A method for collecting and transmitting production and operation data of a mortar mixer

Abstract

The present invention relates to the field of data retransmission technology, and in particular to a method for collecting and transmitting production and operation data of a mortar mixer. The method comprises: obtaining data packets corresponding to different types of production and operation data of a mortar mixer; obtaining the criticality of the data packet based on the standard deviation of the data in a data packet of a type of production and operation data and the difference between two adjacent data; drawing a data change curve based on the data in the data packet, and obtaining a sub-curve on the data change curve; obtaining a first confidence level of the data packet based on the sub-curve corresponding to a data packet; calculating a second confidence level of the data packet based on the frequency domain characteristics of the data in the data packet, and then obtaining a comprehensive confidence level of the data packet; determining the number of retransmissions of the data packet based on the comprehensive confidence level, the criticality level, and a preset number of retransmissions; and performing data transmission based on the number of retransmissions of each data packet of each type of production and operation data. The present application can improve the transmission efficiency of the production and operation data of a mortar mixer.

Description

Technical Field

[0001] The present invention relates to the technical field of data retransmission, and in particular to a method for collecting and transmitting production operation data of a mortar mixer. Background Art

[0002] Mortar mixers, widely used in the construction industry, are primarily used to mix cement, sand, gravel, and other building materials to produce mortar or concrete that meets specific requirements. As the construction industry's demands for efficiency and project quality increase, optimizing mortar mixer stability and equipment performance has become a research priority. Consequently, many mixers require the integration of efficient data acquisition and transmission systems. After data acquisition is complete, efficient and accurate transmission of the collected data to related equipment is crucial, assisting personnel in analyzing the mortar mixer's daily status. After the mortar mixer collects the day's production data (such as motor load, motor power, etc.) through sensors and data acquisition equipment, it will store the collected data in a local cache or temporary storage, and divide the day's data into multiple small packets or blocks (transmitting a large amount of data at one time requires a lot of bandwidth support, otherwise it will cause transmission delays, and it may cause a large load on the system (including the network and server); at the same time, if a network interruption occurs during a transmission, it may cause data loss and the transmission needs to be restarted), and prepare for transmission. During the transmission process, if the data packet transmission fails (such as packet loss, network interruption, etc.), the system will retry according to the preset number of retransmissions until the maximum number of retransmissions is reached or the data packet is successfully transmitted.

[0003] A fixed number of retransmissions means that if a data packet still cannot be successfully transmitted within the specified number of retransmissions, the attempt will be stopped. This may lead to data packet loss, especially in poor network conditions or unstable signals. Data packet loss may affect subsequent analysis work and make it impossible to perform timely maintenance on the equipment. At the same time, if the set number of retransmissions is too high, it may cause continued retransmissions when data packet transmission fails, occupying valuable network bandwidth and system resources, which will affect the transmission efficiency of other tasks and even cause network congestion. Summary of the Invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a method for collecting and transmitting production and operation data of a mortar mixer. The technical solution adopted is as follows:

[0005] An embodiment of the present invention provides a method for collecting and transmitting production and operation data of a mortar mixer:

[0006] Obtain different types of production and operation data of mortar mixers, and obtain data packages corresponding to various production and operation data;

[0007] Obtaining the criticality of a data packet according to the sum of the standard deviation of data in a data packet of production operation data and the difference between two adjacent data;

[0008] Draw a data change curve based on the data in the data packet, and obtain a sub-curve based on the peak points and valley points on the data change curve; obtain a first confidence level of a data packet of a type of production operation data based on the sub-curve corresponding to the data packet;

[0009] Calculating a second confidence level of the data packet based on frequency domain characteristics of data in the data packet; obtaining a comprehensive confidence level of the data packet based on the first and second confidence levels;

[0010] The number of retransmissions of a data packet is determined according to the comprehensive confidence, criticality and preset retransmission number of the data packet; and data transmission is performed based on the number of retransmissions of each data packet of each production operation data.

