A quantitative heating system and method for seafloor heat flow measurements

Abstract

A quantitative heating system and method for measuring seabed heat flow belongs to the field of marine geothermal exploration and thermal property measurement technology. The system includes a constant current drive module (1), a current acquisition module (2), a voltage acquisition module (3), a control and data processing module (4), a heating module (5), and a temperature acquisition module (6). The constant current drive module (1) provides a driving voltage to the heating module (5) to generate a heating current. The current acquisition module (2) is used to acquire the actual current value in the heating module (5) in real time. The system and method of the present invention accurately calculate the total heating amount and invert the thermal conductivity of sediments through PI closed-loop constant current control, resistance-temperature model correction, and power sequence smooth fitting integration, thereby solving the problems of unstable power and large error in traditional open-loop heating and significantly improving the accuracy of seabed heat flow measurement.

Description

Technical Field

[0001] This invention relates to the field of marine geothermal exploration and thermal property measurement technology, specifically to a quantitative heating system and method for measuring seabed heat flow. Background Technology

[0002] Heat flow from seabed sediments is an important physical quantity reflecting the outward transfer of heat energy from the Earth's interior. It is of great significance for understanding the evolution of the marine lithosphere structure, seabed tectonic activity, and marine resource exploration. Accurately obtaining the thermal conductivity of seabed sediments is a key basic parameter for heat flow calculation.

[0003] Currently, in-situ thermal conductivity measurement technology based on probe method is widely used due to its simple structure and strong applicability. Its basic principle is to input heat to the surrounding medium through an electric heating element and invert the thermal conductivity based on the temperature response process. Its measurement accuracy largely depends on the quantitative control level of the heating process.

[0004] However, in actual marine environments, the heating process is easily affected by various factors such as power fluctuations, changes in the resistance of heating elements with temperature, and ambient temperature disturbances, making it difficult to accurately control and quantify the input heat, which in turn restricts the accuracy and reliability of the measurement results.

[0005] Therefore, conducting research on high-precision quantitative constant current heating control systems and methods is of great significance for improving the accuracy and reliability of heat flow measurement of seabed sediments. Summary of the Invention

[0006] In view of this, the main objective of the present invention is to provide a quantitative heating system and method for measuring seabed heat flow, in order to at least partially solve the above-mentioned technical problems.

[0007] To address the shortcomings of existing seabed sediment heat flow measurement techniques, such as the difficulty in precisely controlling heating power due to resistance variations, the lack of real-time feedback adjustment mechanisms during the heating process, and the inaccuracy caused by reliance on nominal parameters in heating quantity calculation, this invention proposes a high-precision quantitative heating control system and method for seabed sediment heat flow measurement. This method achieves closed-loop stable control of the heating current by constructing a negative feedback constant current drive circuit, and establishes a real-time status sensing mechanism for the heating process by acquiring and dynamically processing voltage and current data in real time.

[0008] Building upon this foundation, this invention further employs a method combining online resistance estimation and a resistance-temperature model to dynamically correct for resistance changes in the heating element during operation. Based on real-time electrical parameters, it continuously calculates and integrates instantaneous power over time, achieving quantitative acquisition of the heating input energy. Simultaneously, by combining multi-point temperature measurement data, a sediment thermal conductivity inversion model is constructed, thus forming a complete methodology system of "heating control - energy calculation - parameter inversion" to meet the requirements of heating accuracy and data consistency in seabed sediment heat flow measurement.

[0009] To achieve the above objectives, as a first aspect of the present invention, a quantitative heating system for seabed heat flow measurement is proposed, comprising a constant current drive module (1), a current acquisition module (2), a voltage acquisition module (3), a control and data processing module (4), a heating module (5), and a temperature acquisition module (6). The constant current drive module (1) is used to provide a drive voltage to the heating module (5) to generate a heating current; The current acquisition module (2) is used to acquire the actual current value in the heating module (5) in real time; The voltage acquisition module (3) is used to acquire the actual voltage value in the heating module (5) in real time; The temperature acquisition module (6) is used to collect temperature data of sediments at multiple points distributed along the axial direction of the geothermal probe; The control and data processing module (4) is connected to the constant current drive module (1), the current acquisition module (2), the voltage acquisition module (3) and the temperature acquisition module (6), respectively; The control and data processing module (4) is configured as follows: Receive the preset target current value; Based on the error between the target current value and the actual current value, the driving voltage output by the constant current drive module (1) is adjusted through negative feedback closed loop to make the actual current value track the target current value; during heating, the actual voltage value and the actual current value set are collected, and the instantaneous resistance value of the heating module (5) is calculated in real time. Instantaneous power is calculated based on instantaneous resistance and actual current values, and the instantaneous power is integrated over time during the heating period to obtain the total heating amount. The thermal conductivity of sediments can be calculated by inverting the total heating amount or multi-point temperature data.

