A method and system for automatically evaluating energy consumption of groundwater pumping and irrigation in a foundation pit engineering

Abstract

The present application relates to the technical field of electromechanical parameter monitoring, in particular to a method and system for automatically evaluating the energy consumption of groundwater pumping and irrigation in foundation pit engineering, which obtains the starting current and electric energy data of a submersible pump, analyzes the starting decay characteristics to determine the load parameters, screens the steady-state operation interval and accumulates the electric energy, and realizes the evaluation of the energy consumption of groundwater pumping and irrigation. According to the present application, the current time series data during the starting process of the motor is collected and the waveform decay characteristics are analyzed, the fluid viscosity and mechanical inertia load resistance properties are accurately identified according to the current change rate difference, the energy consumption and water quantity conversion coefficient is adaptively matched without the participation of the physical flow meter, the risk of data failure caused by the erosion of the measuring components by the underground silt is completely avoided, the dispersion analysis is performed on the electric energy increment sequence in the form of sliding window statistics, the interference data during the initial starting and non-steady-state fluctuation period is automatically filtered and the stable operation interval is accurately locked, and the operation is performed based on the pure energy consumption data under the stable working condition and combined with the dynamically matched reference parameters.

Description

Technical Field

[0001] This invention relates to the field of electromechanical parameter monitoring and energy efficiency assessment technology, specifically to an automatic energy consumption assessment method and system for groundwater pumping and irrigation processes in foundation pit engineering. Background Technology

[0002] In the groundwater control phase of foundation pit engineering, the pumping and irrigation operation of dewatering wells is crucial for maintaining pit wall stability and controlling groundwater levels. Accurate assessment of energy consumption and water volume during the pumping and irrigation process is of great significance for optimizing operational strategies, reducing energy costs, and providing early warnings of equipment malfunctions.

[0003] Currently, the commonly used assessment method in the industry is to install mechanical or electromagnetic flow meters on the pumping pipeline to directly measure the pumping volume, while simultaneously using electricity meters to measure power consumption, thereby calculating the energy consumption per unit volume of water. However, in the actual environment of foundation pit engineering, groundwater flow often carries a large amount of silt and fine particles, which can easily cause wear, blockage, or corrosion of flow meter sensing components (such as impellers, ultrasonic probes, or electrodes), leading to a rapid decline in measurement accuracy or even equipment failure. Frequent cleaning, calibration, or replacement not only increases operation and maintenance costs but also causes monitoring data interruption or distortion, making long-term energy efficiency assessments unsustainable.

[0004] Furthermore, existing methods typically correlate the total power consumption throughout the entire operating cycle with the total pumping volume, neglecting the nonlinear and highly fluctuating transient processes present during the motor startup phase. The energy consumption characteristics during this phase differ significantly from steady-state operation; incorporating this into the overall calculation will introduce significant errors, causing the assessment results to deviate from the true energy efficiency level. More importantly, the actual load characteristics of the pump are dynamically changing due to groundwater hydrogeological conditions (such as aquifer permeability and groundwater viscosity variations) and the state of mechanical transmission. Fixed energy-water conversion coefficients cannot accurately reflect these dynamic characteristics, resulting in insufficient universality and accuracy of the assessment model in foundation pit projects with different operating conditions or geological conditions.

[0005] Therefore, there is an urgent need for an automatic assessment technology for groundwater pumping and irrigation energy consumption that can avoid the use of physical flow meters, automatically identify load characteristics, and accurately isolate non-steady-state interference data. Summary of the Invention

[0006] This invention addresses the problems of existing technologies, such as reliance on easily damaged flow meters, inability to distinguish between steady-state and non-steady-state energy consumption, and inability of evaluation models to adapt to dynamic load changes. It proposes an automatic evaluation method and system for groundwater pumping and irrigation energy consumption based on motor starting current characteristic analysis and steady-state screening of operating data.

[0007] The technical solution adopted in this invention is as follows: an automatic assessment method for groundwater pumping and irrigation energy consumption in foundation pit engineering, comprising the following steps: S1: Obtain the real-time current of the submersible pump motor power supply line, lock the motor start-up event trigger time, and construct the start-up process current time series dataset; S2: Determine the peak holding interval of the current holding maximum value in the current timing data of the startup process, and calculate the duration of the first decay stage and the duration of the second decay stage based on the current change between adjacent peak holding intervals. S3: Determine the load resistance attribute category corresponding to the current submersible pump motor based on the duration of the first attenuation stage and the duration of the second attenuation stage, and obtain the load operation reference parameter set; S4: Obtain the cumulative energy of the power metering instrument, construct the power increment sequence, compare the power increment sequence with the load operation reference parameter set, and filter the steady-state operation time index set; S5: Extract the data items corresponding to the steady-state operating time index set from the power increment sequence and accumulate them to obtain the total steady-state pumping power. Combine the data with the load operating benchmark parameter set to construct the groundwater pumping energy consumption assessment result.

[0008] The present invention is improved in that the current timing dataset for the startup process includes a real-time current sequence extracted based on the trigger time of the motor startup event; the duration of the first attenuation phase is specifically the time span during which the absolute value of the current change rate is greater than a preset attenuation rate threshold; the duration of the second attenuation phase is specifically the time span during which the absolute value of the current change rate is less than a preset attenuation rate threshold; the load operation reference parameter set includes energy consumption and water volume conversion coefficients and rated operating power ranges; the steady-state operating time index set is specifically an index of time periods where the average value is within the rated operating power range and the standard deviation is less than a stability threshold; and the groundwater pumping and irrigation energy consumption assessment results include the total steady-state pumping and irrigation electrical energy, the total steady-state pumping and irrigation water volume, the average operating power of the submersible pump, and the compliance judgment results.