[0011] Preferably, obtaining the criticality of a data packet according to the sum of the standard deviation of data in a data packet of production operation data and the difference between two adjacent data includes:

[0012] Obtain the difference between the latter and the previous data in every two adjacent data in a data packet, and calculate the mean of the difference, which is recorded as the average change rate; multiply the standard deviation of the data in the data packet by the average change rate of the data packet to obtain the criticality of the data packet.

[0013] Preferably, obtaining a sub-curve according to the peak points and valley points on the data change curve includes:

[0014] The curve between two adjacent valley points on the data change curve is a sub-curve.

[0015] Preferably, obtaining a first confidence level of a data packet of production operation data according to a sub-curve corresponding to the data packet includes:

[0016] Obtain the difference between the value of a peak point on a sub-curve and the mean of all data on the sub-curve, and compare it with the rated maximum value of the production operation data to obtain a fluctuation characteristic value; the difference between the first preset value and the fluctuation characteristic value is the smoothness of the sub-curve; set a first ratio and a second ratio, and multiply the value of the peak point of the sub-curve by the first ratio and the second ratio respectively to obtain a first data value and a second data value; obtain the duration corresponding to the sub-curve on the sub-curve according to the first data value and the second data value; multiply the smoothness and duration of the sub-curve to obtain a time domain characteristic value of the sub-curve; and calculate the average of the time domain characteristic values ​​of all sub-curves corresponding to the data packet to obtain a first confidence level of the data packet.

[0017] Preferably, obtaining the duration corresponding to the sub-curve on the sub-curve according to the first data value and the second data value includes:

[0018] On the sub-curve, the first data point equal to the first data value is obtained in time sequence and recorded as the starting point. The first data point equal to the second data value is obtained and recorded as the ending point. The duration between the starting point and the ending point is the duration of the sub-curve.

[0019] Preferably, calculating the second confidence level of the data packet based on the frequency domain characteristics of the data in the data packet includes:

[0020] Perform FFT transformation on the data in a data packet to obtain the power spectrum power frequency energy, total power spectrum energy, maximum power spectrum density within the power frequency range, and any power spectrum density within the power frequency range of the data packet; compare the power spectrum power frequency energy of the data packet with the total power spectrum energy to obtain the frequency domain power frequency energy ratio corresponding to the data packet; compare the maximum power spectrum density within the power frequency range with the sum of any power spectrum densities within the power frequency range to obtain a first ratio; calculate the difference between the first preset value and the first ratio to obtain the spectral peak width of the fluctuating data in the data packet, and multiply it by the frequency domain power frequency energy ratio corresponding to the data packet to obtain the second confidence level of the data packet.

[0021] Preferably, obtaining a comprehensive confidence level of the data packet based on the first and second confidence levels comprises:

[0022] The first confidence level and the second confidence level of a data packet are added and normalized to obtain the comprehensive confidence level of the data packet.

[0023] Preferably, determining the number of retransmissions of a data packet based on the comprehensive confidence level, criticality, and preset number of retransmissions of the data packet includes:

[0024] The preset number of retransmissions includes a minimum number of retransmissions and a maximum number of retransmissions; the product of the comprehensive confidence and criticality of a data packet is obtained and normalized to obtain an adjustment factor; the difference between the maximum number of retransmissions and the minimum number of retransmissions is multiplied by the adjustment factor and rounded to obtain an adjustment step; the sum of the minimum number of retransmissions and the adjustment step is the number of retransmissions for the data packet.

[0025] The embodiments of the present invention have at least the following beneficial effects: the present application obtains data packets corresponding to different types of production and operation data of a mortar mixer, and then obtains the criticality of the data packet based on the standard deviation of the data in a data packet and the difference between two adjacent data; in the time domain, a data change curve is drawn according to the data in the data packet, and a sub-curve is obtained according to the peak points and valley points on the data change curve, and a first confidence level of the data packet is obtained according to the sub-curve corresponding to a data packet of a type of production and operation data, and then the second confidence level of the data packet is calculated based on the frequency domain characteristics of the data in the data packet, and the comprehensive confidence level of the data packet is obtained by combining the first confidence level and the second confidence level. The comprehensive confidence level is obtained from a comprehensive analysis of the time domain and frequency domain, which can eliminate data fluctuations caused by other interference and improve the robustness of subsequent retransmission times; finally, the retransmission times of a data packet are determined based on the comprehensive confidence level, criticality and preset retransmission times of the data packet, which not only reduces the packet loss rate of important data, but also greatly improves the overall data transmission efficiency, and further improves the accuracy and integrity of data transmission. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions and advantages of the embodiments of the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 A flow chart of a method for collecting and transmitting production operation data of a mortar mixer provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] To further illustrate the technical means and effectiveness of the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, describes in detail a method for collecting and transmitting production and operation data for a mortar mixer according to the present invention, including its specific implementation, structure, features, and effectiveness. In the following description, different references to "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.