[0010] In one possible implementation, the control and data processing module (4) includes: Error calculation unit, used to construct error function ,in, For error signals, Indicates the target current. Indicates the actual current; The control and regulation unit is used to output the driving voltage regulation amount ΔU(k) ​​according to the error function using a proportional-integral control algorithm.

[0011] In one possible implementation, the control and data processing module (4) further includes a resistance correction unit, which is used to correct the calculated instantaneous resistance value using a pre-established resistance-temperature characteristic model to eliminate the influence of temperature nonlinear drift and to obtain the real-time temperature of the heating module (5).

[0012] In one possible implementation, the resistance-temperature characteristic model is a second-order polynomial fitting model.

[0013] In one possible implementation, the control and data processing module (4) performs polynomial fitting on the instantaneous power time series and then performs time integration to obtain the total heating amount.

[0014] In one possible implementation, the control and data processing module (4) further includes an integral smoothing unit for performing sliding window smoothing on the power sequence before integration, and / or performing polynomial fitting on the power-time sequence after integration, and performing analytical integration on the fitted function to correct discrete integral errors.

[0015] In one possible implementation, the control and data processing module (4) inverts the thermal conductivity of sediments by: constructing a one-dimensional unsteady thermal conductivity equation, discretizing the thermal conductivity equation by the finite difference method, constructing a temperature prediction model, constructing and minimizing the error function between the measured temperature and the predicted temperature, and solving to obtain the thermal conductivity.

[0016] As a second aspect of the present invention, a quantitative heating method for measuring seabed heat flow is proposed, comprising the following steps: S1, Set the target heating parameters, including the target current value; S2 outputs an initial drive voltage to the heating element through the constant current drive module, generating a heating current; S3, real-time acquisition of the actual current value in the heating circuit, and calculation of the error between it and the target current value; S4. Based on the error, the driving voltage is adjusted through a negative feedback closed loop to ensure that the actual current stably tracks the target current value during the heating process. S5, during the heating process, performs high-frequency synchronous acquisition of the actual voltage and actual current in the heating circuit; S6, based on the voltage and current data collected at the same moment, obtain the total input heat through the total heating integration process; S7. Using temperature sensors distributed along the probe axis, multi-point temperature change data of the sediment during the heating process are collected and recorded in layers. Combined with the total input heat and multi-point temperature change data, the thermal conductivity of the sediment is calculated by inversion.

[0017] In one possible implementation, the total heating integration process specifically includes the following steps: S61, calculate the instantaneous resistance value of the heating element; S62, Calculate the instantaneous power based on the instantaneous resistance value and the instantaneous current value; S63 performs discrete-time integration on all instantaneous power during the entire heating period to calculate the total heating amount.

[0018] In one possible implementation, the negative feedback closed-loop regulation described in step S4 employs a proportional-integral control algorithm.

[0019] Based on the above technical solution, it can be seen that the quantitative heating system and method for measuring seabed heat flow of the present invention has at least one of the following beneficial effects compared with the prior art: 1. By constructing a real-time current acquisition and error feedback mechanism, the set current and the actual current are dynamically compared, and the driving voltage is continuously adjusted based on the error, thereby forming a closed-loop control circuit to achieve stable output of heating current under the conditions of load resistance changing with temperature and external power fluctuation.

[0020] 2. During the heating process, voltage and current are synchronously acquired, heating resistance changes are calculated in real time, and electrical parameters are corrected by combining a pre-established resistance-temperature relationship model. On this basis, instantaneous power is calculated point by point and a power time series is constructed. The total heating amount is obtained through time integration and curve fitting methods, and the power change curve is output to realize the continuous quantitative expression of heating input.

[0021] 3. Using the power time series or total heat obtained during the heating process as the heat source input condition, and combining the multi-point temperature measurement data arranged along the probe axis, establish the correspondence between the temperature response and the heat conduction model, and solve the sediment thermal conductivity parameters through numerical calculation or optimization methods, so as to realize the complete calculation process from heating input to temperature response and then to the solution of thermal property parameters. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a structural block diagram of a quantitative heating system for measuring seabed heat flow according to the present invention; Figure 2 This is a schematic flowchart of a quantitative heating method for measuring seabed heat flow according to the present invention. Figure 3 This is a schematic diagram of the total heating integration process of a quantitative heating method for measuring seabed heat flow according to the present invention; In the diagram: 1. Constant current drive module; 2. Current acquisition module; 3. Voltage acquisition module; 4. Control and data processing module; 5. Heating module; 6. Temperature acquisition module. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to specific embodiments and accompanying drawings.

