Special monitoring method for commercial concrete special warehouse based on Internet of Things

Abstract

The invention relates to the technical field of commercial concrete station monitoring management, and discloses a commercial concrete special warehouse special monitoring method based on the Internet of Things, and the method comprises the steps: collecting a plurality of material images and corresponding humidity information at different positions in a current warehouse space, and the storage environment information before the transportation of the materials in the current warehouse space, and the transportation route environment information; extracting a first typical feature of each material image, and extracting a second typical feature in storage environment information before material transportation and route environment information during transportation in the current storage space; matching the second typical feature with the first typical feature and the humidity information, and establishing an influence degree model of the second typical feature on the first typical feature and the humidity information; and monitoring the current state of the materials in the special bin by using the influence degree model. Therefore, the quality of the material in the stock bin can be monitored, and the reason for abnormity is found out and an alarm is given when abnormity is monitored, so that a worker can conveniently and timely find out the quality problem and find out the reason for timely adjustment, and the influence on the quality of commercial concrete is avoided.

Description

Technical Field

[0001] The present application relates to the technical field of monitoring and management of commercial concrete stations, for example, to a dedicated monitoring method for commercial concrete warehouses based on the Internet of Things. Background Art

[0002] During the aggregate transportation process, each loader is required to load the aggregates in the corresponding storage bin and unload the aggregates to the corresponding aggregate bin loading port. However, during the storage and transportation of aggregates, the humidity of the environment as well as dust, dirt, etc. will affect the quality of the aggregates, thereby affecting the subsequent batching of commercial concrete and further affecting the quality of commercial concrete.

[0003] Therefore, there is an urgent need for a dedicated monitoring method for commercial concrete warehouses based on the Internet of Things to monitor the quality of aggregates to avoid the quality of aggregates affecting the quality of subsequent commercial concrete.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] In order to provide a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. The summary is not an extensive review, nor is it intended to identify key / critical components or delineate the scope of protection of these embodiments, but rather serves as a prelude to the detailed description that follows.

[0006] The embodiment of the present disclosure provides a dedicated monitoring method for a commercial concrete warehouse based on the Internet of Things, including:

[0007] Collect multiple material images and corresponding humidity information at different locations in the current warehouse, as well as storage environment information of the materials in the current warehouse before transportation and route environment information during transportation;

[0008] Extracting the first typical feature of each material image and extracting the second typical feature of the storage environment information of the material in the current warehouse before transportation and the route environment information during transportation;

[0009] Matching the second typical feature with the first typical feature and humidity information, and establishing an influence model of the second typical feature on the first typical feature and humidity information;

[0010] The influence model is used to monitor whether the first typical characteristics and humidity information of the materials in the special warehouse are within the corresponding thresholds. If not, an alarm is triggered.

[0011] In one embodiment, collecting multiple material images and corresponding humidity information at different positions in the current warehouse, as well as storage environment information of the materials in the current warehouse before transportation and route environment information during transportation, includes:

[0012] Cameras and humidity sensors are set at different longitudinal height positions and the feed inlet in the current bin to record the feed images and corresponding humidity at different longitudinal height positions and the feed inlet in real time;

[0013] Determine whether the currently fed materials are from the same batch based on the feed image and corresponding humidity;

[0014] In the case of the same batch, record the storage environment information of the current batch of materials before transportation and the route environment information during transportation;

[0015] In the case of different batches, each batch is distinguished according to the time interval, and the storage environment information of each batch of materials before transportation and the route environment information during transportation are recorded.

[0016] In one embodiment, the Internet of Things-based dedicated monitoring method for commercial concrete warehouses also includes: in the case of different batches, recording material images at different longitudinal height positions before and after each batch enters the warehouse.

