Calibration method of metering equipment, metering equipment, electronic equipment and medium

Abstract

The invention provides a calibration method of metering equipment, the metering equipment, electronic equipment and a medium, and the method comprises the steps: a pre-calibration stage: testing in different simulation environments, and generating a parameter comparison table containing simulation environment parameters and corresponding simulation calibration parameters; in the field deployment stage, the field environment parameters of the metering equipment are detected through the environment detection module; on-site calibration parameters corresponding to the on-site environment parameters are determined by inquiring the parameter comparison table, and the actual weight value of the actual load is determined according to the actual dependent variable and the on-site calibration parameters. According to the method, a pre-calibration mode is adopted, tedious work of field calibration is avoided, and the working efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of safety monitoring of lifting equipment, and in particular to a calibration method of a measuring device, a measuring device, an electronic device and a medium. Background Art

[0002] A weight sensor is a sensor used to measure and monitor the weight of hoisted objects. It converts the gravity signal of the object into an electrical signal to achieve real-time detection and control of the hoisting weight. Weight sensors are widely used in lifting machinery, material conveying equipment, industrial automation and other fields, and are of great significance to ensure work safety and stability.

[0003] When the load cell is in use, the accuracy will be affected by factors such as the installation environment. In order to ensure accuracy, existing load cells need to be calibrated on site before use. On-site calibration consumes a lot of time and manpower, and has high technical requirements for operators. It is easy to cause calibration errors due to improper operation, which in turn affects production efficiency and product quality. Summary of the invention

[0004] In view of this, the purpose of the present application is to provide a calibration method for a measuring device, a measuring device, an electronic device and a medium to overcome the problems in the prior art.

[0005] In a first aspect, an embodiment of the present application provides a calibration method for a metering device, which acts on a metering device, wherein the metering device includes a strain sensor module, an environment detection module, and a processing module; the strain sensor module and the environment detection module are both connected to the processing module; the calibration method includes: a pre-calibration stage and an on-site deployment stage;

[0006] The pre-calibration stage: for different simulation environments, obtaining simulation environment parameters of each simulation environment through the environment detection module;

[0007] Performing a weight-lifting test on the metering device in the simulation environment, and recording the simulated strain amount of the metering device under different simulated loads in the simulation environment through the strain sensor module;

[0008] Determine the relationship model between the simulated load and the simulated strain in the simulation environment through the processing module; and generate a parameter comparison table according to the simulated load and the relationship model in each simulation environment; wherein the parameter comparison table includes the simulation environment parameters and the corresponding simulation calibration parameters;

[0009] In the on-site deployment stage: detecting the on-site environmental parameters of the metering equipment through the environmental detection module; and determining the on-site calibration parameters corresponding to the on-site environmental parameters by querying the parameter comparison table through the processing module;

[0010] The real strain amount when the real load is deployed on the measuring device is detected by the strain sensor module; the actual weight value of the real load is determined by the processing module according to the real strain amount and the on-site calibration parameters.

[0011] In some technical solutions of the present application, the above-mentioned simulated environmental parameters include: simulated temperature parameters, simulated inclination parameters and simulated vibration parameters; the simulated calibration parameters include basic gain coefficients and nonlinear error terms; the nonlinear error terms include temperature drift correction coefficients and vibration coupling factors;

[0012] Generate a parameter comparison table in the following ways:

[0013] Bringing the rated simulated load and the corresponding simulated strain into the relationship model to determine the basic gain coefficient;

[0014] Under the condition that the simulated inclination angle parameter and the simulated vibration parameter are fixed, fitting the simulated strain amount with the change of the simulated temperature parameter to determine the temperature drift correction coefficient;

[0015] Determining the vibration coupling factor according to the simulated strain amount when the same simulated load vibrates and the simulated strain amount in a static state;

[0016] Different temperature intervals are set according to the different accuracy of the data under different simulation environments;

[0017] The simulated temperature parameters are divided into different storage units according to the temperature intervals, and the corresponding simulated inclination parameters, simulated vibration parameters, basic gain coefficients, temperature drift correction coefficients and vibration coupling factors are filled in each of the storage units to obtain the parameter comparison table.

[0018] In some technical solutions of the present application, the above-mentioned querying the parameter comparison table by the processing module to determine the on-site calibration parameters corresponding to the on-site environmental parameters includes:

[0019] Comparing the on-site environmental parameters with the simulated environmental parameters in the parameter comparison table, and if the on-site environmental parameters are not completely the same as the simulated environmental parameters, determining a first calibration parameter and a second calibration parameter adjacent to the on-site calibration parameter from the parameter comparison table;

[0020] Obtaining a basic compensation parameter of the on-site environmental parameter by interpolating the first calibration parameter and the second calibration parameter;

[0021] Obtaining a dynamic compensation item of the on-site environmental parameter by predicting the on-site environmental parameter;

[0022] The basic compensation parameter and the dynamic compensation item are used as the on-site calibration parameters.

