Data Acquisition Terminal for Oil and Gas Production Cloud Platform

Abstract

The data acquisition terminal of the oil and gas production cloud platform of the present invention. The production data acquisition module uses multiple sensors to detect the oil and gas production operation parameters, and enters the station control subsystem under the control of the sampling rate. The sampling rate is obtained from the cloud platform congestion assessment circuit, the change amplitude detection circuit, and the clock generation circuit. It realizes adjusting the sampling rate according to the preset sampling rate weight, the change amplitude of the sensor acquisition signal, and the proportion of the cloud platform data transceiver rate, and realizes setting the sampling rate at the data acquisition source of the station control subsystem and then transmitting. It can reduce the amount of data output and avoid missing important data. After data fusion and anomaly analysis, it can ensure the data accuracy and timely detect anomalies, and then enter the communication module. The signal after data fusion is transmitted to the cloud platform through the public network, and the signal after anomaly analysis is transmitted to the cloud platform through the dedicated network to ensure that the cloud platform receives the anomaly data in a timely manner.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas production data acquisition, and particularly relates to a data acquisition terminal for an oil and gas production cloud platform. Background Art

[0002] For the acquisition of existing oil and gas well production data, relevant sensors are used (for example, in pumping wells, a pressure transmitter is used to detect the oil pressure and casing pressure, a load sensor is used to detect the load, a displacement sensor is used to detect the displacement, and the voltage and current of the pumping unit are collected, etc. The production environments of key oil and gas wells and high-risk wells are detected through cameras, gas detection instruments, etc.). The production data of oil and gas wells are automatically collected and transmitted to the station control subsystem through wired or short-range wireless such as ZigBee. Each station control subsystem transmits the data to the cloud platform through a wireless communication network to achieve data acquisition, storage, and can perform real-time working condition analysis, historical working condition comparison analysis, alarm, wax removal control, etc. However, the data received and processed by the cloud platform is huge. The existing technology usually adopts the method of controlling the sampling rate to prevent traffic congestion on the cloud platform server. Especially when there is traffic congestion, the sampling rate is set very low or sampling is stopped. This method of processing at the data acquisition terminal will miss important data. Summary of the Invention

[0003] In view of the above situation, to overcome the defects of the existing technology, the present invention provides a data acquisition terminal for an oil and gas production cloud platform. After setting the sampling rate at the data acquisition source of the station control subsystem according to the pre-set sampling rate weight, the change amplitude of the sensor acquisition signal, and the proportion of the data receiving and transmitting rate of the cloud platform, and then transmitting, it effectively solves the problem that the existing technology misses important data by controlling the sampling rate at the data acquisition terminal.

[0004] Its technical solution is that it includes a production data acquisition module, a station control subsystem, a communication module, and a cloud platform. The production data acquisition module uses multiple sensors to detect oil and gas production operation parameters;

[0005] The station control subsystem receives the oil and gas production operation parameters detected by multiple sensors under the control of the sampling rate, and connects to the communication module after data fusion and anomaly analysis;

[0006] The communication module includes a public network and a private network. The signal after data fusion is transmitted to the cloud platform through the public network, and the signal after anomaly analysis is transmitted to the cloud platform through the private network.

[0007] Preferably, the sampling rate is obtained according to a cloud platform congestion assessment circuit, a change amplitude detection circuit, and a clock generation circuit;

[0008] The congestion assessment circuit of the cloud platform performs a division operation on the rate of data transmitted and received by the cloud platform. The obtained ratio is subjected to amplitude limiting and charging. When there is congestion, the double diodes conduct, and through reverse coupling with the control voltage, the pulse frequency of the data received by the cloud platform is adjusted.

[0009] The change amplitude detection circuit receives the oil and gas production operation parameters detected by the sensor. After filtering, amplitude limiting and amplification, and after sample and hold, it enters the station control subsystem. The signals before and after sample and hold enter the differential amplifier to obtain the amplitude difference. When the change amplitude is large, the amplitude difference is output to the clock generation circuit.