[0017] In one embodiment, extracting the first typical feature of each material image includes:

[0018] A convolutional neural network is used to extract multiple first features of each material image;

[0019] Calculate the ratio of each first feature to the overall area of ​​the corresponding material image;

[0020] Counting the proportion of each first feature of all material images to generate a first typical feature, where the first typical feature includes a plurality of first features and the total amount of the corresponding first features;

[0021] Among them, if the materials are from different batches, the total amount of the first feature of the current batch is the difference between the results corresponding to the material images at different longitudinal height positions before and after the current batch enters the warehouse.

[0022] In one embodiment, matching the second typical feature with the first typical feature and the humidity information includes:

[0023] Matching the second typical feature with a plurality of preset feature information, wherein the plurality of preset feature information includes an image of the current feature and possible effects of the corresponding image on the first typical feature;

[0024] Collecting the second typical features after successful matching and using the corresponding feature information as the information of the second typical features;

[0025] The second typical feature is matched with the first typical feature and the humidity information according to the information of the second typical feature, that is, the first typical feature or the humidity information may correspond to one or more second typical features.

[0026] In one embodiment, establishing an influence model of the second typical feature on the first typical feature and humidity information includes:

[0027] Collect multiple sets of first typical features, humidity information and corresponding second typical features and divide them into a training set, a test set and a validation set;

[0028] The influence model is trained using the training set; wherein the influence model includes the influence of the second typical feature on whether the first feature in the first typical feature is generated or not under different circumstances, the influence on the total amount of the first feature, and the influence on humidity;

[0029] Use the test set to test and adjust the influence model;

[0030] The influence model is verified using the verification set, and the influence model is stored after the verification is completed.

[0031] In one embodiment, the influence model is used to monitor the current status of materials in the dedicated warehouse, including:

[0032] Real-time judgment of whether the first typical feature of the material in the current bin is within the threshold;

[0033] When it is not within the threshold, the second typical feature of the storage environment information before the transportation of the material in the current warehouse and the route environment information during transportation is collected;

[0034] Use the impact model to infer the second typical feature of the problem and issue an alarm.

[0035] In one embodiment, the influence model of the current warehouse also provides the influence model of the next warehouse with the storage environment information before the material is transported to the next warehouse.

[0036] The embodiment of the present disclosure provides a dedicated monitoring method for commercial concrete warehouse based on the Internet of Things, which can achieve the following technical effects:

[0037] It can monitor the quality of materials in the silo, find out the cause of the abnormality and alarm when it is detected, so that the staff can find quality problems in time, find out the cause and make timely adjustments to avoid affecting the quality of commercial concrete.

[0038] The above general description and the following description are exemplary and explanatory only and are not intended to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] One or more embodiments are exemplarily described by corresponding drawings, which do not limit the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements, and the drawings do not constitute a scale limitation, and wherein:

[0040] Figure 1It is a schematic diagram of a dedicated monitoring method for commercial concrete warehouse based on the Internet of Things provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0041] In order to be able to understand the features and technical contents of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not used to limit the embodiments of the present disclosure. In the following technical description, for the convenience of explanation, a full understanding of the disclosed embodiments is provided through multiple details. However, one or more embodiments can still be implemented without these details. In other cases, to simplify the drawings, well-known structures and devices can be simplified for display.

[0042] The terms "first", "second", etc. in the specification and claims of the embodiments of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged where appropriate, so that the embodiments of the embodiments of the present disclosure described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions.

[0043] Unless otherwise stated, the term "plurality" means two or more.

[0044] In the embodiment of the present disclosure, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B indicates: A or B.

[0045] The term "and / or" is a description of the association relationship between objects, indicating that three relationships can exist. For example, A and / or B means: A or B, or, A and B.

[0046] The term "correspondence" may refer to an association relationship or a binding relationship. The correspondence between A and B means that there is an association relationship or a binding relationship between A and B.

[0047] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present disclosure may be combined with each other.

[0048] During the aggregate transportation process, each loader is required to load the aggregates in the corresponding storage bin and unload the aggregates to the corresponding aggregate bin loading port. However, during the storage and transportation of aggregates, the humidity, temperature, dust, dirt, etc. of the environment will affect the quality of the aggregates, thereby affecting the subsequent batching of commercial concrete and further affecting the quality of commercial concrete.