[0023] In some technical solutions of the present application, the above-mentioned measuring device further includes a calibration module;

[0024] The calibration method further includes, when the processing module determines that a preset calibration condition is met, calibrating the error through the calibration module to obtain a calibration result; and updating the parameter comparison table based on the calibration result;

[0025] The preset calibration condition includes at least one of the following: reaching a preset time interval, or the change of the on-site environmental parameter exceeds a preset environmental parameter threshold, or the actual strain exceeds a preset strain threshold;

[0026] When the actual strain exceeds a preset strain threshold, an alarm message is generated by the calibration module.

[0027] In some technical solutions of the present application, when the processing module determines that the preset time interval has been reached, the simulation calibration parameters are calibrated in the following manner:

[0028] The simulation calibration parameters include a basic gain coefficient, and the initial strain amount under the application of multiple preset groups of standard loads is obtained through the strain sensor module; wherein the weights of different groups of standard loads are different;

[0029] By performing error analysis on the initial strain amounts under the multiple groups of the standard loads, the analyzed test strain amounts are obtained;

[0030] The basic gain coefficient is updated according to the linearity error calculated according to the test strain amount.

[0031] In some technical solutions of the present application, the above-mentioned field environment parameters include field temperature parameters; when the processing module determines that the change of the field temperature parameters exceeds a preset temperature difference threshold, the simulation calibration parameters are calibrated in the following manner:

[0032] The analog calibration parameters include a temperature drift correction coefficient and a zero point compensation parameter; the strain sensor module is used to obtain the zero point offset of the metering device when it is unloaded, and the calibration module is used to calculate the zero point offset according to the sliding time window algorithm to generate the zero point compensation parameter;

[0033] Acquiring, by means of the strain sensor module, test strain amounts under different preset standard loads applied by the strain sensor module at various test temperatures;

[0034] The test strain variable is refitted along with the test temperature to obtain a new temperature drift correction coefficient.

[0035] In some technical solutions of the present application, the above-mentioned field environment parameters include field vibration parameters; when the processing module determines that the change of the field vibration parameters exceeds a preset vibration threshold, the simulation calibration parameters are calibrated in the following manner:

[0036] The simulation calibration parameters include the simulation vibration parameters, and under any simulation vibration parameter, a first test strain amount under a preset standard load and a second test strain amount under the standard load without vibration are obtained through the strain sensor module;

[0037] According to the first test strain amount and the second test strain amount, new simulated vibration parameters are determined.

[0038] In a second aspect, an embodiment of the present application provides a metering device, the metering device comprising a strain sensor module, an environment detection module and a processing module; the strain sensor module and the environment detection module are both connected to the processing module:

[0039] In the pre-calibration stage: the environment detection module is used to determine a plurality of different simulation environments of the metering device according to the historical detection environment of the metering device, and obtain the simulation environment parameters of each simulation environment;

[0040] Performing a weight lifting test on the metering device in the simulation environment, wherein the strain sensor module is used to record the simulated strain amount of the metering device under different simulated loads in the simulation environment;

[0041] The processing module is used to determine the relationship model between the simulated load and the simulated strain in the simulation environment; and generate a parameter comparison table according to the simulated load and the relationship model in each simulation environment; wherein the parameter comparison table includes the simulation environment parameters and the corresponding simulation calibration parameters;

[0042] In the on-site deployment stage: the environmental detection module is used to detect the on-site environmental parameters of the metering equipment; the processing module is used to query the parameter comparison table to determine the on-site calibration parameters corresponding to the on-site environmental parameters;

[0043] The strain sensor module is used to detect the real strain amount when the real load is deployed on the measuring device; the processing module is used to determine the actual weight value of the real load according to the real strain amount and the on-site calibration parameters.

[0044] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the calibration method of the above-mentioned measuring device when executing the computer program.

[0045] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the calibration method of the measuring device are executed.

[0046] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0047] The method of the present application includes the pre-calibration stage: for different simulation environments, the simulation environment parameters of each simulation environment are obtained through the environment detection module; the weight lifting test is performed on the metering equipment under the simulation environment, and the simulated strain amount of the metering equipment under different simulated loads in the simulation environment is recorded through the strain sensor module; the relationship model between the simulated load and the simulated strain amount in the simulation environment is determined through the processing module; and a parameter comparison table is generated according to the simulated load and the relationship model in each simulation environment; wherein the parameter comparison table includes the simulation environment parameters and the corresponding simulation calibration parameters;

[0048] During the on-site deployment phase: the on-site environmental parameters of the metering device are detected by the environmental detection module; the on-site calibration parameters corresponding to the on-site environmental parameters are determined by querying the parameter comparison table by the processing module; the real strain amount when the real load is deployed on the metering device is detected by the strain sensor module; the actual weight value of the real load is determined by the processing module based on the real strain amount and the on-site calibration parameters.

[0049] This application adopts a pre-calibration method, which avoids the tedious work of on-site calibration and improves work efficiency.

[0050] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0052] Figure 1 A schematic diagram of a flow chart of a calibration method for a measuring device provided in an embodiment of the present application is shown;

[0053] Figure 2 A schematic diagram of a metering device provided in an embodiment of the present application is shown;

[0054] Figure 3 A schematic diagram of a data query table provided in an embodiment of the present application is shown;

[0055] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of explanation and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn in real proportion. The flowchart used in this application shows the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowchart can be implemented out of sequence, and the steps without logical context can be reversed in order or implemented simultaneously. In addition, those skilled in the art can add one or more other operations to the flowchart under the guidance of the content of the present application, or remove one or more operations from the flowchart.

