Oil and gas RTU multi-signal concurrent acquisition and intelligent control method and system

Abstract

The application discloses an oil and gas RTU multi-signal concurrent acquisition and intelligent control method, step 1, building a BSP layer, a kernel real-time scheduling layer, a middleware layer and an industry application layer; step 2, multi-type signal parallel concurrent synchronous acquisition, creating a multi-thread independent acquisition task to acquire data; step 3, real-time monitoring of the whole machine CPU and memory occupancy rate; dynamic allocation of system thread priority; step 4, local edge intelligent diagnosis and logic interlocking control; step 5, enabling wired link and wireless link dual-channel transmission of the data analyzed in step 4; real-time monitoring of the link operation. The application adopts multi-thread parallel acquisition to replace traditional serial polling, multi-type instrument synchronous acquisition, improves the acquisition efficiency, realizes dynamic self-adaptive management and control of system resources, realizes on-site intelligent diagnosis of oil and gas equipment faults by using local edge computing, and reduces the cloud transmission pressure.

Description

Technical Field

[0001] This invention belongs to the field of industrial Internet of Things technology, and relates to intelligent oil and gas measurement and control technology, specifically to a method and system for concurrent acquisition and intelligent control of multiple signals from an oil and gas RTU. Background Technology

[0002] A Remote Terminal Unit (RTU) is a terminal device used in industrial fields to collect sensor data, remotely upload data, and remotely control equipment. Existing oil and gas RTU control methods are mostly based on foreign closed-source Linux systems, relying on overseas chips for both hardware and software, which poses information security vulnerabilities. Traditional data acquisition methods employ polling serial acquisition, with time-sharing acquisition from AI (analog input), DI (digital input), wireless ZigBee instruments, and RS485 flow meters. These methods have weak concurrent processing capabilities, leading to system lag and excessive CPU usage when multiple signals are simultaneously accessed. Traditional equipment lacks local edge computing capabilities, and all data is uploaded to a remote SCADA platform (Supervisory Control and Data Acquisition) for analysis. When the network is interrupted, it cannot achieve local logic interlocking and fault early warning. Data transmission is only transmitted via a single wired link, and data is lost when the link is broken, resulting in a high packet loss rate. Meanwhile, existing equipment lacks a unified driver adaptation solution for multiple buses compatible with HarmonyOS. Protocols such as Modbus and CANopen require separate development of adaptation programs, resulting in high development costs. There is no automatic temperature drift correction or dynamic resource management mechanism, leading to a continuous decrease in acquisition accuracy under high and low temperature environments, and system resource overflow and crashes during long-term operation. Furthermore, there is a lack of intelligent diagnostic algorithms for oil and gas pumping unit operating conditions, making it impossible to locally identify problems such as motor failures, balance abnormalities, and pipeline leaks. Summary of the Invention

[0003] To address the shortcomings of existing RTU control methods, such as reliance on foreign systems, low efficiency of serial acquisition, lack of local edge computing, single transmission link, lack of adaptive resource management and control, and lack of local intelligent diagnosis of oil and gas equipment, this paper proposes a method for concurrent acquisition and intelligent control of multiple signals in oil and gas RTUs. This method enables parallel synchronous acquisition of multiple types of signals, dynamic management and control of system resources, lossless transmission with multi-link redundancy, intelligent diagnosis of local edge faults, and unified adaptation to multiple industrial protocols.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: A method for concurrent multi-signal acquisition and intelligent control of oil and gas RTUs includes the following steps: Step 1. Build the BSP layer, kernel real-time scheduling layer, middleware layer, and industry application layer; complete hardware driver adaptation in the BSP layer; embed a real-time interrupt scheduling module in the kernel real-time scheduling layer; build a unified industrial protocol abstraction interface in the middleware layer; and load the control software package in the industry application layer. Step 2: Parallel and concurrent synchronous acquisition of multiple signal types Create multi-threaded independent data acquisition tasks, and simultaneously start multiple analog signal acquisition threads, multiple digital signal acquisition threads, wireless instrument acquisition threads, and third-party flow meter acquisition threads; collect data and generate standardized point data with timestamps; Step 3: Adaptive Dynamic Management of System Resources Real-time monitoring of overall system CPU and memory usage; dynamic allocation of system thread priorities; Step 4: Local Edge Intelligent Diagnosis and Logic Interlocking Control The local edge computing module loads the device intelligent diagnostic algorithm, parses the standardized location data obtained in step 2, judges the device operating status, and takes abnormal handling measures when the device is judged to be abnormal. Step 5: Multi-link redundant lossless data long-distance transmission Enable dual-channel transmission of the data parsed in step 4 to the remote SCADA platform via both wired and wireless links; monitor the link operation status in real time.

