A weighing detection method, device, system, apparatus and storage medium

Abstract

The embodiment of the application discloses a kind of weighing detection method, device, system, equipment and storage medium.The technical scheme provided in the embodiment of the application obtains the first weighing data detected by a plurality of weighing sensors and the inertial measurement data detected by inertial sensor, calculates the second weighing data in the direction of resultant force according to each first weighing data, and determines the target vibration frequency according to the inertial measurement data, obtains the third weighing data after the first filtering processing to the second weighing data, and determines the second filtering mode according to the fluctuation degree of the third weighing data and the target vibration frequency, and obtains the target weighing data according to the second filtering mode to the third weighing data, effectively reduces the influence of vibration on weighing detection, improves the adaptability and weighing detection accuracy of weighing detection system.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the technical field of computer, and in particular, to a weighing detection method, device, system, equipment and storage medium. BACKGROUND

[0002] When the unmanned equipment loads materials to perform work, the weight of the materials loaded by the unmanned aerial vehicle needs to be fed back in real time to ensure the work efficiency of the unmanned equipment.

[0003] At present, the weighing detection method of the common weighing detection system of the unmanned equipment generally collects the weighing data detected by the weighing sensor, and directly outputs the weighing result after simple filtering of the weighing data. When the unmanned equipment loads materials to perform work, the weighing detection system thereof is easily affected by environmental factors and other factors. For example, when the unmanned equipment performs flight work, the vibration generated by flight easily affects the measurement accuracy of the weighing detection system, and the weighing detection accuracy is low. SUMMARY

[0004] Embodiments of the present application provide a weighing detection method, device, system, equipment and storage medium to solve the problem that the weighing detection system in the related art is easily affected by the environment, resulting in low weighing detection accuracy, and effectively improve the weighing detection accuracy of the weighing detection system.

[0005] In a first aspect, embodiments of the present application provide a weighing detection method applied to a weighing detection system, wherein the weighing detection system is provided with an inertial sensor and a plurality of weighing sensors, and the weighing detection method comprises:

[0006] obtaining first weighing data detected by the plurality of weighing sensors and inertial measurement data detected by the inertial sensor;

[0007] calculating second weighing data in the direction of the resultant force of each weighing sensor based on the first weighing data, and determining a target vibration frequency in each axial direction based on the axial vibration frequency of the inertial measurement data;

[0008] performing first filtering processing on the second weighing data to obtain third weighing data;

[0009] determining a second filtering mode of the third weighing data based on the fluctuation degree of the third weighing data and the target vibration frequency, and performing second filtering processing on the third weighing data according to the second filtering mode to obtain target weighing data.

[0010] In a second aspect, embodiments of the present application provide a weighing detection device applied to a weighing detection system, the weighing detection system being provided with an inertial sensor and a plurality of weighing sensors, the weighing detection device comprising a data acquisition module, a data processing module, a first filtering module and a second filtering module, wherein:

[0011] The data acquisition module is configured to acquire first weighing data detected by the plurality of weighing sensors and inertial measurement data detected by the inertial sensor.

[0012] The data processing module is configured to calculate second weighing data of each of the weighing sensors in a direction of resultant force based on the first weighing data, and determine a target vibration frequency based on an axial vibration frequency of each axis of the inertial measurement data.

[0013] The first filtering module is configured to perform first filtering processing on the second weighing data to obtain third weighing data.

[0014] The second filtering module is configured to determine a second filtering manner of the third weighing data based on a fluctuation degree of the third weighing data and the target vibration frequency, and perform second filtering processing on the third weighing data according to the second filtering manner to obtain target weighing data.

[0015] In a third aspect, embodiments of the present application provide a weighing detection system comprising a processing unit, an inertial sensor and a plurality of weighing sensors.

[0016] The plurality of weighing sensors are configured to be installed on a material box of a working device to detect first weighing data of the material box, the inertial sensor is configured to be installed on the working device to detect inertial measurement data of the working device, and the processing unit is in communication connection with the inertial sensor and the plurality of weighing sensors.

[0017] The processing unit is configured to perform the weighing detection method of the first aspect.

[0018] In a fourth aspect, embodiments of the present application provide a working device comprising the weighing detection system of the third aspect.

[0019] In a fifth aspect, embodiments of the present application provide a weighing detection device comprising a memory and one or more processors.

[0020] The memory is configured to store one or more programs.

[0021] When the one or more programs are executed by the one or more processors, the one or more processors implement the weighing detection method of the first aspect.

[0022] In a sixth aspect, the embodiments of the present application provide a storage medium storing computer executable instructions, which when executed by a computer processor, are used to perform the weighing detection method as described in the first aspect.

[0023] The embodiments of the present application obtain the first weighing data detected by the plurality of weighing sensors and the inertial measurement data detected by the inertial sensor, calculate the second weighing data in the direction of the resultant force according to the respective first weighing data, determine the target vibration frequency according to the inertial measurement data, perform the first filtering processing on the second weighing data to obtain the third weighing data, determine the second filtering mode according to the fluctuation degree of the third weighing data and the target vibration frequency, and perform the second filtering processing on the third weighing data according to the second filtering mode to obtain the target weighing data. The third weighing data obtained by the first filtering processing on the second weighing data according to the target vibration frequency corresponding to the inertial measurement data is subjected to the second filtering processing, which effectively reduces the influence of vibration on the weighing detection and improves the adaptability and weighing detection accuracy of the weighing detection system. BRIEF DESCRIPTION OF DRAWINGS

[0024] Figure 1 is a flowchart of a weighing detection method provided by the embodiments of the present application;

[0025] Figure 2 is a structural schematic diagram of a weighing detection system provided by the embodiments of the present application;

[0026] Figure 3 is a flowchart of another weighing detection method provided by the embodiments of the present application;

[0027] Figure 4 is a flowchart of a determination of an axial vibration frequency provided by the embodiments of the present application;

[0028] Figure 5 is a structural schematic diagram of a weighing detection device provided by the embodiments of the present application;

[0029] Figure 6 is a structural schematic diagram of a weighing detection device provided by the embodiments of the present application. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solutions and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. It should also be noted that, for ease of description, only some, but not all, of the contents related to the present application are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow charts describe each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of the operations can be rearranged. The above process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The above process can correspond to a method, function, procedure, subroutine, subprogram, etc.