[0057] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0058] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0059] A weight sensor is a sensor used to measure and monitor the weight of hoisted objects. It converts the gravity signal of the object into an electrical signal to achieve real-time detection and control of the hoisting weight. Weight sensors are widely used in lifting machinery, material conveying equipment, industrial automation and other fields, and are of great significance to ensure work safety and stability.

[0060] When the load cell is in use, the accuracy will be affected by factors such as the installation environment. In order to ensure accuracy, existing load cells need to be calibrated on site before use. On-site calibration consumes a lot of time and manpower, and has high technical requirements for operators. It is easy to cause calibration errors due to improper operation, which in turn affects production efficiency and product quality.

[0061] Based on this, the embodiments of the present application provide a weight sensor, a method of use, an electronic device, and a storage medium, which use a pre-calibration method to avoid the tedious work of on-site calibration and improve work efficiency. The following is described by way of embodiments. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0062] Figure 1 A flow chart of a calibration method for a measuring device provided in an embodiment of the present application is shown, wherein the method comprises steps S101-S102; specifically: S101, a pre-calibration stage and S102, an on-site deployment stage;

[0063] The pre-calibration stage: for different simulation environments, obtaining simulation environment parameters of each simulation environment through the environment detection module;

[0064] Performing a weight-lifting test on the metering device in the simulation environment, and recording the simulated strain amount of the metering device under different simulated loads in the simulation environment through the strain sensor module;

[0065] Determine the relationship model between the simulated load and the simulated strain in the simulation environment through the processing module; and generate a parameter comparison table according to the simulated load and the relationship model in each simulation environment; wherein the parameter comparison table includes the simulation environment parameters and the corresponding simulation calibration parameters;

[0066] In the on-site deployment stage: detecting the on-site environmental parameters of the metering equipment through the environmental detection module; and determining the on-site calibration parameters corresponding to the on-site environmental parameters by querying the parameter comparison table through the processing module;

[0067] The real strain amount when the real load is deployed on the measuring device is detected by the strain sensor module; the actual weight value of the real load is determined by the processing module according to the real strain amount and the on-site calibration parameters.

[0068] This application adopts a pre-calibration method, which avoids the tedious work of on-site calibration and improves work efficiency.

[0069] like Figure 2As shown, an embodiment of the present application provides a metering device, where the computing device is a weight sensor, and the metering device includes a strain sensor module, an environmental detection module, and a processing module; the strain sensor module and the environmental detection module are both connected to the processing module. The strain sensor module, the environmental detection module, and the processing module in the embodiment of the present application all need to execute two stages: a pre-calibration stage and an on-site deployment stage. That is, the embodiment of the present application calibrates the parameters in the pre-calibration stage, and can directly match the calibrated parameters in the on-site deployment stage, and the appropriate parameters can be directly used, avoiding the cumbersome operation of on-site calibration.

[0070] Regarding the pre-calibration stage: In this stage, in order to obtain comprehensive (simulated) calibration parameters, the embodiments of the present application need to simulate different on-site deployment environments. For the sake of ease of description, the embodiments of the present application refer to the simulated environment as a simulation environment, the calibration parameters under the simulation environment as simulation calibration parameters, and the calibration parameters in the on-site deployment stage as on-site calibration parameters. In different simulation environments, the weight-lifting sensor is tested separately. During the test, the environmental detection module obtains the simulated environmental parameters of each simulated environment; the simulated strain amount of the measuring device under different simulated loads in the simulated environment is recorded by the strain sensor module.

[0071] The processing module obtains simulated environmental parameters from the environmental monitoring module, and obtains each simulated load and the simulated strain corresponding to the simulated load from the strain sensor module. The environmental detection module in the embodiment of the present application includes a temperature sensor, an inclination sensor, and a vibration sensor. Therefore, the simulated environmental parameters here include simulated temperature parameters, simulated inclination parameters, and simulated vibration parameters.

[0072] In the specific implementation, the strain sensor module can use a fiber Bragg grating (FBG) sensor, and the simulated strain is represented by Δλ. The measuring equipment is placed on a six-degree-of-freedom platform, and different temperatures are then cyclically applied at various angles (-40℃→25℃→80℃→25℃, with each step kept warm for 2 hours). The FBG sensor records the FBG wavelength offset Δλ at each temperature point. Under each temperature condition, apply 0% to 120% of the rated load (such as 0kg to 200kg). Record the load F and the corresponding Δλ. Adjust the platform inclination (0° to 30°) to simulate different installation postures. Apply 0 to 200Hz vibration, and record Δλ and the corresponding vibration energy E.

[0073] After the processing module obtains the above data, since there is a lot of data, in order to improve the matching efficiency in the field deployment stage, the embodiment of the present application adopts a method of generating a parameter comparison table. The processing module analyzes the above data to determine the relationship model between the simulated load and the simulated strain in each simulation environment. Then, according to the simulated load in each simulation environment and the relationship model, a parameter comparison table is generated; wherein, the parameter comparison table includes the simulation environment parameters and the corresponding simulation calibration parameters. The simulation calibration parameters include a basic gain coefficient and a nonlinear error term; the nonlinear error term includes a temperature drift correction coefficient and a vibration coupling factor.