[0009] The present invention is improved in that step S1 is specifically as follows: S101: Continuously acquire the real-time current value in the power supply line of the submersible pump motor according to a preset time interval, compare the acquired real-time current with the preset silence threshold, and when the continuously acquired real-time current value exceeds the silence threshold, determine that the motor has entered the start-up state and record the current timestamp to obtain the motor start-up event trigger time. S102: Set the length of the extended time interception window, locate and extract data points in the continuously acquired real-time current data stream that are within the range from the trigger time of the motor start event to the end time of the time interception window, and generate the original start current data segment. S103: Arrange the current data in the original starting current data segment in chronological order, construct a two-dimensional data structure with time index and corresponding current, and interpolate and fill in the missing points to obtain the starting process current time series dataset.

[0010] The present invention is improved in that step S2 is specifically as follows: S201: Identify the maximum value of the current in the current timing data of the startup process, determine the start time point and end time point where the maximum current value remains unchanged or fluctuates within a preset error range, calculate the time span between the start time point and the end time point, and obtain the peak value holding interval. S202: Extract the current data segment located after the peak holding interval in the current time series dataset of the startup process, calculate the difference between two adjacent current sampling points in the current data segment and the corresponding time interval difference, and calculate the ratio of the difference to the time interval difference to obtain the current change rate sequence. S203: Traverse each current change rate in the current change rate sequence, compare the absolute value of the current change rate with a preset attenuation rate threshold, divide the current data area where the absolute value of the current change rate is greater than the attenuation rate threshold into the first stage, accumulate the time length covered by the first stage to obtain the duration of the first attenuation stage, divide the current data area where the absolute value of the current change rate is less than the attenuation rate threshold into the second stage, accumulate the time length covered by the second stage to obtain the duration of the second attenuation stage.

[0011] The present invention is improved in that step S3 is specifically as follows: S301: Compare the duration of the first attenuation phase with a preset first time limit reference value, and simultaneously compare the duration of the second attenuation phase with a preset second time limit reference value. Based on the two comparison results, determine the characteristics of the load resistance currently experienced by the motor and classify the load resistance attribute category. S302: Based on the load resistance attribute category, perform an index lookup in the preset parameter mapping table to locate the parameter item that has a unique mapping relationship with the load resistance attribute category, and extract the energy consumption water volume conversion coefficient corresponding to each kilowatt-hour of electrical energy consumed and the rated working power range of the motor during normal operation. S303: Associate the energy consumption and water consumption conversion coefficient with the rated operating power range to construct a parameter set with energy efficiency conversion standards and power operation specifications. Standardize the data format in the parameter set to obtain a load operation reference parameter set.

[0012] The present invention is improved in that step S4 is specifically as follows: S401: Access the register of the power meter at a fixed sampling frequency, obtain the cumulative power reading, calculate the power consumption difference between the cumulative power reading at the current sampling time and the cumulative power reading at the previous sampling time, and obtain the power increment sequence. S402: Set the step spacing of the sliding window, perform sliding window grouping operation on the power increment sequence, and calculate the window arithmetic mean and window standard deviation of all power increments within each window. S403: Call the rated operating power range in the load operating reference parameter set, preset the stability threshold, determine whether the window arithmetic mean is within the rated operating power range, and at the same time determine whether the window standard deviation is less than the stability threshold, filter the time period index that simultaneously meets the judgment conditions, and obtain the steady-state operating time index set.

[0013] The present invention is improved in that step S5 is specifically as follows: S501: Based on the steady-state operating time index set, locate and extract the data items at the corresponding time points in the energy increment sequence, accumulate all energy increment data items, and calculate the total power consumption of the motor in the steady-state pumping power. S502: Call the energy consumption and water volume conversion coefficient in the load operation reference parameter set, calculate the product of the total steady-state pumping and irrigation power and the energy consumption and water volume conversion coefficient, and at the same time, count the total time span covered by the steady-state operation time index set, calculate the ratio of the total steady-state pumping and irrigation power to the total time span, and obtain the average operating power of the submersible pump motor. S503: Perform interval matching verification between the average operating power of the submersible pump motor and the rated operating power range in the load operating reference parameter set, determine whether the actual power deviates from the rated range of the rated operating power range, and obtain the groundwater pumping and irrigation energy consumption assessment result.

[0014] An automatic assessment system for energy consumption of groundwater pumping and irrigation in foundation pit engineering, the system comprising: The startup current acquisition module acquires the real-time current of the submersible pump motor power supply line, locks the trigger time of the motor startup event, and constructs a startup process current time series dataset. The attenuation characteristic analysis module determines the peak holding interval of the current in the current time series data of the startup process, and calculates the duration of the first attenuation stage and the duration of the second attenuation stage based on the current change between adjacent peak holding intervals. The load attribute determination module determines the load resistance attribute category corresponding to the current submersible pump motor based on the duration of the first attenuation stage and the duration of the second attenuation stage, and obtains the load operation reference parameter set. The steady-state operation identification module acquires the cumulative energy of the power metering instrument, constructs an energy increment sequence, compares the energy increment sequence with the load operation reference parameter set, and filters the steady-state operation time index set. The energy consumption assessment module extracts data items corresponding to the steady-state operating time index set from the incremental power sequence and accumulates them to obtain the total steady-state pumping and irrigation power. Combined with the load operation benchmark parameter set, it constructs the groundwater pumping and irrigation energy consumption assessment result.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by collecting current timing data during motor startup and analyzing waveform attenuation characteristics, the fluid viscosity and mechanical inertial load resistance attributes are accurately identified based on the difference in current change rate. Adaptive matching of energy consumption and water volume conversion coefficients is achieved without the participation of a physical flowmeter, completely avoiding the risk of data failure caused by the erosion of metering components by sediment in the well. Discreteness analysis is performed on the incremental power sequence using a sliding window statistical method, automatically filtering interference data from the initial startup phase and non-steady-state fluctuation period and accurately locking the stable operating range. Based on pure energy consumption data under stable operating conditions combined with dynamic matching benchmark parameters, calculations are performed to achieve high-precision automatic assessment of the health status and energy efficiency level of the groundwater pumping and irrigation process. Attached Figure Description