[0031] Figure 1 A flowchart of a weighing detection method provided in an embodiment of the present application is given. The weighing detection method provided in an embodiment of the present application can be applied to a weighing detection system, and the weighing detection method provided in an embodiment of the present application can be executed by a weighing detection device, which can be implemented by hardware and / or software and integrated into a weighing detection device.

[0032] The following description is based on the weighing detection method performed by the weighing detection device. Figure 1 , the weighing detection method includes:

[0033] S101: Acquire first weighing data detected by a plurality of weighing sensors and inertial measurement data detected by an inertial sensor.

[0034] Figure 2 This is a structural diagram of a weighing detection system provided in an embodiment of the present application. Figure 2As shown, the weighing detection system provided by the scheme is provided with an inertial sensor 21 (IMU, Inertial Measurement Unit) and a plurality of weighing sensors 22. The weighing detection system further comprises a processing unit 23 and a material box 24 for loading materials. The plurality of weighing sensors 22 are installed on the material box 24, and the processing unit 23 is in communication connection with the inertial sensor 21 and the plurality of weighing sensors 22. The weighing sensor 22 can measure the weight of the material box 24 and the materials loaded in the material box 24 and output corresponding first weighing data. The resultant force of the first weighing data detected by each weighing sensor 22 is the second weighing data corresponding to the material box 24 and the materials loaded in the material box 24. Optionally, the plurality of weighing sensors 22 can be uniformly distributed on the material box 24 and arranged on a horizontal plane, so that the pressure centers of the plurality of weighing sensors 22 are distributed on the center position of the plane (or the material box 24) where the plurality of weighing sensors 22 are located. For example, three weighing sensors 22 are arranged in a regular triangle on the material box 24, and the three weighing sensors 22 are arranged on the same horizontal plane, so that the stress of each weighing sensor 22 is more uniform, and the measurement accuracy is improved.

[0035] Optionally, the weighing detection system can further be provided with a mounting bracket 25. One end of each weighing sensor 22 is fixedly installed on the mounting bracket 25, and the other end is fixedly installed on the material box 24. The weighing sensor 22 can be connected to the mounting bracket 25 or the material box 24 through a structural member. The weighing sensor 22 can be connected to the top or bottom of the material box 24. Correspondingly, the first weighing data can reflect the tension or pressure of the material box 24 on the weighing sensor 22. Optionally, the inertial sensor 21 provided by the scheme can be installed on the mounting bracket 25, the material box 24 or other set installation positions, for detecting the inertial state of the material box 24 and outputting corresponding inertial measurement data.

[0036] After the weighing sensor 22 detects the first weighing data and the inertial sensor 21 detects the inertial measurement data, the first weighing data and the inertial measurement data are respectively sent to the processing unit 23. The processing unit 23 provided by the scheme can be installed on the mounting bracket 25, the material box 24 or other set installation positions.

[0037] The processing unit 23 can be a processor arranged inside the weighing detection system, or a processor arranged outside the weighing detection system. The processor can be installed on an unmanned device, or can be an external device capable of communicating with the unmanned device, such as a mobile phone, a remote controller, or a server. The processing unit 23 can be used to execute the weighing detection method provided in any embodiment of the present application. That is, the first weighing data detected by the plurality of weighing sensors 22 and the inertial measurement data detected by the inertial sensor 21 are obtained, the second weighing data in the direction of the resultant force is calculated according to each first weighing data, the target vibration frequency is determined according to the inertial measurement data, the third weighing data is obtained after the first filtering processing of the second weighing data, the second filtering mode is determined according to the fluctuation degree of the third weighing data and the target vibration frequency, and the target weighing data is obtained by performing the second filtering processing on the third weighing data according to the second filtering mode. The weighing detection system can perform the second filtering processing on the third weighing data obtained by the first filtering processing of the second weighing data according to the target vibration frequency corresponding to the inertial measurement data, effectively reducing the influence of vibration on weighing detection, and improving the adaptability and weighing detection accuracy of the weighing detection system.

[0038] The weighing detection system provided in the present application can be arranged on an unmanned device such as an unmanned vehicle or an unmanned aerial vehicle, and can place materials (such as fertilizers or medicines) in the material box 24 and carry the materials for work. For example, the fertilizers or medicines are placed in the material box 24 on the unmanned aerial vehicle, and the unmanned aerial vehicle flies over the target land and sprays the fertilizers or medicines in the material box 24 for work. During the work, the target weighing data can be determined based on the weighing detection method provided in the present application, and the remaining fertilizers or medicines in the material box 24 can be determined based on the target weighing data, so that more accurate work planning can be performed.

[0039] For example, a plurality of first weighing data detected by the plurality of weighing sensors on the weight of the material box, and inertial measurement data detected by the inertial sensor on the inertial state (the inertial state of the material box or the mounting bracket) are obtained. Optionally, the first weighing data detected by the plurality of weighing sensors in a set time period, and the inertial measurement data detected by the inertial sensor in the set time period are obtained. The inertial measurement data reflects the inertial state of the inertial sensor in different axial directions, such as acceleration, speed, and angle in different axial directions. For example, the inertial sensor is a three-axis acceleration sensor, and the inertial measurement data is acceleration, speed, and angle in three axial directions.