[0074] The parameter comparison table is generated in the following manner: the rated simulated load and the corresponding simulated strain amount are brought into the relationship model to determine the basic gain coefficient; under the condition that the simulated inclination angle parameter and the simulated vibration parameter are fixed, the simulated strain amount is fitted with the change of the simulated temperature parameter to determine the temperature drift correction coefficient; according to the simulated strain amount when the same simulated load vibrates and the simulated strain amount under static state, the vibration coupling factor is determined; according to the different accuracy of the data under different simulation environments, different temperature intervals are set; according to the temperature intervals, the simulated temperature parameters are divided into different storage units, and the corresponding simulated inclination angle parameter, simulated vibration parameter, basic gain coefficient, temperature drift correction coefficient and vibration coupling factor are filled in each storage unit to obtain the parameter comparison table.

[0075] In the specific implementation, the simulated environment parameters in the embodiment of the present application include simulated temperature parameters, simulated inclination parameters and simulated vibration parameters, so the parameter comparison table here adopts a LUT (Look-Up Table) data table, which is a three-dimensional data table.

[0076] The specific process of generating the query table is as follows: after obtaining the simulated temperature parameter T, simulated inclination parameter θ and simulated vibration parameter E, for each (T, θ, E) combination, fit the relationship model between Δλ and load F:

[0077] Δλ=K base (T, θ, E)·F+∈(T, θ, E)

[0078] Where: K base : Basic gain coefficient (unit: nm / kg); ∈: Nonlinear error term (including temperature drift correction coefficient and vibration coupling factor, etc.).

[0079] Basic gain factor:

[0080]

[0081] Among them, F refis the rated load, for example 100kg, Δλ ref For example, when T = 80°C, θ = 15°, and E = 0.5g2 / Hz, the measured Δλ ref =0.8nm, then K base =0.8 / 100=0.008nm / kg.

[0082] Temperature drift correction coefficient: Under fixed θ and E, a second-order polynomial fit is performed on the change of Δλ with temperature:

[0083] Δλ(T)=α0+α1T+α2T 2

[0084] Example: At θ = 0°, E = 0.1g 2 / Hz, it was measured that: T = 25℃ → Δλ = 0.5nm, T = 50℃ → Δλ = 0.52nm, T = 75℃ → Δλ = 0.55nm, and the fitting results were: α0 = 0.48; α1 = 0.0015, α2 = 0.00002.

[0085] Vibration coupling factor: Calculate the additional influence factor of vibration energy E on Δλ:

[0086]

[0087] Δλ vib is the simulated strain when simulating load vibration, Δλ static is the simulated strain under static state of the simulated load.

[0088] Example: When static (E = 0), Δλ = 0.5nm, when vibrating (E = 0.5g 2 / Hz), Δλ=0.53nm→β=0.53 / 0.5=1.06.

[0089] After obtaining the above data, in order to ensure the accuracy of the generated parameter comparison table. The embodiment of the present application needs to clean the above data and remove abnormal points. Specifically, different elimination rules can be set according to business needs, and then the above data can be processed based on the elimination rules. For example, data jumps caused by the loss of control of the vibration table can be eliminated.

[0090] After obtaining accurate data, the above data needs to be filled into the preset parameter comparison table. In order to facilitate query, the parameter comparison table here is divided into different storage units according to user needs. The storage units here are distinguished based on the simulation temperature parameters, such as Figure 2As shown. When dividing the storage units, they can be divided equally according to the preset temperature intervals. The temperature interval here is determined based on the accuracy of the data in the simulation environment. When the accuracy is high, a smaller temperature interval needs to be set; when the accuracy is low, a larger temperature interval can be set. For example: the storage units here are divided into: the first storage unit: -40℃~0℃ (5 temperature nodes); the second storage unit: 0℃~40℃ (4 temperature nodes); the third storage unit: 40℃~80℃ (4 temperature nodes); the fourth storage unit: 80℃~120℃ (5 temperature nodes). Each storage unit contains a temperature node, and the temperature node here is a simulated temperature parameter that has been simulated and tested. For example, 0℃~40℃ contains four temperature nodes of 10℃, 20℃, 30℃ and 35℃, which indicates that the simulation test of 10℃, 20℃, 30℃ and 35℃ is carried out, and the temperature of 11℃, 15℃ and so on is not simulated. After determining each storage unit, fill in the corresponding parameters.

[0091] Through the above process, the load sensor is pre-calibrated. After the pre-calibration, it does not need to be calibrated again during the on-site deployment phase and can be used directly, avoiding tedious operations.

[0092] Regarding the on-site deployment stage: the embodiment of the present application first detects the on-site environmental parameters of the lifting weight sensor through the environmental detection module, and then uses the on-site environmental parameters to query the on-site calibration parameters corresponding to the on-site environmental parameters in the parameter comparison table.

[0093] When querying the parameter comparison table, since the data parameter comparison table is stored in blocks according to the simulated temperature parameters, it is necessary to first compare the on-site temperature parameters with the simulated temperature parameters to determine the corresponding target storage unit. After determining the target storage unit, the on-site inclination parameters and on-site vibration parameters are compared with the simulated inclination parameters and simulated vibration parameters in the target storage unit to determine the corresponding on-site calibration parameters.