[0029] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0030] The following describes in detail a method for collecting and transmitting production and operation data of a mortar mixer provided by the present invention in conjunction with the accompanying drawings.

[0031] Example:

[0032] The main application scenario of the present invention is to optimize the number of retransmissions during the transmission of the collected production operation data of the mortar mixer.

[0033] See also Figure 1 , which shows a method flow chart of a method for collecting and transmitting production and operation data of a mortar mixer provided by an embodiment of the present invention, the method comprising the following steps:

[0034] Step S1, acquiring different types of production and operation data of a mortar mixer, and obtaining data packets corresponding to various production and operation data.

[0035] The operating data of the mortar mixer is mainly collected through sensors and data acquisition equipment. It includes various types, such as mixing speed, motor load, motor power, mortar ratio, etc. The collection of this data is an existing technology and will not be elaborated on here. Different types of production and operation data of the mortar mixer are collected for the day, and the data collected that day is stored in a local cache or temporary storage. Because transmitting a large amount of data at one time requires a lot of bandwidth support, otherwise it will cause transmission delays; and transmitting a large amount of data at one time will place a large load on the system (including the network and server); at the same time, if a network interruption occurs during a transmission, it may cause data loss, and the transmission needs to be restarted.

[0036] Therefore, when transmitting a type of production and operation data, the data needs to be divided into multiple small packets or blocks. In this application, the data packets are divided according to the set time length. Preferably, the preset time length is 1 minute, which is a reference value, that is, one type of production and operation data is divided into multiple data packets for transmission by minutes. The same is true for other types of production and operation data. In this way, data packets corresponding to various production and operation data can be obtained.

[0037] Step S2: obtaining the criticality of a data packet according to the sum of the standard deviation of the data in a data packet of production operation data and the difference between two adjacent data.

[0038] After acquiring the data packets corresponding to various production and operation data for the mortar mixer, the data can be transmitted. However, before transmission, the number of retransmissions for each packet must be set. Important data, such as data reflecting changes in the mixer's operation, requires multiple retransmissions regardless of channel quality to ensure data integrity. However, routine operation data does not require multiple retransmissions to avoid wasting resources. Therefore, for each data packet, its criticality must first be determined. Then, data fluctuations caused by various external interferences must be eliminated to determine the true importance of each packet. Finally, an adaptive retransmission count is determined based on its importance.

[0039] For the data packets of various production and operation data of the mortar mixer, when the operating status of the mixer changes, the data in the corresponding data packet will fluctuate; when the mixer operates normally, the corresponding data packet will show a stable change; therefore, the criticality of the data packet is first obtained through the degree of fluctuation of the data in each data packet, among which the data reflecting the change of the mixer status is more critical. Loss may lead to errors in the current equipment status analysis and inability to perform maintenance in advance.

[0040] The criticality of a data packet is obtained by the degree of fluctuation of the data in the data packet. When the operating status of the mixer changes during the period corresponding to the data packet, the degree of fluctuation of the data in the data packet is large, and the rate of change of each data is large, which corresponds to a large standard deviation of the data in the data packet and a large mean value of the rate of change.

[0041] The criticality of a data packet is determined based on the sum of the standard deviation of the data within a data packet and the difference between two adjacent data items. Specifically, the difference between the two adjacent data items within a data packet is obtained and the mean of these differences is calculated, which is recorded as the average rate of change. The criticality of the data packet is then multiplied by the standard deviation of the data within the data packet and the average rate of change.

