Data analysis method and system for miscellaneous source collapse supporting environment

Abstract

The invention relates to a data analysis method and system for a miscellaneous source collapse support environment, and the method comprises the steps: receiving real-time input data of a sensor system, and judging whether temperature information is in a temperature steady-state range or not based on an alarm information judgment function. At least an acceleration sensor, a high-precision angle sensor and a pressure sensor are arranged in the terminal, modular design is adopted, and a gas sensor and other sensors can be expanded through an external expansion interface. The data analysis method for the miscellaneous source collapse supporting environment has an intelligent early warning function and a self working condition and fault judgment function. According to a preset mode and a threshold value, the stability of the supporting structure can be actively judged through multi-parameter comprehensive analysis and evaluation, an audible and visual alarm is automatically carried out when the stability is insufficient, and data of stability reduction is recorded. And when the equipment is not installed in place and is not correct and is influenced by the environment, automatic compensation or fault reminding can be carried out.

Description

Technical Field

[0001] The present application relates to the technical field of emergency support systems, and in particular to a data analysis method and system for a mixed-source collapse support environment. Background Art

[0002] The emergency support system is a comprehensive solution to improve the safety and efficiency of on-site operations. It is suitable for high-risk environments such as collapsed houses, mines, and tunnels. By integrating advanced communication technologies, the system realizes efficient information transmission and collaborative work between devices, thus providing strong technical support for disaster prevention and emergency response. The traditional emergency support system uses the vibration sensor data collected by the terminal device to feedback the vibration state of the on-site working environment, and then warns and alarms the high-risk environment on site. However, it is difficult for the traditional emergency support system to quickly judge the risk of the mixed source collapse support environment. To this end, it is necessary to propose a data analysis method and system for the mixed source collapse support environment in view of the defect that the traditional emergency support system is difficult to quickly judge the risk of the mixed source collapse environment. Summary of the invention

[0003] Based on this, it is necessary to propose a data analysis method and system for the mixed-source collapse support environment to address the defect that the traditional emergency support system is difficult to quickly judge the risk of the mixed-source collapse environment.

[0004] The present application provides a data analysis method for a miscellaneous source collapse support environment, comprising: Call the alarm information judgment function; receiving real-time incoming data about sensor systems; Based on the alarm information judgment function, determine whether the temperature information is within the temperature steady-state range; If the temperature information is not within the temperature steady-state range, the alarm information judgment function is terminated and the temperature characteristic value is fed back; If the temperature information is within the temperature steady-state range, then determine whether the pressure information is within the pressure steady-state range; If the pressure information is not within the pressure steady-state range, the alarm information judgment function is terminated and the pressure characteristic value is fed back; If the pressure information is within the pressure steady-state range, then determine whether the vibration information is within the vibration steady-state range; If the vibration information is not within the vibration steady-state range, the alarm information judgment function is terminated and the vibration characteristic value is fed back; If the vibration information is within the vibration steady-state range, the process returns to receiving the real-time incoming data about the sensor system until a shutdown instruction is received.

[0005] The present application provides a data analysis system for a miscellaneous source collapse support environment, comprising: Terminal equipment, used to execute the data analysis method of the miscellaneous source collapse support environment; A host device, communicatively connected to the terminal device; A host computer is communicatively connected with the terminal device.

[0006] The present application relates to a data analysis method and system for a miscellaneous source collapse support environment, which receives real-time incoming data about the sensor system and judges whether the temperature information is within the temperature steady-state range based on the alarm information judgment function. The terminal is equipped with at least an acceleration sensor, a high-precision angle sensor, and a pressure sensor, and adopts a modular design. Other sensors such as gas sensors can be expanded through external expansion interfaces. The data analysis method for a miscellaneous source collapse support environment has an intelligent early warning function and its own working condition and fault judgment function. It can actively judge the stability of the support structure through multi-parameter comprehensive analysis and evaluation based on pre-set modes and thresholds, automatically sound and light alarms when the stability is insufficient, and record data on decreased stability. When the equipment is not installed in place, incorrectly, or affected by the environment, it can perform autonomous compensation or fault reminders. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 A flow chart of a data analysis method for a miscellaneous source collapse support environment provided in one embodiment of the present application.

[0008] Figure 2 A structural connection diagram of a data analysis system for a miscellaneous source collapse support environment provided in one embodiment of the present application.