[0040] S102: calculating the second weighing data in the direction of the resultant force of each weighing sensor based on the first weighing data, and determining the target vibration frequency based on the axial vibration frequency in each axis direction of the inertial measurement data.

[0041] For example, the first weighing data output by each weighing sensor is used to calculate the second weighing data of each weighing sensor in the direction of the resultant force, which is the total weight data of the initial detected material box and the material loaded therein.

[0042] Further, the axial vibration frequency in each axial direction is calculated according to the inertial measurement data, and the axial vibration frequency that has the greatest impact on the weighing detection is determined from the axial vibration frequencies in each axial direction, and the axial vibration frequency is determined as the target vibration frequency.

[0043] Optionally, the maximum axial vibration frequency in each axial direction is used as the target vibration frequency. For example, the inertial sensor is a three-axis acceleration sensor, and the axial vibration frequencies in three axial directions are calculated according to the inertial measurement data output by the inertial sensor. The maximum axial vibration frequency in the three axial directions is used as the target vibration frequency.

[0044] In one possible embodiment, the weighing detection method provided by the present scheme further comprises: in the case where the target vibration frequency reaches a set early warning frequency range, performing an abnormal early warning after the target vibration frequency is determined based on the axial vibration frequencies in each axial direction according to the inertial measurement data.

[0045] For example, after the target vibration frequency is determined each time, it is determined whether the target vibration frequency is within the set early warning frequency range, or whether the target vibration frequency reaches a set early warning frequency threshold, to determine whether the current vibration is abnormal. When the target vibration frequency is within the set early warning frequency range, or the target vibration frequency reaches the set early warning frequency threshold, it is determined that the current vibration is abnormal, and an abnormal early warning is performed according to a set early warning mode, so as to reduce the damage to the unmanned equipment (for example, the unmanned aerial vehicle crashes). For example, in the case where the material in the material box is unevenly distributed, or the on-site environment is poor (for example, the wind is strong), the unmanned equipment starts or stops moving (for example, the unmanned aerial vehicle takes off or lands), the unmanned equipment turns around, the unmanned equipment is overweight or underweight, or the unmanned equipment itself vibrates abnormally, at least one axial vibration frequency is likely to be large. In order to ensure the safety of the equipment, an abnormal early warning is performed when the target vibration frequency reaches the set early warning frequency range, reminding the operator to pay attention to the safety of the equipment and to promptly investigate the abnormality.

[0046] S103: performing first filtering processing on the second weighing data to obtain third weighing data.

[0047] For example, the second weighing data is subjected to first filtering processing according to a set first filtering processing mode to obtain third weighing data. By performing first filtering processing on the second weighing data, the influence of noise on the weighing detection effect can be effectively reduced, and more accurate third weighing data can be obtained.

[0048] Optionally, the first filtering processing on the second weighing data can be one or more of a combination of median filtering processing, infinite impulse response filtering (IIR second-order filtering) processing, Kalman filtering processing, mean sliding window filtering, and low-pass filtering processing. For example, when the first filtering processing on the second weighing data is based on median filtering processing, the second weighing data determined in a set time period are sequentially arranged according to numerical values, the second weighing data at the middle position and a plurality of second weighing data adjacent to the second weighing data are extracted, and an average value of the second weighing data is calculated to obtain third weighing data, which effectively reduces the influence of extreme values on weighing detection and can be applied to application scenarios in which a linear filter cannot be used, thereby improving the weighing detection accuracy.

[0049] S104: determining a second filtering manner for the third weighing data based on the fluctuation degree of the third weighing data and the target vibration frequency, and performing second filtering processing on the third weighing data according to the second filtering manner to obtain target weighing data.

[0050] For example, the fluctuation degree of the third weighing data is determined, and the second filtering manner for filtering the third weighing data is determined according to the fluctuation degree of the third weighing data and the target vibration frequency, and the second filtering processing on the third weighing data is performed according to the determined second filtering manner to obtain the target weighing data.

[0051] Optionally, different fluctuation degrees and target vibration frequencies correspond to different second filtering manners. For example, when the fluctuation degree of the third weighing data is less than a set fluctuation degree threshold, it is considered that the vibration received by the unmanned device has less influence on the weighing detection, and the third weighing data does not need to be further filtered, that is, the second filtering processing on the third weighing data is not filtering the third weighing data, and the third weighing data is output as the target weighing data. When the fluctuation degree of the third weighing data reaches the set fluctuation degree threshold, it is considered that the vibration received by the unmanned device has greater influence on the weighing detection, and a specific second filtering manner needs to be determined according to the frequency range corresponding to the target vibration frequency, wherein different frequency ranges correspond to different second filtering manners.

[0052] In one possible embodiment, after the target weighing data is obtained, the target weighing data can be sent to a set target device (for example, a user terminal, a server, a local processing terminal, and the like connected by communication).

[0053] According to the above, the first weighing data detected by the plurality of weighing sensors and the inertial measurement data detected by the inertial sensor are acquired, the second weighing data in the direction of the resultant force is calculated according to the first weighing data, the target vibration frequency is determined according to the inertial measurement data, the third weighing data is obtained after the first filtering processing is performed on the second weighing data, the second filtering mode is determined according to the fluctuation degree of the third weighing data and the target vibration frequency, and the second filtering processing is performed on the third weighing data according to the second filtering mode to obtain the target weighing data. The third weighing data obtained by the first filtering processing of the second weighing data according to the target vibration frequency corresponding to the inertial measurement data is subjected to the second filtering processing, the influence of vibration on the weighing detection is effectively reduced, and the adaptability and the weighing detection accuracy of the weighing detection system are improved.