[0094] When comparing the on-site temperature parameters with the simulated temperature parameters, the following situations exist: In the first case, the on-site environmental parameters are the same as the simulated environmental parameters. In this case, the corresponding on-site calibration parameters (including basic gain coefficient, temperature drift correction coefficient and vibration coupling factor) can be directly found in the parameter comparison table and used directly. In the second case, the on-site environmental parameters are not exactly the same as the simulated environmental parameters. In this case, the on-site calibration parameters need to be calculated by interpolation.

[0095] For example, the current T = 30°C, matching the adjacent temperature nodes in the LUT (T1 = 25°C, T2 = 40°C), the current θ = 12.2°, matching the LUT θ1 = 10°, θ2 = 15°. The current E = 0.4g 2 / Hz matching LUT E1 = 0.3g 2 / Hz,E2=0.5g 2 / Hz. It is calculated by the following three-dimensional linear interpolation method:

[0096]

[0097] ω ijk Represents the weight, which is determined based on the distance to the adjacent nodes:

[0098]

[0099] If the adjacent node parameters are:

[0100] K1_base(T1=25℃, θ1=10°, E1=0.3)=0.0075;

[0101] K2_base(T2=40℃, θ2=15°, E2=0.5)=0.0082;

[0102] Interpolation gives K_base = 0.0078nm / kg. Similarly, we can get α0 = 0.47, α1 = 0.0016, α2 = 0.000018, β = 1.05.

[0103] In order to further improve the accuracy of the data, when determining the on-site temperature drift correction coefficient and vibration coupling factor, the embodiment of the present application compensates the basic gain coefficient obtained from the query of the parameter comparison table to obtain the compensated basic gain coefficient. Specifically, the basic gain coefficient, temperature drift correction coefficient and vibration coupling factor are obtained from the parameter comparison table in the above manner. The queried basic gain coefficient, temperature drift correction coefficient and vibration coupling factor are input into the LSTM network model to obtain the dynamic compensation term of the queried basic gain coefficient. The actual weight value of the real load is calculated based on the queried basic gain coefficient and the dynamic compensation term of the basic gain coefficient in the following manner:

[0104]

[0105] Where Δλ_temp: temperature drift correction coefficient (Δλ_temp=α0+α1T+α2T 2 interpolated from LUT); β(E): vibration coupling factor (interpolated from LUT); E_fiber: fiber elastic coefficient; A: effective cross-sectional area of ​​fiber.

[0106] In an optional embodiment, the measuring device in the embodiment of the present application further includes a calibration module, and the specific calibration module includes an electromagnetic force generator, a lever amplification mechanism and a laser interferometer. In order to ensure the accuracy of the data, the above method also includes calibration through the calibration module. The calibration content of the calibration module includes zero drift error, linearity error and environmental coupling error.

[0107] Zero drift error: The error of the sensor's output value (Δλ) deviating from the theoretical zero point when there is no load.

[0108] Calibration method: The electromagnetic force generator applies a load of 0kg (ie, zero-position calibration); the current Δλ value is recorded (eg, Δλ=0.02nm); if Δλ exceeds a threshold value (eg, ±0.01nm), the zero-point offset is corrected.

[0109] The zero point compensation parameter is calculated by a sliding time window algorithm. For example, when the time window length is 60 seconds, the calculation formula is:

[0110]

[0111] Among them, yt is the instantaneous offset and μt is the temperature drift.

[0112] Example: Before calibration: Δλ=0.02nm (zero point drift +0.02nm); After calibration: Δλ=0.00nm (zero point correction completed).

[0113] Linearity Error: The nonlinear relationship between the sensor output and the input load.

[0114] Calibration method: Apply multiple standard loads (such as 50kg, 100kg, 200kg); record the Δλ value under each load;

[0115] Calculate the linearity error:

[0116]

[0117] If the error is greater than 0.5%, an alarm is triggered and the compensation parameters are updated.

[0118] Example: Under a load of 200 kg, the measured Δλ=0.82 nm, the theoretical value=0.80 nm, and the error is 2.5%; the basic gain coefficient K_base is updated (eg, adjusted from 0.008 nm / kg to 0.0082 nm / kg).

[0119] Environmental coupling error: the additional impact of environmental factors such as temperature and vibration on sensor output.

[0120] Calibration method: read the real-time data (T, θ, a) of the environmental module; extract the temperature drift coefficient α (T) and vibration coupling factor β (E) according to the multidimensional parameter table (LUT);

[0121] Dynamic correction Δλ value:

[0122]

[0123] Example: When T = 40°C, temperature drift causes Δλ to increase by 0.02nm. After correction, Δλ = 0.80nm.

[0124] The error is calibrated by the calibration module to obtain a calibration result, and the parameter comparison table is updated based on the calibration result. The update of the parameter comparison table specifically includes adding a zero compensation parameter, replacing a basic gain coefficient, replacing a temperature drift correction coefficient, and replacing a vibration coupling factor.

[0125] Basic gain coefficient (K_base) definition: wavelength shift caused by unit load (unit: nm / kg). Update logic:

[0126] Adjust K_base according to the linearity error calibration result;

[0127] formula:

[0128]

[0129] Example: Under 200kg load, Δλ correction = 0.80nm → K_base = 0.004nm / kg.