[0049] Therefore, the embodiments of the present disclosure provide a dedicated monitoring method for a commercial concrete warehouse based on the Internet of Things to monitor the quality of aggregates to prevent the quality of aggregates from affecting the quality of subsequent commercial concrete.

[0050] Combination Figure 1 As shown, the dedicated monitoring method for commercial concrete warehouse based on the Internet of Things provided by the embodiment of the present disclosure includes:

[0051] S101, collecting multiple material images and corresponding humidity information at different positions in the current warehouse, as well as storage environment information of the materials in the current warehouse before transportation and route environment information during transportation.

[0052] S102, extracting the first typical feature of each material image and extracting the second typical feature of the storage environment information of the material in the current warehouse before transportation and the route environment information during transportation.

[0053] S103, matching the second typical feature with the first typical feature and the humidity information, and establishing an influence model of the second typical feature on the first typical feature and the humidity information.

[0054] S104, using the influence model to monitor whether the first typical characteristics and humidity information of the materials in the special warehouse are within the corresponding thresholds, and if not, an alarm is issued.

[0055] The dedicated monitoring method for commercial concrete silos based on the Internet of Things provided in the embodiments of the present disclosure can monitor the quality of materials in the silo, find out the cause of the abnormality and issue an alarm when an abnormality is detected, thereby facilitating staff to promptly discover quality problems, find out the cause and make timely adjustments to avoid affecting the quality of the commercial concrete.

[0056] In this embodiment, humidity information is actually one of the first typical features. Since humidity information is difficult to be extracted from an image, it can be measured using a sensor.

[0057] Optionally, multiple material images and corresponding humidity information at different positions in the current warehouse, as well as storage environment information of the materials in the current warehouse before transportation and route environment information during transportation are collected, including: setting cameras and humidity sensors at different longitudinal height positions and the feed port in the current warehouse and recording the feed images and corresponding humidity at different longitudinal height positions and the feed port in real time; judging whether the materials currently being fed are from the same batch based on the feed images and corresponding humidity; if they are from the same batch, recording the storage environment information of the current batch of materials before transportation and route environment information during transportation; if they are from different batches, distinguishing each batch based on the time interval, and recording the storage environment information of each batch of materials before transportation and route environment information during transportation.

[0058] Optionally, the Internet of Things-based dedicated monitoring method for commercial concrete warehouses also includes: in the case of different batches, recording material images at different longitudinal height positions before and after each batch enters the warehouse.

[0059] The quality of aggregates may vary from batch to batch, and the factors that affect the quality of aggregates during transportation may be different. Therefore, distinguishing batches of aggregates can help to intuitively and conveniently find the corresponding reasons when there are quality problems with aggregates, so that the staff can make adjustments.

[0060] Optionally, extracting the first typical feature of each material image includes: extracting multiple first features of each material image using a convolutional neural network; calculating the ratio of each first feature to the overall area of ​​the corresponding material image; and generating a first typical feature by counting the ratios of the first features of all material images, wherein the first typical feature includes the total amount of multiple first features and the corresponding first features; wherein, if the materials are from different batches, the total amount of the first features of the current batch is the difference between the results corresponding to the material images at different longitudinal height positions before and after the current batch is put into storage.

[0061] The area ratio calculation algorithm can intuitively reflect the proportion of each first sign and estimate the total amount of each first feature. By clarifying the changes in the types and total amount of the first features in multiple sets of data, the relationship between the first feature and the corresponding second typical feature can be quickly obtained during the subsequent training of the influence model, which is convenient for the subsequent training of the influence model.

[0062] Optionally, matching the second typical feature with the first typical feature and humidity information includes: matching the second typical feature with multiple preset feature information, wherein the preset multiple feature information includes an image of the current feature and the impact that the corresponding image may have on the first typical feature; collecting the second typical feature after successful matching and using the corresponding feature information as information of the second typical feature; matching the second typical feature with the first typical feature and humidity information according to the information of the second typical feature, that is, the first typical feature or humidity information can correspond to one or more second typical features.

