Classification method, processor, classification device and engineering equipment for working condition data

Abstract

The application relates to the field of engineering machinery, and discloses a classification method for working condition data, a processor, a classification device and engineering equipment. The classification method for working condition data comprises the following steps: obtaining multiple working condition data uploaded by engineering equipment within a preset time period, wherein the working condition data comprises an upload time stamp and an upload construction quantity; performing initial classification on the multiple working condition data according to time intervals between multiple upload time stamps and a preset time interval, so as to obtain multiple working condition data sets; determining a set construction quantity of each working condition data set; and performing reclassification on the working condition data set according to the set construction quantity, so as to determine whether the working condition data set is a construction process data set or a non-construction process data set. The utilization rate of the working condition data can be improved by adopting the scheme.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of engineering machinery, in particular to a classification method for working condition data, a processor, a classification device and an engineering equipment. BACKGROUND

[0002] With the rapid development of the economy, the construction behavior of engineering equipment (for example, concrete pumping equipment) is no longer time-sensitive, and the actual pumping performance of the concrete pumping equipment cannot be displayed to customers to meet their needs. In the prior art, the concrete pumping equipment only performs simple calculation on the collected data in the controller or directly uploads it to the data platform for storage, so as to facilitate subsequent query and analysis of the working condition data. However, the construction process is not effectively divided, and therefore the utilization rate of the working condition data is not high. SUMMARY

[0003] The present application aims to provide a classification method for working condition data, a processor, a classification device, an engineering equipment and a storage medium, so as to solve the problem of low utilization rate of working condition data in the prior art.

[0004] To achieve the above-mentioned purpose, the present application provides a classification method for working condition data, which comprises:

[0005] obtaining a plurality of working condition data uploaded by the engineering equipment within a preset time period, wherein the working condition data comprises an upload timestamp and an upload construction quantity;

[0006] preliminarily classifying the plurality of working condition data according to the time interval between the plurality of upload timestamps and a preset time interval, to obtain a plurality of working condition data sets;

[0007] determining a set construction quantity of each working condition data set;

[0008] reclassifying the working condition data set according to the set construction quantity, to determine whether the working condition data set is a construction process data set or a non-construction process data set.

[0009] In the embodiment of the present application, the preset time interval comprises a first preset time interval; the preliminary classification of the plurality of working condition data according to the time interval between the plurality of upload timestamps and the preset time interval, to obtain the plurality of working condition data sets, comprises: sorting the plurality of working condition data in ascending order according to the time sequence of the upload timestamps; determining the time interval between the upload timestamps in each adjacent working condition data; and preliminarily classifying the plurality of working condition data according to the time interval and the first preset time interval, to obtain the plurality of working condition data sets.

[0010] In the embodiment of the present application, the preliminary classification of the plurality of working condition data according to the time interval and the first preset time interval comprises: comparing the time interval with the first preset time interval; and in the case that the time interval is greater than the first preset time interval, dividing two working condition data involved by the time interval into different working condition data sets.

[0011] In the embodiment of the present application, the working condition data comprises a position of the engineering equipment; the preset time interval comprises a second preset time interval, wherein the second preset time interval is less than the first preset time interval; and the preliminary classification of the plurality of working condition data according to the time interval between the plurality of upload time stamps and the preset time interval to obtain the plurality of working condition data sets comprises: sorting the plurality of working condition data in ascending order according to the time sequence of the upload time stamps; determining a distance interval between the positions and a time interval between the upload time stamps of adjacent working condition data; and preliminarily classifying the plurality of working condition data according to the distance interval, the time interval and the second preset time interval to obtain the plurality of working condition data sets.

[0012] In the embodiment of the present application, the preliminary classification of the plurality of working condition data according to the distance interval, the time interval and the second preset time interval comprises: comparing the distance interval with a preset distance interval and the time interval with the second preset time interval; and in the case that the distance interval is greater than the preset distance interval and the time interval is greater than the second preset time interval, dividing two working condition data involved by the distance interval into different working condition data sets.

[0013] In the embodiment of the present application, the reclassification of the working condition data set according to the set construction quantity to determine whether the working condition data set is a construction process data set or a non-construction process data set comprises: comparing the set construction quantity with a preset construction quantity threshold; and in the case that the set construction quantity is less than the preset construction quantity threshold, determining that the working condition data set is a non-construction process data set.

[0014] In the embodiment of the present application, the working condition data further comprises an idle time of the engineering equipment; and the classification method further comprises: determining a total idle time of the non-construction process data set; and reclassifying the non-construction process data set according to the total idle time to determine whether the non-construction process data set is a shutdown data set or a non-shutdown data set.

[0015] In the embodiment of the present application, the reclassification of the non-construction process data set according to the total idle time to determine whether the non-construction process data set is a shutdown data set or a non-shutdown data set comprises: in the case that the total idle time is equal to zero, determining that the non-construction process data set is a shutdown data set.

[0016] In the embodiment of the present application, the non-construction process data set is reclassified according to the total idle time to determine whether the non-construction process data set is a shutdown data set or a non-shutdown data set, including: in the case that the total idle time is not equal to zero, determining that the non-construction process data set is a non-shutdown data set.