[0016] Figure 1 This is a flowchart of the method of the present invention; Figure 2 This is a detailed flowchart of step S1 of the present invention; Figure 3 This is a detailed flowchart of step S2 of the present invention; Figure 4 This is a detailed flowchart of step S3 of the present invention; Figure 5 This is a detailed flowchart of step S4 of the present invention; Figure 6 This is a detailed flowchart of step S5 of the present invention; Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. These embodiments are merely illustrative of the invention and are not intended to limit the scope of protection of the invention.

[0018] Please see Figure 1 This invention provides a technical solution: an automatic assessment method for energy consumption of groundwater pumping and irrigation in foundation pit engineering, comprising the following steps: S1: Obtain the real-time current of the submersible pump motor power supply line, lock the motor start-up event trigger time, and construct the start-up process current time series dataset; S2: Determine the peak holding interval of the current in the current timing data during the startup process, and calculate the duration of the first decay stage and the duration of the second decay stage based on the current changes between adjacent peak holding intervals. S3: Determine the load resistance attribute category corresponding to the current submersible pump motor based on the duration of the first attenuation stage and the duration of the second attenuation stage, and obtain the load operation reference parameter set; S4: Obtain the cumulative energy of the power metering instrument, construct the power increment sequence, compare the power increment sequence with the load operation reference parameter set, and filter the steady-state operation time index set; S5: Extract the data items corresponding to the steady-state operating time index set from the power increment sequence and accumulate them to obtain the total steady-state pumping power. Combine this with the load operating benchmark parameter set to construct the groundwater pumping energy consumption assessment result.

[0019] The startup process current time series dataset includes real-time current sequences captured based on the trigger time of the motor startup event. The duration of the first decay stage is specifically the time span during which the absolute value of the current change rate is greater than the preset decay rate threshold, and the duration of the second decay stage is specifically the time span during which the absolute value of the current change rate is less than the preset decay rate threshold. The load operation benchmark parameter set includes energy consumption and water volume conversion coefficients and rated operating power range. The steady-state operating time index set specifically includes the index of time periods where the average value is within the rated operating power range and the standard deviation is less than the stability threshold. The groundwater pumping and irrigation energy consumption assessment results include the total steady-state pumping and irrigation electrical energy, the total steady-state pumping and irrigation water volume, the average operating power of the submersible pump, and the compliance judgment results.

[0020] Please see Figure 2 Step S1 is as follows: S101: Continuously acquire the real-time current value in the power supply line of the submersible pump motor at preset time intervals, compare the acquired real-time current with the preset silent threshold, and when the continuously acquired real-time current value exceeds the silent threshold, determine that the motor has entered the start-up state and record the current timestamp to obtain the motor start-up event trigger time. A Hall effect current sensor deployed in the submersible pump motor power supply line continuously outputs an analog voltage signal at a pre-set sampling frequency of 1 kilohertz (i.e., 1,000 data points per second). This signal is then converted into a digital real-time current value after analog-to-digital conversion. Before performing real-time monitoring and judgment, a pre-determined silence threshold is retrieved. This silence threshold is determined by: selecting historical background noise current data from 10,000 continuous sampling points when the submersible pump motor is completely stationary after power failure; calculating the arithmetic mean and standard deviation of all values ​​in this dataset; and adding the arithmetic mean to four times the standard deviation to obtain the silence threshold. For example, if the calculated background noise arithmetic mean is 0.05 amperes and the standard deviation is 0.01 amperes, the silence threshold is calculated as follows: The silence threshold is set to 0.09 amperes. The real-time current values ​​collected during real-time monitoring need to be compared with the 0.09 ampere silence threshold. There are two possibilities for this comparison: First, the currently collected real-time current value is less than or equal to 0.09 amperes. In this case, the motor is determined to be still stationary, and data collection continues for the next moment. Second, the real-time current values ​​for five consecutive sampling cycles are all greater than 0.09 amperes. In this case, the motor is determined to have ended its stationary state and entered the start-up state. The system clock timestamp corresponding to the first sampling point exceeding the silence threshold, for example, 12:00:00:100 milliseconds, is locked and marked as the motor start-up event trigger time.

[0021] S102: Set the length of the extended time interception window, locate and extract data points in the continuously acquired real-time current data stream that are within the range from the moment the motor start event is triggered to the end of the time interception window, and generate the original start current data segment. The extended time truncation window length needs to be preset. This length is based on 1.5 times the longest historical statistical time required for the submersible pump motor of this model to accelerate from rest to rated speed under rated voltage. For example, if the longest start-up time of this motor is found to be 3000 milliseconds in the historical operation database, the calculation process for the time truncation window length is as follows: The window length is set to 4500 milliseconds. Based on the motor start-up event trigger time, a starting data pointer is located in the circular buffer storing real-time current data. Then, starting from this pointer, the current value and corresponding timestamp are extracted sequentially from subsequent storage units along the positive time axis until the timestamp of the extracted data point equals the start-up event trigger time plus the time truncation window length, i.e., up to 12:00:04.60 milliseconds. This series of extracted data pairs containing timestamps and current values ​​is copied from the circular buffer to a separate memory space, forming an independent raw start-up current data segment. This segment completely covers the entire dynamic process of the motor from standstill to completion of startup.