[0005] Preferably, the oil and gas RTU multi-signal concurrent acquisition and edge intelligent control method further includes: Step 6: Remote Secure Partition Firmware Upgrade The system employs a dual-partition backup mechanism and remotely encrypted distribution of HarmonyOS firmware; the upgrade process involves power outages and automatic rollback to the original stable system; upon completion of the upgrade, hardware driver compatibility is automatically verified, and the oil and gas industry control software package is updated simultaneously.

[0006] Preferably, the dual-partition backup mechanism includes a system running partition and a firmware backup partition, and automatically switches back to the running partition when firmware verification fails or upgrade is interrupted.

[0007] Preferably, a segmented temperature drift compensation algorithm is used for the data acquired by the analog acquisition thread in step 2, and the acquired values ​​are dynamically corrected according to the real-time temperature of the device. The segmented temperature drift compensation algorithm is as follows:

[0008] Where C is the data value after temperature compensation correction; C_raw is the original data collected; α is the temperature compensation coefficient, obtained from experimental calibration; T is the temperature value measured in real time by the temperature sensor; and T_ref is the reference temperature during calibration.

[0009] Preferably, in step 3, the CPU and memory usage of the entire machine are monitored in real time; the main control frequency is automatically adjusted under high and low temperature environments, the frequency is reduced at low temperatures to stabilize power consumption, and the frequency is reduced at high temperatures to avoid overheating and crashing; a resource overflow protection mechanism is set up, and idle acquisition threads are automatically released when the threshold is exceeded.

[0010] Preferably, in step 5, the wired link is a dual Ethernet wired link and the wireless link is a Wi-Fi wireless link; the communication latency and packet loss rate of each link are monitored in real time; when a link fails, it automatically switches to another link; the transmission adopts a breakpoint resume mechanism, and the cached historical data is retransmitted after the network interruption is restored.

[0011] Preferably, the abnormal handling measures in step 4 include directly outputting a control signal to shut down the valve and stop the machine when the data exceeds the limit, automatically triggering an audio alarm, and storing the fault record locally.

[0012] This invention also discloses a multi-signal concurrent acquisition and intelligent control system for oil and gas RTUs. The system, used to execute the multi-signal concurrent acquisition and edge intelligent control method for oil and gas RTUs, includes a CPU module, a communication module, an input module, an output module, an audio alarm module connected to the CPU module, and a power supply module for powering the system. The input module includes analog acquisition channels and digital acquisition channels. The communication module includes at least two of the following: RS232 interface, RS485 interface, CAN interface, dual-channel Ethernet interface, Wi-Fi interface, and ZigBee interface, with each interface having independent and isolated wiring.

[0013] Preferably, it also includes a watchdog module; the watchdog module includes an SD8931 clock chip connected to the CPU module and a watchdog timer connected to the clock chip.

[0014] Preferably, the audio alarm module includes a WM8960 audio chip and a 24V power amplifier output interface connected to the audio chip.

[0015] The oil and gas RTU multi-signal concurrent acquisition and edge intelligent control method described in this invention can be adapted to domestic open-source HarmonyOS system and domestic hardware; it adopts multi-threaded parallel acquisition to replace traditional serial polling, and multiple types of instruments acquire data simultaneously, improving acquisition efficiency by more than 3 times; the temperature drift compensation algorithm has a long-term stable acquisition error of less than ±0.5%. Attached Figure Description

[0016] Figure 1 This is a schematic diagram illustrating a specific implementation of the oil and gas RTU multi-signal concurrent acquisition and intelligent control method described in this invention. Figure 2This is a schematic diagram illustrating a specific implementation of the oil and gas RTU multi-signal concurrent acquisition and intelligent control system described in this invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention.