[0017] In the embodiment of the present application, further comprising: in the case that the total construction quantity is greater than or equal to the preset construction quantity threshold, determining that the working condition data set is a construction process data set.

[0018] In the embodiment of the present application, the working condition data further includes walking time of the engineering equipment; the classification method further includes: determining total walking time of the construction process data set; and reclassifying the construction process data set according to the total walking time to determine whether the construction process data set is a mobile construction data set or a non-mobile construction data set.

[0019] In the embodiment of the present application, the construction process data set is reclassified according to the total walking time to determine whether the construction process data set is a mobile construction data set or a non-mobile construction data set, including: in the case that the total walking time is equal to zero, determining that the construction process data set is a non-mobile construction data set.

[0020] In the embodiment of the present application, the construction process data set is reclassified according to the total walking time to determine whether the construction process data set is a mobile construction data set or a non-mobile construction data set, including: in the case that the total walking time is not equal to zero, determining that the construction process data set is a mobile construction data set.

[0021] The second aspect of the present application provides a processor configured to execute the classification method for working condition data according to the above.

[0022] The third aspect of the present application provides a classification device for working condition data, including: the processor according to the above.

[0023] The fourth aspect of the present application provides an engineering equipment, including: a working condition data detection device; and the classification device for working condition data according to the above.

[0024] The fifth aspect of the present application provides a machine readable storage medium, the machine readable storage medium has instructions stored thereon, the instructions, when executed by a processor, cause the processor to execute the classification method for working condition data according to the above.

[0025] The above technical solution acquires multiple operational data points uploaded by engineering equipment within a preset time period. These operational data points include upload timestamps and uploaded construction volume. The data is initially categorized based on the time intervals between upload timestamps and a preset time interval to obtain multiple operational data sets. Then, the aggregate construction volume of each operational data set is determined. Finally, the operational data sets are recategorized based on the aggregate construction volume to determine whether they are construction process data sets or non-construction process data sets. This technical solution, by initially categorizing operational data based on the time intervals between upload timestamps to obtain multiple operational data sets, and further recategorizing them based on aggregate construction volume, accurately reflects the actual construction process of the engineering equipment, improving the utilization rate of operational data. By dividing the data into construction and non-construction processes, users can accurately understand the construction status of the engineering equipment for evaluation.

[0026] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0027] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the following detailed description to explain the invention, but do not constitute a limitation thereof. In the drawings:

[0028] Figure 1 The schematic diagram illustrates a flowchart of a method for classifying operating condition data according to an embodiment of the present invention;

[0029] Figure 2 The schematic diagram illustrates a flowchart of a method for classifying operating condition data according to another embodiment of the present invention;

[0030] Figure 3 The schematic diagram illustrates a hierarchical model of the construction saturation evaluation system architecture in one embodiment of the present invention. Detailed Implementation

[0031] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0032] Figure 1 The illustration schematically shows a flowchart of a method for classifying operating condition data according to an embodiment of the present invention. For example... Figure 1 As shown, in this embodiment of the invention, a method for classifying operating condition data is provided. Taking the application of this method to a processor as an example, the classification method may include the following steps:

[0033] In step S102, multiple working condition data uploaded by the engineering equipment in a preset time period is acquired, wherein the working condition data comprises an upload timestamp and an upload construction party amount.

[0034] It can be understood that the engineering equipment is equipment performing a construction action on a construction site, for example, a pumping device. The working condition data is construction data uploaded by the engineering equipment (for example, a concrete pumping device) to a processor, which can include but is not limited to a server. The upload timestamp is a specific time when the engineering equipment uploads the construction data to the processor. The upload construction party amount is the cumulative construction amount uploaded by the engineering equipment up to the current time, which can include but is not limited to construction volume or construction weight, etc. The preset time period is a time period set in advance for which the working condition data needs to be classified, for example, one month.

[0035] Specifically, the processor can acquire multiple working condition data uploaded by the engineering equipment (for example, a concrete pumping device) in a preset time period (for example, one month), wherein the working condition data comprises an upload timestamp and an upload construction party amount of the working condition data.

[0036] In step S104, the multiple working condition data is preliminarily classified according to a time interval between the multiple upload timestamps and a preset time interval, to obtain multiple working condition data sets.

[0037] It can be understood that the preset time interval is a time interval set in advance as a reference basis for dividing the working condition data sets. The working condition data set is a set or interval obtained after the working condition data is preliminarily classified according to the time interval.

[0038] Specifically, after the processor acquires the multiple working condition data in the preset time period, the time interval between the upload timestamps corresponding to the multiple working condition data is determined, so that the multiple working condition data is preliminarily classified according to the time interval and the preset time interval, to obtain the multiple working condition data sets. For example, the working condition data with a time interval greater than the preset time interval can be divided into different working condition data sets, and further, the working condition data with a time interval less than or equal to the preset time interval can be divided into the same working condition data set.

[0039] In step S106, a set construction party amount of each working condition data set is determined.