[0009] Reference numerals: 100-terminal device; 200-host device; 300-host computer. DETAILED DESCRIPTION

[0010] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0011] The present application provides a data analysis method for a miscellaneous source collapse support environment.

[0012] like Figure 1 As shown, in one embodiment of the present application, a data analysis method for a miscellaneous source collapse support environment includes: S100, calling the alarm information judgment function.

[0013] S200, receiving real-time incoming data about the sensor system.

[0014] S300, judging whether the temperature information is within a temperature steady-state range based on the alarm information judgment function.

[0015] Specifically, the edge computing capability based on the alarm information judgment function can significantly reduce data delay and improve system response speed. The use of multi-parameter comprehensive detection technology and intelligent sensor network can provide more comprehensive and accurate detection results.

[0016] S400: If the temperature information is not within the temperature steady-state range, the alarm information judgment function is terminated and the temperature characteristic value is fed back.

[0017] S500: If the temperature information is within the temperature steady-state range, determine whether the pressure information is within the pressure steady-state range.

[0018] S600: If the pressure information is not within the pressure steady-state range, the alarm information judgment function is terminated and the pressure characteristic value is fed back.

[0019] S700: If the pressure information is within the pressure steady-state range, determine whether the vibration information is within the vibration steady-state range.

[0020] S800: If the vibration information is not within the vibration steady-state range, the alarm information judgment function is terminated and the vibration characteristic value is fed back.

[0021] S900: If the vibration information is within the vibration steady-state range, return to the step of receiving real-time incoming data about the sensor system until a shutdown instruction is received.

[0022] The present embodiment relates to a data analysis method for a miscellaneous source collapse support environment, which receives real-time incoming data about the sensor system and judges whether the temperature information is within the temperature steady-state range based on the alarm information judgment function. The terminal is equipped with at least an acceleration sensor, a high-precision angle sensor, and a pressure sensor, and adopts a modular design. Other sensors such as gas sensors can be expanded through external expansion interfaces. The data analysis method for a miscellaneous source collapse support environment has an intelligent early warning function and its own working condition and fault judgment function. It can actively judge the stability of the support structure through multi-parameter comprehensive analysis and evaluation based on pre-set modes and thresholds, automatically sound and light alarms when the stability is insufficient, and record data on decreased stability. When the equipment is not installed in place, incorrectly, or affected by the environment, it can perform autonomous compensation or fault reminders.

[0023] In one embodiment of the present application, the method further includes: S911, receiving a check cycle.

[0024] Specifically, in addition to data collection, preliminary data processing and analysis (edge ​​computing) can be performed on the device itself, which can significantly reduce the demand for data transmission, reduce dependence on communication networks, and reduce data processing delays.

[0025] Based on the low latency feature, the inspection cycle can be within a smaller time range, thereby achieving high-frequency sampling.

[0026] S912, during the inspection cycle, the real-time cached data of the temperature characteristic value, the pressure characteristic value, and the vibration characteristic value are sequentially called.

[0027] Specifically, the judgment results of the alarm information judgment functions such as temperature characteristic values, pressure characteristic values, vibration characteristic values, etc. can become real-time cache data.

[0028] S913, determining whether the temperature characteristic value is a first alarm characteristic value.

[0029] S914: If the temperature characteristic value is the first alarm characteristic value, stop real-time data caching and output an alarm instruction.

[0030] S915: If the temperature characteristic value is not the first alarm characteristic value, determine whether the pressure characteristic value is the second alarm characteristic value.

[0031] Specifically, based on the temperature characteristic value and the first alarm characteristic value, the system has intelligent early warning functions and its own working condition and fault judgment functions. It can actively judge the stability of the support structure through multi-parameter comprehensive analysis and evaluation according to the pre-set mode and threshold, automatically sound and light alarm when the stability is insufficient, and record the data of stability decline. When the equipment is not installed properly, incorrectly, or affected by the environment, it can perform autonomous compensation or fault reminder.

[0032] S916: If the pressure characteristic value is the second alarm characteristic value, stop caching data in real time and output an alarm instruction.

[0033] S917: If the pressure characteristic value is not the second alarm characteristic value, determine whether the vibration characteristic value is the third alarm characteristic value.