[0010] The clock generation circuit uses a voltage-controlled oscillator composed of a NOT gate, resistors, capacitors, and a varactor diode DC1 to generate square wave pulses as the sampling time rate. The voltage after ring filtering is subjected to weighted proportional operation and coupled to the power supply of the voltage-controlled oscillator to adjust the square wave pulse frequency. The amplitude difference is coupled to the negative electrode of the varactor diode DC1 to adjust the duty cycle of the square wave pulse.

[0011] Preferably, the specific steps after data fusion and anomaly analysis are as follows:

[0012] Step 1: Use the moving average method to obtain the predicted values of the oil and gas production operation parameters detected by multiple sensors.

[0013] Step 2: Use low-pass filtering to receive the oil and gas production operation parameters detected by multiple sensors.

[0014] Step 3: On the basis of Step 2, use skewness to establish a dynamic detection threshold to discriminate and eliminate gross errors, and obtain the measured values.

[0015] Step 4: Use the weighted fusion algorithm to calculate the measured values and predicted values to obtain the measurement data of a single sensor.

[0016] Step 5: Use the iterative clustering algorithm to fuse the measurement data of each sensor to obtain the fused data. Compare the fused data with the historical fault model. When the similarity is 96%, it is determined as abnormal or faulty.

[0017] Preferably, the clock generation circuit includes a NOT gate U2 and a capacitor C9. One end of pin 1 of the NOT gate U2 and one end of the capacitor C9 are connected to the positive pole of a diode D5. Pin 2 of the NOT gate U2 is connected to one end of a capacitor C10. The other end of the capacitor C10 is respectively connected to one end of a resistor R23 and pin 2 of a NAND gate U3. Pin 1 of the NAND gate U3 is respectively connected to the other end of the capacitor C9 and one end of a resistor R22. The other end of the resistor R22 and the other end of the resistor R23 are connected to the power supply +5V. Pin 3 of the NAND gate U3 is connected to pin 1 of a NOT gate U4. Pin 4 of the NOT gate U4 is connected to one end of a resistor R3. The other end of the resistor R3 is respectively connected to one end of a capacitor C3 and one end of a resistor R5. The other end of the capacitor C3 is respectively connected to one end of a grounding resistor R4 and one end of a grounding capacitor C4. The other end of the resistor R5 is respectively connected to the inverting input terminal of an operational amplifier AR3 and one end of a resistor R6. The non-inverting input terminal of the operational amplifier AR3 is connected to ground through a resistor R7. The output terminal of the operational amplifier AR3 is respectively connected to the other end of the resistor R6 and one end of a resistor R8A. The other end of the resistor R8A is respectively connected to one end of a resistor R9, one end of a resistor R8B, and one end of a resistor R10. The other end of the resistor R8B is connected to the power supply +5V. The other end of the resistor R9 is respectively connected to one end of a capacitor C5 and pin 1 of a NOT gate NOT1. Pin 2 of the NOT gate NOT1 is connected to one end of a capacitor C6. The other end of the capacitor C6 is respectively connected to the other end of the resistor R10 and pin 1 of a NOT gate NOT2. Pin 2 of the NOT gate NOT2 is connected to the control terminal of a switch K1 and the positive pole of a varactor diode DC1. The negative pole of the varactor diode DC1 is connected to the other end of the capacitor C5 and the other end of a resistor R15.

[0018] Advantages of the present invention: 1. By setting a cloud platform congestion assessment circuit, a clock generation circuit, and a change amplitude detection circuit in the station control subsystem, adjusting the sampling rate according to the pre-set sampling rate weight, the change amplitude of the sensor acquisition signal, and the data rate ratio of the cloud platform for data transmission and reception, adjusting the oil and gas production operation parameters detected by the receiving sensor, and realizing the setting of the sampling rate at the data acquisition source of the station control subsystem before transmission, it can reduce the amount of data output and avoid missing important data.