[0040] It can be understood that the set construction party amount is the cumulative construction party amount of each working condition data set. Since the value of the upload construction party amount generally increases with time, the specific calculation method of the set construction party amount is usually the last upload construction party amount of the working condition data set minus the first upload construction party amount, to obtain the set construction party amount of the working condition data set.

[0041] Specifically, after obtaining the multiple working condition data sets, the processor can determine the set construction quantity of each working condition data set according to the uploaded construction quantity of each working condition data obtained in advance. Specifically, the uploaded construction quantity contained in the last working condition data (i.e., the working condition data with the largest upload timestamp in the working condition data set) of the working condition data set can be subtracted from the uploaded construction quantity contained in the first working condition data (i.e., the working condition data with the smallest upload timestamp in the working condition data set), so as to obtain the set construction quantity of the working condition data set.

[0042] In step S108, the working condition data set is reclassified according to the set construction quantity to determine whether the working condition data set is a construction process data set or a non-construction process data set.

[0043] It can be understood that the construction process data set is a set of working condition data in the construction process or construction state. The non-construction process data set is a set of working condition data in the non-construction process or non-construction state.

[0044] Specifically, after obtaining the set construction quantity corresponding to each working condition data set, the processor can reclassify the working condition data set according to the set construction quantity, so as to determine whether the working condition data set is a construction process data set or a non-construction process data set. That is, the processor also classifies the working condition data set to determine whether the working condition data set is a construction process data set or a non-construction process data set.

[0045] The above classification method for working condition data obtains multiple working condition data uploaded by the engineering equipment in a preset time period, wherein the working condition data includes an upload timestamp and an upload construction quantity, and performs initial classification on the multiple working condition data according to the time interval between the multiple upload timestamps and a preset time interval to obtain multiple working condition data sets, and then determines the set construction quantity of each working condition data set, and reclassifies the working condition data set according to the set construction quantity to determine whether the working condition data set is a construction process data set or a non-construction process data set. The above technical solution classifies the working condition data according to the time interval between the upload timestamps in the working condition data to obtain multiple working condition data sets, and further reclassifies the working condition data sets according to the set construction quantity to determine whether each working condition data set is a construction process data set or a non-construction process data set. The classification of working condition data can accurately reflect the real construction process of the engineering equipment, improve the utilization rate of working condition data, and facilitate users to accurately understand the construction situation of the engineering equipment by dividing the construction process and the non-construction process, so as to evaluate the engineering equipment.

[0046] In one embodiment, the preset time interval includes a first preset time interval; and the multiple working condition data are preliminarily classified according to the time intervals between the multiple upload time stamps and the preset time interval to obtain multiple working condition data sets, including: sorting the multiple working condition data in ascending order according to the time sequence of the upload time stamps; determining the time intervals between the upload time stamps in each adjacent working condition data; and preliminarily classifying the multiple working condition data according to the time intervals and the first preset time interval to obtain the multiple working condition data sets.

[0047] It can be understood that the first preset time interval is a preset time interval, which can be adjusted according to actual conditions.

[0048] Specifically, the processor can sort the multiple working condition data in ascending order according to the time sequence of the upload time stamps, further determine the time intervals between the upload time stamps in each adjacent working condition data, and then preliminarily classify the multiple working condition data according to the time intervals and the first preset time interval to obtain the multiple working condition data sets.

[0049] In the embodiment of the application, by setting the first preset time interval, the multiple working condition data are classified according to the time intervals, that is, the working condition data are classified according to the working time information of the engineering equipment, which can improve the accuracy of the working condition data classification.

[0050] In one embodiment, the preliminarily classifying the multiple working condition data according to the time intervals and the first preset time interval includes: comparing the time intervals with the first preset time interval; and in the case that the time interval is greater than the first preset time interval, dividing the two working condition data involved in the time interval into different working condition data sets.

[0051] Specifically, the processor can compare the time intervals between the upload time stamps in each adjacent working condition data with the first preset time interval, and when the time interval is greater than the first preset time interval, the processor divides the two working condition data involved in the time interval into different working condition data sets. Further, when the time interval is less than or equal to the first preset time interval, the processor divides the two working condition data involved in the time interval into the same working condition data set.

[0052] In one embodiment, the working condition data comprises a location of the engineering equipment; the preset time interval comprises a second preset time interval, wherein the second preset time interval is smaller than the first preset time interval; and the preliminary classification of the plurality of working condition data according to the time interval between the plurality of upload time stamps and the preset time interval to obtain the plurality of working condition data sets comprises: sorting the plurality of working condition data in ascending order according to the time sequence of the upload time stamps; determining the time interval between the upload time stamps and the distance interval between the locations of adjacent working condition data; and preliminarily classifying the plurality of working condition data according to the distance interval, the time interval and the second preset time interval to obtain the plurality of working condition data sets.

[0053] It can be understood that the second preset time interval is a preset time interval, and the value of the time interval is smaller than the first preset time interval, that is, the value is generally small, which can be adjusted according to actual conditions.

[0054] Specifically, the processor can sort the plurality of working condition data in ascending order according to the time sequence of the upload time stamps, further determine the time interval between the upload time stamps and the distance interval between the locations of adjacent working condition data, and preliminarily classify the plurality of working condition data according to the time interval, the distance interval and the second preset time interval to obtain the plurality of working condition data sets.