[0025] The terminology used in this invention is for the purpose of describing particular embodiments only and is not intended to limit the embodiments of the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of the invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0026] To achieve the goal of accurate measurement of heat flow in seabed sediments, it is necessary to overcome key problems in the heating control and energy calculation processes of existing technologies, specifically including: (1) The problem of difficulty in accurately controlling heating power due to resistance change: During the heating process, the resistance of the heating resistance wire changes nonlinearly with temperature. Existing technologies usually estimate power based on the initial nominal resistance or fixed parameters, which fails to reflect the resistance change under actual working conditions, resulting in deviation of heating power over time.

[0027] (2) The problem of lack of real-time feedback and dynamic adjustment mechanism for heating process: Existing methods mostly adopt open-loop or weak feedback control mode, and simply set the current or voltage. They lack the ability to adjust the closed loop based on real-time data acquisition, and it is difficult to dynamically respond to power fluctuations, load changes and environmental disturbances during the heating process.

[0028] (3) Problems of inaccurate heating calculation and lack of full-process data support: Traditional methods usually estimate the heating amount by setting current and nominal parameters, or rely on offline correction methods. They lack a continuous integral calculation process based on real-time sampling data of voltage and current, making it difficult to form a complete energy input time series.

[0029] To address the aforementioned problems, this invention aims to provide a high-precision quantitative heating control system and method for measuring heat flux in seabed sediments. Its core objective is to achieve closed-loop stable control of the heating current by constructing a negative feedback constant current drive circuit. During the heating process, voltage and current are acquired in real time, and resistance changes are calculated. Dynamic corrections are then performed using a resistance-temperature characteristic model. Subsequently, instantaneous power is continuously calculated, and the total heating amount is obtained through time integration. Simultaneously, a power-time variation sequence is output, and the sediment thermal conductivity is inverted using multi-point temperature measurement data, thus forming a complete heating control and parameter solution process.

[0030] Currently, in-situ measurements of the thermal conductivity of seabed sediments mainly employ the geothermal probe method. This method involves placing an electric heating element inside the probe, releasing heat to the surrounding sediment over a certain period, and then inverting the thermal conductivity parameters based on the temperature change over time. Existing technologies typically use constant current or constant voltage sources for heating control, with constant current heating being more widely used. In practice, a fixed heating current is generally set and maintained relatively constant during the heating phase. The heating power is then calculated based on the set current value and the nominal resistance to estimate the input heat. Additionally, some systems obtain the relationship curve between the heating element resistance and temperature through experimental calibration, allowing for some correction of the heating power during data processing. However, overall, the heating process largely relies on preset parameters and offline calibration results, lacking a real-time monitoring and dynamic adjustment mechanism for the actual heating state.

[0031] The existing technology has the following problems: (1) The problem of difficulty in accurately controlling heating power due to resistance changes During the heating process, the resistance of the heating element will drift non-linearly with temperature changes. Existing technologies typically estimate power based on initial calibration resistance or fixed parameters, failing to reflect resistance changes under actual operating conditions. Furthermore, traditional constant current control methods only regulate the current and do not effectively control the heating power. When the resistance changes, the actual heating power fluctuates accordingly, leading to unstable heating input and affecting measurement accuracy.

[0032] (2) Lack of real-time feedback on the heating process and environmental adaptability In the complex marine environment, factors such as power supply voltage fluctuations, ambient temperature changes, and measurement noise can all interfere with the heating process. Existing technologies mostly rely on preset parameters or offline calibration results, lacking a dynamic feedback and correction mechanism based on real-time measurement data. This makes it difficult to adjust for changes in the heating process in a timely manner, thereby reducing the stability and reliability of the system under complex operating conditions.

[0033] (3) Inaccurate calculation of heating amount and lack of traceability Existing methods typically estimate the heating amount based on a set current and nominal parameters, or compensate through offline correction. They lack precise calculation methods based on real-time voltage and current sampling data, making it difficult to accurately reflect the actual heat input during the heating process. Furthermore, the lack of a complete data recording and dynamic correction mechanism for the heating process results in untraceable heat calculations, thus affecting the accuracy and reliability of seabed thermal conductivity inversion results.

[0034] Existing seafloor geothermal probe systems possess a solid technological foundation in terms of hardware, enabling high-frequency, high-precision real-time acquisition of key parameters such as voltage and current. By further integrating online resistance estimation and power closed-loop regulation mechanisms, it is hoped that the heating process can be upgraded from single current control to multi-parameter coordinated control, providing hardware support for high-precision quantitative heating.