[0019] 2. Combining the detection data of each sensor that causes faults, data fusion, and anomaly analysis can ensure the accuracy of the data, timely detect abnormal data, and select to transmit to the cloud platform through a public network or a private network according to the abnormal situation of data preprocessing to ensure that the cloud platform receives abnormal data in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 is the circuit schematic diagram of the present invention.

[0021] Figure 2 is the step flow chart of the present invention.

[0022] Figure 3 This is the system diagram of the present invention. Specific embodiments

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments.

[0024] The following combines the description of the specification Figures 1 to 3 to further elaborate on the specific embodiments of the present invention.

[0025] Embodiment 1, a data acquisition terminal for an oil and gas production cloud platform, including a production data acquisition module, a station control subsystem, a communication module, and a cloud platform. The production data acquisition module uses multiple sensors to detect oil and gas production operation parameters;

[0026] The station control subsystem receives the oil and gas production operation parameters detected by multiple sensors under the control of the sampling time rate. After setting the sampling time rate at the data acquisition source of the station control subsystem according to the pre-set sampling time rate weight, the change amplitude of the sensor acquisition signal, and the data transmission rate ratio of the cloud platform for transmission, it can reduce the amount of data transmission. At the same time, it can avoid the problem of important data leakage caused by traffic congestion of the cloud platform server due to the method of controlling the sampling time rate commonly used in the prior art. By combining the detection data of each sensor that causes faults, data fusion, and anomaly analysis, it can ensure the accuracy of the data and timely detect abnormal data;

[0027] The communication module includes a public network and a private network. The signal after data fusion is transmitted to the cloud platform through the public network, and the signal after anomaly analysis is transmitted to the cloud platform through the private network to ensure that the cloud platform receives abnormal data in a timely manner.

[0028] Embodiment 2, the specific steps after data fusion and anomaly analysis are as follows:

[0029] Step 1, use the moving average method to obtain the predicted values of the oil and gas production operation parameters detected by multiple sensors;

[0030] Step 2, use low-pass filtering to receive the oil and gas production operation parameters detected by multiple sensors;

[0031] Step 3, on the basis of Step 2, use skewness to establish a dynamic detection threshold for discrimination and eliminate gross errors, that is, when the oil and gas production operation parameters detected by the sensor deviate from the dynamic detection threshold by a certain value, they are eliminated to obtain the measured values;

[0032] Step 4, use the weighted fusion algorithm to calculate the measured values and predicted values to obtain the measurement data of a single sensor;

[0033] Step 5: Use the iterative clustering algorithm to fuse the measurement data of each sensor to obtain the fused data. Approximate the fused data with the historical fault model. When the similarity is 96%, it is determined as abnormal or faulty. Combine the detection data of each sensor that causes the fault, perform data fusion and anomaly analysis to ensure the accuracy of the data and timely detect abnormal data.