[0130] Temperature drift correction coefficient (α(T)): describes the effect of temperature change on wavelength shift. Update logic: calibrate Δλ at multiple temperature points (such as 25℃, 50℃, 75℃), and fit a second-order polynomial:

[0131] Δλ(T)=α0+α1T+α2T 2

[0132] Update the α0, α1, α2 fields in the LUT.

[0133] Example: Fitting results: α0=0.48, α1=0.0015, α2=0.00002.

[0134] Vibration coupling factor (β(E)): The ratio of vibration energy to wavelength shift. Update logic: Under different vibration energies (such as 0.1g 2 / Hz, 0.5g 2 / Hz, 1.0g 2 / Hz) calibration Δλ;

[0135] Calculate β(E):

[0136]

[0137] Update the β(E) field in the LUT.

[0138] Example: E = 0.5 g 2 / Hz, β=1.06.

[0139] When calibrating through the calibration module, it is necessary to determine through the processing module whether the preset calibration conditions are met. Only when the preset calibration conditions are met, the analog calibration parameters are calibrated through the calibration module. The preset calibration conditions include at least one of the following: reaching a preset time interval, or the on-site environmental parameter change exceeds a preset environmental parameter threshold, or the real strain exceeds a preset strain threshold. Different scenarios meet different calibration conditions, and different calibration conditions correspond to different calibration contents and updated analog calibration parameters. For example, when the preset time interval is reached, the basic gain coefficient is updated. When the on-site temperature parameter changes exceed the preset temperature difference threshold, the temperature drift correction coefficient is updated. When the on-site vibration parameter changes exceed the preset vibration threshold, the simulated vibration parameter is updated.

[0140] For example, port cranes (temperature + vibration coupling)

[0141] Scenario: T = 40℃ suddenly drops to -10℃ (cold wave), and at the same time, the sea waves cause E = 1.5g 2 / Hz vibration.

[0142] System response: The sudden temperature change triggers the zero point calibration, correcting Δλ0=0.02nm→0.00nm; the vibration out-of-limit update β(E)=1.12, and activates the 50Hz / 100Hz dual notch filter; after compensation, the error is reduced from ±2.1% to ±0.3%.

[0143] Mine hoist (mechanical fatigue)

[0144] Scenario: After 6 months of continuous operation, the bolt preload decreases, causing θ to shift by 5°. System response: Regular calibration detects a linearity error of 1.2%, and updates K_base = 0.008 → 0.0083nm / kg; the laser interferometer finds δ = 0.15mm, triggering the ERR-05 alarm; after the maintenance personnel tighten the bolts, the confidence of the θ compensation parameter is restored.

[0145] Figure 3 A measuring device provided in an embodiment of the present application is shown, the measuring device comprising a strain sensor module, an environment detection module and a processing module; the strain sensor module and the environment detection module are both connected to the processing module:

[0146] In the pre-calibration stage: the environment detection module is used to determine a plurality of different simulation environments of the metering device according to the historical detection environment of the metering device, and obtain the simulation environment parameters of each simulation environment;

[0147] Performing a weight lifting test on the metering device in the simulation environment, wherein the strain sensor module is used to record the simulated strain amount of the metering device under different simulated loads in the simulation environment;

[0148] The processing module is used to determine the relationship model between the simulated load and the simulated strain in the simulation environment; and generate a parameter comparison table according to the simulated load and the relationship model in each simulation environment; wherein the parameter comparison table includes the simulation environment parameters and the corresponding simulation calibration parameters;

[0149] In the on-site deployment stage: the environmental detection module is used to detect the on-site environmental parameters of the metering equipment; the processing module is used to query the parameter comparison table to determine the on-site calibration parameters corresponding to the on-site environmental parameters;

[0150] The strain sensor module is used to detect the real strain amount when the real load is deployed on the measuring device; the processing module is used to determine the actual weight value of the real load according to the real strain amount and the on-site calibration parameters.

[0151] The simulated environment parameters include: simulated temperature parameters, simulated inclination parameters and simulated vibration parameters; the simulated calibration parameters include basic gain coefficients and nonlinear error terms; the nonlinear error terms include temperature drift correction coefficients and vibration coupling factors;

[0152] Generate a parameter comparison table in the following ways:

[0153] Bringing the rated simulated load and the corresponding simulated strain into the relationship model to determine the basic gain coefficient;

[0154] Under the condition that the simulated inclination angle parameter and the simulated vibration parameter are fixed, fitting the simulated strain amount with the change of the simulated temperature parameter to determine the temperature drift correction coefficient;

[0155] Determining the vibration coupling factor according to the simulated strain amount when the same simulated load vibrates and the simulated strain amount in a static state;

[0156] Different temperature intervals are set according to the different accuracy of the data under different simulation environments;

[0157] The simulated temperature parameters are divided into different storage units according to the temperature intervals, and the corresponding simulated inclination parameters, simulated vibration parameters, basic gain coefficients, temperature drift correction coefficients and vibration coupling factors are filled in each of the storage units to obtain the parameter comparison table.

