data value i at time point t.

[0010] Preferably, the integrated collector based on the multi-source heterogeneous data synchronous acquisition algorithm comprises: an acquisition module, an interface adapter module, a data acquisition module, a data processing module, a data storage module and a data forwarding module; The acquisition module is used to connect with the sensor; The interface adapter module is electrically connected to the acquisition module, and the interface adapter module is used to adapt different types of sensors according to the types of sensors; The data acquisition module is electrically connected to the interface adapter module and the acquisition module, and the data acquisition module is used to allocate system resources according to the access status of the acquisition module and obtain the information data collected by the acquisition module; The data processing module is electrically connected to the data acquisition module, and the data processing module pre-processes the information data acquired by the data acquisition module to eliminate data anomalies or errors; The data storage module is electrically connected to the data acquisition module, and the data storage module stores and backs up the information data processed by the data processing module; The data forwarding module is electrically connected to the data acquisition module, and the data storage module wirelessly forwards the information data processed by the data processing module.

[0011] Preferably, when the integrated collector detects that the type or quantity of connected sensors has changed, it will automatically re-perform the interface adaptation and signal collection process.

[0012] Preferably, the integrated collector dynamically adjusts the allocation of system resources according to the actual load conditions of each collection module.

[0013] Preferably, the data forwarding module transmits the real-time data to the remote monitoring center, and the remote monitoring center handles the sensor failure and insufficient system resources according to the information.

[0014] Compared with the prior art, the present invention has the following beneficial effects: This application replaces the traditional multi-sensor multi-collector with an integrated collector, and the integrated collector uses an interface adaptation algorithm to achieve the same interface adaptation of different types of status sensor access, ensuring the synchronization and integrity of multi-source multi-channel data acquisition, and providing an intelligent prediction and optimization scheduling algorithm to solve the data synchronization acquisition of access sensors. The algorithm solves the problems of abnormal and erroneous collected data, and ensures the consistency of collected data from multiple aspects, thereby achieving accuracy and timeliness of marine equipment status monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a framework diagram of an integrated collector based on a multi-source heterogeneous data synchronous acquisition algorithm. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] The present invention provides a technical solution: a synchronous acquisition algorithm for multi-source heterogeneous data of state monitoring, the method steps of the synchronous acquisition algorithm are: S1. The sensor is connected to the acquisition module of the integrated collector. The interface adapter module collects the sensor signal, determines the signal type, and automatically adapts it. This not only simplifies the traditional manual configuration steps, but also greatly improves the flexibility and efficiency of data acquisition. S2. After completing sensor access and signal adaptation, the integrated collector uses the data acquisition module to obtain the number and type information of the connected sensors and starts the self-test process; S3, the self-test process tests the connected sensors one by one in the order of interfaces. During this process, the collector pays special attention to and records the sampling frequency of each sensor, which is a key factor in determining the data acquisition rate and synchronization accuracy. By accurately measuring the sampling frequency, it provides key parameter support for subsequent data processing; S4. After the self-test process is completed, the integrated collector arranges the acquired sampling frequencies in reverse order to form F pmaxi 、F pmax(i-1) ……F pmax(i-i+2) 、Fpmax (i-i+1) , and interrupt the collection to prepare for the subsequent resource allocation and data synchronization collection; S5, based on the sorted sampling frequency and the evaluation of the total system resources, automatically allocate system resources according to the sensor collection frequency, collect data, and pre-process the collected data; S6. After the preprocessing is completed, the integrated collector stores the processed data in the built-in large-capacity storage medium to ensure the security and traceability of the data. The collector also has a data backup function to deal with possible hardware failures or data loss risks. The collector forwards the data to the data center in real time for subsequent data analysis, monitoring and early warning and other applications.