[0042] The specific calculation model of criticality is:

[0043] ,

[0044] Among them, Gi represents the criticality of the i-th data packet, They are the jth and j-1th data of the data packet respectively; is the number of data contained in the data packet; θi is the standard deviation of the data in the data packet, reflecting the degree of fluctuation of the data in the data packet. The greater the degree of fluctuation, the more important the operating state of the mixer is. This value represents the average rate of change of each data point within the data packet. A larger average value indicates a greater rate of change of each data point within the data packet, which means the data within the data packet is more likely to change, and the corresponding data packet is more critical. This can be used to determine the criticality of data packets corresponding to various types of production operation data.

[0045] Step S3: draw a data change curve based on the data in the data packet, and obtain a sub-curve based on the peak points and valley points on the data change curve; obtain a first confidence level of a data packet based on the sub-curve corresponding to a data packet of a production operation data.

[0046] After determining the criticality of each data packet, due to the presence of other equipment and unexpected events at the construction site, data collection will contain certain interference data. The interfering mixer data will also manifest as localized data fluctuations. Therefore, to further improve data retransmission efficiency and eliminate external interference from non-critical data, it is necessary to combine time-domain and frequency-domain features to eliminate interference and determine the confidence level of the data packet's criticality. First, critical data typically has a stable amplitude and a long duration, while sudden interference manifests as a transient spike (short-term, high-energy event). Therefore, the first confidence level of the data packet is determined through time-domain feature analysis. Second, critical data (such as motor power) primarily concentrates its energy at the power frequency (50Hz-60Hz) and has a wide signal distribution, while periodic interference (such as welding machines) has a specific frequency point and a relatively concentrated signal. Therefore, the second confidence level of the data packet is determined through frequency-domain feature analysis.

[0047] After obtaining the criticality of each data packet, due to the presence of other equipment and emergencies on the construction site, there will be a certain amount of interference data in the collected data when collecting data. The interfering mixer data will also manifest as fluctuations in local data. Therefore, in order to further improve the efficiency of data retransmission and eliminate external interference from non-important data, it is also necessary to combine time domain and frequency domain characteristics to eliminate interference and obtain the confidence level of the criticality of the data packet.

[0048] Critical data usually has a stable amplitude and a long duration, while sudden interference manifests as an instantaneous spike (short-term high energy). Therefore, the first confidence level of the data packet is obtained through time domain feature analysis. First, the data change curve of the data packet is drawn based on the data in the data packet to obtain all peak and valley points. The curve is divided into multiple sub-curves based on the peak and valley points. For any sub-curve, it may be a change caused by critical data or a change caused by sudden interference. However, after the critical data changes, its change is smooth and lasts for a long time, while the sudden interference is a sudden change in amplitude and lasts for a short time. Therefore, for this data packet, its first confidence level is obtained through the smoothness and duration of each sub-curve change.

[0049] A sub-curve is obtained based on the peak points and valley points on the data change curve. Specifically, the curve between two adjacent valley points on the data change curve is a sub-curve.

[0050] Furthermore, a first confidence level of a data packet of a type of production and operation data is obtained based on a sub-curve corresponding to the data packet of the data packet. Specifically, the difference between the value of a peak point on a sub-curve and the mean value of all data on the sub-curve is obtained, and compared with the rated maximum value of the production and operation data of the type to obtain a fluctuation characteristic value; the difference between the first preset value and the fluctuation characteristic value is the degree of stability of the sub-curve; a first ratio and a second ratio are set, and the value of the peak point of the sub-curve is multiplied by the first ratio and the second ratio respectively to obtain a first data value and a second data value; the duration corresponding to the sub-curve is obtained on the sub-curve based on the first data value and the second data value; the degree of stability and the duration of the sub-curve are multiplied to obtain a time domain characteristic value of the sub-curve; and the average of the time domain characteristic values ​​of all sub-curves corresponding to the data packet is calculated to obtain the first confidence level of the data packet.