[0034] Embodiment 3: The cloud platform congestion assessment circuit receives the rate signals of the cloud platform server for receiving and transmitting data detected by the rate detector transmitted through the dedicated network, and enters the divider composed of the operational amplifier AR5, resistors R16 - R18, and multiplier IC1 for division operation. The obtained ratio signal is amplitude-limited bidirectionally by the series-connected diodes D3 and D4, and the resistor R19 and the capacitor C8 are charged. When there is no instantaneous congestion, the charging voltage is high and the double diode SD2 conducts. The reverse voltage is output through the reverse operation circuit composed of the operational amplifier AR6, resistors R20 and R21, and is coupled to the control voltage of the voltage-controlled oscillator in the clock generation circuit through the diode D5 for adjusting the pulse frequency of the cloud platform for receiving data. It includes the operational amplifier AR5. The inverting input terminal of the operational amplifier AR5 is respectively connected to one end of the resistor R16 and one end of the resistor R17. The other end of the resistor R16 is connected to the cloud platform server receiving data rate signal. The non-inverting input terminal of the operational amplifier AR5 is connected to the ground through the resistor R18. The output terminal of the operational amplifier AR5 is respectively connected to the pin 4 of the multiplier IC1, one end of the resistor R19, the positive electrode of the diode D4, and the negative electrode of the diode D3. The pin 1 of the multiplier IC1 is connected to the cloud platform server forwarding data rate signal. The pin 6 of the multiplier IC1 is connected to the other end of the resistor R17. The negative electrode of the diode D4 is connected to the power supply +5V. The positive electrode of the diode D3 is connected to the power supply -5V. The other end of the resistor R19 is respectively connected to one end of the grounded capacitor C8 and the left end of the bidirectional diode SD2. The right end of the bidirectional diode SD2 is respectively connected to one end of the resistor R21 and the inverting input terminal of the operational amplifier AR6. The non-inverting input terminal of the operational amplifier AR6 is connected to the ground through the resistor R20. The output terminal of the operational amplifier AR6 is respectively connected to the other end of the resistor R21 and the negative electrode of the diode D5. The positive electrode of the diode D5 is connected to the pin 1 of the NOT gate U2.

[0035] Embodiment 4. The change amplitude detection circuit receives the oil and gas production operation parameters detected by the sensor. Here, the parameters detected by one sensor are taken as an example for detailed explanation. After being filtered by the inductor L1 and the capacitor C1, and amplitude-limited and amplified by the operational amplifier AR1, resistors R1 and R2, and diodes D1 and D2, it enters the station control subsystem after being sampled and held by the sampling and holding circuit composed of the switch K1, the capacitor C2, and the operational amplifier AR2. The station control subsystem performs fusion and anomaly processing and then transmits it to the cloud platform through the communication module. The signals before and after sampling and holding enter the differential amplifier composed of the operational amplifier AR4 and resistors R11 - R14 to obtain the amplitude difference. When the change amplitude is large, the bidirectional diode SD1 conducts, and after being filtered by the resistor R15 and the capacitor C7, the amplitude difference is output to the clock generation circuit, including the inductor L1. One end of the inductor L1 is connected to the sensor detection data, and the other end of the inductor L1 is respectively connected to one end of the grounded capacitor C1 and one end of the resistor R1. The other end of the resistor R1 is respectively connected to the positive electrode of the diode D1, the negative electrode of the diode D2, the non-inverting input terminal of the operational amplifier AR1, and one end of the resistor R2. The negative electrode of the diode D1, the positive electrode of the diode D2, and the inverting input terminal of the operational amplifier AR1 are grounded. The output terminal of the operational amplifier AR1 is respectively connected to one end of the resistor R14 and the left end of the switch K1. The right end of the switch K1 is respectively connected to one end of the grounded capacitor C2 and the non-inverting input terminal of the operational amplifier AR2. The inverting input terminal and the output terminal of the operational amplifier, and one end of the resistor R11 output signals to the station control subsystem. The other end of the resistor R14 is respectively connected to one end of the grounded resistor R13 and the inverting input terminal of the operational amplifier AR4. The other end of the resistor R11 is respectively connected to the non-inverting input terminal of the operational amplifier AR4 and one end of the resistor R12. The output terminal of the operational amplifier AR4 is respectively connected to the other end of the resistor R12 and the left end of the bidirectional diode SD1. The right end of the bidirectional diode SD1 is connected to one end of the resistor R15. The other end of the resistor R15 is respectively connected to one end of the grounded capacitor C7 and the negative electrode of the varactor diode DC1.