[0054] On the basis of the above embodiment, Figure 3 A flowchart of another weighing detection method provided by the embodiment of the application is given. Referring to Figure 3 The weighing detection method comprises the following steps.

[0055] S201: acquiring first weighing data detected by a plurality of weighing sensors and inertial measurement data detected by an inertial sensor.

[0056] S202: calculating second weighing data in the direction of the resultant force of each weighing sensor based on the first weighing data.

[0057] S203: calculating an axial vibration frequency of the inertial measurement data in each axial direction, and determining the maximum axial vibration frequency as a target vibration frequency.

[0058] For example, the axial vibration frequencies of the collected inertial measurement data in each axial direction are calculated respectively, and the maximum axial vibration frequency is determined as the target vibration frequency. The maximum axial vibration frequency is used as the target vibration frequency, the axial direction corresponding to the vibration direction having the greatest influence on the weighing detection and the target vibration frequency are accurately determined, a more suitable second filtering mode is determined, and the weighing detection accuracy is improved.

[0059] In one possible embodiment, the axial vibration frequency in each axial direction of the inertial measurement data can be calculated according to the acceleration information in each axial direction of the inertial measurement data. Based on this, Figure 4 As shown in the axial vibration frequency determination flowchart provided by the embodiment, when calculating the axial vibration frequency of the inertial measurement data in each axial direction, the embodiment comprises steps S2031-S2033:

[0060] S2031: performing twice integral processing on the acceleration information of the inertial measurement data in each axial direction to obtain displacement information in each axial direction.

[0061] S2032: Fourier transform processing is performed on the displacement information of each axis respectively to obtain amplitude information corresponding to a plurality of set frequency bands in each axis.

[0062] S2033: The axial vibration frequency in each axis is determined based on the set frequency band corresponding to the maximum amplitude information in each axis.

[0063] For example, the acceleration information in each axis in the inertial measurement data is subjected to twice integral processing, and the twice integral processing result in each axis is the displacement information in each axis. For example, the inertial sensor is a three-axis acceleration sensor, and the displacement information in three axes is obtained by twice integral processing based on the twice integral formula on the acceleration information.

[0064] Further, based on the Fourier transform formula The displacement information in each axis is subjected to Fourier transform processing based on a plurality of set frequency bands respectively to obtain amplitude information corresponding to a plurality of set frequency bands in each axis, wherein f(t) is the displacement information, i is a first set coefficient, ω is the angular velocity information corresponding to the inertial measurement data, and t is the sampling time corresponding to the inertial measurement data. In an embodiment, after obtaining the amplitude information corresponding to a plurality of set frequency bands in each axis, the amplitude information is subjected to normalized discrete processing based on the normalized discrete processing formula , wherein f(n) is the amplitude information, n is the axis corresponding to the inertial measurement data, N is the number of sampling points of the inertial measurement data in the set time period, j is a second set coefficient, ω is the angular velocity information corresponding to the inertial measurement data, k is the amplitude information obtained based on the inertial measurement data, and v is the speed information obtained based on the inertial measurement data.

[0065] Further, the set frequency band corresponding to the maximum amplitude information in the amplitude information corresponding to each axis is determined as the axial vibration frequency in the corresponding axis. The axial vibration frequency is the frequency on the corresponding set frequency band, for example, the end value or the median value on the set frequency band. In an embodiment, when the axial vibration frequency in each axis is determined, the energy information corresponding to each axis can be determined based on the amplitude information, and the set frequency band corresponding to the maximum energy information is determined as the axial vibration frequency in the corresponding axis. For example, the Fourier series transform is performed on the displacement information in the time domain to obtain the amplitude spectrum corresponding to a plurality of set frequency bands, the value in the amplitude spectrum is the amplitude information, the energy value in the amplitude spectrum is the energy information, the energy information can be described by the energy spectrum, and the energy information is generally the square of the modulus of the amplitude information.

[0066] ​Optionally, the set frequency bands can include the first set frequency band, the third set frequency band and the second set frequency band, and the frequency ranges corresponding to the first set frequency band, the third set frequency band and the second set frequency band correspond to values that increase in turn, for example, the frequency ranges corresponding to the first set frequency band, the third set frequency band and the second set frequency band are low frequency range, medium frequency range and high frequency range respectively. Optionally, the frequency ranges corresponding to the first set frequency band, the third set frequency band and the second set frequency band can be within 200 Hz, 200-300 Hz and 800-100 Hz.

[0067] The present scheme determines the amplitude information or energy information corresponding to different set frequency bands by performing secondary integration processing and Fourier transform processing on the inertial measurement data, thereby determining the set frequency band that has the greatest impact on the weighing measurement in each axis, and determining the target vibration frequency according to the set frequency band with the greatest impact, so as to determine a more appropriate second filtering mode according to the influence of different vibration frequencies on the weighing detection, thereby improving the weighing detection accuracy.

[0068] S204: performing first filtering processing on the second weighing data to obtain third weighing data.

[0069] S205: determining the fluctuation degree of the third weighing data.

[0070] In one possible embodiment, the fluctuation degree of the third weighing data can be represented by the difference between the peak value and the valley value of the third weighing data within a set time period, or the variance or standard deviation of the third weighing data within the set time period. It can be understood that the greater the difference between the peak value and the valley value, the greater the variance or standard deviation, and the greater the fluctuation degree of the third weighing data.

[0071] In one possible embodiment, when the fluctuation degree of the third weighing data is represented by the difference between the peak value and the valley value of the third weighing data within a set time period, the present scheme specifically determines the fluctuation degree of the third weighing data by determining the peak information and the valley information of the third weighing data, and determining the fluctuation degree of the third weighing data based on the peak information and the valley information.