[0055] In one embodiment, the preliminary classification of the plurality of working condition data according to the distance interval, the time interval and the second preset time interval comprises: comparing the distance interval and the preset distance interval and the time interval and the second preset time interval; and in the case that the distance interval is greater than the preset distance interval and the time interval is greater than the second preset time interval, dividing the two working condition data involved in the distance interval into different working condition data sets.

[0056] Specifically, the processor can compare the time interval between the upload time stamps and the second preset time interval in adjacent working condition data, compare the distance interval between the locations and the preset distance interval in adjacent working condition data, and when the time interval is greater than the second preset time interval and the distance interval is greater than the preset distance interval, the processor divides the two working condition data involved in the distance interval (or the time interval) into different working condition data sets, otherwise, the processor divides the two working condition data involved in the distance interval (or the time interval) into different working condition data sets.

[0057] In the embodiment of the present application, the plurality of working condition data are classified according to the distance interval by setting the preset distance interval, so that the working condition data are classified according to the specific position information of the engineering equipment, and the second preset time interval is set to prevent the processor from mistakenly dividing two working condition data with a distance interval greater than the preset distance interval but a time interval less than the second preset time interval into different working condition data sets, thereby improving the accuracy of working condition data classification.

[0058] In one embodiment, the working condition data set is reclassified according to the set construction quantity to determine whether the working condition data set is a construction process data set or a non-construction process data set, including: comparing the set construction quantity with a preset construction quantity threshold; and in the case that the set construction quantity is less than the preset construction quantity threshold, determining that the working condition data set is a non-construction process data set.

[0059] It can be understood that the preset construction quantity threshold is a preset reference threshold of the set construction quantity, which can be set according to actual conditions.

[0060] Specifically, the processor can compare the set construction quantity (e.g., set construction volume) of each working condition data set with the preset construction quantity threshold, and in the case that the set construction quantity of the working condition data set is less than the preset construction quantity threshold, the processor can determine that the working condition data set is a non-construction process data set. Further, the working condition data in the non-construction process data set can represent a state that the engineering equipment (e.g., pumping product) is resting or debugging or cleaning, etc.

[0061] In one embodiment, the working condition data further include an idling time of the engineering equipment; the classification method further includes: determining a total idling time of the non-construction process data set; and reclassifying the non-construction process data set according to the total idling time to determine whether the non-construction process data set is a resting data set or a non-resting data set.

[0062] It can be understood that, with respect to the idle time, the minimum rotating speed for maintaining the stable operation of the engine is referred to as the idle speed, the idle speed is a working condition of the engineering equipment, the engine is in idle when idling, and the gear is in neutral at this time. When the engine is running, if the accelerator pedal is completely released, the engine is in an idle state at this time. The engine runs under no load, only to overcome the frictional resistance of its own internal parts, and does not output power externally. Therefore, the time for maintaining the stable operation of the engine is the idle time. The total idle time is the sum of the idle times contained in each working condition data in the working condition data set. The non-construction process can include various non-construction states, for example, the engineering equipment (such as pumping products) is in a state of rest or is in a state of debugging or is in a state of cleaning, and the like, and therefore, the non-construction process data set can be divided into a rest data set and a non-rest data set. The rest data set is a set of working condition data representing the non-construction state of the engineering equipment in the rest. The non-rest data set is a set of working condition data representing the non-construction state of the engineering equipment not in the rest, for example, can include a state in which the engineering equipment is in debugging or cleaning, and the like.

[0063] Specifically, after determining that the working condition data set is the non-construction process data set, the processor can determine the total idle time of the non-construction process data set, and further classify the non-construction process data set according to the total idle time, so as to determine that the non-construction process data set is the rest data set or the non-rest data set.

[0064] In one embodiment, the re-classification of the non-construction process data set according to the total idle time to determine that the non-construction process data set is the rest data set or the non-rest data set comprises: in the case that the total idle time is equal to zero, determining that the non-construction process data set is the rest data set.

[0065] Specifically, the processor can determine whether the total idle time of the non-construction process data set is zero, and in the case that the total idle time is determined to be zero, the processor can directly determine that the non-construction process data set corresponding to the total idle time is the rest data set, that is, can represent a state in which the engineering equipment (such as pumping products) is in rest, and the like.

[0066] In one embodiment, the re-classification of the non-construction process data set according to the total idle time to determine that the non-construction process data set is the rest data set or the non-rest data set comprises: in the case that the total idle time is not equal to zero, determining that the non-construction process data set is the non-rest data set.

[0067] Specifically, the processor can determine whether the total idle time of the non-construction process data set is zero, and in a case where it is determined that the total idle time is not zero, the processor can directly determine that the non-construction process data set corresponding to the total idle time is the non-stop data set, that is, it can represent that the construction equipment (such as a pumping product) is in a state of debugging or cleaning and the like.

[0068] In one embodiment, further comprising: in a case where the aggregate construction volume of the data set is greater than or equal to a preset construction volume threshold, determining that the working condition data set is a construction process data set.