[0036] Embodiment 5. The clock generation circuit receives the output voltage of the cloud platform congestion assessment circuit, and then is coupled to the control voltage of the voltage-controlled oscillator composed of NAND gates U2 and U4, capacitors C9 and C10, NAND gate U3, resistors R22 and R23, for adjusting the pulse frequency of the data received by the cloud platform. After the voltage is loop-filtered by the ring filter composed of resistors R3 and R4 and capacitors C3 and C4, according to the sampling rate weights preset according to the importance of the detection data of each sensor, it is weighted and proportionally operated by the proportional amplifier composed of resistors R5 - R7 and operational amplifier AR3. The multiple of the weighted proportional operation can be obtained by setting the resistance values of the input resistor R5 and the feedback resistor R6. Then it is coupled to the power supply voltage of the voltage-controlled oscillator composed of NAND gates NOT1 and NOT2, resistors R8A and R8B, R9, R10, capacitor C5, and varactor diode DC1, for adjusting the frequency of the generated square wave pulse. This is applied to the control end of the sampling switch K1 as the sampling rate, and is coupled to the negative electrode of the varactor diode DC1 by the amplitude difference to adjust the duty cycle of the square wave pulse. According to the preset sampling rate weights, the change amplitude of the sensor acquisition signal, and the ratio of the cloud platform data transceiver rate, the sampling rate is adjusted to realize the setting of the sampling rate at the data acquisition source of the station control subsystem and then transmission, which can reduce the amount of data output and avoid missing important data. It includes NAND gate U2 and capacitor C9. The pin 1 of NAND gate U2 and one end of capacitor C9 are connected to the positive electrode of diode D5. The pin 2 of NAND gate U2 is connected to one end of capacitor C10. The other end of capacitor C10 is respectively connected to one end of resistor R23 and the pin 2 of NAND gate U3. The pin 1 of NAND gate U3 is respectively connected to the other end of capacitor C9 and one end of resistor R22. The other ends of resistor R22 and resistor R23 are connected to the power supply +5V. The pin 3 of NAND gate U3 is connected to the pin 1 of NAND gate U4. The pin 4 of NAND gate U4 is connected to one end of resistor R3. The other end of resistor R3 is respectively connected to one end of capacitor C3 and one end of resistor R5. The other end of capacitor C3 is respectively connected to one end of the grounding resistor R4 and one end of the grounding capacitor C4. The other end of resistor R5 is respectively connected to the inverting input terminal of operational amplifier AR3 and one end of resistor R6. The non-inverting input terminal of operational amplifier AR3 is connected to ground through resistor R7. The output terminal of operational amplifier AR3 is respectively connected to the other end of resistor R6 and one end of resistor R8A. The other end of resistor R8A is respectively connected to one end of resistor R9, one end of resistor R8B, and one end of resistor R10. The other end of resistor R8B is connected to the power supply +5V. The other end of resistor R9 is respectively connected to one end of capacitor C5 and the pin 1 of NAND gate NOT1. The pin 2 of NAND gate NOT1 is connected to one end of capacitor C6. The other end of capacitor C6 is respectively connected to the other end of resistor R10 and the pin 1 of NAND gate NOT2. The pin 2 of NAND gate NOT2 is connected to the control end of switch K1 and the positive electrode of varactor diode DC1. The negative electrode of varactor diode DC1 is connected to the other end of capacitor C5 and the other end of resistor R15.