[0158] The step of querying the parameter comparison table by the processing module to determine the on-site calibration parameters corresponding to the on-site environmental parameters includes:

[0159] Comparing the on-site environmental parameters with the simulated environmental parameters in the parameter comparison table, and if the on-site environmental parameters are not completely the same as the simulated environmental parameters, determining a first calibration parameter and a second calibration parameter adjacent to the on-site calibration parameter from the parameter comparison table;

[0160] Obtaining a basic compensation parameter of the on-site environmental parameter by interpolating the first calibration parameter and the second calibration parameter;

[0161] Obtaining a dynamic compensation item of the on-site environmental parameter by predicting the on-site environmental parameter;

[0162] The basic compensation parameter and the dynamic compensation item are used as the on-site calibration parameters.

[0163] The metrology device also includes a calibration module;

[0164] The calibration method further includes, when the processing module determines that a preset calibration condition is met, calibrating the error through the calibration module to obtain a calibration result; and updating the parameter comparison table based on the calibration result;

[0165] The preset calibration condition includes at least one of the following: reaching a preset time interval, or the change of the on-site environmental parameter exceeds a preset environmental parameter threshold, or the actual strain exceeds a preset strain threshold;

[0166] When the actual strain exceeds a preset strain threshold, an alarm message is generated by the calibration module.

[0167] When the processing module determines that the preset time interval has been reached, the simulation calibration parameters are calibrated in the following manner:

[0168] The simulation calibration parameters include a basic gain coefficient, and the initial strain amount under the application of multiple preset groups of standard loads is obtained through the strain sensor module; wherein the weights of different groups of standard loads are different;

[0169] By performing error analysis on the initial strain amounts under the multiple groups of the standard loads, the analyzed test strain amounts are obtained;

[0170] The basic gain coefficient is updated according to the linearity error calculated according to the test strain amount.

[0171] The field environment parameters include field temperature parameters; when the processing module determines that the field temperature parameter changes beyond a preset temperature difference threshold, the simulation calibration parameters are calibrated in the following manner:

[0172] The analog calibration parameters include a temperature drift correction coefficient and a zero point compensation parameter; the strain sensor module is used to obtain the zero point offset of the metering device when it is unloaded, and the calibration module is used to calculate the zero point offset according to the sliding time window algorithm to generate the zero point compensation parameter;

[0173] Acquiring, by means of the strain sensor module, test strain amounts under different preset standard loads applied by the strain sensor module at various test temperatures;

[0174] The test strain variable is refitted along with the test temperature to obtain a new temperature drift correction coefficient.

[0175] The field environment parameters include field vibration parameters; when the processing module determines that the field vibration parameter changes beyond a preset vibration threshold, the simulation calibration parameters are calibrated in the following manner:

[0176] The simulation calibration parameters include the simulation vibration parameters, and under any simulation vibration parameter, a first test strain amount under a preset standard load and a second test strain amount under the standard load without vibration are obtained through the strain sensor module;

[0177] According to the first test strain amount and the second test strain amount, new simulated vibration parameters are determined.

[0178] like Figure 4 As shown, an embodiment of the present application provides an electronic device for executing the calibration method of the measuring device in the present application, the device includes a memory, a processor, a bus, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the calibration method of the measuring device when executing the computer program.

[0179] Specifically, the above-mentioned memory and processor may be general-purpose memory and processor, which are not specifically limited here. When the processor runs the computer program stored in the memory, the above-mentioned calibration method of the measuring device can be executed.

[0180] Corresponding to the calibration method of the measuring device in the present application, an embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the calibration method of the measuring device are executed.

[0181] Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, etc. When the computer program on the storage medium is run, the calibration method of the measuring device described above can be executed.

[0182] In the embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. The system embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0183] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0184] In addition, each functional unit in the embodiments provided in the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0185] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0186] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description and are not to be understood as indicating or implying relative importance.

[0187] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application. They should all be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A calibration method for a measuring device, characterized in that: Acting on a metering device, the metering device includes a strain sensor module, an environment detection module and a processing module; the strain sensor module and the environment detection module are both connected to the processing module; the calibration method includes: a pre-calibration stage and an on-site deployment stage; The pre-calibration stage: for different simulation environments, obtaining simulation environment parameters of each simulation environment through the environment detection module; Performing a weight-lifting test on the metering device in the simulation environment, and recording the simulated strain amount of the metering device under different simulated loads in the simulation environment through the strain sensor module; Determine the relationship model between the simulated load and the simulated strain in the simulation environment through the processing module; and generate a parameter comparison table according to the simulated load and the relationship model in each simulation environment; wherein the parameter comparison table includes the simulation environment parameters and the corresponding simulation calibration parameters; In the on-site deployment stage: detecting the on-site environmental parameters of the metering equipment through the environmental detection module; and determining the on-site calibration parameters corresponding to the on-site environmental parameters by querying the parameter comparison table through the processing module; The real strain amount when the real load is deployed on the measuring device is detected by the strain sensor module; the actual weight value of the real load is determined by the processing module according to the real strain amount and the on-site calibration parameters.