[0022] S103: Arrange the current data in the original starting current data segment in chronological order, construct a two-dimensional data structure with time index and corresponding current, and interpolate and fill in the missing points to obtain the starting process current time series dataset. All data points in the original starting current data segment are rearranged in ascending order based on their timestamp values. After rearrangement, the timestamp difference between two adjacent data points is calculated and compared with the standard sampling interval corresponding to the sampling frequency. This comparison has two possibilities: the first possibility is that the calculated timestamp difference equals the standard sampling interval, in which case the data is considered continuous; the second possibility is that the calculated timestamp difference is greater than the standard sampling interval, for example, if two adjacent timestamps are 10 milliseconds and 13 milliseconds respectively, the difference is 3 milliseconds, in which case a missing point is identified. For the missing point in the second possibility, linear interpolation is performed: the current value (set to 10 amps) before and after the missing interval (set to 16 amps) is read, along with the corresponding time difference (3 milliseconds), and the slope of change is calculated. Amperes per millisecond, thus the current value at the missing 11 milliseconds is calculated as follows: Ampere, the current value at 12 milliseconds is Ampere. The calculated completion points are inserted at the corresponding positions until the time intervals of all adjacent points meet the standard sampling interval, finally generating a startup process current time series dataset with a continuous time axis and complete numerical values.

[0023] Please see Figure 3 Step S2 is as follows: S201: Identify the maximum value of the current in the current timing data during the startup process, determine the start and end time points when the maximum current value remains unchanged or fluctuates within a preset error range, calculate the time span between the start and end time points, and obtain the peak value holding interval. The startup current timing dataset is scanned to filter out the current point with the highest value, which is determined as the startup peak current. Subsequently, a fluctuation error range is determined, set at two percent of the startup peak current value. For example, if the filtered startup peak current is 80 amperes, the fluctuation error range is calculated as follows: Ampere, which is the allowable range of current fluctuations. Ampere Amperes. Centering on the time point corresponding to the peak value, current is measured point by point forward and backward along the time axis to determine if the current value at each sampling point falls within the range of 78.4 amperes to 81.6 amperes. The first time point consecutively within this range is marked as the start time point, and the last time point is marked as the end time point. Finally, the difference between the timestamp of the end time point and the timestamp of the start time point represents the time span of the peak hold interval.

[0024] S202: Extract the current data segment located after the peak holding interval in the current time series dataset during the startup process, calculate the difference between two adjacent current sampling points in the current data segment and the corresponding time interval difference, and calculate the ratio of the difference to the time interval difference to obtain the current change rate sequence. In the startup process current timing dataset, all current data after the end of the peak hold interval are extracted to form a falling segment data stream. Adjacent current sampling points in this stream are read sequentially. The current difference is obtained by subtracting the current value of the previous sampling point from the current value of the subsequent sampling point; simultaneously, the time difference is obtained by subtracting the time value of the previous sampling point from the time value of the subsequent sampling point. Dividing the current difference by the time difference yields the rate of change of current at that moment. For example, if the current is 70 amps at the previous moment and 68 amps at the next moment, with a time interval of 1 millisecond (0.001 seconds), the calculation process for the rate of change of current is as follows: Amperes per second. The above calculation is repeated for each pair of adjacent points in the falling segment of the data stream to generate a sequence of current change rates, which reflects how quickly the current decreases after the motor starts.

[0025] S203: Traverse each current change rate in the current change rate sequence, compare the absolute value of the current change rate with the preset decay rate threshold, divide the current data area where the absolute value of the current change rate is greater than the decay rate threshold into the first stage, accumulate the time length covered by the first stage to obtain the duration of the first decay stage, divide the current data area where the absolute value of the current change rate is less than the decay rate threshold into the second stage, accumulate the time length covered by the second stage to obtain the duration of the second decay stage; The attenuation rate threshold needs to be pre-read. This threshold is set based on the average rate of natural current decay during no-load idling and shutdown of this motor model in a laboratory environment. Fifty percent of this average rate is then set as the attenuation rate threshold. For example, if the measured average attenuation rate during idling and shutdown is 1000 amperes per second, the calculation process for the attenuation rate threshold is as follows: The threshold is set to 500 amperes per second. The absolute value of each value in the current rate of change sequence is calculated and compared with 500. There are two possibilities for this comparison: First, if the absolute value of the current rate of change at a certain moment is greater than 500, the time interval corresponding to that moment is included in the first stage, and the duration of that stage is accumulated. Second, if the absolute value of the current rate of change at a certain moment is less than or equal to 500, the time interval corresponding to that moment is included in the second stage, and the duration of that stage is accumulated. After the traversal is complete, the two accumulated time sums are output as the duration of the first decay stage and the duration of the second decay stage, respectively.

[0026] Please see Figure 4 Step S3 is as follows: S301: Compare the duration of the first attenuation stage with the preset first time limit reference value, and at the same time compare the duration of the second attenuation stage with the preset second time limit reference value. Based on the two comparison results, determine the characteristics of the load resistance currently experienced by the motor and classify the load resistance attribute category. The process of determining the characteristics of the current load resistance on the motor and classifying the load resistance attribute category based on the logical combination result of the two comparison operations is as follows: The state in which the duration of the first decay phase is greater than the first time limit benchmark value and the duration of the second decay phase is less than the second time limit benchmark value is defined as the first judgment condition, and the state in which the duration of the first decay phase is less than the first time limit benchmark value and the duration of the second decay phase is greater than the second time limit benchmark value is defined as the second judgment condition. When the first determination condition is met, the characteristic of the load resistance currently experienced by the motor is determined to be viscous-dominant resistance characteristic, and the load resistance attribute category is marked as viscous-dominant load category. When the second determination condition is met, the characteristic of the load resistance currently experienced by the motor is determined to be the inertia-dominated resistance characteristic, and the load resistance attribute category is marked as the inertia-dominated load category. By deeply analyzing the current decay characteristics during motor startup, adaptive load identification of the operating environment is achieved. Without the need for manually preset complex operating parameters, the system can automatically distinguish whether the motor is in a fluid load state (viscous dominance) for pumping groundwater or in a state of idling or mechanical inertial load (inertia dominance) based on the duration distribution of the current in the rapid decay phase and the slow tailing phase.