[0069] Specifically, the processor can compare the aggregate construction volume (such as the aggregate construction volume) of each working condition data set with a preset construction volume threshold, and in a case where it is determined that the aggregate construction volume of the working condition data set is greater than or equal to the preset construction volume threshold, the processor can determine that the working condition data set is a construction process data set, that is, it can represent that the construction equipment (such as a pumping product) is in a construction process or a construction state.

[0070] In one embodiment, the working condition data further comprises walking time of the construction equipment; the classification method further comprises: determining total walking time of the construction process data set; and reclassifying the construction process data set according to the total walking time to determine that the construction process data set is a mobile construction data set or a non-mobile construction data set.

[0071] It can be understood that the walking time of the construction equipment is also the driving time. The total walking time is the sum of the walking time contained in each working condition data in each working condition data set. According to whether there is mobile construction in the construction process, the construction process data set can be further divided into a mobile construction data set or a non-mobile construction data set. The mobile construction process data set is a set of working condition data of the construction process in which the construction equipment is in a mobile state. The non-mobile construction process data set is a set of working condition data of the construction process in which the construction equipment is in a non-mobile state.

[0072] Specifically, after determining that the working condition data set is a construction process data set, the processor can further determine the total walking time of the construction process data set, so as to further classify the non-construction process data set according to the total walking time to determine that the construction process data set is a mobile construction data set or a non-mobile construction data set.

[0073] In one embodiment, reclassifying the construction process data set according to the total walking time to determine that the construction process data set is a mobile construction data set or a non-mobile construction data set comprises: in a case where the total walking time is equal to zero, determining that the construction process data set is a non-mobile construction data set.

[0074] Specifically, the processor can determine whether the total walking time of the construction process data set is zero, and in a case where it is determined that the total walking time is equal to zero, the processor can determine that the construction process data set is a non-mobile construction data set.

[0075] In one embodiment, reclassifying the construction process data set according to the total walking time to determine whether the construction process data set is a mobile construction data set or a non-mobile construction data set comprises: in a case where the total walking time is not equal to zero, determining that the construction process data set is a mobile construction data set.

[0076] Specifically, the processor can determine whether the total walking time of the construction process data set is zero, and in a case where it is determined that the total walking time is not equal to zero, the processor can determine that the construction process data set is a mobile construction data set.

[0077] The existing construction process division of engineering equipment mostly takes a natural day as the division basis, that is, one construction per day. However, taking a pumping device as an example, the pumping device often works continuously for several days in actual work, and there may be small-range mobile construction. Therefore, the embodiment of the present application proposes a construction process division mode of engineering equipment within a specified time, taking the time interval and distance interval of adjacent working condition data as the construction process division basis, and taking the single construction volume as the judgment basis of whether to construct. Taking a pumping device as an example, as shown in FIG. 1, the embodiment of the present application can be analyzed according to the following specific steps: Figure 2

[0078] (1) Under the GPS84 coordinate, the time interval T and the distance interval D between consecutive time points are calculated.

[0079] (2) Taking the time interval greater than or equal to the time interval threshold T0 (i.e. the first preset time interval) or the distance interval greater than or equal to the distance threshold D0 (i.e. the preset distance interval) and the time interval greater than or equal to the time interval threshold T1 (i.e. the second preset time interval) as the judgment standard, wherein T0>T1, all data are divided into N intervals, and the single construction volume (interval construction volume difference P) is calculated.

[0080] The specific calculation method of the time threshold, the distance threshold and the single construction volume threshold can be as follows: first, according to the user experience, set the minimum change threshold E of the variable X, and difference the input variable X data X to obtain diff X Xdiff X >E, and then take the intermediate threshold tdiff X ; second, calculate the number of data corresponding to each tdiff X threshold, obtain the threshold event number tdiff Xcnt , and take the threshold event number tdiff Xcnt ​Recorded as T, and then again differential event number change slope, recorded as T diff ; then T diff Smooth processing, take N T diff The average value of T diffavg Sequence; finally take the minimum value of T diffavgd Corresponding index minus the smoothing value N, take the corresponding threshold value is the target threshold TS. Wherein N value according to take the middle threshold number half minus 1.

[0081] (3), again whether the construction process is construction, if the interval idling time (DT) is equal to 0, it is stop work rest; if the interval idling time (DT) is not equal to 0, and the interval pumping volume is greater than or equal to the single construction volume threshold (P0) square, the process is construction process; if the interval idling time (DT) is not equal to 0, and the interval pumping volume is less than the single construction volume threshold (P0) square, the process is construction process. The specific flow is shown in Figure 2 .

[0082] The specific application of the embodiment of the application can be as follows:

[0083] 1. Construction range analysis

[0084] Through construction process division, the construction process (recorded as Y) and non construction process (recorded as X) in a period of time can be obtained.

[0085] For non construction process, all non construction processes with interval data number greater than 10 are selected, if the time interval of point X i And the time interval of the previous and subsequent construction time points is greater than the time threshold, it can be considered as a stop point, if the distance between two stop point positions is less than D0 meters, it can be considered as the same place, so the frequency of each position (latitude and longitude) can be calculated. Here, the highest frequency is the commonly used stop point, and the rest is the temporary stop point.