[0018] The oil and gas RTU multi-signal concurrent acquisition and intelligent control method described in this invention can be applied to the RK3568 HarmonyOS RTU hardware terminal based on the domestically developed oil and gas RTU multi-signal concurrent acquisition and edge intelligent control method using the open-source HarmonyOS operating system. It includes the following steps: Step 1: Operating System Initialization and Adaptation In the oil and gas RTU multi-signal concurrent acquisition and edge intelligent control system, a BSP (Board Support Package) layer, a kernel real-time scheduling layer, a middleware layer, and an industry application layer are built. At the BSP layer, hardware driver adaptation for domestic RK3568 terminals, AI / DI / DO (digital signal output), RS485 / CAN / Wi-Fi / ZigBee is completed. A real-time interrupt scheduling module is embedded in the kernel real-time scheduling layer to shorten the response latency of acquisition commands. A unified industrial protocol abstraction interface is built in the middleware layer, compatible with Modbus RTU / TCP and CANopen multi-bus protocols. A standardized control software package for the oil and gas industry is loaded at the industry application layer.

[0019] Step 2: Parallel and concurrent synchronous acquisition of multiple signal types Create multi-threaded independent acquisition tasks, simultaneously starting 8 AI analog signal acquisition threads, 10 DI digital signal acquisition threads, ZigBee wireless instrument acquisition threads, and RS485 third-party flow meter acquisition threads; employ a segmented temperature drift compensation algorithm for the analog input (AI) acquired data, dynamically correcting the acquired values ​​based on the real-time temperature of the equipment to suppress long-term operating errors; locally cache the acquired data to 8GB Flash, generating timestamped standardized point data.

[0020] The segmented temperature drift compensation algorithm can be implemented in the following ways:

[0021] Where C is the data value after temperature compensation correction; C_raw is the original data collected; α is the temperature compensation coefficient, which is obtained by experimental calibration. For example, for mica slurry, the typical value range is 0.0002~0.0008 / °C; T is the temperature value (°C) measured in real time by the temperature sensor; T_ref is the reference temperature (°C) when the concentration sensor is calibrated, usually taken as 20°C or 25°C.

[0022] Step 3: Adaptive Dynamic Management of System Resources Real-time monitoring of overall CPU and memory usage; dynamic allocation of system thread priorities when multiple signals are collected concurrently at peak values, limiting peak CPU usage to ≤75% and memory usage to ≤60%; automatic adjustment of main control frequency under high and low temperature environments, frequency reduction at low temperatures to stabilize power consumption, and frequency reduction at high temperatures to avoid overheating and crashes; setting a resource overflow protection mechanism, automatically releasing idle acquisition threads when thresholds are exceeded.

[0023] Step 4: Local Edge Intelligent Diagnosis and Logic Control The local edge computing module loads an intelligent diagnostic algorithm for the pumping unit, simultaneously analyzing multi-dimensional data such as load, angular displacement, oil pressure, and motor electrical parameters. It can automatically identify faults such as motor overload, imbalance, pipeline leakage, and abnormal dynamic fluid level. It has built-in visualized multi-condition interlocking logic and supports AND / OR combination judgment. That is, when determining whether a fault has occurred, it is necessary to perform AND / OR combination judgment on the data. For example, if the internal pressure of the pipeline decreases and the input is normal, it is determined that the pipeline is leaking. When the data exceeds the limit, the control signal is output directly from the local digital signal output channel DO to shut down the valve and stop the machine without relying on a remote SCADA platform. Faults automatically trigger audio and voice alarms, and fault records are stored locally.

[0024] Step 5: Multi-link redundant data transmission Simultaneously, dual Ethernet wired links and Wi-Fi wireless links are enabled for dual-channel transmission; real-time monitoring of communication latency and packet loss rate of each link; automatic switching to backup channels in milliseconds when a link fails; transmission adopts a breakpoint resume mechanism, and cached historical data is retransmitted after network interruption recovery, with a packet loss rate of ≤0.001% for massive data transmission of the whole machine and an end-to-end transmission latency of ≤200ms.