[0027] The first and second time limit reference values ​​are invoked. The first time limit reference value is set based on the historical statistical average duration of the rapid decay phase when the motor of this model starts under a pure water fluid load, for example, 0.6 seconds; the second time limit reference value is set based on the historical statistical average duration of the slow tailing phase when the motor of this model starts under a high inertia flywheel load, for example, 2.0 seconds. The durations of the first and second attenuation phases are logically compared with the baseline values. There are two possibilities: The first possibility is that the duration of the first attenuation phase (e.g., 0.8 seconds) is greater than the first time limit baseline value (0.6 seconds), and the duration of the second attenuation phase (e.g., 0.5 seconds) is less than the second time limit baseline value (2.0 seconds). In this case, it is determined that the resistance experienced by the motor is mainly due to fluid viscosity, and the load resistance attribute category is marked as viscosity-dominated load category. The second possibility is that the duration of the first attenuation phase (e.g., 0.3 seconds) is less than the first time limit baseline value (0.6 seconds), and the duration of the second attenuation phase (e.g., 2.5 seconds) is greater than the second time limit baseline value (2.0 seconds). In this case, it is determined that the resistance is mainly due to rotational inertia, and the load resistance attribute category is marked as inertia-dominated load category.

[0028] S302: Based on the load resistance attribute category, perform an index lookup in the preset parameter mapping table to locate the parameter item that has a unique mapping relationship with the load resistance attribute category, and extract the energy consumption water volume conversion coefficient corresponding to each kilowatt-hour of electrical energy consumed and the rated operating power range of the motor during normal operation. Based on the determined load resistance attribute category, a pre-built parameter mapping table is accessed. This mapping table was constructed through extensive energy efficiency tests on motors under different load types, establishing a unique correspondence between load categories and physical parameters. Depending on the input load category, there are two possibilities: the first is that the input is a viscous-dominated load category. In this case, the entry is located in the table, and the corresponding energy-water conversion coefficient (set based on the volume of groundwater that can be extracted for every 1 kWh of electricity consumed under this type of load, e.g., 3.5 cubic meters per kWh) and the rated operating power range of the motor during normal operation (set based on the power range corresponding to the motor's highest efficiency point under this type of load, e.g., 10,000 watts to 12,000 watts) are extracted. The second possibility is that the input is an inertial-dominated load category. In this case, another set of corresponding coefficients and power ranges are extracted. This parameter extraction process based on adaptive load identification results ensures that the benchmark parameters used in subsequent energy consumption assessments match the actual physical load characteristics borne by the motor, improving the relevance and accuracy of the assessment.

[0029] S303: The energy consumption and water consumption conversion coefficients are associated and combined with the rated operating power range to construct a parameter set with energy efficiency conversion standards and power operation specifications. The data format in the parameter set is standardized to obtain the load operation benchmark parameter set. The extracted energy and water consumption conversion factor (e.g., 3.5) and the rated operating power range (e.g., 10000 to 12000) need to be formatted. The rated operating power range is split into a lower power limit (10000) and a higher power limit (12000), and the energy and water consumption conversion factor is converted to double-precision floating-point format. These three values ​​are encapsulated into a structured parameter set, named the load operation baseline parameter set.

[0030] Please see Figure 5 Step S4 is as follows: S401: Access the register of the power meter at a fixed sampling frequency, obtain the cumulative power reading, calculate the power consumption difference between the cumulative power reading at the current sampling time and the cumulative power reading at the previous sampling time, and obtain the power increment sequence. The register of the energy meter connected to the front end of the submersible pump motor is accessed via the RS485 communication interface at a fixed sampling frequency (e.g., once every 60 seconds) to read the current cumulative energy reading. The cumulative energy reading at the current sampling time (e.g., 100.5 kWh) is subtracted from the cumulative energy reading at the previous sampling time (e.g., 100.3 kWh). The calculation process is as follows: The resulting 0.2 kWh is the energy consumption difference within that 60-second sampling period. This operation is performed continuously, and each calculated energy consumption difference is stored in a data queue in chronological order, forming an energy increment sequence.

[0031] S402: Set the step spacing of the sliding window, perform sliding window grouping operation on the power increment sequence, and calculate the window arithmetic mean and window standard deviation of all power increments within each window. The sliding window's step size is set to 1, and the window width is set to 5. A data segment containing five consecutive energy increment values ​​is extracted from the energy increment sequence; for example, the extracted values ​​are [0.20, 0.21, 0.19, 0.20, 0.20]. First, the window's arithmetic mean is calculated. The calculation process is as follows: Next, the standard deviation of the window is calculated. First, the square of the difference between each value and the mean is calculated, then the sum is divided by 5, and finally the square root is taken to calculate the dispersion of the data in that window. After completing the calculation of the current window, the window moves forward by one step, and the same mean and standard deviation calculation is performed on the next group of 5 data, until the entire energy increment sequence is traversed, generating a series of corresponding window arithmetic means and window standard deviations.