[0034] Specifically, based on the pressure characteristic value and the second alarm characteristic value, the system has intelligent early warning functions and its own working condition and fault judgment functions. It can actively judge the stability of the support structure through multi-parameter comprehensive analysis and evaluation according to the pre-set mode and threshold, automatically sound and light alarm when the stability is insufficient, and record the data of stability decline. When the equipment is not installed properly, incorrectly, or affected by the environment, it can perform autonomous compensation or fault reminder.

[0035] S918: If the vibration characteristic value is the third alarm characteristic value, stop real-time data caching and output an alarm instruction.

[0036] S919, if the vibration characteristic value is not the third alarm characteristic value, then return to the real-time cache data of the temperature characteristic value, the pressure characteristic value, and the vibration characteristic value in sequence during the inspection cycle until a shutdown command is received.

[0037] Specifically, based on the vibration characteristic value and the third alarm characteristic value, the system has intelligent early warning functions and its own working condition and fault judgment functions. It can actively judge the stability of the supporting structure through multi-parameter comprehensive analysis and evaluation according to the pre-set mode and threshold, automatically sound and light alarm when the stability is insufficient, and record the data of stability decline. When the equipment is not installed properly, incorrectly, or affected by the environment, it can perform autonomous compensation or fault reminder.

[0038] The data analysis method for the mixed source collapse support environment is characterized by high sensitivity, and can collect and warn of changes that are not easily perceived. The integrated edge computing capability significantly reduces data latency and improves system response speed. The use of multi-parameter comprehensive detection technology and intelligent sensor networks can provide more comprehensive and accurate detection results.

[0039] In one embodiment of the present application, in S100, the method for constructing the alarm information judgment function includes: S111, calling the fast Fourier transform function.

[0040] S112, receiving vibration frequency data and vibration amplitude data of a coordinate axis.

[0041] S113, incorporating the vibration frequency data and vibration amplitude data of the coordinate axis into a fast Fourier transform function.

[0042] S114, obtaining vibration frequency interval data.

[0043] S115, returning to the step of receiving the vibration frequency data and the vibration amplitude data of one coordinate axis until the reception of the vibration frequency data and the vibration amplitude data of three orthogonal coordinate axes is completed.

[0044] The pressure and angle are measured based on sensors. For example, electronic sensors such as acceleration sensors, high-precision angle sensors, and pressure sensors, as well as mechanical sensors, are used to measure temperature, pressure, and vibration parameters. This solves the problem of requiring close observation under the support column, lack of wireless communication means, and remote data collection capabilities. The data is highly real-time, with high alarm reference, accuracy, and professionalism, and alarms are generated in a timely manner.

[0045] Specifically, the fast Fourier transform function can be used to quickly receive the vibration frequency data and vibration amplitude data of a coordinate axis, and determine the frequency point interval data of the vibration frequency data and vibration amplitude data of a coordinate axis. Based on the frequency point interval data, the alarm information can be judged relatively quickly and accurately.

[0046] In one embodiment of the present application, in S111, the method for establishing the fast Fourier transform function includes: S121, establishing arrays of parameters related to vibration frequency and parameters related to vibration amplitude.

[0047] S122, calling the vibration amplitude data in the dimension of the vibration frequency parameter of the array.

[0048] S123, determining whether the vibration amplitude data is the current maximum data.

[0049] S124: If the vibration amplitude data is the current maximum data, save the vibration amplitude data.

[0050] S125: If the vibration amplitude data is not the current maximum data, determine whether the vibration amplitude data is the current minimum data.

[0051] S126: If the vibration amplitude data is the current minimum data, save the vibration amplitude data.

[0052] S127, if the vibration amplitude data is not the current minimum data, then replace the parameters of the vibration frequency of the array, return the dimension of the parameters of the vibration frequency in the array, and call the vibration amplitude data until the fast Fourier transform of the array of parameters about the vibration frequency and the parameters about the vibration amplitude is completed.

[0053] The arrays of parameters about vibration frequency and vibration amplitude can update vibration parameters, and small changes in these vibration parameters are often key indicators for evaluating structural stability. By monitoring these data, the stability index of the structure can be evaluated more accurately.