[0086] Suppose that in a specified period of time (at least one month) in construction, there are X stop points and Y construction points, the distances of X stop points and Y construction points are calculated respectively, the closer distance is a class, for example, in Y1 and X distance, the distance of X1 is the smallest, Y1 belongs to the construction radiation range of X1, and the rest is the same. According to the latitude and longitude of the stop point and the latitude and longitude of the construction point, the equipment construction coverage range can be drawn on the map.

[0087] 2. Construction label establishment

[0088] The construction behavior label is objectively existing, complex and variable, and these quality factors have great fuzziness. Therefore, based on the single construction model, the monthly data is taken as the basis, the point, line and surface are started from, and the multi-dimensional construction behavior label is finally formed according to the expert opinion.

[0089] Taking single construction as the starting point, considering the equipment carrying capacity, that is, considering the single construction quantity, construction time and pumping time ratio, the construction intensity label is finally formed.

[0090] Taking time series as the timeline, considering the equipment persistence, that is, considering the construction frequency, construction days and working time ratio, the construction frequency label is finally formed.

[0091] Taking the construction site as the construction surface, considering the equipment influence, that is, considering the construction area, construction distance, construction county number and construction site number, the construction breadth is finally formed.

[0092] Table 1 Construction behavior label

[0093]

[0094] 3, Construction saturation analysis

[0095] According to the above construction behavior label content, the construction intensity, construction frequency and construction breadth are established. The construction saturation of the first label is shown in the following formula: Figure 3 The construction saturation evaluation model is a two-level three-layer structure model, and the target layer of the model is the construction saturation score S. The first index factor set S=(S1, S2, S3), wherein S i is the i-th sub-factor set in the first index. The second index factor set S i =(S i1 , S i2 ,…,S im ), wherein S im is the m-th element in the i-th sub-factor set in the second index.

[0096] The construction saturation evaluation method adopts the percentage system, which is equivalent to 101 levels of 0-100. Therefore, we need to establish a membership function for each index.

[0097] Combined with user opinions and based on the relevant index data distribution of the big data platform, the membership functions of construction quantity, construction time, pumping time ratio, construction frequency, construction days, working time ratio, construction area, construction distance, construction site number and construction county number are confirmed.

[0098] Considering the meaning of the index and the relationship between the indexes, different weighting methods are used for two levels of indexes. For the first index, they are equally important, so the objective weighting method is used, that is, the weight is calculated according to the information possessed by the current sample itself. For the second index, the subjective weighting method is used, that is, the weight is assigned according to the subjective information of the evaluators (such as expert experience). The specific examples are as follows:

[0099] (1) Subjective weighting method

[0100] The subjective weighting method includes various methods, and the present embodiment uses the analytic hierarchy process for illustration. First, a judgment matrix (denoted as A) of the secondary indexes under the construction intensity is constructed, as shown in Table 2 below: ij The value filled in by the expert, which represents S i The importance of S j , and the size is d or d = 1, 2, … 9 (1-9 ratio method), wherein o ij = 1 / o ji ).

[0101] Table 2 Two-by-two comparison matrix table of indexes of target layer

[0102]

[0103] Secondly, the data of each column of the evaluation matrix A is normalized, and finally the maximum eigenvalue λ max and the corresponding eigenvector are calculated according to the matrix eigenvalue calculation method.

[0104] Then, the consistency ratio CR of the judgment index for constructing the eigenvalue is calculated:

[0105]

[0106] wherein, n is the number of indexes, and RI is the average random consistency index, the value of which can be obtained by referring to the table.

[0107] Finally, when CR < 0.1, A meets the consistency test, and the weights of the factors are W = (w1, w2, …, w n ) T , wherein C = (C1, C2, …, C n ) T , and C is the eigenvector corresponding to the maximum eigenvalue.

[0108] Similarly, the weights of the secondary indexes under the construction frequency and the construction breadth can be obtained.

[0109] (2) Objective weighting method

[0110] The objective weighting method includes various methods, and the present embodiment uses the entropy weight method for illustration. First, an initial evaluation matrix A is constructed according to the construction intensity, the construction frequency, the construction breadth, and the sample size M, and then the data of each column of A is normalized to obtain a normalized matrix B = (b ij ) M×N , wherein N is the number of indexes.

[0111] Then the information entropy e of construction intensity, construction frequency and construction breadth are calculated respectively j .

[0112]

[0113] wherein, Ln represents the natural logarithm with base e.

[0114] Finally, the weight w of each index is calculated j .

[0115]

[0116] wherein, d j = 1-e j

[0117] Table 3 weight of construction behavior

[0118]

[0119] Finally, the construction saturation score S is obtained as:

[0120]

[0121] wherein t is the number of primary indexes, u is the number of secondary indexes contained in the primary index. S iu is the value after membership transformation of the secondary index, w iu is the weight of the secondary index, w i is the weight of the primary index. Refer to Table 3.