[0032] S403: Call the rated operating power range in the load operating reference parameter set, preset the stability threshold, determine whether the window arithmetic mean is within the rated operating power range, and at the same time determine whether the window standard deviation is less than the stability threshold, filter the time period index that meets the judgment conditions, and obtain the steady-state operating time index set. To more accurately identify the steady-state operating range, a stability confidence score based on a weighted penalty mechanism can be calculated to perform steady-state evaluation on the data for each window. The median of the rated operating power range from the load operating reference parameter set is calculated as the ideal operating target value, and a stability judgment threshold is set. Stability confidence score. Calculated using the following formula: ,in, To prevent the denominator from being zero and to adjust the smoothing constant for sensitivity, it is set based on ten times the minimum allowable calculation error accuracy of the system, for example, set to... ; The window arithmetic mean calculated in step S402, for example kilowatt-hours; The center value of the rated energy increment range (e.g., the range is ). to kilowatt-hours, then the central value for (kilowatt-hours), this value is derived from the load operating reference parameter set; The window standard deviation calculated in step S402, for example kilowatt-hours; This is the mean deviation penalty weight, which is set based on the tolerance for the mean deviating from the nominal center value. The lower the tolerance, the greater the weight. For example, it can be set to... ; This is a volatility penalty weight, set based on the sensitivity to operational instability; the more stable the operation, the larger the value should be. For example, it can be set to... Substituting the above values ​​into the calculation: First, calculate the square of the mean deviation. After weighting, it becomes Next, calculate the variance. After weighting, it becomes The sum of the denominators is Finally, the confidence level was calculated. Calculated Compared with the preset stability judgment threshold (e.g.) A comparison is performed, and there are two possibilities: the first possibility is... At this point, it is determined that the current window data meets the steady-state requirements, and the intermediate time index corresponding to this window is added to the steady-state running time index set; the second possibility is... If the current window data does not meet the steady-state requirements, it will not be indexed or recorded. By using the dual constraints of sliding window statistics and stability confidence, the system can automatically filter steady-state data. It can automatically remove start-stop disturbances, fluctuating operating conditions, and abnormal peak intervals, and only retain steady-state time periods that meet the rated range and whose fluctuations are controlled for energy consumption assessment. This improves the reliability and repeatability of energy efficiency accounting under the "no flow meter" condition.

[0033] Please see Figure 6 Step S5 is as follows: S501: Based on the steady-state operating time index set, locate and extract the data items at the corresponding time points in the energy increment sequence, accumulate all energy increment data items, and calculate the total power consumption of the motor in the steady-state pumping power. Based on each index value recorded in the steady-state operating time index set, the corresponding energy increment data item is precisely located and extracted from the original energy increment sequence. An accumulator with a value of zero is initialized, and all extracted energy increment data items are accumulated one by one. For example, if the extracted data items are 0.2, 0.2, and 0.19, the accumulation process is as follows: After traversing all indices in the set and performing the summation, the final value obtained is the total power consumption of the submersible pump motor under all conditions determined to be stable operation. This value is recorded as the total steady-state pumping and irrigation energy.

[0034] S502: Call the energy consumption and water volume conversion coefficient in the load operation reference parameter set, calculate the product of the total steady-state pumping and irrigation power and the energy consumption and water volume conversion coefficient, and at the same time, count the total time span covered by the steady-state operation time index set, calculate the ratio of the total steady-state pumping and irrigation power to the total time span, and obtain the average operating power of the submersible pump motor. The energy consumption conversion factor (e.g., 3.5 cubic meters per kilowatt-hour) from the load operation baseline parameter set is invoked. The number of indices in the steady-state operation time index set is counted and multiplied by the time interval corresponding to the sampling frequency (e.g., 60 seconds, or 0.0166 hours) to obtain the total steady-state operation time span. Subsequently, the total steady-state pumping and irrigation power is divided by the total steady-state operation time span (in hours). For example, if the total steady-state pumping and irrigation power is 50 kilowatt-hours and the total time span is 5 hours, the calculation process is as follows: The obtained 10 kilowatts is the actual average operating power of the submersible pump motor under stable conditions. This flow meter-less design avoids the problems of traditional flow sensors being easily damaged and difficult to maintain in deep well high-pressure and silt-corrosion environments, reducing hardware costs while ensuring long-term monitoring stability.

[0035] S503: Perform range matching verification between the average operating power of the submersible pump motor and the rated operating power range in the load operating reference parameter set to determine whether the actual power deviates from the rated range of the rated operating power range, and obtain the energy consumption assessment result of groundwater pumping and irrigation. The process of performing interval matching verification between the average operating power of the submersible pump motor and the rated operating power range in the load operating reference parameter set to determine whether the actual power deviates from the rated range of the rated operating power range, and obtaining the groundwater pumping and irrigation energy consumption assessment result is as follows: Analyze the rated operating power range to determine the lower and upper power limit boundary values; When the average operating power of the submersible pump motor is less than the lower power limit, the equipment is determined to be in an inefficient underload state, and an underload operation assessment result is generated. When the average operating power of the submersible pump motor exceeds the upper limit of the power limit, the equipment is determined to be in an overload risk state, and an overload operation assessment result is generated. When the average operating power of the submersible pump motor is between the lower power limit and the upper power limit, the equipment is determined to be in a rated compliance state, and a steady-state operation assessment result is generated. The underload operation assessment results, overload operation assessment results, or steady-state operation assessment results are packaged and output as groundwater pumping and irrigation energy consumption assessment results. The rated operating power range from the load operation benchmark parameter set is parsed to obtain the lower power limit boundary value (e.g., 10 kW) and the upper power limit boundary value (e.g., 12 kW). The average operating power of the submersible pump motor is logically compared with these two boundary values. This comparison process includes three possible determinations: the first possibility is that the average operating power (e.g., 8 kW) is less than the lower power limit boundary value (10 kW), in which case the equipment is determined to be in an inefficient underload state, generating an underload operation assessment result; the second possibility is that the average operating power (e.g., 13 kW) is greater than the upper power limit boundary value (12 kW), in which case the equipment is determined to be in an overload risk state, generating an overload operation assessment result; the third possibility is that the average operating power (e.g., 11 kW) is greater than or equal to the lower power limit boundary value and less than or equal to the upper power limit boundary value, in which case the equipment is determined to be in a rated compliance state, generating a steady-state operation assessment result. Finally, the specific assessment results generated by the above logical determinations are packaged into a groundwater pumping and irrigation energy consumption assessment report output.