[0072] For example, the peak information (maximum weight value) and the valley information (minimum weight value) of the third weighing data within a set time period are obtained, and the difference between the peak information and the valley information is calculated, which is the fluctuation degree of the third weighing data. The present scheme determines the fluctuation degree of the third weighing data by the peak information and the valley information, accurately evaluates the filtering effect of the first filtering processing, determines a more appropriate second filtering mode, and improves the weighing detection accuracy.

[0073] S206: in the case where the fluctuation degree does not meet the set fluctuation requirement, determining a second filtering mode for the third weighing data based on the vibration type corresponding to the target vibration frequency.

[0074] Exemplarily, the fluctuation degree of the determined third weighing data is compared with the set fluctuation requirement to determine whether the fluctuation degree meets the set fluctuation requirement. For example, the value corresponding to the fluctuation degree is compared with the set fluctuation threshold value. When the value corresponding to the fluctuation degree is less than the set fluctuation threshold value, it is considered that the fluctuation degree meets the set fluctuation requirement. When the value corresponding to the fluctuation degree reaches the set fluctuation threshold value, it is considered that the fluctuation degree does not meet the set fluctuation requirement.

[0075] When the fluctuation degree does not meet the set fluctuation requirement, it is considered that the filtering effect of the first filtering processing does not meet the set requirement, the vibration of the weighing detection system has a greater impact on the weighing detection effect, and the vibration type corresponding to the target vibration frequency needs to be determined, and the second filtering mode for the third weighing data is determined according to the vibration type.

[0076] In one possible embodiment, different second filtering modes can be set for different vibration types according to the impact of different vibration types on the weighing detection of the weighing sensor, and the corresponding second filtering mode can be determined according to the vibration type corresponding to the target vibration frequency. Based on this, when the second filtering mode for the third weighing data is determined based on the vibration type corresponding to the target vibration frequency, the present scheme includes:

[0077] S2061: determining the vibration type based on the set frequency band corresponding to the target vibration frequency.

[0078] S2062: determining the second filtering mode for the third weighing data based on the correspondence between the vibration type and the set second filtering mode.

[0079] Exemplarily, when it is determined that the fluctuation degree does not meet the set fluctuation requirement, the vibration type corresponding to the current target vibration frequency is determined, and the second filtering mode for the third weighing data is determined according to the correspondence between the vibration type and the set second filtering mode. The present scheme determines the second filtering mode according to the vibration type corresponding to the target vibration frequency which has the greatest impact on the weighing detection, and more specifically filters the third weighing data, retains and highlights the smooth and continuous weighing data, and the output weighing data is smoother, thereby improving the weighing detection accuracy.

[0080] Optionally, the vibration type provided by the present scheme can be set based on a set frequency band. For example, when the set frequency band is a first set frequency band (low frequency band), a third set frequency band (medium frequency band) and a second set frequency band (high frequency band) corresponding to the values in turn increasing, the corresponding vibration types are a first vibration type (low frequency vibration), a third vibration type (medium frequency vibration) and a second vibration type (high frequency vibration) respectively.

[0081] In a possible embodiment, the scheme determines the second filtering mode for the third weighing data based on the correspondence between the vibration type and the set second filtering mode, including: determining the second filtering mode for the third weighing data as high-pass filtering in the case that the vibration type is a first vibration type; and determining the second filtering mode for the third weighing data as low-pass filtering in the case that the vibration type is a second vibration type, the frequency corresponding to the first vibration type being lower than the frequency corresponding to the second vibration type.

[0082] It needs to be explained that the vibration frequency of the unmanned device will affect the detection data of the weighing sensor, and different vibration frequencies can adopt different software filtering modes to ensure the smoothness and stability of the detection data. Different frequency bands have different effects on the weighing sensor. In the first set frequency band, the vibration frequency is proportional to the displacement, and the vibration (low frequency vibration) in the first set frequency band has a greater impact on the weighing detection. In the second set frequency band, the vibration intensity is proportional to the acceleration, and the vibration (high frequency vibration) in the second set frequency band has a greater impact on the weighing detection. In the third set frequency band, the vibration intensity is proportional to the velocity, and when the target vibration frequency is in the third set frequency band (the target vibration frequency is a medium frequency vibration), the fluctuation degree of the third weighing data generally meets the set fluctuation requirement, and it can be determined that the third weighing data does not need to be subjected to the second filtering processing.

[0083] For example, the scheme sets the second filtering mode corresponding to the first set frequency band as the second filtering processing based on the high-pass filtering algorithm, and sets the second filtering mode corresponding to the second set frequency band as the second filtering processing based on the low-pass filtering algorithm.

[0084] When it is determined that the vibration type corresponding to the target vibration frequency is the first vibration type, the second filtering mode for the third weighing data is determined as the second filtering processing based on the high-pass filtering algorithm to improve the signal-to-noise ratio of the third weighing data, enhance the high-frequency signal in the third weighing data, and attenuate the low-frequency signal in the third weighing data, thereby suppressing the interference of the low-frequency signal on the weighing detection. When it is determined that the vibration type corresponding to the target vibration frequency is the second vibration type, the second filtering mode for the third weighing data is determined as the second filtering processing based on the low-pass filtering algorithm to improve the signal-to-noise ratio of the third weighing data, enhance the low-frequency signal in the third weighing data, and attenuate the high-frequency signal in the third weighing data, thereby suppressing the interference of the high-frequency signal on the weighing detection.

[0085] The scheme sets different second filtering modes according to the effects of different vibration types on the weighing detection, more specifically filters the third weighing data, retains and highlights the smooth and continuous weighing data, and the output weighing data is smoother, thereby improving the weighing detection accuracy.