[0054] The vibration sensor can measure the lowest vibration frequency of 1 Hz, and the minimum angular velocity resolution of the sensor is 0.2 mg, and the maximum range is 200 g, which can meet the needs of earthquake monitoring. However, according to the current situation, there must be noise interference from various engineering machinery and equipment on site, which may affect the judgment of tiny and infrasonic vibrations. Based on the array, the vibration sensor can determine which vibration is dangerous.

[0055] In one embodiment of the present application, S112 includes: S131, receiving a sampling period.

[0056] S132, receiving data from the vibration sensor within a sampling period.

[0057] S133, calling the algorithm of the ConfDes component.

[0058] S134, based on the algorithm of the ConfDes component, parses the data of the vibration sensor.

[0059] S135, obtaining vibration frequency data and vibration amplitude data of the coordinate axis.

[0060] During the sampling period, the data analysis method of the miscellaneous source collapse support environment is responsible for the collection of sensor data, preliminary processing (including data filtering and compression), threshold judgment and immediate alarm. These devices also have edge computing capabilities and can independently execute data-based decisions, thereby reducing dependence on central systems.

[0061] Among them, the algorithm of the ConfDes component can be used for preliminary processing. The edge computing capability of terminal devices has become a key technology to improve system response speed, reduce cloud load and optimize data processing. The terminal devices in the emergency support system integrate edge computing functions, which significantly enhances the real-time performance, reliability and data processing efficiency of the system.

[0062] In one embodiment of the present application, S100 includes: S141, calling the coordinate axis fusion calculation data update function.

[0063] S142, select a coordinate axis.

[0064] S143, receiving the frequency interval data of the coordinate axis.

[0065] S144, updating the data of the coordinate axis based on the coordinate axis fusion calculation data update function.

[0066] S145, returning to the step of selecting a coordinate axis until the data of all coordinate axes are selected.

[0067] Specifically, after collecting sensor data, the terminal device immediately performs preprocessing, including sliding filtering, Fourier transform, amplitude feature extraction, intelligent data calibration, etc. This not only reduces the amount of data transmitted to the host terminal, but also improves the data quality, laying the foundation for subsequent advanced analysis.

[0068] Based on the data of the updated coordinate axis, the terminal device can perform real-time analysis on the collected data, such as trend prediction, anomaly detection, fault diagnosis, etc. Based on the analysis results, the terminal device can make preliminary decisions immediately, such as triggering alarms, adjusting sensor parameters, etc., to ensure on-site safety.

[0069] In one embodiment of the present application, S100 includes: S151, based on bit reversal sorting, butterfly operation, and fast Fourier transform function, the real-time incoming data is updated.

[0070] Based on the updated real-time incoming data, the terminal device can perform real-time analysis on the collected data, such as trend prediction, anomaly detection, fault diagnosis, etc. Based on the analysis results, the terminal device can make preliminary decisions instantly, such as triggering alarms, adjusting sensor parameters, etc., to ensure on-site safety.

[0071] The terminal device compresses and filters the data and transmits only the key data to the host terminal. This greatly reduces the network bandwidth requirements, especially in environments with poor network conditions, and can effectively avoid data transmission bottlenecks.

[0072] The terminal device is equipped with a local storage function, which can temporarily store data and upload it when the network conditions improve. This method not only improves the reliability of data transmission, but also reduces the dependence on cloud storage.

[0073] The present application provides a data analysis system for a miscellaneous source collapse support environment.

[0074] like Figure 2 As shown, in one embodiment of the present application, a data analysis system for a miscellaneous source collapse support environment includes: The terminal device 100 is used to execute the data analysis method for the miscellaneous source collapse support environment.

[0075] The host device 200 is communicatively connected with the terminal device 100 .

[0076] The host computer 300 is connected to the terminal device 100 for communication.

[0077] Terminal device 100 Device registration: After each startup, the terminal device must first send a registration request to the host device, and can only be officially put into operation after obtaining authorization. Data collection and processing: The successfully registered terminal device will regularly read the value of the built-in sensor and determine whether to trigger an alarm based on the preset threshold. Data upload: According to the communication method adopted (CAN bus or LoRa), the terminal device follows different rules to upload data to the host device or directly to the PC host computer. Threshold and calibration command execution: The terminal device should have the ability to store and apply the threshold information received from the PC host computer, and support the execution of calibration commands to ensure the accuracy of the measurement results. Alarm mechanism: Once the detection value exceeds the safety range, the terminal device should immediately start the alarm program and synchronize the relevant alarm information to the PC host computer to assist decision makers in responding quickly. Upload of abnormal device status: When the sensor on the terminal device is damaged or abnormal, the terminal device will promptly report the current abnormal sensor so that the staff can quickly handle the relevant terminal device.