[0035] In terms of systems, existing systems already possess data acquisition, storage, and basic processing capabilities, and can perform a certain degree of analysis and calculation on measurement data. With the improvement of embedded processing performance and the maturity of real-time algorithm applications, it has become possible to fuse multi-source data such as voltage, current, and temperature. Based on this, by introducing methods such as online resistance modeling, power feedback regulation, and heat integral calculation, an integrated algorithm system of "real-time sensing - dynamic calculation - closed-loop control" can be constructed, providing a new technical path for achieving precise control and quantitative energy assessment of the heating process.

[0036] The present invention will be further illustrated below through specific embodiments. It should be noted that the following embodiments are merely illustrative and not intended to limit the scope of the invention. All other embodiments obtained by those skilled in the art based on the embodiments shown below without inventive effort are within the scope of protection of the embodiments of the present invention.

[0037] Therefore, as Figure 1 As shown, this application proposes a quantitative heating system for seabed heat flow measurement, comprising: The constant current drive module 1 is electrically connected to the heating module 5, receives the voltage adjustment command from the control and data processing module 4, and outputs the drive voltage to the heating module 5 to generate heating current. The current acquisition module 2 is connected in series in the heating circuit. It acquires the actual current value of the heating circuit in real time at a preset sampling frequency (1kHz in this embodiment) and transmits it to the control and data processing module 4. Voltage acquisition module 3 is connected in parallel across heating module 5 and uses the same clock to synchronously sample current acquisition module 2. It collects the actual voltage value of heating circuit in real time and transmits it to control and data processing module 4. Temperature acquisition module 6 is equipped with multiple temperature sensors arranged along the axis of the geothermal probe to collect multi-point temperature data of seabed sediments during the heating process in layers and transmit them to control and data processing module 4. The control and data processing module 4 is electrically connected to each of the above modules and integrates an error calculation unit, a control adjustment unit, a resistance correction unit, an integral smoothing unit, and a thermal conductivity inversion unit to realize the whole process of data processing, including closed-loop constant current control, electrical parameter acquisition, resistance correction, power integration, and thermal conductivity inversion. Control and data processing module 4 is configured as follows: Receive the preset target current value; Based on the error between the target current value and the actual current value, the driving voltage output by the constant current drive module 1 is adjusted through a negative feedback closed loop to make the actual current value track the target current value; during heating, the actual voltage value and the actual current value set are collected, and the instantaneous resistance value of the heating module 5 is calculated in real time. Instantaneous power is calculated based on instantaneous resistance and actual current values, and the instantaneous power is integrated over time during the heating period to obtain the total heating amount. The thermal conductivity of sediments can be calculated by inverting the total heating amount or multi-point temperature data.

[0038] In one possible implementation, the control and data processing module 4 includes: Error calculation unit, used to construct error function ,in, For error signals, Indicates the target current. Indicates the actual current; The control and regulation unit is used to output the driving voltage regulation amount ΔU(k) ​​according to the error function using a proportional-integral control algorithm.

[0039] In this embodiment, a negative feedback closed-loop control mechanism is used to achieve a stable output of the heating current. The entire process includes target setting, signal acquisition, error calculation, control adjustment, and execution feedback. After the system starts, the control and data processing module 4 first sets the target current value according to the experimental requirements. This is used as the reference input signal for the entire heating process. Subsequently, the constant current drive module outputs an initial drive voltage under the action of the control signal, causing the heating resistance wire to enter the working state.

[0040] During the heating process, the current acquisition module obtains the actual current value in the circuit in real time through a high-precision sampling resistor or current sensor. The data is then transmitted to the control module at a set sampling frequency. The control module preprocesses the acquired signal, including filtering, noise reduction, and sampling synchronization, to ensure the stability and continuity of the current data. Based on this, an error function is constructed: in, This represents the error signal, which is then input into the control algorithm module.

[0041] The control algorithm can adopt proportional-integral (PI) control or discrete digital control, and its output is the drive voltage adjustment amount ΔU(k). The control and regulation unit sends the calculated drive voltage adjustment amount ΔU(k) ​​to the constant current drive module 1 to adjust the output drive voltage, so that the actual current value I(t) gradually tracks the target current value Iref. The controller dynamically corrects the drive signal according to the error change trend, so that the output voltage U(k) changes in real time, thereby regulating the loop current. This process is in a continuous iterative form in time, that is, a "sampling-calculation-adjustment" operation is performed once in each sampling period.

[0042] In this embodiment, the sampling period is set to 1ms, and the stability of the heating current is better than ±0.1%, which can ensure the power stability of the heating process.

[0043] During actual operation, the heating resistance wire experiences resistance drift due to temperature changes, leading to dynamic changes in the circuit impedance. In this case, the system automatically adjusts the drive voltage through feedback regulation to maintain the current within the set range. Furthermore, the system can also compensate for power input fluctuations through a voltage regulation mechanism to ensure stable current output.