[0086] In a possible embodiment, the scheme determines the second filtering manner of the third weighing data based on the fluctuation degree of the third weighing data and the target vibration frequency, and further includes: determining not to perform the second filtering processing on the third weighing data when the fluctuation degree meets the set fluctuation requirement.

[0087] When the fluctuation degree meets the set fluctuation requirement, it can be considered that the filtering effect of the first filtering processing has reached the set requirement, the fluctuation of the third weighing data obtained by filtering in the set time period is within an acceptable range, the third weighing data can be directly output as the current weighing detection result without the second filtering processing, or the third weighing data is taken as the target weighing data to determine the current weighing detection result, so as to reduce unnecessary data processing process, and effectively improve the weighing detection efficiency while ensuring the weighing detection accuracy.

[0088] S207: performing the second filtering processing on the third weighing data according to the second filtering manner to obtain the target weighing data.

[0089] According to the above, the first weighing data detected by the plurality of weighing sensors and the inertial measurement data detected by the inertial sensor are obtained, the second weighing data in the resultant direction is calculated according to each first weighing data, the target vibration frequency is determined according to the inertial measurement data, the third weighing data is obtained by performing the first filtering processing on the second weighing data, the second filtering manner is determined according to the fluctuation degree of the third weighing data and the target vibration frequency, and the target weighing data is obtained by performing the second filtering processing on the third weighing data according to the second filtering manner. The scheme effectively reduces the influence of vibration on weighing detection and improves the adaptability and weighing detection accuracy of the weighing detection system by performing the second filtering processing on the third weighing data obtained by performing the first filtering processing on the second weighing data according to the target vibration frequency corresponding to the inertial measurement data. Meanwhile, the target vibration frequency is determined based on the double integration processing and the Fourier transform processing of the inertial measurement data, so that a more appropriate second filtering manner is determined according to the influence of different vibration frequencies on weighing detection, and the weighing detection accuracy is improved. The filtering effect of the first filtering processing is accurately evaluated according to the fluctuation degree of the third weighing data to determine a more appropriate second filtering manner and improve the weighing detection accuracy. The second filtering manner is determined according to the vibration type corresponding to the target vibration frequency having the greatest influence on weighing detection, the output weighing data is smoother, and the weighing detection accuracy is improved.

[0090] Figure 5 A structural schematic diagram of a weighing detection device provided by an embodiment of the present application is given, which can be applied to a weighing detection system provided with an inertial sensor and a plurality of weighing sensors. Referring to Figure 5The weighing detection device comprises a data acquisition module 51, a data processing module 52, a first filtering module 53 and a second filtering module 54.

[0091] The data acquisition module 51 is configured to acquire first weighing data detected by the plurality of weighing sensors and inertial measurement data detected by the inertial sensor. The data processing module 52 is configured to calculate second weighing data in the direction of the resultant force of each weighing sensor based on the first weighing data, and determine a target vibration frequency based on the axial vibration frequencies of each axis of the inertial measurement data. The first filtering module 53 is configured to perform first filtering processing on the second weighing data to obtain third weighing data. The second filtering module 54 is configured to determine a second filtering mode for the third weighing data based on the fluctuation degree of the third weighing data and the target vibration frequency, and perform second filtering processing on the third weighing data according to the second filtering mode to obtain target weighing data.

[0092] The above, by acquiring the first weighing data detected by the plurality of weighing sensors and the inertial measurement data detected by the inertial sensor, calculating the second weighing data in the direction of the resultant force according to each first weighing data, and determining the target vibration frequency according to the inertial measurement data, performing first filtering processing on the second weighing data to obtain the third weighing data, and determining the second filtering mode according to the fluctuation degree of the third weighing data and the target vibration frequency, and performing second filtering processing on the third weighing data according to the second filtering mode to obtain the target weighing data, the present scheme performs second filtering processing on the third weighing data obtained by first filtering processing of the second weighing data by combining the target vibration frequency corresponding to the inertial measurement data, effectively reduces the influence of vibration on weighing detection, and improves the adaptability and weighing detection accuracy of the weighing detection system.

[0093] In one possible embodiment, the data processing module 52 comprises a target vibration frequency determination unit, which is configured to calculate the axial vibration frequencies of each axis of the inertial measurement data, and determine the maximum axial vibration frequency as the target vibration frequency.

[0094] In one possible embodiment, when the target vibration frequency determination unit calculates the axial vibration frequencies of each axis of the inertial measurement data, the target vibration frequency determination unit comprises:

[0095] performing second integral processing on the acceleration information of each axis of the inertial measurement data to obtain displacement information of each axis;

[0096] performing Fourier transform processing on the displacement information of each axis respectively to obtain amplitude information corresponding to a plurality of set frequency bands of each axis;

[0097] determining the axial vibration frequency of each axis based on the set frequency band corresponding to the maximum amplitude information of each axis.

[0098] In a possible embodiment, the first filtering processing includes one or more of a combination of median filtering processing, infinite impulse response filtering processing, Kalman filtering processing, mean sliding window filtering, and low-pass filtering processing.

[0099] In a possible embodiment, the second filtering module 54 includes a fluctuation degree determination unit and a second filtering determination unit.

[0100] The fluctuation degree determination unit is configured to determine a fluctuation degree of the third weighing data.

[0101] The second filtering determination unit is configured to determine a second filtering manner for the third weighing data based on a vibration type corresponding to the target vibration frequency, in a case where the fluctuation degree does not satisfy a set fluctuation requirement.

[0102] In a possible embodiment, the fluctuation degree determination unit includes the following when determining the fluctuation degree of the third weighing data.