[0051] The calculation model of the first confidence level is specifically as follows:

[0052] ,

[0053] in, represents the first confidence of the i-th data packet, is the value of the peak point in the j-th sub-curve in the data packet; is the mean of the data contained in the sub-curve; The rated maximum value for this type of data (such as rated load, rated voltage, etc.);

[0054] The first ratio and the second ratio are set to 90% and 10%. The sub-curve may have other situations that cause the curve time span to be longer, that is, it continues to maintain a certain size, resulting in the stable state being classified as within the duration, and thus the accurate duration cannot be obtained. Therefore, the setting here can filter out the relatively stable part of the sub-curve and focus on the duration of the part with more obvious changes. The value of the peak point is multiplied by the first ratio and the second ratio respectively to obtain the first data value. and the second data value Then, the duration of the sub-curve corresponding to the sub-curve is obtained on the sub-curve according to the first data value and the second data value. Specifically, the first data point equal to the first data value is obtained on the sub-curve in chronological order and recorded as the starting point. The first data point equal to the second data value is obtained and recorded as the ending point. The duration between the starting point and the ending point is the duration of the sub-curve. The values ​​of the first ratio and the second ratio can be adjusted according to actual conditions to capture the change and duration of the sub-curve. The duration of the jth sub-curve corresponding to the i-th data packet is represented by the duration. The longer the duration, the more likely it is critical data, and the shorter the duration, the more likely it is sudden interference.

[0055] This indicates the smoothness of the sub-curve data change, or the degree of stability. The closer the maximum value is to the mean, the smoother the data change corresponding to the sub-curve, and the less likely it is interference data. This allows us to obtain the first confidence level for each data packet.

[0056] Step S4: Calculate a second confidence level of the data packet based on the frequency domain characteristics of the data in the data packet; and obtain a comprehensive confidence level of the data packet based on the first and second confidence levels.

[0057] Key data (such as motor power) mainly concentrates its energy at the industrial frequency (50Hz-60Hz) and has a wide signal distribution. However, periodic interference (such as welding machines) has specific frequency points and relatively concentrated signals. Therefore, it is necessary to analyze the frequency domain characteristics to obtain a second confidence level for the data packet.

[0058] Perform FFT transformation on the data in a data packet to obtain the power spectrum power frequency energy of the data packet, that is, the total energy in the frequency band range of the current data power frequency range. For the key data of the mortar mixer, its energy is generally concentrated in the power frequency, while periodic interference is distributed in other specific frequency points. At the same time, when the key data fluctuates, the main frequency energy will show a certain diffusion in the spectrum, so its spectrum peak is wider, while the periodic interference is relatively stable, so its peak spectrum is sharper. The power distribution of the data packet signal at each frequency can reflect the possibility that it is key data; therefore, for this data packet, its second confidence is obtained through its frequency domain power frequency energy ratio and spectrum peak dispersion.

[0059] Specifically, an FFT transform is performed on the data in a data packet to obtain the power spectrum power frequency energy, total power spectrum energy, maximum power spectrum density within the power frequency range, and any power spectrum density within the power frequency range of the data packet; the power spectrum power frequency energy of the data packet is compared with the total power spectrum energy to obtain the frequency domain power frequency energy ratio corresponding to the data packet; the maximum power spectrum density within the power frequency range is compared with the sum of any power spectrum density within the power frequency range to obtain a first ratio; the difference between the first preset value and the first ratio is calculated to obtain the spectral peak width of the fluctuating data in the data packet, and multiplied by the frequency domain power frequency energy ratio corresponding to the data packet to obtain the second confidence level of the data packet.

[0060] The specific calculation model of the second confidence level is:

[0061] ,

[0062] Where Cfi represents the second confidence of the i-th data packet; is the power spectrum power frequency energy of the data packet, that is, the total energy of the frequency band range of the current data power frequency range, Ei is the total power spectrum energy; Pmax (f) is the maximum power spectrum density within the power frequency range, and P (f) is any power spectrum density within the power frequency range; Indicates the power frequency energy ratio in the frequency domain corresponding to the data packet. The larger the power frequency energy ratio, the more likely the data fluctuation contained in the data packet is critical data, because the energy of critical data is concentrated in the power frequency. represents the first ratio, Indicates the spectral peak width of the fluctuation data in the data packet. The wider the spectral peak, the larger the denominator, that is, the larger the whole result. The wider the corresponding spectrum peak, the more likely the fluctuation data in the data packet is critical data. The first preset value is 1.