[0044] Furthermore, during the control implementation process, the current sample values ​​can be processed by moving average or digital filtering to reduce the impact of high-frequency noise on control accuracy. Simultaneously, a limiting constraint is introduced at the control output to prevent sudden changes or over-limit situations in the drive voltage. For digital implementation systems, discrete control equations can also be used: in, Represents the proportionality coefficient. Represents the integral coefficient. This represents the output drive voltage value at the k-th sampling time. This represents the output drive voltage value at the previous sampling time (time k-1). This represents the current error value at the k-th sampling time. This represents the current error value at the previous sampling time (time k-1).

[0045] Through the above process, a stable closed-loop control path is formed, namely the cyclic process of "target setting - current acquisition - error calculation - control adjustment - voltage output - current update", which enables the system to continuously operate in a closed-loop state throughout the heating stage, providing stable current conditions for subsequent resistance calculation and heat analysis.

[0046] Building upon the stable output of constant current drive, this invention further constructs a high-precision quantitative heating control process. Its core lies in the real-time acquisition and dynamic calculation of electrical parameters during the heating process, and the continuous accumulation of energy through an integral method. The entire process includes multiple stages such as data acquisition, resistance calculation, model correction, power calculation, time series construction, integral calculation, and fitting correction.

[0047] First, after heating begins, the system synchronously collects voltage and current data in the heating circuit according to a set sampling period Δt, forming a discrete sequence: in, This represents the voltage value at time k. This represents the current value at time k. To ensure the validity of the sampled data, the system performs synchronization alignment on the original signal and removes high-frequency interference using a filtering algorithm, ensuring data consistency across the time axis. During sampling, voltage and current data must maintain the same time reference to avoid phase errors affecting subsequent calculations.

[0048] Subsequently, at each sampling moment, the system calculates the instantaneous resistance value of the heating module at the k-th sampling moment according to Ohm's law: The resistance sequence is stored as an important parameter reflecting the state of the heating element. Since the resistance value is significantly affected by temperature, and its change process usually has continuous and nonlinear characteristics, a resistance-temperature characteristic model needs to be introduced for correction.

[0049] In one possible implementation, the resistance-temperature characteristic model is a second-order polynomial fitting model.

[0050] In the model building stage of this application embodiment, the functional relationship between resistance and temperature is obtained through experimental calibration, and the high-order polynomial fitting model can be expressed as: in, This represents the real-time resistance value of the heating module at temperature T, where T represents the real-time temperature of the heating module, and m represents the highest order of the polynomial. This represents the term number of the polynomial. The coefficients represent the fitting coefficients of the nth-order polynomial, which are generally fitted using a second-order polynomial fitting model. in, This indicates the reference resistance value of the heating module. This represents the first-order temperature coefficient of the heating module. This represents the second-order temperature coefficient of the heating module. In practical calculations, the temperature can be derived from the resistance by solving the inverse function of the above relationship or by interpolation from a table. The system calculates the instantaneous resistance value in real time during operation. The corresponding real-time temperature value can be obtained by looking up a table or solving an inverse function. This process also performs consistency correction on resistance changes. This allows the resistance sequence to more accurately reflect the actual thermal state.

[0051] After obtaining the corrected electrical parameters, the system calculates the instantaneous power at each moment: ; Although constant current control ensures a relatively stable current, the voltage still varies with temperature due to changes in resistance. The power will change dynamically, resulting in a time-varying characteristic for the actual power. Therefore, this invention does not employ a fixed power estimation method, but instead performs point-by-point calculations based on real-time sampled data to ensure the accuracy of the power calculation. Based on this, the system performs time integration calculations on the power sequence to obtain the total heating amount. The discrete integral form is: ,in, Indicates the sampling time sequence number. This indicates the total number of sampling points during the heating period. Indicates the sampling time interval.

[0052] During the calculation, the system accumulates the power contribution point by point in chronological order, so that the heat is continuously updated over time, forming a cumulative sequence. This integration process can be updated in real time in each sampling period, thereby realizing dynamic calculation of heat.

[0053] To improve the stability of the calculation process, the system preprocesses the power sequence before integration, which can be achieved by using a sliding window method to smooth the power data. ,in, This represents the smoothed instantaneous heating power at the k-th sampling time. Indicates the length of the sliding window. Indicates the sequence number of the sampling time within the window. This indicates the sequence number of the current sampling time. Indicates the first The original instantaneous heating power at each sampling time point is used, and the smoothed sequence is used for integration.

[0054] In one possible implementation, the control and data processing module 4 performs polynomial fitting on the instantaneous power time series and then performs time integration to obtain the total heating amount.