[0018] Furthermore, the method for automatic adaptation of the interface adaptation module in step S1 is: The integrated collector module interface detection checks the status of each access port to see if a sensor is connected, and checks the physical connection status of each access port, including voltage level and resistance value, to confirm whether a sensor has been correctly connected, ensuring the accuracy of the system and avoiding invalid operations on unconnected interfaces; Once it is confirmed that there are sensors connected, the system will sort these sensors according to the physical layout order of the acquisition modules and collect signals from the first sensor through the interface adapter module; The signal is transmitted to the high-impedance input voltage detection unit to determine whether the signal type is voltage. If the detection signal type is voltage, the interface adapter module will process the sensor data according to the voltage signal. If the detection signal type is not voltage, the signal is transmitted to the low-impedance current detection unit to detect and determine that the signal type is current. The interface adapter module will process the sensor data according to the current signal. After the signal type is determined, the interface adapter module automatically switches to the corresponding signal processing mode according to the determination result, and the integrated collector interrupts the determination of the first sensor and adapts the remaining sensors in sequence; When a single sensor signal line is interrupted or abnormal, a re-adaptation process will be performed for that interface; During the entire adaptation process, the adaptation status, signal type, processing mode and other information of each sensor will be recorded in detail, and this information will be used as the basis for debugging and fault diagnosis. At the same time, the system also provides necessary feedback to the user or the superior management system, including notifications of successful and failed adaptation, recommended follow-up operations, etc., to improve the maintainability of the overall system and user experience.

[0019] Furthermore, the detailed steps of the self-test process in step S2 are: The integrated collector first prepares to start the self-test process according to the sensor quantity information obtained in step S1, selects the first acquisition module as the self-test object according to the interface order, and controls the first acquisition module to collect data at a speed of 100KHz, and the acquisition time is 10S; During the data collection process, the integrated collector analyzes the collected data in real time, especially focusing on the changes in data values. The integrated collector performs change timing on the collected data, determines the sampling frequency of the current sensor through the change timing, and obtains the data of the collection module again to verify the accuracy of this sampling frequency. Using the newly acquired data segment, the system calculates the sampling frequency again and compares it with the previous result. If the sampling frequencies obtained by verification are consistent, the sampling frequencies of the acquisition modules of the remaining connected sensors are obtained in sequence. This verification step increases the reliability of the self-test process and reduces misjudgments caused by single measurement errors. If the sampling frequencies obtained by verification are inconsistent, re-test until the obtained detection sampling frequency is consistent with the verification sampling frequency, and then obtain the sampling frequencies of the acquisition modules of the remaining connected sensors in sequence; At each stage of the self-test process, detailed information is recorded, including the interface order of each sensor, the initial detected sampling frequency, the verification results, and the final determined sampling frequency.

[0020] Furthermore, the calculation method for automatically allocating system resources in step S5 is: The quantity information and frequency information of the acquisition modules obtained based on the integrated collector; Based on the total number of resources of the integrated collector itself, calculate the system resources automatically allocated to the corresponding collection module; The calculation formula for automatically allocating system resources is: In the formula, f i Indicates the system resources f allocated to acquisition module i, F i represents the acquisition frequency F of acquisition module i, n represents the total number of acquisition modules, R total Indicates the total system resources, where the total system resources are calculated as follows: In the formula, represents the weight of memory usage, Indicates memory usage, which is a value between 0 and 1, indicating the percentage of memory occupied. Indicates the weight of CPU usage. Indicates the CPU usage, which is a value between 0 and 1, indicating the percentage of memory usage.

[0021] Furthermore, in the data preprocessing in step S5, for abnormal or erroneous sensor data collected, during the entire preprocessing process, the system will record all errors and abnormalities in detail, including data loss, outlier detection, denoising failure, etc. These log information are crucial for subsequent troubleshooting, system optimization and data quality control.

[0022] Furthermore, the preprocessing calculation formula for data anomalies or errors is: Where ∆MA(t,n) represents the time series difference between the previous and next values, N represents the number of data points used to calculate the moving average, n represents the total number of acquisition modules, t represents the current time point, and x(i) represents the original data value i at time point t.