[0063] Furthermore, by combining the first and second confidence scores for a data packet and comprehensively considering both the time and frequency domain characteristics of the data packet, the credibility of the data packet can be more accurately determined. Specifically, the first and second confidence scores for a data packet are added and normalized to obtain the comprehensive confidence score for the data packet. This allows the comprehensive confidence score for each data packet to be obtained.

[0064] Step S5, determining the number of retransmissions of a data packet according to the comprehensive confidence, criticality and preset number of retransmissions of the data packet; and performing data transmission based on the number of retransmissions of each data packet of each production operation data.

[0065] After obtaining the criticality of each data packet and combining it with its corresponding confidence level, the importance of the data packet can be obtained. After setting the maximum and minimum retransmission times in turn, the adaptive retransmission times can be obtained according to the importance of each data packet, ensuring the accuracy of data transmission while avoiding waste of resources.

[0066] The number of retransmissions for a data packet is determined based on the packet's comprehensive confidence, criticality, and a preset number of retransmissions. Specifically, the preset number of retransmissions is set, including a minimum number of retransmissions and a maximum number of retransmissions. An adjustment factor is obtained by multiplying the product of the comprehensive confidence and criticality of the data packet and normalizing the result. The difference between the maximum and minimum number of retransmissions is multiplied by the adjustment factor and rounded to the nearest integer to obtain an adjustment step. The sum of the minimum number of retransmissions and the adjustment step is the number of retransmissions for the data packet.

[0067] The calculation model for the number of retransmissions of a data packet is as follows:

[0068] ,

[0069] Where Zi is the number of retransmissions corresponding to the i-th data packet; Zmin and Zmax are the minimum and maximum retransmission times (reference values ​​are 1-7 times, which can also be set according to actual conditions); Ci is the comprehensive confidence of the i-th data packet, and Round represents the rounding function. Indicates that a data packet has a minimum number of retransmissions. The number of retransmissions increases with the importance of the data packet. More important data is retransmitted more often. norm indicates a normalization operation.

[0070] After obtaining the number of retransmissions for a data packet as above, the method for obtaining the number of retransmissions for other data packets is similar. After obtaining the number of retransmissions corresponding to all data packets, the production and operation data of the mortar mixer collected on that day can be transmitted; by adjusting the number of retransmissions corresponding to each data packet, not only the packet loss rate of important data is reduced, but also the overall data transmission efficiency is greatly improved, and the accuracy and integrity of data transmission are further improved, which can better assist relevant personnel in understanding the current production and operation status of the mortar mixer, grasping the performance degradation of the mortar mixer, and performing necessary maintenance on the mortar mixer in advance.

[0071] In summary, the purpose of this application is to optimize the number of retransmissions of data packets corresponding to various production and operation data of a mortar mixer. First, the criticality of the data packet is obtained based on the degree of fluctuation of the data in each data packet. Then, the frequency domain and time domain characteristics of the data in the data packet are combined to eliminate the influence of periodic interference (such as other equipment such as welding machines on construction sites) and sudden interference (such as metal collisions) to obtain its comprehensive confidence. The criticality and comprehensive confidence of the data packet and the preset number of retransmissions are combined to obtain the number of retransmissions of the data packet. The number of retransmissions of each data packet is obtained in turn, and then the production and operation data of the mortar mixer collected on that day are transmitted.

[0072] It should be noted that the order in which the embodiments of the present invention are described above is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential sequence shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0073] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments.