[0103] The fluctuation degree determination unit is configured to determine peak information and valley information of the third weighing data, and determine the fluctuation degree of the third weighing data based on the peak information and the valley information.

[0104] In a possible embodiment, the second filtering determination unit includes the following when determining the second filtering manner for the third weighing data based on the vibration type corresponding to the target vibration frequency.

[0105] The second filtering determination unit is configured to determine the vibration type based on a set frequency range corresponding to the target vibration frequency.

[0106] The second filtering determination unit is configured to determine the second filtering manner for the third weighing data based on a correspondence relationship between the vibration type and a set second filtering manner.

[0107] In a possible embodiment, the second filtering determination unit includes the following when determining the second filtering manner for the third weighing data based on the correspondence relationship between the vibration type and the set second filtering manner.

[0108] In a case where the vibration type is a first vibration type, the second filtering determination unit is configured to determine that the second filtering manner for the third weighing data is high-pass filtering.

[0109] In a case where the vibration type is a second vibration type, the second filtering determination unit is configured to determine that the second filtering manner for the third weighing data is low-pass filtering, and a frequency corresponding to the first vibration type is lower than a frequency corresponding to the second vibration type.

[0110] In a possible embodiment, the data processing module is further configured to determine not to perform the second filtering processing on the third weighing data, in a case where the fluctuation degree satisfies the set fluctuation requirement.

[0111] In a possible embodiment, the weighing detection apparatus further comprises an abnormality early warning module, which is configured to, after determining the target vibration frequency based on the axial vibration frequency of the inertial measurement data in each axial direction, perform early warning of abnormality when the target vibration frequency reaches a set early warning frequency range.

[0112] It is worth noting that in the above embodiments of the weighing detection apparatus, each unit and module included is only divided according to functional logic, but is not limited to the above division, as long as the corresponding functions can be implemented; in addition, the specific names of each functional unit are only for the convenience of mutual differentiation, and are not used to limit the protection scope of the embodiments of the present application.

[0113] The embodiments of the present application also provide a working device, which comprises the weighing detection system provided by any of the above embodiments. The working device is provided with a material box, and the weighing detection system comprises a processing unit, an inertial sensor and a plurality of weighing sensors. The plurality of weighing sensors are configured to be installed on the material box of the working device to detect first weighing data of the material box. The inertial sensor is configured to be installed on the working device to detect inertial measurement data of the working device. The processing unit is in communication connection with the inertial sensor and the plurality of weighing sensors, and performs the weighing detection method provided by any of the above embodiments to obtain target weighing data. The working device can perform work based on the target weighing data.

[0114] The embodiments of the present application also provide a weighing detection device, which can integrate the weighing detection apparatus provided by the embodiments of the present application. Figure 6 FIG. 1 is a structural schematic diagram of a weighing detection device provided by an embodiment of the present application. As shown in FIG. 1, the weighing detection device comprises an input device 63, an output device 64, a memory 62 and one or more processors 61. Figure 6 The weighing detection device comprises an input device 63, an output device 64, a memory 62 and one or more processors 61; the memory 62 is configured to store one or more programs; when the one or more programs are executed by the one or more processors 61, the one or more processors 61 implement the weighing detection method provided by the above embodiments. The input device 63, the output device 64, the memory 62 and the processor 61 can be connected through a bus or other means, Figure 6 In the above embodiment, the connection through the bus is taken as an example.

[0115] The memory 62 can be used to store software programs, computer executable programs and modules, such as program instructions / modules of the weight detection method provided by any of the embodiments of the present application (for example, the data acquisition module 51, the data processing module 52, the first filtering module 53 and the second filtering module 54 in the weight detection device), as a readable storage medium of a computing device. The memory 62 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and application programs required by at least one function; the data storage area can store data created according to the use of the device, etc. In addition, the memory 62 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some examples, the memory 62 can further include a memory remotely arranged with respect to the processor 61, which can be connected to the device through a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network and a combination thereof.

[0116] The input device 63 can be used to receive input digital or character information, and generate key signal input related to user settings and function control of the device. The output device 64 can include a display device such as a display screen.

[0117] The processor 61 executes various function applications and data processing of the device by running software programs, instructions and modules stored in the memory 62, that is, implements the above-mentioned weight detection method.

[0118] The weight detection device, system, device and computer provided above can be used to execute the weight detection method provided by any of the above-mentioned embodiments, and have corresponding functions and beneficial effects.

[0119] The embodiments of the present application also provide a storage medium storing computer executable instructions, which, when executed by a computer processor, are used to execute the weight detection method provided by the above-mentioned embodiments, which can be applied to a weight detection system provided with an inertial sensor and a plurality of weight sensors. The weight detection method comprises: acquiring first weight data detected by the plurality of weight sensors and inertial measurement data detected by the inertial sensor; calculating second weight data of each weight sensor in the direction of the resultant force based on the first weight data, and determining a target vibration frequency based on the axial vibration frequency of each axis based on the inertial measurement data; performing first filtering processing on the second weight data to obtain third weight data; determining a second filtering mode of the third weight data based on the fluctuation degree of the third weight data and the target vibration frequency, and performing second filtering processing on the third weight data according to the second filtering mode to obtain target weight data.

[0120] Storage medium - any type of memory device or storage device. The term "storage medium" is intended to include an installation medium, e.g., a CD-ROM, floppy disks, or tape apparatus; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; or a non-volatile memory such as a magnetic medium (e.g., a hard drive or optical storage); registers or other similar types of memory elements, etc. The memory medium can also include other types of storage medium and / or combinations thereof. Moreover, the memory medium can be located in a first computer system in which the programs are executed, or can be located in a second different computer system which connects to the first computer system over a network (e.g., the Internet). The second computer system can provide program instructions to the first computer system for execution. The term "memory medium" can include two or more memory mediums which can reside in different locations, e.g., in different computer systems that are connected over a network. The memory medium can store program instructions (e.g., as an installed program) that can be executed by one or more processors.