[0023] Furthermore, the integrated collector based on the multi-source heterogeneous data synchronous acquisition algorithm includes: an acquisition module, an interface adapter module, a data acquisition module, a data processing module, a data storage module and a data forwarding module; The acquisition module is used to connect with the sensor; The interface adapter module is electrically connected to the acquisition module. The interface adapter module is used to adapt to different types of sensors according to the sensor type. It has high flexibility and scalability. The interface adapter module can quickly identify the sensor type and adjust its own configuration parameters to ensure the accuracy and stability of data transmission. The data acquisition module is electrically connected to the interface adapter module and the acquisition module. The data acquisition module allocates system resources according to the access status of the acquisition module. Through the algorithm, the data acquisition module can optimize the data acquisition process, ensure that each sensor can be processed, and obtain the information data collected by the acquisition module; The data processing module is electrically connected to the data acquisition module, and the data processing module pre-processes the information data acquired by the data acquisition module to eliminate data anomalies or errors; The data storage module is electrically connected to the data acquisition module. The data storage module stores and backs up the information data processed by the data processing module and also has data compression and encryption functions to reduce storage space occupation and improve data transmission security; The data forwarding module is electrically connected to the data acquisition module, and the data storage module wirelessly forwards the information data processed by the data processing module.

[0024] Furthermore, when the integrated collector detects a change in the type or number of connected sensors, it will automatically re-perform the interface adaptation and signal acquisition process. When a change in the sensor type is detected, the integrated collector will immediately start the automatic interface adaptation process and automatically adjust the interface adaptation module according to the detection process.

[0025] Furthermore, the integrated collector dynamically adjusts the allocation of system resources according to the actual load of each acquisition module. As the number of sensors increases or decreases, the data acquisition module needs to dynamically adjust the allocation of its system resources. While re-adapting the interface, the data acquisition module will recalculate the current system load and available resources, and re-plan the resource allocation strategy based on the new sensor access status.

[0026] Furthermore, the data forwarding module transmits the encrypted real-time data to the remote monitoring center to ensure data security and real-time performance. After receiving the data, the remote monitoring center parses and analyzes it, identifies sensor failures or insufficient system resources, and takes corresponding actions. At the same time, the monitoring center transmits the processing results and feedback back to the collector, forming a closed-loop feedback mechanism to jointly ensure the stable operation of the data acquisition system.

[0027] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0028] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring, characterized in that: The method steps of the synchronous acquisition algorithm are: S1. The sensor is connected to the acquisition module of the integrated collector, and the sensor signal is collected through the interface adapter module, the signal type is determined, and the signal is automatically adapted; S2. After the adaptation is completed, the integrated collector uses the data acquisition module to obtain the number and type information of the connected sensors and starts the self-test process; S3, the self-test process tests the connected sensors one by one in the order of interfaces to obtain the sensor sampling frequency; S4. After the self-test process is completed, the integrated collector arranges the acquired sampling frequencies in reverse order to form F pmaxi 、F pmax(i-1) ……F pmax(i-i+2) 、Fpmax (i-i+1) , and interrupt the collection; S5, the integrated collector calculates the total system resources, and then automatically allocates system resources according to the sensor collection frequency, collects data, and pre-processes the collected data; S6. After the preprocessing is completed, the data is stored in the integrated collector for backup and forwarding.

2. The synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring according to claim 1 is characterized in that: The method for automatic adaptation of the interface adaptation module in step S1 is: Integrated collector acquisition module interface detection to check the status of each access port and whether the sensor is connected; The sensors connected to the integrated collector are arranged in the order of the acquisition modules, and the signal of the first sensor is acquired through the interface adapter module; The signal is transmitted to the high-impedance input voltage detection unit to determine whether the signal type is voltage. If the detection signal type is voltage, the interface adapter module will process the sensor data according to the voltage signal. If the detection signal type is not voltage, the signal is transmitted to the low-impedance current detection unit to detect and determine that the signal type is current. The interface adapter module will process the sensor data according to the current signal. After the judgment is completed, the integrated collector interrupts the judgment of the first sensor and adapts the remaining sensors in sequence; When a single sensor signal line is interrupted or abnormal, a re-adaptation process will be performed for the interface.