[0122] From the construction saturation analysis, the equipment construction portrait can be established, and the construction conditions of the same equipment at different times and different equipment at the same time can be compared and analyzed, as follows:

[0123] (1) If the construction intensity of a certain equipment is large, the construction frequency is high, and the construction breadth is wide, it means that the customer has a large construction coverage area and has a certain influence.

[0124] (2) If the construction intensity of a certain equipment is large, but the construction frequency is low, and the construction breadth is narrow, it means that the customer has a small construction coverage area and has a fixed construction point.

[0125] (3) If the construction intensity of a certain equipment is small, the construction frequency is high, and the construction breadth is wide, it means that the construction site of the customer is unstable, and the construction resources are not fixed.

[0126] (4) If the construction intensity of a certain equipment is small, and the construction frequency is low, and the construction breadth is narrow, it means that the construction site of the customer is extremely unstable, and the construction resources are lacking, and the influence of the customer needs to be strengthened.

[0127] In summary, the method for classifying working condition data provided by the embodiment has the following advantages: the mechanism of engineering equipment is combined with big data, the construction process of the equipment is divided by the threshold optimization method, and the actual construction process is accurately reflected; by dividing each construction process, the user can accurately understand the construction situation of the engineering equipment, and the engineering equipment can be conveniently evaluated.

[0128] The embodiment provides a processor configured to execute the method for classifying working condition data according to the above-described embodiments.

[0129] It can be understood that the processor can include but is not limited to a server.

[0130] The embodiment provides a device for classifying working condition data, including a processor, wherein the processor is configured to: acquire a plurality of working condition data uploaded by an engineering equipment in a preset time period, wherein the working condition data includes an upload timestamp and an upload construction quantity; preliminarily classify the plurality of working condition data according to a time interval between a plurality of upload timestamps and a preset time interval to obtain a plurality of working condition data sets; determine a set construction quantity of each working condition data set; and reclassify the working condition data sets according to the set construction quantity to determine whether the working condition data sets are construction process data sets or non-construction process data sets.

[0131] The device for classifying working condition data classifies the working condition data according to the time interval between the upload timestamps in the working condition data to obtain a plurality of working condition data sets, and further reclassifies the working condition data sets according to the set construction quantity to determine whether each working condition data set is a construction process data set or a non-construction process data set, so that the classification of the working condition data can accurately reflect the actual construction process of the engineering equipment, improve the utilization rate of the working condition data, and facilitate the user to accurately understand the construction situation of the engineering equipment, so as to evaluate the engineering equipment.

[0132] In an embodiment, the preset time interval includes a first preset time interval; the processor is further configured to: sort the plurality of working condition data in ascending order according to time sequence of the uploading time stamps; determine time intervals between the uploading time stamps of adjacent working condition data; and preliminarily classify the plurality of working condition data according to the time intervals and the first preset time interval to obtain a plurality of working condition data sets.

[0133] In an embodiment, the processor is further configured to: compare the time intervals with the first preset time interval; and in a case that the time interval is greater than the first preset time interval, divide two working condition data involved in the time interval into different working condition data sets.

[0134] In an embodiment, the working condition data includes a position of the engineering equipment; the preset time interval includes a second preset time interval, wherein the second preset time interval is less than the first preset time interval; the processor is further configured to: sort the plurality of working condition data in ascending order according to time sequence of the uploading time stamps; determine distance intervals between the positions and time intervals between the uploading time stamps of adjacent working condition data; and preliminarily classify the plurality of working condition data according to the distance intervals, the time intervals and the second preset time interval to obtain a plurality of working condition data sets.

[0135] In an embodiment, the processor is further configured to: compare the distance intervals with a preset distance interval and compare the time intervals with a second preset time interval; and in a case that the distance interval is greater than the preset distance interval and the time interval is greater than the second preset time interval, divide two working condition data involved in the distance interval into different working condition data sets.

[0136] In an embodiment, the processor is further configured to: compare the set contractor amount with a preset contractor amount threshold; and in a case that the set contractor amount is less than the preset contractor amount threshold, determine that the working condition data set is a non-construction process data set.

[0137] In an embodiment, the working condition data further includes an idling time of the engineering equipment; the processor is further configured to: determine a total idling time of the non-construction process data set; and reclassify the non-construction process data set according to the total idling time to determine that the non-construction process data set is a shutdown data set or a non-shutdown data set.

[0138] In an embodiment, the processor is further configured to: in a case that the total idling time is equal to zero, determine that the non-construction process data set is the shutdown data set.

[0139] In an embodiment, the processor is further configured to: in a case that the total idling time is not equal to zero, determine that the non-construction process data set is the non-shutdown data set.

[0140] In one embodiment, the processor is further configured to determine that the working condition data set is a construction process data set when the total construction quantity is greater than or equal to a preset construction quantity threshold.

[0141] In one embodiment, the working condition data further comprises walking time of the engineering equipment; the processor is further configured to determine total walking time of the construction process data set; and reclassify the construction process data set according to the total walking time to determine that the construction process data set is a mobile construction data set or a non-mobile construction data set.

[0142] In one embodiment, the processor is further configured to determine that the construction process data set is a non-mobile construction data set when the total walking time is equal to zero.