[0037] When the present invention is specifically used, the station control subsystem receives the oil and gas production operation parameters detected by multiple sensors under the control of the sampling rate. The sampling rate is obtained from the cloud platform congestion evaluation circuit, the change amplitude detection circuit, and the clock generation circuit. Specifically, the clock generation circuit receives the output voltage of the cloud platform congestion evaluation circuit, and then couples it with the control voltage of the voltage-controlled oscillator to adjust the pulse frequency of the data received by the cloud platform. After the voltage is converted by the ring filter loop filtering, according to the sampling rate weight preset according to the importance of the detection data of each sensor, it is weighted and proportionally operated by the proportional amplifier, and then coupled with the power supply voltage of the voltage-controlled oscillator to adjust the frequency of the generated square wave pulse. This is added to the control end of the sampling switch K1 as the sampling rate, and the amplitude difference output by the change amplitude detection circuit is coupled to the negative electrode of the varactor diode DC1 to adjust the duty cycle of the square wave pulse. According to the preset sampling rate weight, the change amplitude of the sensor acquisition signal, and the data rate ratio of the cloud platform sending and receiving data, the sampling rate is adjusted to realize the setting of the sampling rate at the data acquisition source of the station control subsystem and then transmit it, which can reduce the amount of data output and avoid missing important data. Among them, the change amplitude detection circuit receives the oil and gas production operation parameters detected by the sensors, and after filtering, limiting amplification, and sample and hold, it enters the station control subsystem. The amplitude difference is obtained by the signal differential amplifier before and after sample and hold. When the change amplitude is large, the bidirectional diode SD1 conducts, and the amplitude difference is output to the clock generation circuit after filtering by the resistor R15 and the capacitor C7. The cloud platform congestion evaluation circuit receives the rate signals of the cloud platform server receiving and sending data detected by the rate detector transmitted by the dedicated network, enters the divider for division operation, and the obtained ratio signal is subjected to bidirectional limiting and charging. When there is no instantaneous congestion, the charging voltage is high and the double diode SD2 conducts, and the reverse voltage is output through the reverse operation circuit and coupled with the control voltage of the voltage-controlled oscillator in the clock generation circuit. By combining, data fusion, and abnormal analysis of the detection data of each sensor that may cause faults, the accuracy of the data can be ensured and abnormal data can be detected in time. The specific process is as follows: First, the predicted values of the oil and gas production operation parameters detected by multiple sensors are obtained by using the moving average method; the oil and gas production operation parameters detected by multiple sensors are received by using low-pass filtering; then the skewness is used to establish a dynamic detection threshold to distinguish and eliminate gross errors to obtain the measured values; and then the measured values and predicted values are calculated by the weighted fusion algorithm to obtain the measurement data of a single sensor.Finally, the iterative clustering algorithm is used to fuse the measurement data of each sensor to obtain the fused data. When the fused data is approximated to the historical fault model and the similarity is 96%, it is determined as abnormal or faulty. By combining the detection data of each sensor that causes the fault, data fusion, and anomaly analysis, the accuracy of the data can be ensured and abnormal data can be detected in a timely manner. The signal after data fusion is transmitted to the cloud platform through the public network, and the signal after anomaly analysis is transmitted to the cloud platform through the dedicated network. Based on the pre-set sampling rate weight, the change amplitude of the sensor acquisition signal, and the proportion of the data transmission and reception rate of the cloud platform, the sampling rate is adjusted to realize the setting of the sampling rate at the data acquisition source of the station control subsystem before transmission. This can reduce the amount of data output, avoid missing important data, and select to transmit to the cloud platform through the public network or dedicated network according to the abnormal situation of data preprocessing to ensure that the cloud platform receives abnormal data in a timely manner.