[0055] Furthermore, in this embodiment, to address the errors caused by discrete sampling, the system performs polynomial function fitting on the power time series: By analytically integrating the power using a continuous fitting function, a smoother and more accurate heat estimate can be obtained. By employing a dual mechanism of "discrete integration + curve fitting correction," numerical integration errors can be significantly reduced, improving the accuracy of heat calculation. After heating is complete, the system outputs the total heating amount Q and generates a complete curve of power variation over time. This curve can be represented as a discrete point set or a fitted function for subsequent analysis and processing.

[0056] In one possible implementation, the control and data processing module 4 inverts the thermal conductivity of sediments by: constructing a one-dimensional unsteady thermal conductivity equation, discretizing the thermal conductivity equation using the finite difference method, constructing a temperature prediction model, constructing and minimizing the error function between the measured temperature and the predicted temperature, and solving for the thermal conductivity.

[0057] In this embodiment, after completing the heating process and energy calculation, the present invention further realizes the inversion calculation of sediment thermal conductivity through the relationship between temperature data and heat input. First, after the geothermal probe is inserted into the sediment, the temperature acquisition module sets up multiple measuring points at preset intervals and acquires temperature data at each location with a fixed sampling period, forming a spatial-temporal two-dimensional data sequence T( , ),in Indicates different depth positions. This represents a time series. During the heating process, the temperature of the sediment changes over time, and its distribution satisfies a one-dimensional unsteady-state heat conduction equation: in, This represents the thermal conductivity to be determined. Indicates density, Indicates specific heat capacity. The heat source term is represented by the heating power function P(t) or the total heat Q distribution. Next, the heat conduction equation is discretized using the finite difference method, and a temperature prediction model is first constructed. The model output was then compared with the actual measurement data, and an error function was constructed: in, This represents the measured temperature. The thermal conductivity parameter is calculated iteratively or through optimization algorithms. The process involves gradual adjustments to minimize the error function. During each iteration, the temperature distribution is recalculated and the error value is updated until the convergence condition is met, i.e., the thermal conductivity k of the sediment is obtained. Finally, the heat flux value is calculated using the thermal conductivity. In one possible implementation, the control and data processing module 4 also includes a resistance correction unit, which is used to correct the calculated instantaneous resistance value using a pre-established resistance-temperature characteristic model to eliminate the influence of temperature nonlinear drift and to obtain the real-time temperature of the heating module 5.

[0058] In this embodiment, the heating module 5 is a metal heating wire, whose resistance value exhibits non-linear characteristics with temperature changes. Directly calculating the instantaneous resistance using voltage / current would introduce errors. Therefore, the resistance correction unit of the control and data processing module 4 corrects the instantaneous resistance value using a pre-established resistance-temperature characteristic model.

[0059] In one possible implementation, the control and data processing module 4 further includes an integral smoothing unit for performing sliding window smoothing on the power sequence before integration, and / or performing polynomial fitting on the power-time series after integration, and performing analytical integration on the fitted function to correct discrete integration errors.

[0060] In this embodiment, a sliding window of length 10 is used to perform moving average filtering on the instantaneous power sequence to eliminate high-frequency noise interference and obtain a smoothed power sequence. The smoothed power time sequence is then fitted with a quadratic polynomial to obtain a fitting function. The fitted power function is then analytically integrated over the heating period. Based on the total heating amount Q calculation formula, the calculation error is controlled within ±3%, providing a reliable basis for subsequent thermal conductivity inversion.

[0061] As a second aspect of the invention, a quantitative heating method for measuring seabed heat flow is proposed, such as... Figure 2 As shown, it includes the following steps: S1, Set the target heating parameters, including the target current value; S2 outputs an initial drive voltage to the heating element through the constant current drive module, generating a heating current; S3, real-time acquisition of the actual current value in the heating circuit, and calculation of the error between it and the target current value; S4, based on the error, adjusts the drive voltage through negative feedback closed loop to ensure that the actual current stably tracks the target current value during the heating process; S5, during the heating process, performs high-frequency synchronous acquisition of the actual voltage and actual current in the heating circuit; S6, based on the voltage and current data collected at the same moment, obtain the total input heat through the total heating integration process; S7 utilizes temperature sensors distributed along the probe axis to collect and record multi-point temperature change data of sediments during the heating process in layers. Combining the total input heat and multi-point temperature change data, the thermal conductivity of the sediments is calculated by inversion.

[0062] In this embodiment of the application, before heating measurement, step S1: the control and data processing module 4 presets target heating parameters, including key parameters such as target current value, total heating time, sampling frequency, sliding window length, and polynomial fitting order. The target current value is set according to the heating power requirement and serves as a reference benchmark for subsequent closed-loop control.

[0063] Step S2: After the initial heating drive system is started, the control and data processing module 4 sends an initial drive voltage command to the constant current drive module 1. The constant current drive module 1 applies the command voltage to both ends of the heating module, so that the heating circuit generates an initial heating current and begins to heat the seabed sediment.