2. The method according to claim 1, characterized in that The simulated environment parameters include: simulated temperature parameters, simulated inclination parameters and simulated vibration parameters; the simulated calibration parameters include basic gain coefficients and nonlinear error terms; the nonlinear error terms include temperature drift correction coefficients and vibration coupling factors; Generate a parameter comparison table in the following ways: Bringing the rated simulated load and the corresponding simulated strain into the relationship model to determine the basic gain coefficient; Under the condition that the simulated inclination angle parameter and the simulated vibration parameter are fixed, fitting the simulated strain amount with the change of the simulated temperature parameter to determine the temperature drift correction coefficient; According to the simulated strain amount when the same simulated load is vibrating and the simulated strain amount in a static state; Different temperature intervals are set according to the different accuracy of the data under different simulation environments; The simulated temperature parameters are divided into different storage units according to the temperature intervals, and the corresponding simulated inclination parameters, simulated vibration parameters, basic gain coefficients, temperature drift correction coefficients and vibration coupling factors are filled in each of the storage units to obtain the parameter comparison table.

3. The method according to claim 1, characterized in that The step of querying the parameter comparison table by the processing module to determine the on-site calibration parameters corresponding to the on-site environmental parameters includes: Comparing the on-site environmental parameters with the simulated environmental parameters in the parameter comparison table, and if the on-site environmental parameters are not completely the same as the simulated environmental parameters, determining a first calibration parameter and a second calibration parameter adjacent to the on-site calibration parameter from the parameter comparison table; Obtaining a basic compensation parameter of the on-site environmental parameter by interpolating the first calibration parameter and the second calibration parameter; Obtaining a dynamic compensation item of the on-site environmental parameter by predicting the on-site environmental parameter; The basic compensation parameter and the dynamic compensation item are used as the on-site calibration parameters.

4. The method according to claim 1, characterized in that The metrology device also includes a calibration module; The calibration method further includes, when the processing module determines that a preset calibration condition is met, calibrating the error through the calibration module to obtain a calibration result; and updating the parameter comparison table based on the calibration result; The preset calibration condition includes at least one of the following: reaching a preset time interval, or the change of the on-site environmental parameter exceeds a preset environmental parameter threshold, or the actual strain exceeds a preset strain threshold; When the actual strain exceeds a preset strain threshold, an alarm message is generated by the calibration module.

5. The method according to claim 4, characterized in that When the processing module determines that the preset time interval has been reached, the simulation calibration parameters are calibrated in the following manner: The simulation calibration parameters include a basic gain coefficient, and the initial strain amount under the application of multiple preset groups of standard loads is obtained through the strain sensor module; wherein the weights of different groups of standard loads are different; By performing error analysis on the initial strain amounts under the multiple groups of the standard loads, the analyzed test strain amounts are obtained; The basic gain coefficient is updated according to the linearity error calculated according to the test strain amount.

6. The method according to claim 4, characterized in that The field environment parameters include field temperature parameters; when the processing module determines that the field temperature parameter changes beyond a preset temperature difference threshold, the simulation calibration parameters are calibrated in the following manner: The analog calibration parameters include a temperature drift correction coefficient and a zero point compensation parameter; the strain sensor module is used to obtain the zero point offset of the metering device when it is unloaded, and the calibration module is used to calculate the zero point offset according to the sliding time window algorithm to generate the zero point compensation parameter; Acquiring, by means of the strain sensor module, test strain amounts under different preset standard loads applied by the strain sensor module at various test temperatures; The test strain variable is refitted along with the test temperature to obtain a new temperature drift correction coefficient.

7. The method according to claim 4, characterized in that The field environment parameters include field vibration parameters; when the processing module determines that the field vibration parameter changes beyond a preset vibration threshold, the simulation calibration parameters are calibrated in the following manner: The simulation calibration parameters include simulation vibration parameters. Under any simulation vibration parameter, a first test strain amount under a preset standard load and a second test strain amount under the standard load without vibration are obtained through the strain sensor module; According to the first test strain amount and the second test strain amount, new simulated vibration parameters are determined.

8. A measuring device, characterized in that: The metering device includes a strain sensor module, an environment detection module and a processing module; the strain sensor module and the environment detection module are both connected to the processing module: Pre-calibration stage: the environment detection module is used to determine a plurality of different simulation environments of the metering device according to the historical detection environment of the metering device, and obtain the simulation environment parameters of each simulation environment; The measuring device is subjected to a weight lifting test in the simulation environment, and the strain sensor module is used to record the simulated strain amount of the measuring device under different simulated loads in the simulation environment; The processing module is used to determine the relationship model between the simulated load and the simulated strain in the simulation environment; and generate a parameter comparison table according to the simulated load and the relationship model in each simulation environment; wherein the parameter comparison table includes the simulation environment parameters and the corresponding simulation calibration parameters; On-site deployment stage: the environmental detection module is used to detect the on-site environmental parameters of the metering equipment; the processing module is used to query the parameter comparison table to determine the on-site calibration parameters corresponding to the on-site environmental parameters; The strain sensor module is used to detect the real strain amount when the real load is deployed on the measuring device; the processing module is used to determine the actual weight value of the real load according to the real strain amount and the on-site calibration parameters.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of the calibration method of the measuring device as described in any one of claims 1 to 7 are performed.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the calibration method of the measuring device as claimed in any one of claims 1 to 7 are executed.

Images