[0036] Please see Figure 7 An automatic assessment system for energy consumption of groundwater pumping and irrigation in foundation pit engineering, the system comprising: The startup current acquisition module acquires the real-time current of the submersible pump motor power supply line, locks the trigger time of the motor startup event, and constructs a startup process current time series dataset. The attenuation characteristic analysis module determines the peak holding interval of the current in the current time series data during the startup process, and calculates the duration of the first attenuation stage and the duration of the second attenuation stage based on the current changes between adjacent peak holding intervals. The load attribute determination module determines the load resistance attribute category corresponding to the current submersible pump motor based on the duration of the first attenuation stage and the duration of the second attenuation stage, and obtains the load operation reference parameter set. The steady-state operation identification module acquires the cumulative energy of the power metering instrument, constructs the power increment sequence, compares the power increment sequence with the load operation benchmark parameter set, and filters the steady-state operation time index set. The energy consumption assessment module extracts data items corresponding to the steady-state operating time index set from the incremental power sequence and accumulates them to obtain the total steady-state pumping and irrigation power. Combined with the load operation benchmark parameter set, it constructs the groundwater pumping and irrigation energy consumption assessment result.

[0037] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. An automatic assessment method for energy consumption of groundwater pumping and irrigation in foundation pit engineering, characterized in that, Includes the following steps: S1: Obtain the real-time current of the submersible pump motor power supply line, lock the motor start-up event trigger time, and construct the start-up process current time series dataset; S2: Determine the peak holding interval of the current holding maximum value in the current timing data of the startup process, and calculate the duration of the first decay stage and the duration of the second decay stage based on the current change between adjacent peak holding intervals. S3: Determine the load resistance attribute category corresponding to the current submersible pump motor based on the duration of the first attenuation stage and the duration of the second attenuation stage, and obtain the load operation reference parameter set; S4: Obtain the cumulative energy of the power metering instrument, construct the power increment sequence, compare the power increment sequence with the load operation reference parameter set, and filter the steady-state operation time index set; S5: Extract the data items corresponding to the steady-state operating time index set from the power increment sequence and accumulate them to obtain the total steady-state pumping power. Combine the data with the load operating benchmark parameter set to construct the groundwater pumping energy consumption assessment result.

2. The automatic assessment method for energy consumption of groundwater pumping and irrigation in foundation pit engineering according to claim 1, characterized in that: The startup process current time series dataset includes a real-time current sequence extracted based on the trigger time of the motor startup event. The duration of the first attenuation phase is specifically the time span during which the absolute value of the current change rate is greater than a preset attenuation rate threshold. The duration of the second attenuation phase is specifically the time span during which the absolute value of the current change rate is less than a preset attenuation rate threshold. The load operation reference parameter set includes energy consumption and water volume conversion coefficients and rated operating power range. The steady-state operating time index set is specifically an index of time periods where the average value is within the rated operating power range and the standard deviation is less than a stability threshold. The groundwater pumping and irrigation energy consumption assessment results include the total steady-state pumping and irrigation electrical energy, the total steady-state pumping and irrigation water volume, the average operating power of the submersible pump, and the compliance judgment results.

3. The automatic assessment method for energy consumption of groundwater pumping and irrigation in foundation pit engineering according to claim 1, characterized in that: Step S1 is as follows: S101: Continuously acquire the real-time current value in the power supply line of the submersible pump motor according to a preset time interval, compare the acquired real-time current with the preset silence threshold, and when the continuously acquired real-time current value exceeds the silence threshold, determine that the motor has entered the start-up state and record the current timestamp to obtain the motor start-up event trigger time. S102: Set the length of the extended time interception window, locate and extract data points in the continuously acquired real-time current data stream that are within the range from the trigger time of the motor start event to the end time of the time interception window, and generate the original start current data segment. S103: Arrange the current data in the original starting current data segment in chronological order, construct a two-dimensional data structure with time index and corresponding current, and interpolate and fill in the missing points to obtain the starting process current time series dataset.

4. The automatic assessment method for energy consumption of groundwater pumping and irrigation in foundation pit engineering according to claim 1, characterized in that: Step S2 is as follows: S201: Identify the maximum value of the current in the current timing data of the startup process, determine the start time point and end time point where the maximum current value remains unchanged or fluctuates within a preset error range, calculate the time span between the start time point and the end time point, and obtain the peak value holding interval. S202: Extract the current data segment located after the peak holding interval in the current time series dataset of the startup process, calculate the difference between two adjacent current sampling points in the current data segment and the corresponding time interval difference, and calculate the ratio of the difference to the time interval difference to obtain the current change rate sequence. S203: Traverse each current change rate in the current change rate sequence, compare the absolute value of the current change rate with a preset attenuation rate threshold, divide the current data area where the absolute value of the current change rate is greater than the attenuation rate threshold into the first stage, accumulate the time length covered by the first stage to obtain the duration of the first attenuation stage, divide the current data area where the absolute value of the current change rate is less than the attenuation rate threshold into the second stage, accumulate the time length covered by the second stage to obtain the duration of the second attenuation stage.