Claims

1. The data acquisition terminal of the oil and gas production cloud platform includes a production data acquisition module, a station control subsystem, a communication module, and a cloud platform, and is characterized in that, The production data acquisition module uses multiple sensors to detect oil and gas production operation parameters; The station control subsystem receives the oil and gas production operation parameters detected by multiple sensors under the control of the sampling time rate, and connects to the communication module after data fusion and anomaly analysis; The communication module includes a public network and a private network. After data fusion, the signal is transmitted to the cloud platform through the public network, and after anomaly analysis, the signal is transmitted to the cloud platform through the private network; The sampling time rate is obtained according to the cloud platform congestion assessment circuit, the change amplitude detection circuit, and the clock generation circuit; The cloud platform congestion assessment circuit receives the rate signals of the cloud platform server for receiving and sending data detected by the rate detector transmitted through the private network, and enters the divider composed of operational amplifier AR5, resistors R16 - R18, and multiplier IC1 for division operation. The obtained ratio is amplitude-limited and charged. When congested, the double diode conducts, and after being reversed and coupled with the control voltage, it adjusts the pulse frequency of the cloud platform for receiving data; The change amplitude detection circuit receives the oil and gas production operation parameters detected by the sensors. After filtering by inductor L1 and capacitor C1, and amplitude-limited amplification by operational amplifier AR1, resistors R1 and R2, and diodes D1 and D2, it enters the sample and hold circuit composed of switch K1, capacitor C2, and operational amplifier AR2 for sample and hold, and then enters the station control subsystem. After the station control subsystem performs fusion and anomaly processing, it is transmitted to the cloud platform through the communication module. The signals before and after sample and hold enter the differential amplifier composed of operational amplifier AR4, resistors R11 - R14 to obtain the amplitude difference. When the change amplitude is large, the bidirectional diode SD1 conducts, and after filtering by resistor R15 and capacitor C7, the amplitude difference is output to the clock generation circuit; The clock generation circuit receives the output voltage of the cloud platform congestion assessment circuit, and then is coupled with the control voltage of the voltage-controlled oscillator composed of NAND gates U2 and U4, capacitors C9 and C10, NAND gate U3, resistors R22 and R23 to adjust the pulse frequency of the cloud platform for receiving data. After the voltage is converted by loop filtering through the ring filter composed of resistors R3 and R4, capacitors C3 and C4, according to the sampling rate weights preset according to the importance of the data detected by each sensor, it undergoes weighted proportional operation by the proportional amplifier composed of resistors R5 - R7 and operational amplifier AR3. The multiple of the weighted proportional operation can be obtained by setting the resistance values of the input resistor R5 and the feedback resistor R6. Then it is coupled with the power supply voltage of the voltage-controlled oscillator composed of NAND gates NOT1 and NOT2, resistors R8A and R8B, R9, R10, capacitor C5, and varactor diode DC1 to adjust the frequency of the generated square wave pulse. This is applied to the control terminal of the sampling switch K1 as the sampling time rate, and the amplitude difference is coupled to the negative electrode of the varactor diode DC1 to adjust the duty cycle of the square wave pulse; The specific steps after data fusion and anomaly analysis are as follows: Step 1, use the moving average method to obtain the predicted values of the oil and gas production operation parameters detected by multiple sensors; Step 2, use low-pass filtering to receive the oil and gas production operation parameters detected by multiple sensors; Step 3: On the basis of Step 2, establish a dynamic detection threshold discriminant using skewness to identify and eliminate gross errors, and obtain the measured value; Step 4: Use a weighted fusion algorithm to calculate the measured value and the predicted value to obtain the measurement data of a single sensor; Step 5: Use an iterative clustering algorithm to fuse the measurement data of each sensor to obtain the fused data. When the similarity between the fused data and the historical fault model is 96%, it is determined as abnormal or faulty.

2. The data acquisition terminal of the oil and gas production cloud platform according to claim 1, wherein The cloud platform congestion assessment circuit includes an operational amplifier AR5. The inverting input terminal of the operational amplifier AR5 is respectively connected to one end of a resistor R16 and one end of a resistor R17. The other end of the resistor R16 is connected to the data reception rate signal of the cloud platform server. The non-inverting input terminal of the operational amplifier AR5 is connected to ground through a resistor R18. The output terminal of the operational amplifier AR5 is respectively connected to pin 4 of a multiplier IC1, one end of a resistor R19, the positive electrode of a diode D4, and the negative electrode of a diode D3. Pin 1 of the multiplier IC1 is connected to the data forwarding rate signal of the cloud platform server. Pin 6 of the multiplier IC1 is connected to the other end of the resistor R17. The negative electrode of the diode D4 is connected to the power supply +5V, and the positive electrode of the diode D3 is connected to the power supply -5V. The other end of the resistor R19 is respectively connected to one end of a grounded capacitor C8 and the left end of a bidirectional diode SD2. The right end of the bidirectional diode SD2 is respectively connected to one end of a resistor R21 and the inverting input terminal of an operational amplifier AR6. The non-inverting input terminal of the operational amplifier AR6 is connected to ground through a resistor R20. The output terminal of the operational amplifier AR6 is respectively connected to the other end of the resistor R21 and the negative electrode of a diode D5. The positive electrode of the diode D5 is connected to pin 1 of a NOT gate U2.