[0064] Step S3: Real-time calculation of current error. During the heating process, the current acquisition module 2 acquires the actual current value in the heating circuit in real time at a preset sampling frequency (e.g., 1kHz) and transmits it to the control and data processing module 4. The control and data processing module 4 constructs a current error function, calculates the deviation between the current actual current value and the preset target current value, and provides an error signal for closed-loop regulation.

[0065] Step S4: The negative feedback closed-loop constant current regulation control and data processing module 4 adopts a proportional-integral (PI) control algorithm. Based on the current error obtained in step S3, it performs closed-loop regulation on the output drive voltage of the constant current drive module 1: the proportional term of the error quickly responds to the deviation change, and the integral term eliminates the steady-state error, so that the actual current stably tracks the target current value throughout the heating process, ensuring the stability of the heating power.

[0066] Step S5: High-frequency synchronous electrical parameter acquisition During the heating process, the current acquisition module 2 and the voltage acquisition module 3 use the same clock to perform synchronous high-frequency sampling, and acquire the actual current value and actual voltage value in the heating circuit in real time to ensure that the voltage and current data at the same moment correspond one-to-one, and avoid power calculation errors caused by phase deviation.

[0067] Step S6: Total Heating Integration Calculation Based on the synchronous voltage and current data collected in step S5, the total input heat is calculated through the total heating integration process: First, the instantaneous resistance value of heating module 5 is calculated based on the voltage and current data at the same time, and temperature drift correction is performed through a pre-established resistance-temperature characteristic model; then, the corrected instantaneous heating power is calculated, the power sequence is smoothed by a sliding window and fitted with a polynomial, and then the fitted continuous power function is analytically integrated to obtain the total input heat during the heating period.

[0068] Step S7: During the heating process for sediment thermal conductivity inversion, the temperature acquisition module 6 collects and records multi-point temperature change data of the seabed sediment in layers through multiple temperature sensors distributed along the axial direction of the geothermal probe. After heating, the control and data processing module 4 combines the total input heat and multi-point temperature change data obtained in step S6 to construct a one-dimensional unsteady-state heat conduction equation and discretize it using the finite difference method. The error function is constructed by the residual between the measured temperature and the predicted temperature and minimized to obtain the thermal conductivity of the seabed sediment, and finally the quantitative measurement of seabed heat flow is completed.

[0069] In one possible implementation, such as Figure 3 As shown, the total heating integration process specifically includes the following steps: S61, calculate the instantaneous resistance value of the heating element; S62, calculates instantaneous power based on instantaneous resistance and instantaneous current values; S63 performs discrete-time integration on all instantaneous power during the entire heating period to calculate the total heating amount.

[0070] In one possible implementation, the negative feedback closed-loop regulation in step S4 employs a proportional-integral control algorithm.

[0071] This invention addresses the challenge of accurately quantifying heating input during seabed sediment heat flow measurement by constructing a heating control method based on real-time multi-parameter acquisition and dynamic calculation. By organically combining constant current drive, online resistance identification, and power integral calculation, the heating process is transformed from a traditional open-loop control method based on set parameters into a closed-loop adjustment and dynamic calculation process based on real-time data. This allows the heating input to be fully described in time-series form and possesses a unified data expression format. Furthermore, this invention establishes the correlation between voltage, current, resistance, and temperature, achieving data coupling between electrical parameters and thermal response during the heating process. This data is then introduced into the sediment thermal conductivity inversion calculation, allowing heat source input conditions and temperature response data to be processed within the same data system. By recording and uniformly modeling the entire heating process, a continuous and complete data foundation is provided for subsequent thermal conductivity calculations, thus forming an integrated technical solution covering the entire "heating-measurement-calculation" process.

[0072] This invention, based on negative feedback constant current control and real-time electrical parameter calculation mechanisms, achieves the following expected technical effects in terms of heating control accuracy and energy quantification capability: During constant current drive, closed-loop regulation ensures high stability of the heating current throughout the entire operating phase, with steady-state error controlled within ±1% of the set value and short-term fluctuations not exceeding ±2%. Regarding electrical parameter measurement and power calculation, synchronous high-precision acquisition of voltage and current, combined with online resistance calculation and resistance-temperature model correction, controls instantaneous power calculation error within ±1%. Furthermore, by performing discrete integration and fitting correction on the power time series, the total heating calculation error can be controlled within ±1% to ±3%. Simultaneously, through full-process data acquisition and time series construction, continuous expression of heating power changes over time can be achieved, outputting complete power curve data. In the thermal conductivity inversion process, due to the quantitative expression of heating input, the repeatability error of the measurement results can be controlled within approximately ±5% under the same test conditions, thus forming a continuous data processing process from current control and power calculation to heat acquisition and parameter inversion.