[0074] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for collecting and transmitting production and operation data of a mortar mixer, characterized in that: The method includes: Obtain different types of production and operation data of mortar mixers, and obtain data packages corresponding to various production and operation data; Obtaining the criticality of a data packet based on the sum of the standard deviation of data in a data packet of production operation data and the difference between two adjacent data, including: obtaining the difference between the latter data and the previous data of every two adjacent data in a data packet, calculating the average of the differences, recording the average change rate, and multiplying the standard deviation of the data in the data packet by the average change rate of the data packet to obtain the criticality of the data packet; Draw a data change curve based on the data in the data packet, and obtain a sub-curve based on the peak points and valley points on the data change curve; obtain a first confidence level of a data packet of a type of production operation data based on the sub-curve corresponding to the data packet; Calculating a second confidence level of the data packet based on frequency domain characteristics of data in the data packet; obtaining a comprehensive confidence level of the data packet based on the first and second confidence levels; Determining the number of retransmissions of a data packet based on the comprehensive confidence, criticality, and preset number of retransmissions of the data packet, including: the preset number of retransmissions includes a minimum number of retransmissions and a maximum number of retransmissions, obtaining the product of the comprehensive confidence and criticality of the data packet and normalizing the product to obtain an adjustment factor, multiplying the difference between the maximum number of retransmissions and the minimum number of retransmissions by the adjustment factor, and rounding the difference to obtain an adjustment step, where the sum of the minimum number of retransmissions and the adjustment step is the number of retransmissions of the data packet; Data transmission is performed based on the number of retransmissions per data packet for each type of production run data.

2. A method for collecting and transmitting production and operation data of a mortar mixer according to claim 1, characterized in that: The step of obtaining a sub-curve according to the peak points and valley points on the data change curve includes: The curve between two adjacent valley points on the data change curve is a sub-curve.

3. A method for collecting and transmitting production and operation data of a mortar mixer according to claim 1, characterized in that: The obtaining a first confidence level of a data packet according to a sub-curve corresponding to a data packet of production operation data includes: Obtain the difference between the value of a peak point on a sub-curve and the mean of all data on the sub-curve, and compare it with the rated maximum value of the production operation data to obtain a fluctuation characteristic value; the difference between the first preset value and the fluctuation characteristic value is the smoothness of the sub-curve; set a first ratio and a second ratio, and multiply the value of the peak point of the sub-curve by the first ratio and the second ratio respectively to obtain a first data value and a second data value; obtain the duration corresponding to the sub-curve on the sub-curve according to the first data value and the second data value; multiply the smoothness and duration of the sub-curve to obtain a time domain characteristic value of the sub-curve; and calculate the average of the time domain characteristic values ​​of all sub-curves corresponding to the data packet to obtain a first confidence level of the data packet.

4. A method for collecting and transmitting production and operation data of a mortar mixer according to claim 3, characterized in that: The step of obtaining a duration corresponding to the sub-curve on the sub-curve according to the first data value and the second data value includes: On the sub-curve, the first data point equal to the first data value is obtained in time sequence and recorded as the starting point. The first data point equal to the second data value is obtained and recorded as the ending point. The duration between the starting point and the ending point is the duration of the sub-curve.

5. The method for collecting and transmitting production and operation data of a mortar mixer according to claim 1, characterized in that: The calculating the second confidence level of the data packet based on the frequency domain characteristics of the data in the data packet includes: Perform FFT transformation on the data in a data packet to obtain the power spectrum power frequency energy, total power spectrum energy, maximum power spectrum density within the power frequency range, and any power spectrum density within the power frequency range of the data packet; compare the power spectrum power frequency energy of the data packet with the total power spectrum energy to obtain the frequency domain power frequency energy ratio corresponding to the data packet; compare the maximum power spectrum density within the power frequency range with the sum of any power spectrum densities within the power frequency range to obtain a first ratio; calculate the difference between the first preset value and the first ratio to obtain the spectral peak width of the fluctuating data in the data packet, and multiply it by the frequency domain power frequency energy ratio corresponding to the data packet to obtain the second confidence level of the data packet.

6. A method for collecting and transmitting production and operation data of a mortar mixer according to claim 1, characterized in that: The step of obtaining a comprehensive confidence level of the data packet based on the first and second confidence levels comprises: The first confidence level and the second confidence level of a data packet are added and normalized to obtain the comprehensive confidence level of the data packet.

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