[0143] In one embodiment, the processor is further configured to determine that the construction process data set is a mobile construction data set when the total walking time is not equal to zero.

[0144] The embodiment of the present application provides an engineering equipment, comprising: a working condition data detection device; and a classification device for working condition data according to the above-mentioned embodiments.

[0145] It can be understood that the working condition data detection device can be used to detect or collect data such as position and single construction quantity, idling time and walking time of the engineering equipment.

[0146] The embodiment of the present application provides a machine readable storage medium, which stores instructions, and the instructions make the processor execute the classification method for working condition data according to the above-mentioned embodiments when executed by the processor.

[0147] The preferred embodiments of the present application are described in detail above with reference to the drawings, but the present application is not limited to the specific details in the above-mentioned embodiments, and various simple modifications can be made to the technical solutions of the present application within the technical concept of the present application, and these simple modifications all belong to the protection scope of the present application.

[0148] In addition, it should be noted that each specific technical feature described in the above-mentioned specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, various possible combinations are not described again by the present application.

[0149] In addition, various different embodiments of the present application can also be combined in any appropriate manner, as long as it does not deviate from the technical concept of the present application, and it should be considered as disclosed by the present application.

Claims

1. A method for classifying operating condition data, characterized by, The classification method comprises: Obtaining multiple working condition data uploaded by an engineering equipment within a preset time period, wherein the working condition data comprises an upload timestamp, an upload construction quantity, an idle time of the engineering equipment, and a walking time of the engineering equipment, the engineering equipment comprises a concrete pumping equipment, and the construction quantity comprises a pumping quantity; Preliminary classifying the multiple working condition data according to a time interval between multiple upload timestamps and a preset time interval, to obtain multiple working condition data sets; Determining a set construction quantity of each working condition data set; Re-classifying the working condition data set according to the set construction quantity, to determine whether the working condition data set is a construction process data set or a non-construction process data set; The classification method further comprises: Determining a total idle time of the non-construction process data set and a total walking time of the construction process data set; In the case that the total idle time is equal to zero, determining that the non-construction process data set is a shutdown data set; In the case that the total idle time is not equal to zero, determining that the non-construction process data set is a non-shutdown data set; In the case that the total walking time is equal to zero, determining that the construction process data set is a non-mobile construction data set; In the case that the total walking time is not equal to zero, determining that the construction process data set is a mobile construction data set.

2. The classification method of claim 1, wherein, The preset time interval comprises a first preset time interval; and the preliminary classifying the multiple working condition data according to a time interval between multiple upload timestamps and a preset time interval, to obtain multiple working condition data sets, comprises: Sorting the multiple working condition data in ascending order according to the time sequence of the upload timestamps; Determining a time interval between the upload timestamps in adjacent working condition data; Preliminary classifying the multiple working condition data according to the time interval and the first preset time interval, to obtain multiple working condition data sets.

3. The classification method of claim 2, wherein, The preliminary classifying the multiple working condition data according to the time interval and the first preset time interval comprises: Comparing the time interval and the first preset time interval; In the case that the time interval is greater than the first preset time interval, dividing two working condition data involved by the time interval into different working condition data sets.

4. The classification method of claim 2, wherein, The working condition data comprises a position of the engineering equipment; and the preset time interval comprises a second preset time interval, wherein the second preset time interval is smaller than the first preset time interval; The preliminary classifying the multiple working condition data according to a time interval between multiple upload timestamps and a preset time interval, to obtain multiple working condition data sets, comprises: Sorting the multiple working condition data in ascending order according to the time sequence of the upload timestamps; Determining a time interval between the upload timestamps and a distance interval between the positions in adjacent working condition data; Preliminary classifying the multiple working condition data according to the distance interval, the time interval, and the second preset time interval, to obtain multiple working condition data sets.

5. The classification method of claim 4, wherein, The preliminary classification of the multiple pieces of working condition data according to the distance interval, the time interval, and the second preset time interval comprises: comparing the distance interval with a preset distance interval and the time interval with a second preset time interval; in a case where the distance interval is greater than the preset distance interval and the time interval is greater than the second preset time interval, dividing the two pieces of working condition data involved in the distance interval into different working condition data sets.

6. The classification method of claim 1, wherein, The reclassification of the working condition data set according to the set construction quantity comprises: comparing the set construction quantity with a preset construction quantity threshold value; in a case where the set construction quantity is less than the preset construction quantity threshold value, determining that the working condition data set is a non-construction process data set.

7. The classification method of claim 6, wherein, Further comprising: in a case where the set construction quantity is greater than or equal to the preset construction quantity threshold value, determining that the working condition data set is a construction process data set.

8. A processor, comprising: The processor is configured to perform the classification method for working condition data according to any one of claims 1 to 7.

9. An apparatus for classifying operating condition data, characterized by The processor according to claim 8. The working condition data detection device comprises:

10. An engineering apparatus characterised in that, and The classification device for working condition data according to claim 9. The instructions, when executed by the processor, cause the processor to perform the classification method for working condition data according to any one of claims 1 to 7. ​ 11. A machine-readable storage medium having stored thereon instructions, the instructions being executable by a machine to cause the machine to: ​

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