[0025] Step 6: Remote Secure Partition Firmware Upgrade The system employs a dual-partition backup mechanism, remotely encrypting and distributing HarmonyOS firmware; during the upgrade process, it automatically rolls back to the original stable system in the event of a power outage; upon completion of the upgrade, it automatically verifies hardware driver compatibility and synchronously updates the oil and gas industry control software package. The dual-partition backup mechanism includes a system running partition and a firmware backup partition. If firmware verification fails or the upgrade is interrupted, it automatically switches back to the running partition to prevent device failure.

[0026] The software implementing the method described in this invention is deployed on a domestic HarmonyOS RTU terminal. After the device is powered on, the OpenHarmony four-layer architecture is initialized, and all domestic hardware drivers and unified protocol middleware are loaded. Subsequently, the system starts four independent acquisition threads to simultaneously acquire oil pressure, temperature AI analog signals, valve position DI switch signals, ZigBee wireless pressure data, and RS485 flow meter flow data. The internal temperature of the device is read in real time, and the AI ​​acquisition temperature drift error is corrected in segments. All data is stored locally. The background monitors CPU and memory resources in real time. In the summer, when the well site is hot, the main control frequency is automatically reduced. In the winter, when the temperature is low, the thread scheduling priority is increased. When the resource usage reaches the threshold, idle tasks are automatically cleaned up. Step 4 involves the pre-loaded edge computing software module inside the CPU module to analyze the operating parameters of the pumping unit in real time. When the load fluctuation exceeds the threshold or the motor current is abnormal, a fault alarm is generated locally, the audio module is driven to broadcast the fault type, and a DO signal is output to cut off the pumping unit motor. The interlocking logic is configured with high and low pressure protection, and the air inlet valve is automatically closed when the casing pressure exceeds the upper limit. Data is simultaneously uploaded to the SCADA system via dual network ports. When the main network port is disconnected, the Wi-Fi channel is automatically switched. Once the network is restored, all historical data cached during the network outage is retransmitted. When an upgrade is needed, the firmware is remotely distributed via debugging software, the system writes to the backup partition, and the system partition is switched after verification. If the power is interrupted during the upgrade, the original system partition is automatically retained to ensure uninterrupted operation of the device.

[0027] like Figure 2 The illustration shows a specific embodiment of the oil and gas RTU multi-signal concurrent acquisition and intelligent control system of the present invention. The oil and gas RTU multi-signal concurrent acquisition and intelligent control system is used to execute the oil and gas RTU multi-signal concurrent acquisition and intelligent control method of the present invention.

[0028] The oil and gas RTU multi-signal concurrent acquisition and intelligent control system includes a CPU module, a communication module, an input module, an output module, a watchdog module, an audio alarm module, and a display module connected to the CPU module, as well as a power supply module for powering the system.

[0029] The CPU module uses a domestically produced RK3568 quad-core main control chip, equipped with 2GB of domestically produced RAM and 8GB of domestically produced Flash, providing strong computing and storage capabilities and supporting local edge data caching. The input module includes analog and digital acquisition channels. The analog acquisition channel integrates eight 16-bit analog acquisition circuits, a voltage reference chip, and an ADC (Analog-to-Digital Converter) chip, compatible with two-wire and four-wire 4-20mA instruments. The digital acquisition channel uses a 10-channel digital input isolation circuit, paired with a ULN2803 driver chip including an eight-channel Darlington transistor array. Each channel supports AC250V / DC30V 5A loads and uses optocoupler isolation to distinguish between 0~7V low levels and 12~24V high levels, achieving isolated acquisition of high and low voltage signals. The output module uses a 10-channel relay output driver circuit.

[0030] Figure 2 In the specific implementation shown, the 8 channels of the analog acquisition channel synchronously acquire analog signals such as oil pressure, casing pressure, temperature, and liquid level, which are then converted by a 16-bit ADC and uploaded to the CPU module; the 10 channels of the digital acquisition channel acquire digital signals representing the well site switch and valve position status, and the 10 digital signals of the output module control the pumping unit motor and control valves, respectively.