3. The data acquisition terminal of the oil and gas production cloud platform according to claim 1, characterized in that The change amplitude detection circuit includes an inductor L1. One end of the inductor L1 is connected to the sensor detection data. The other end of the inductor L1 is respectively connected to one end of a grounded capacitor C1 and one end of a resistor R1. The other end of the resistor R1 is respectively connected to the positive electrode of a diode D1, the negative electrode of a diode D2, the non-inverting input terminal of an operational amplifier AR1, and one end of a resistor R2. The negative electrode of the diode D1, the positive electrode of the diode D2, and the inverting input terminal of the operational amplifier AR1 are connected to ground. The output terminal of the operational amplifier AR1 is respectively connected to one end of a resistor R14 and the left end of a switch K1. The right end of the switch K1 is respectively connected to one end of a grounded capacitor C2 and the non-inverting input terminal of an operational amplifier AR2. The inverting input terminal, output terminal of the operational amplifier, and one end of a resistor R11 output a signal to the station control subsystem. The other end of the resistor R14 is respectively connected to one end of a grounded resistor R13 and the inverting input terminal of an operational amplifier AR4. The other end of the resistor R11 is respectively connected to the non-inverting input terminal of the operational amplifier AR4 and one end of a resistor R12. The output terminal of the operational amplifier AR4 is respectively connected to the other end of the resistor R12 and the left end of a bidirectional diode SD1. The right end of the bidirectional diode SD1 is connected to one end of a resistor R15. The other end of the resistor R15 is respectively connected to one end of a grounded capacitor C7 and the negative electrode of a varactor diode DC1.

4. The data acquisition terminal of the oil and gas production cloud platform according to claim 1, wherein The clock generation circuit includes a NOT gate U2 and a capacitor C9. One end of pin 1 of the NOT gate U2 and one end of the capacitor C9 are connected to the positive pole of a diode D5. Pin 2 of the NOT gate U2 is connected to one end of a capacitor C10. The other end of the capacitor C10 is respectively connected to one end of a resistor R23 and pin 2 of a NAND gate U3. Pin 1 of the NAND gate U3 is respectively connected to the other end of the capacitor C9 and one end of a resistor R22. The other end of the resistor R22 and the other end of the resistor R23 are connected to the power supply +5V. Pin 3 of the NAND gate U3 is connected to pin 1 of a NOT gate U4. Pin 4 of the NOT gate U4 is connected to one end of a resistor R3. The other end of the resistor R3 is respectively connected to one end of a capacitor C3 and one end of a resistor R5. The other end of the capacitor C3 is respectively connected to one end of a grounding resistor R4 and one end of a grounding capacitor C4. The other end of the resistor R5 is respectively connected to the inverting input terminal of an operational amplifier AR3 and one end of a resistor R6. The non-inverting input terminal of the operational amplifier AR3 is connected to ground through a resistor R7. The output terminal of the operational amplifier AR3 is respectively connected to the other end of the resistor R6 and one end of a resistor R8A. The other end of the resistor R8A is respectively connected to one end of a resistor R9, one end of a resistor R8B, and one end of a resistor R10. The other end of the resistor R8B is connected to the power supply +5V. The other end of the resistor R9 is respectively connected to one end of a capacitor C5 and pin 1 of a NOT gate NOT1. Pin 2 of the NOT gate NOT1 is connected to one end of a capacitor C6. The other end of the capacitor C6 is respectively connected to the other end of the resistor R10 and pin 1 of a NOT gate NOT2. Pin 2 of the NOT gate NOT2 is connected to the control terminal of a switch K1 and the positive pole of a varactor diode DC1. The negative pole of the varactor diode DC1 is connected to the other end of the capacitor C5 and the other end of a resistor R15.

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