[0121] Of course, the storage medium storing computer executable instructions provided by the embodiments of the present application is not limited to the weighing detection method provided above, and can also execute the related operations in the weighing detection method provided by any of the embodiments of the present application.

[0122] The weighing detection apparatus, system, device and storage medium provided in the above embodiments can execute the weighing detection method provided by any of the embodiments of the present application, and the technical details not described in the above embodiments can be referred to the weighing detection method provided by any of the embodiments of the present application.

[0123] The above are only the preferred embodiments of the present application and the technical principles applied. The present application is not limited to the specific embodiments provided herein, and various obvious changes, re-adjustments and replacements made by those skilled in the art without departing from the protection scope of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and can include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A method of weight detection applied to a weight detection system, characterized in that, The weighing detection system is provided with an inertial sensor and a plurality of weighing sensors, and the weighing detection method comprises the following steps: Obtaining first weighing data detected by the plurality of weighing sensors and inertial measurement data detected by the inertial sensor; Calculating second weighing data in the direction of the resultant force of each weighing sensor based on the first weighing data, and calculating the axial vibration frequency of the inertial measurement data in each axis, and determining the maximum axial vibration frequency as the target vibration frequency; Performing first filtering processing on the second weighing data to obtain third weighing data; Determining the fluctuation degree of the third weighing data; in the case that the fluctuation degree does not meet the set fluctuation requirement, determining the second filtering mode of the third weighing data based on the vibration type corresponding to the target vibration frequency, and performing second filtering processing on the third weighing data according to the second filtering mode to obtain target weighing data.

2. The load detection method according to claim 1, wherein The calculation of the axial vibration frequency of the inertial measurement data in each axis comprises: Performing twice integral processing on the acceleration information in each axis to obtain displacement information in each axis; Respectively performing Fourier transform processing on the displacement information in each axis to obtain amplitude information corresponding to a plurality of set frequency bands in each axis; Determining the axial vibration frequency in each axis based on the set frequency band corresponding to the maximum amplitude information in each axis.

3. The method of claim 1, wherein, The first filtering processing comprises one or a combination of median filtering processing, infinite impulse response filtering processing, Kalman filtering processing, mean sliding window filtering and low pass filtering processing.

4. The method of claim 1, wherein The determination of the fluctuation degree of the third weighing data comprises: Determining the peak information and the valley information of the third weighing data, and determining the fluctuation degree of the third weighing data based on the peak information and the valley information.

5. The method of claim 1, wherein The determination of the second filtering mode of the third weighing data based on the vibration type corresponding to the target vibration frequency comprises: Determining the vibration type based on the set frequency band corresponding to the target vibration frequency; Determining the second filtering mode of the third weighing data based on the corresponding relationship between the vibration type and the set second filtering mode.

6. The method of claim 5, wherein, The determination of the second filtering mode of the third weighing data based on the corresponding relationship between the vibration type and the set second filtering mode comprises: In the case that the vibration type is a first vibration type, determining that the second filtering mode of the third weighing data is high pass filtering; In the case that the vibration type is a second vibration type, determining that the second filtering mode of the third weighing data is low pass filtering, and the frequency corresponding to the first vibration type is lower than the frequency corresponding to the second vibration type.

7. The method of claim 1, wherein, After the determination of the fluctuation degree of the third weighing data, the method further comprises: In the case that the fluctuation degree meets the set fluctuation requirement, determining not to perform second filtering processing on the third weighing data.

8. The method of claim 1, wherein, After the determination of the target vibration frequency based on the axial vibration frequency of the inertial measurement data in each axis, the method further comprises: In the case that the target vibration frequency reaches a set early warning frequency range, performing abnormal early warning.

9. A weighing detection device applied to a weighing detection system, characterized in that, The weighing detection system is provided with an inertial sensor and a plurality of weighing sensors, and the weighing detection device comprises a data acquisition module, a data processing module, a first filtering module and a second filtering module, wherein: The data acquisition module is configured to acquire first weighing data detected by the plurality of weighing sensors and inertial measurement data detected by the inertial sensor. The data processing module is configured to calculate second weighing data of each weighing sensor in the direction of the resultant force based on the first weighing data, calculate the axial vibration frequency of the inertial measurement data in each axis, and determine the maximum axial vibration frequency as a target vibration frequency. The first filtering module is configured to perform first filtering processing on the second weighing data to obtain third weighing data. The second filtering module is configured to determine the fluctuation degree of the third weighing data, determine a second filtering mode of the third weighing data based on the vibration type corresponding to the target vibration frequency when the fluctuation degree does not meet the set fluctuation requirement, and perform second filtering processing on the third weighing data according to the second filtering mode to obtain target weighing data.

10. A weigh detection system characterized by, The processing unit, the inertial sensor and the plurality of weighing sensors are included. The plurality of weighing sensors are configured to be installed on a material box of a working device to detect first weighing data of the material box, the inertial sensor is configured to be installed on the working device to detect inertial measurement data of the working device, and the processing unit is in communication connection with the inertial sensor and the plurality of weighing sensors. The processing unit is configured to execute the weighing detection method according to any one of claims 1-8.

11. A work apparatus characterized by comprising: The weighing detection system according to claim 10 is included.

12. A weighing detection device, characterized in that: It includes: a memory and one or more processors; The memory is configured to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the weighing detection method according to any one of claims 1-8.

13. A storage medium storing computer-executable instructions, wherein: The computer executable instructions, when executed by a computer processor, are configured to perform the weighing detection method according to any one of claims 1-8.

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