[0031] The communication module integrates 2 RS232 interfaces, 2 RS485 interfaces, 1 CAN interface, dual Ethernet interfaces, a Wi-Fi interface, and a ZigBee interface. Each communication channel has independent and isolated wiring for connecting different devices. Figure 2 In the specific implementation shown, during data acquisition and system operation, the flow meter and moisture meter are connected via RS485 and RS232 interfaces respectively, the CAN interface is connected to the local control cabinet, the dual Ethernet interfaces are connected to the remote SCADA platform via wired connection, and the Wi-Fi and ZigBee interfaces are connected to the pressure and temperature transmitters on site via wireless connection.

[0032] The power module adopts a DC-DC+LDO multi-level isolated power supply architecture, supports DC24V wide voltage input, and provides independent power supply for CPU, IO, communication, and audio circuits.

[0033] The audio alarm module integrates a WM8960 audio chip and a 24V power amplifier output interface, enabling local fault voice broadcasting; the watchdog module integrates a domestic SD8931 clock chip and a hardware watchdog timer, which can automatically reset when the device crashes and save time parameters when power is lost.

[0034] After a 7-day long-term test in the applicant's laboratory, all 120,000+ data requests were responded to with a 0% dropout rate; under cyclic testing at high and low temperatures of -40℃ to +85℃, the acquisition accuracy was stable, and the CPU usage was at most 6% under multi-signal concurrent conditions, meeting the long-term stable monitoring and control requirements of oil and gas fields.

[0035] The oil and gas RTU multi-signal concurrent acquisition and intelligent control method described in this invention is based on the domestically produced OpenHarmony system and domestically produced hardware, with no dependence on overseas underlying systems throughout the entire process, which improves the information security of oil and gas industrial control and complies with the national policy of localization of industrial equipment. This invention employs multi-threaded parallel data acquisition instead of traditional serial polling, enabling simultaneous data acquisition from multiple instrument types, thus improving acquisition efficiency by more than 3 times; the temperature drift compensation algorithm maintains a stable acquisition error of less than ±0.5% over long-term operation. The system resources of this invention achieve dynamic adaptive management and control, and it operates stably under high and low temperature conditions. During 7 days of continuous testing, the average CPU usage was only 1.95% and the average memory usage was 29.75%, with no crashes or lags. This invention utilizes local edge computing to achieve on-site intelligent diagnosis of oil and gas equipment faults and independent logical interlocking, ensuring equipment safety and controllability even in the event of a network outage, and significantly reducing cloud transmission pressure. This invention utilizes multi-link redundant transmission and breakpoint resume to effectively overcome zero data loss in complex network environments in the field, making it suitable for unattended scenarios in dispersed oilfield well sites. This invention employs a dual-zone secure remote upgrade, avoiding system downtime during on-site equipment upgrades and reducing on-site maintenance labor costs; it also uses a unified industrial protocol middleware to quickly adapt to multiple scenarios such as oil pumping units, water injection wells, gas wells, and water utilities, shortening project development cycles.

[0036] The foregoing descriptions are preferred embodiments of the present invention. Unless there is a clear contradiction between the preferred embodiments or a premise based on a particular preferred embodiment, the preferred embodiments can be arbitrarily combined and used. The embodiments and specific parameters described are only for clearly illustrating the inventor's invention verification process and are not intended to limit the scope of patent protection of the present invention. The scope of patent protection of the present invention shall still be determined by its claims. Similarly, any equivalent structural changes made based on the content of the specification of the present invention shall also be included within the scope of protection of the present invention.

Claims

1. A method for concurrent multi-signal acquisition and intelligent control of oil and gas RTUs, characterized in that, Includes the following steps: Step 1. Build the BSP layer, kernel real-time scheduling layer, middleware layer, and industry application layer; complete hardware driver adaptation in the BSP layer; embed a real-time interrupt scheduling module in the kernel real-time scheduling layer; build a unified industrial protocol abstraction interface in the middleware layer; and load the control software package in the industry application layer. Step 2: Parallel and concurrent synchronous acquisition of multiple signal types Create multi-threaded independent data acquisition tasks, and simultaneously start multiple analog signal acquisition threads, multiple digital signal acquisition threads, wireless instrument acquisition threads, and third-party flow meter acquisition threads; collect data and generate standardized point data with timestamps; Step 3: Adaptive Dynamic Management of System Resources Real-time monitoring of overall system CPU and memory usage; dynamic allocation of system thread priorities; Step 4: Local Edge Intelligent Diagnosis and Logic Interlocking Control The local edge computing module loads the device intelligent diagnostic algorithm, parses the standardized location data obtained in step 2, judges the device operating status, and takes abnormal handling measures when the device is judged to be abnormal. Step 5: Multi-link redundant lossless data long-distance transmission Enable dual-channel transmission of the data parsed in step 4 to the remote SCADA platform via both wired and wireless links; monitor the link operation status in real time.