[0078] The host device 200 is used for device management: in scanning mode, the host device can automatically identify newly added terminal devices and assign unique identifiers to them, and has the ability to clean up the offline device list to ensure the effective use of system resources. In non-scanning mode, the host device will refuse unauthorized new devices to join the network. Data parsing and forwarding: the host device will parse the data information of all terminal devices uploaded through the CAN bus or wireless LoRa, and convert it into JSON format and forward it to the PC host computer through Ethernet. Mode switching: set a reasonable scanning cycle to ensure that the host device can automatically return to the normal operation mode after completing the device scan. Data interaction rules: for different communication paths (CAN bus and LoRa), the host device sets differentiated data transmission strategies to ensure efficient flow of information. For example, for terminal devices connected to the CAN bus, data can only be uploaded after waiting for the host query command; for devices connected to LoRa, they are allowed to report information autonomously at a preset frequency. Offline processing mechanism: when a terminal device is detected to be unresponsive for a long time, the host device will mark it as offline and report it to the PC host computer so that corresponding measures can be taken. Threshold management: The host device supports receiving and forwarding global or individual device thresholds set by the PC host computer to ensure that each terminal device operates according to the latest standards. In addition, the host is also responsible for solidifying the default threshold in local storage. For terminal devices that have not been distributed by the host computer, the host device will distribute the default threshold. Data on the cloud: The host device collects data information from all terminal devices, and through the cloud pushed by MQTT, customers can remotely obtain all sensor data from the cloud.

[0079] The host computer 300 is used for data collection: the PC host computer collects sensor data of the terminal device through the host terminal, including various types of data such as angle, pressure, vibration, and the status information of the device. These data are crucial for evaluating the safety of the on-site environment. Command issuance: the PC host computer can send various control instructions to the host terminal and the terminal device according to the operator's needs or preset logic, including but not limited to device registration, data request, threshold setting, calibration commands, etc. These instructions are transmitted to the host terminal via Ethernet, and then forwarded to the corresponding terminal device by the host terminal according to actual needs. Feedback reception: the PC host computer receives the command execution result feedback from the host terminal in real time, as well as the sensor data and alarm information uploaded by the terminal device. These feedback information is used to verify the execution effect of the instruction and ensure that the system operation status meets expectations. Local storage: the PC host computer is equipped with a large-capacity storage device, which can store the historical data uploaded by the terminal device for a long time, providing support for subsequent data analysis and auditing. Data visualization: the PC host computer provides a graphical interface to display the sensor data and status information of the terminal device in real time. The operator can intuitively understand the working status of each device through charts, dashboards, etc., and quickly discover potential problems. Alarm control: When the terminal device detects an abnormal situation, the PC host computer will immediately display the alarm information. At the same time, by configuring the active alarm and automatic alarm options, the host device can flexibly respond to various emergency situations. The alarm can be triggered remotely by the PC host computer, and the alarm process can be automatically started according to the preset conditions. Device abnormality prompt: When the terminal device is offline or a sensor on the terminal device is abnormal, the host computer will display the offline or abnormal state of the device, so that the operator can handle or replace the relevant equipment in time.

[0080] The technical features of the above-described embodiments may be arbitrarily combined, and the execution order of the method steps is not limited. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0081] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A data analysis method for a mixed source collapse support environment, characterized in that: include: Call the alarm information judgment function; receiving real-time incoming data about sensor systems; Based on the alarm information judgment function, determine whether the temperature information is within the temperature steady-state range; If the temperature information is not within the temperature steady-state range, the alarm information judgment function is terminated and the temperature characteristic value is fed back; If the temperature information is within the temperature steady-state range, then determine whether the pressure information is within the pressure steady-state range; If the pressure information is not within the pressure steady-state range, the alarm information judgment function is terminated and the pressure characteristic value is fed back; If the pressure information is within the pressure steady-state range, then determine whether the vibration information is within the vibration steady-state range; If the vibration information is not within the vibration steady-state range, the alarm information judgment function is terminated and the vibration characteristic value is fed back; If the vibration information is within the vibration steady-state range, the process returns to receiving the real-time incoming data about the sensor system until a shutdown instruction is received.