5. The automatic assessment method for energy consumption of groundwater pumping and irrigation in foundation pit engineering according to claim 1, characterized in that: Step S3 is as follows: S301: Compare the duration of the first attenuation phase with a preset first time limit reference value, and simultaneously compare the duration of the second attenuation phase with a preset second time limit reference value. Based on the two comparison results, determine the characteristics of the load resistance currently experienced by the motor and classify the load resistance attribute category. S302: Based on the load resistance attribute category, perform an index lookup in the preset parameter mapping table to locate the parameter item that has a unique mapping relationship with the load resistance attribute category, and extract the energy consumption water volume conversion coefficient corresponding to each kilowatt-hour of electrical energy consumed and the rated working power range of the motor during normal operation. S303: Associate the energy consumption and water consumption conversion coefficient with the rated operating power range to construct a parameter set with energy efficiency conversion standards and power operation specifications. Standardize the data format in the parameter set to obtain a load operation reference parameter set.

6. The automatic assessment method for energy consumption of groundwater pumping and irrigation in foundation pit engineering according to claim 5, characterized in that: Step S4 is as follows: S401: Access the register of the power meter at a fixed sampling frequency, obtain the cumulative power reading, calculate the power consumption difference between the cumulative power reading at the current sampling time and the cumulative power reading at the previous sampling time, and obtain the power increment sequence. S402: Set the step spacing of the sliding window, perform sliding window grouping operation on the power increment sequence, and calculate the window arithmetic mean and window standard deviation of all power increments within each window. S403: Call the rated operating power range in the load operating reference parameter set, preset the stability threshold, determine whether the window arithmetic mean is within the rated operating power range, and at the same time determine whether the window standard deviation is less than the stability threshold, filter the time period index that simultaneously meets the judgment conditions, and obtain the steady-state operating time index set.

7. The automatic assessment method for energy consumption of groundwater pumping and irrigation in foundation pit engineering according to claim 6, characterized in that: Step S5 is as follows: S501: Based on the steady-state operating time index set, locate and extract the data items at the corresponding time points in the energy increment sequence, accumulate all energy increment data items, and calculate the total power consumption of the motor in the steady-state pumping power. S502: Call the energy consumption and water volume conversion coefficient in the load operation reference parameter set, calculate the product of the total steady-state pumping and irrigation power and the energy consumption and water volume conversion coefficient, and at the same time, count the total time span covered by the steady-state operation time index set, calculate the ratio of the total steady-state pumping and irrigation power to the total time span, and obtain the average operating power of the submersible pump motor. S503: Perform interval matching verification between the average operating power of the submersible pump motor and the rated operating power range in the load operating reference parameter set, determine whether the actual power deviates from the rated range of the rated operating power range, and obtain the groundwater pumping and irrigation energy consumption assessment result.

8. The automatic assessment method for energy consumption of groundwater pumping and irrigation in foundation pit engineering according to claim 5, characterized in that: The process of determining the characteristics of the current load resistance on the motor and classifying the load resistance attribute category based on the logical combination result of the two comparison operations is as follows: The state in which the duration of the first decay phase is greater than the first time limit benchmark value and the duration of the second decay phase is less than the second time limit benchmark value is defined as the first judgment condition, and the state in which the duration of the first decay phase is less than the first time limit benchmark value and the duration of the second decay phase is greater than the second time limit benchmark value is defined as the second judgment condition. When the first determination condition is met, the characteristic of the load resistance currently experienced by the motor is determined to be viscous-dominant resistance characteristic, and the load resistance attribute category is marked as viscous-dominant load category. When the second determination condition is met, the characteristic of the load resistance currently experienced by the motor is determined to be an inertia-dominated resistance characteristic, and the load resistance attribute category is marked as an inertia-dominated load category.

9. The automatic assessment method for energy consumption of groundwater pumping and irrigation in foundation pit engineering according to claim 7, characterized in that: The process of performing interval matching verification between the average operating power of the submersible pump motor and the rated operating power range in the load operating reference parameter set to determine whether the actual power deviates from the rated range of the rated operating power range, and obtaining the groundwater pumping and irrigation energy consumption assessment result is as follows: Analyze the rated operating power range to determine the lower and upper power limit boundary values; When the average operating power of the submersible pump motor is less than the lower power limit, the equipment is determined to be in an inefficient underload state, and an underload operation assessment result is generated. When the average operating power of the submersible pump motor exceeds the upper limit of the power limit, the equipment is determined to be in an overload risk state, and an overload operation assessment result is generated. When the average operating power of the submersible pump motor is between the lower power limit and the upper power limit, the equipment is determined to be in a rated compliance state, and a steady-state operation assessment result is generated. The underload operation assessment results, overload operation assessment results, or steady-state operation assessment results are packaged and output as groundwater pumping and irrigation energy consumption assessment results.

10. An automatic assessment system for energy consumption of groundwater pumping and irrigation in foundation pit engineering, characterized in that, The method for automatically assessing the energy consumption of groundwater pumping and irrigation in foundation pit engineering according to any one of claims 1-9 is implemented, wherein the system comprises: The startup current acquisition module acquires the real-time current of the submersible pump motor power supply line, locks the trigger time of the motor startup event, and constructs a startup process current time series dataset. The attenuation characteristic analysis module determines the peak holding interval of the current in the current time series data of the startup process, and calculates the duration of the first attenuation stage and the duration of the second attenuation stage based on the current change between adjacent peak holding intervals. The load attribute determination module determines the load resistance attribute category corresponding to the current submersible pump motor based on the duration of the first attenuation stage and the duration of the second attenuation stage, and obtains the load operation reference parameter set. The steady-state operation identification module acquires the cumulative energy of the power metering instrument, constructs an energy increment sequence, compares the energy increment sequence with the load operation reference parameter set, and filters the steady-state operation time index set. The energy consumption assessment module extracts data items corresponding to the steady-state operating time index set from the incremental power sequence and accumulates them to obtain the total steady-state pumping and irrigation power. Combined with the load operation benchmark parameter set, it constructs the groundwater pumping and irrigation energy consumption assessment result.

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