2. The method for concurrent acquisition and intelligent control of oil and gas RTU signals according to claim 1, characterized in that, The oil and gas RTU multi-signal concurrent acquisition and edge intelligent control method also includes: Step 6: Remote Secure Partition Firmware Upgrade The system employs a dual-partition backup mechanism and remotely encrypted distribution of HarmonyOS firmware; the upgrade process involves power outages and automatic rollback to the original stable system; upon completion of the upgrade, hardware driver compatibility is automatically verified, and the oil and gas industry control software package is updated simultaneously.

3. The method for concurrent acquisition and intelligent control of oil and gas RTU signals according to claim 2, characterized in that, The dual-partition backup mechanism includes a system running partition and a firmware backup partition. When firmware verification fails or the upgrade is interrupted, it automatically switches back to the running partition.

4. The method for concurrent acquisition and intelligent control of oil and gas RTU signals according to claim 1, characterized in that, The data acquired by the analog acquisition thread in step 2 is processed using a segmented temperature drift compensation algorithm. The acquired values ​​are dynamically corrected based on the real-time temperature of the device. The segmented temperature drift compensation algorithm is as follows: ； Where C is the data value after temperature compensation correction; C_raw is the original data collected; α is the temperature compensation coefficient, obtained from experimental calibration; T is the temperature value measured in real time by the temperature sensor; and T_ref is the reference temperature during calibration.

5. The method for concurrent acquisition and intelligent control of oil and gas RTU signals according to claim 1, characterized in that, In step 3, the CPU and memory usage of the entire machine are monitored in real time; the main control frequency is automatically adjusted under high and low temperature conditions, the frequency is reduced at low temperatures to stabilize power consumption, and the frequency is reduced at high temperatures to avoid overheating and crashing; a resource overflow protection mechanism is set up, and idle acquisition threads are automatically released when the threshold is exceeded.

6. The method for concurrent acquisition and intelligent control of oil and gas RTU signals according to claim 1, characterized in that, In step 5, the wired link is a dual Ethernet wired link and the wireless link is a Wi-Fi wireless link; the communication latency and packet loss rate of each link are monitored in real time; when a link fails, it automatically switches to another link; the transmission adopts a breakpoint resume mechanism, and the cached historical data is retransmitted after the network interruption is restored.

7. The method for concurrent acquisition and intelligent control of oil and gas RTU signals according to claim 1, characterized in that, The abnormal handling measures in step 4 include directly outputting a control signal to shut down the valve and stop the machine when the data exceeds the limit, automatically triggering an audio alarm, and storing the fault record locally.

8. A multi-signal concurrent acquisition and intelligent control system for oil and gas RTUs, characterized in that, The system is used to execute the oil and gas RTU multi-signal concurrent acquisition and edge intelligent control method as described in any one of claims 1 to 7, comprising a CPU module, a communication module, an input module, an output module, an audio alarm module connected to the CPU module, and a power supply module for powering the system. The input module includes analog signal acquisition channels and digital signal acquisition channels. The communication module includes at least two of the following: RS232 interface, RS485 interface, CAN interface, dual-channel Ethernet interface, Wi-Fi interface, and ZigBee interface, with each interface having independent and isolated wiring.

9. The oil and gas RTU multi-signal concurrent acquisition and edge intelligent control system according to claim 8, characterized in that, It also includes a watchdog module; the watchdog module includes an SD8931 clock chip connected to the CPU module and a watchdog timer connected to the clock chip.

10. The oil and gas RTU multi-signal concurrent acquisition and edge intelligent control system according to claim 8, wherein the audio alarm module integrates a WM8960 audio chip and a 24V power amplifier output interface.

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