[0063] For example, if the aggregate is coarse aggregate, it is detected in the image that the coarse aggregate contains mud and sand, and stones that do not meet the size. Then when extracting the first typical feature, the mud and sand and stones that do not meet the size are recorded as the first feature, and the corresponding content is recorded. Correspondingly, in the storage environment information before transportation and the route environment information during transportation, the second typical feature may be that the initial storage location itself contains mud or stones, the transportation vehicle contains mud or stones, and the mud in the air caused by environmental reasons such as wind or construction. Then the second typical feature here is that the initial storage location itself contains mud or stones and the corresponding amount that may be caused, the transportation vehicle and the corresponding amount that may be caused, and the relevant meteorological information and construction site information / equipment and the corresponding amount that may be caused. Then match the second typical feature with the first typical feature. The first typical feature can correspond to multiple second typical features, that is, there may be multiple scenarios where the second typical features exist during storage and transportation.

[0064] By clarifying the characteristic information of the second typical feature and the relationship between the humidity information and the first typical feature, the changing pattern of the second typical feature and its relationship with the first typical feature can be quickly obtained during the subsequent training of the influence model, which facilitates the subsequent training of the influence model.

[0065] Optionally, a model of the influence of the second typical feature on the first typical feature and humidity information is established, including: collecting multiple groups of first typical features, humidity information and corresponding second typical features and dividing them into training sets, test sets and validation sets; using the training set to train the influence model; wherein the influence model includes the influence of the second typical feature on whether the first feature in the first typical feature is generated or not under different circumstances, as well as the influence on the total amount of the first feature and the influence on humidity; using the test set to test and adjust the influence model; using the validation set to verify the influence model, and storing the influence model after the verification is completed.

[0066] Optionally, the influence model is used to monitor the current status of materials in the special warehouse, including: real-time determination of whether the first typical feature of the materials in the current warehouse is within the threshold; when it is not within the threshold, collecting the second typical feature of the storage environment information of the materials in the current warehouse before transportation and the route environment information during transportation; using the influence model to infer the second typical feature of the problem and issue an alarm.

[0067] It can monitor the quality of materials in the silo, find out the cause of the abnormality and alarm when it is detected, so that the staff can find quality problems in time, find out the cause and make timely adjustments to avoid affecting the quality of commercial concrete.

[0068] Optionally, the influence model of the current warehouse also provides the influence model of the next warehouse with storage environment information before the material is transported to the next warehouse.

[0069] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure so that those skilled in the art can practice them. Other embodiments may include structural, logical, electrical, process and other changes. The embodiments represent only possible changes. Unless explicitly required, separate components and functions are optional, and the order of operation may vary. The parts and features of some embodiments may be included in or replace the parts and features of other embodiments. Moreover, the words used in this application are only used to describe the embodiments and are not used to limit the claims. As used in the description of the embodiments and the claims, unless the context clearly indicates, the singular forms of "a", "an" and "the" are intended to include plural forms as well. Similarly, the term "and / or" as used in this application refers to any and all possible combinations of listings containing one or more associated ones. In addition, when used in the present application, the term "comprise" and its variants "comprises" and / or comprising refer to the presence of stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or groups thereof. In the absence of further restrictions, the elements defined by the sentence "comprising a ..." do not exclude the presence of other identical elements in the process, method or device comprising the elements. In this article, each embodiment may focus on the differences from other embodiments, and the same and similar parts between the various embodiments may refer to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, then the relevant parts can refer to the description of the method part.

[0070] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software may depend on the specific application and design constraints of the technical solution. The technicians may use different methods for each specific application to implement the described functions, but such implementations should not be considered to exceed the scope of the embodiments of the present disclosure. The technicians may clearly understand that, for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above may refer to the corresponding processes in the aforementioned method embodiments, and will not be repeated here.