[0073] The foregoing has described specific embodiments of the present invention. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps described in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired results. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0074] In the description of the embodiments of the present invention, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In the embodiments of the present invention, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in a suitable manner in any one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in the embodiments of the present invention, as well as the features of the different embodiments or examples.

[0075] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of embodiments of the present invention, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0076] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of preferred embodiments of the invention includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of the invention pertain.

[0077] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A quantitative heating system for measuring seabed heat flow, characterized in that, It includes a constant current drive module (1), a current acquisition module (2), a voltage acquisition module (3), a control and data processing module (4), a heating module (5), and a temperature acquisition module (6). The constant current drive module (1) is used to provide a drive voltage to the heating module (5) to generate a heating current; The current acquisition module (2) is used to acquire the actual current value in the heating module (5) in real time; The voltage acquisition module (3) is used to acquire the actual voltage value in the heating module (5) in real time; The temperature acquisition module (6) is used to collect temperature data of sediments at multiple points distributed along the axial direction of the geothermal probe; The control and data processing module (4) is connected to the constant current drive module (1), the current acquisition module (2), the voltage acquisition module (3) and the temperature acquisition module (6), respectively; The control and data processing module (4) is configured as follows: Receive the preset target current value; Based on the error between the target current value and the actual current value, the driving voltage output by the constant current drive module (1) is adjusted through negative feedback closed loop to make the actual current value track the target current value; during heating, the actual voltage value and the actual current value set are collected, and the instantaneous resistance value of the heating module (5) is calculated in real time. Instantaneous power is calculated based on instantaneous resistance and actual current values, and the instantaneous power is integrated over time during the heating period to obtain the total heating amount. The thermal conductivity of sediments can be calculated by inverting the total heating amount or multi-point temperature data.

2. The system according to claim 1, characterized in that, The control and data processing module (4) includes: Error calculation unit, used to construct error function ,in, For error signals, Indicates the target current. Indicates the actual current; The control and regulation unit is used to output the driving voltage regulation amount ΔU(k) ​​according to the error function using a proportional-integral control algorithm.

3. The system according to claim 1, characterized in that, The control and data processing module (4) also includes a resistance correction unit, which is used to correct the calculated instantaneous resistance value using a pre-established resistance-temperature characteristic model, so as to eliminate the influence of temperature nonlinear drift and obtain the real-time temperature of the heating module (5).

4. The system according to claim 3, characterized in that, The resistance-temperature characteristic model is a second-order polynomial fitting model.

5. The system according to claim 1, characterized in that, The control and data processing module (4) performs polynomial fitting on the instantaneous power time series and then performs time integration to obtain the total heating amount.

6. The system according to claim 5, characterized in that, The control and data processing module (4) further includes an integral smoothing unit, which is used to perform sliding window smoothing on the power sequence before integration, and / or to perform polynomial fitting on the power-time sequence after integration, and to perform analytical integration on the fitting function to correct discrete integral errors.

7. The system according to claim 1, characterized in that, The control and data processing module (4) specifically includes the following steps to invert the thermal conductivity of sediments: constructing a one-dimensional unsteady thermal conductivity equation, discretizing the thermal conductivity equation using the finite difference method, constructing a temperature prediction model, constructing and minimizing the error function between the measured temperature and the predicted temperature, and solving to obtain the thermal conductivity.

8. A quantitative heating control method for measuring seabed heat flow, characterized in that, Includes the following steps: S1, Set the target heating parameters, including the target current value; S2 outputs an initial drive voltage to the heating element through the constant current drive module, generating a heating current; S3, real-time acquisition of the actual current value in the heating circuit, and calculation of the error between it and the target current value; S4. Based on the error, the driving voltage is adjusted through a negative feedback closed loop to ensure that the actual current stably tracks the target current value during the heating process. S5, during the heating process, performs high-frequency synchronous acquisition of the actual voltage and actual current in the heating circuit; S6, based on the voltage and current data collected at the same moment, obtain the total input heat through the total heating integration process; S7. Using temperature sensors distributed along the probe axis, multi-point temperature change data of the sediment during the heating process are collected and recorded in layers. Combined with the total input heat and multi-point temperature change data, the thermal conductivity of the sediment is calculated by inversion.

9. The method according to claim 8, characterized in that, The total heating integration process specifically includes the following steps: S61, calculate the instantaneous resistance value of the heating element; S62, Calculate the instantaneous power based on the instantaneous resistance value and the instantaneous current value; S63 performs discrete-time integration on all instantaneous power during the entire heating period to calculate the total heating amount.

10. The method according to claim 8, characterized in that, The negative feedback closed-loop regulation described in step S4 adopts a proportional-integral control algorithm.

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