2. The data analysis method for the miscellaneous source collapse support environment according to claim 1 is characterized in that: The method further includes: receiving an inspection cycle; During the inspection cycle, the real-time cache data of the temperature characteristic value, the pressure characteristic value, and the vibration characteristic value are called in sequence; Determining whether the temperature characteristic value is a first alarm characteristic value; If the temperature characteristic value is the first alarm characteristic value, stop real-time caching data and output an alarm instruction; If the temperature characteristic value is not the first alarm characteristic value, determining whether the pressure characteristic value is the second alarm characteristic value; If the pressure characteristic value is the second alarm characteristic value, stop real-time caching data and output an alarm instruction; If the pressure characteristic value is not the second alarm characteristic value, determining whether the vibration characteristic value is the third alarm characteristic value; If the vibration characteristic value is the third alarm characteristic value, stop real-time caching data and output an alarm instruction; If the vibration characteristic value is not the third alarm characteristic value, the method returns to the real-time cache data of the temperature characteristic value, the pressure characteristic value, and the vibration characteristic value, which are sequentially called during the inspection cycle, until a shutdown command is received.

3. The data analysis method for the miscellaneous source collapse support environment according to claim 2 is characterized in that: In the calling of the alarm information judgment function, the construction method of the alarm information judgment function includes: Call the fast Fourier transform function; Receive the vibration frequency data and vibration amplitude data of a coordinate axis; Incorporating the vibration frequency data and vibration amplitude data of the coordinate axis into the fast Fourier transform function; Obtain vibration frequency interval data; The process of receiving the vibration frequency data and the vibration amplitude data of one coordinate axis is returned until the vibration frequency data and the vibration amplitude data of three orthogonal coordinate axes are all received.

4. The data analysis method for the miscellaneous source collapse support environment according to claim 3 is characterized in that: Before calling the fast Fourier transform function, the method for establishing the fast Fourier transform function includes: Create arrays of parameters related to vibration frequency and parameters related to vibration amplitude; In the dimension of the vibration frequency parameter of the array, call the vibration amplitude data; Determine whether the vibration amplitude data is the current maximum data; If the vibration amplitude data is the current maximum data, then save the vibration amplitude data; If the vibration amplitude data is not the current maximum data, determine whether the vibration amplitude data is the current minimum data; If the vibration amplitude data is the current minimum data, then save the vibration amplitude data; If the vibration amplitude data is not the current minimum data, the parameters of the vibration frequency of the array are replaced, the dimension of the parameters of the vibration frequency in the array is returned, and the vibration amplitude data is called until the fast Fourier transform of the array of parameters about the vibration frequency and the parameters about the vibration amplitude is completed.

5. The data analysis method for the miscellaneous source collapse support environment according to claim 4 is characterized in that: The receiving of vibration frequency data and vibration amplitude data of a coordinate axis includes: Receive sampling period; During the sampling period, the data of the vibration sensor is received; Call the algorithm of the ConfDes component; Analyze the vibration sensor data based on the algorithm of ConfDes component; Obtain the vibration frequency data and vibration amplitude data of the coordinate axis.

6. The data analysis method for the miscellaneous source collapse support environment according to claim 5 is characterized in that: In the calling of the alarm information judgment function, the method for constructing the alarm information judgment function further includes: Call the coordinate axis fusion calculation data update function; Select an axis; Receive frequency point interval data of the coordinate axis; Based on the coordinate axis fusion calculation data update function, update the data of the coordinate axis; Return to selecting a coordinate axis until all the coordinate axis data are selected.

7. The data analysis method for the miscellaneous source collapse support environment according to claim 6 is characterized in that: In the calling of the alarm information judgment function, the method for constructing the alarm information judgment function further includes: Based on bit reversal sorting, butterfly operation, and fast Fourier transform functions, the real-time incoming data is updated.

8. A data analysis system for a miscellaneous source collapse support environment, characterized in that: include: A terminal device, used to execute the data analysis method for a miscellaneous source collapse support environment according to any one of claims 1 to 7; A host device, communicatively connected to the terminal device; A host computer is communicatively connected with the terminal device.

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