[0071] The flowchart and block diagram in the accompanying drawings show the possible architecture, function and operation of the system, method and computer program product according to the embodiment of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of the code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. In the description corresponding to the flowchart and the block diagram in the accompanying drawings, the operations or steps corresponding to different boxes can also occur in a different order from the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, which can depend on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A dedicated monitoring method for commercial concrete warehouse based on the Internet of Things, comprising: Collect multiple material images and corresponding humidity information at different locations in the current warehouse, as well as storage environment information of the materials in the current warehouse before transportation and route environment information during transportation; Extracting the first typical feature of each material image and extracting the second typical feature of the storage environment information of the material in the current warehouse before transportation and the route environment information during transportation; Matching the second typical feature with the first typical feature and humidity information, and establishing an influence model of the second typical feature on the first typical feature and humidity information; The influence model is used to monitor whether the first typical characteristics and humidity information of the materials in the special warehouse are within the corresponding thresholds. If not, an alarm is triggered.

2. The method according to claim 1, characterized in that Collect multiple material images and corresponding humidity information at different locations in the current warehouse, as well as the storage environment information of the materials in the current warehouse before transportation and the route environment information during transportation, including: Cameras and humidity sensors are set at different longitudinal height positions and the feed inlet in the current bin to record the feed images and corresponding humidity at different longitudinal height positions and the feed inlet in real time; Determine whether the currently fed materials are from the same batch based on the feed image and corresponding humidity; In the case of the same batch, record the storage environment information of the current batch of materials before transportation and the route environment information during transportation; In the case of different batches, each batch is distinguished according to the time interval, and the storage environment information of each batch of materials before transportation and the route environment information during transportation are recorded.

3. The method according to claim 2, characterized in that Also includes: In the case of different batches, record the material images at different longitudinal height positions before and after each batch enters the warehouse.

4. The method according to claim 3, characterized in that: Extract the first typical features of each material image, including: A convolutional neural network is used to extract multiple first features of each material image; Calculate the ratio of each first feature to the overall area of ​​the corresponding material image; Counting the proportion of each first feature of all material images to generate a first typical feature, where the first typical feature includes a plurality of first features and the total amount of the corresponding first features; Among them, if the materials are from different batches, the total amount of the first feature of the current batch is the difference between the results corresponding to the material images at different longitudinal height positions before and after the current batch enters the warehouse.

5. The method according to claim 1, characterized in that Matching the second typical characteristic with the first typical characteristic and the humidity information includes: Matching the second typical feature with a plurality of preset feature information, wherein the plurality of preset feature information includes an image of the current feature and possible effects of the corresponding image on the first typical feature; Collecting the second typical features after successful matching and using the corresponding feature information as the information of the second typical features; The second typical feature is matched with the first typical feature and the humidity information according to the information of the second typical feature, that is, the first typical feature or the humidity information may correspond to one or more second typical features.

6. The method according to claim 5, characterized in that Establishing the influence model of the second typical feature on the first typical feature and humidity information, including: Collect multiple sets of first typical features, humidity information and corresponding second typical features and divide them into a training set, a test set and a validation set; The influence model is trained using the training set; wherein the influence model includes the influence of the second typical feature on whether the first feature in the first typical feature is generated or not under different circumstances, the influence on the total amount of the first feature, and the influence on humidity; Use the test set to test and adjust the influence model; The influence model is verified using the verification set, and the influence model is stored after the verification is completed.

7. The method according to claim 1, characterized in that Use the influence model to monitor whether the first typical characteristics and humidity information of the materials in the special warehouse are within the corresponding thresholds. If not, an alarm will be issued, including: Real-time judgment of whether the first typical feature of the material in the current bin is within the threshold; When it is not within the threshold, the second typical feature of the storage environment information before the transportation of the material in the current warehouse and the route environment information during transportation is collected; Use the impact model to infer the second typical feature of the problem and issue an alarm.

8. The method according to claim 1, characterized in that The influence model of the current warehouse also provides the storage environment information of the material before it is transported to the next warehouse for the influence model of the next warehouse.

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