3. The synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring according to claim 1 is characterized in that: The detailed steps of the self-test process in step S2 are: Based on the information of the number of sensors obtained, the integrated collector controls the first acquisition module to collect data at a speed of 100KHz according to the order of interfaces, and the acquisition time is 10S; The integrated collector performs change timing on the collected data, determines the sampling frequency of the current sensor through the change timing, and obtains the data of the collection module again to verify the accuracy of this sampling frequency; If the sampling frequencies obtained by verification are consistent, the sampling frequencies of the acquisition modules of the remaining connected sensors are obtained in sequence; If the sampling frequencies obtained by verification are inconsistent, re-detection is performed until the detection sampling frequency obtained is consistent with the verification sampling frequency, and then the sampling frequencies of the acquisition modules of the remaining connected sensors are obtained in sequence.

4. The synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring according to claim 1 is characterized in that: The calculation method for automatically allocating system resources in step S5 is: The quantity information and frequency information of the acquisition modules obtained based on the integrated collector; Based on the total number of resources of the integrated collector itself, calculate the system resources automatically allocated to the corresponding collection module; The calculation formula for automatically allocating system resources is: In the formula, f i Indicates the system resources f allocated to acquisition module i, F i represents the acquisition frequency F of acquisition module i, n represents the total number of acquisition modules, R total Indicates the total system resources, where the total system resources are calculated as follows: In the formula, represents the weight of memory usage, Indicates memory usage, which is a value between 0 and 1, indicating the percentage of memory occupied. Indicates the weight of CPU usage. Indicates the CPU usage, which is a value between 0 and 1, indicating the percentage of memory usage.

5. The synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring according to claim 1 is characterized by: The data preprocessing in step S5 is aimed at abnormal or erroneous sensor data collected.

6. The synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring according to claim 5 is characterized in that: The preprocessing calculation formula for data anomalies or errors is: Where ∆MA(t,n) represents the time series difference between the previous and next values, N represents the number of data points used to calculate the moving average, n represents the total number of acquisition modules, t represents the current time point, and x(i) represents the original data value i at time point t.

7. The synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring according to claim 1 is characterized in that: The integrated collector based on the multi-source heterogeneous data synchronous acquisition algorithm includes: an acquisition module, an interface adapter module, a data acquisition module, a data processing module, a data storage module and a data forwarding module; The acquisition module is used to connect with the sensor; The interface adapter module is electrically connected to the acquisition module, and the interface adapter module is used to adapt different types of sensors according to the types of sensors; The data acquisition module is electrically connected to the interface adapter module and the acquisition module, and the data acquisition module is used to allocate system resources according to the access status of the acquisition module and obtain the information data collected by the acquisition module; The data processing module is electrically connected to the data acquisition module, and the data processing module pre-processes the information data acquired by the data acquisition module to eliminate data anomalies or errors; The data storage module is electrically connected to the data acquisition module, and the data storage module stores and backs up the information data processed by the data processing module; The data forwarding module is electrically connected to the data acquisition module, and the data storage module wirelessly forwards the information data processed by the data processing module.

8. The synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring according to claim 1 is characterized by: When the integrated collector detects a change in the type or number of connected sensors, it will automatically re-perform the interface adaptation and signal acquisition process.

9. The synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring according to claim 1 is characterized by: The integrated collector dynamically adjusts the allocation of system resources according to the actual load of each acquisition module.

10. The synchronous acquisition algorithm for multi-source heterogeneous data of condition monitoring according to claim 1 is characterized by: The data forwarding module transmits real-time data to the remote monitoring center, which handles sensor failures and insufficient system resources based on the information.

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