29 results about "Ready mixed concrete" patented technology

To provide a pressure feeding technique capable of maintaining quality without interfering with a reinforcing bar and a form by lifting a pressure feeding pipe by a crane, since there is a regulation for placing ready-mixed concrete within a limited time in concrete placing work.SOLUTION: In the concrete placing method, rubber hoses 2A and 2B are connected to both ends of a suspension pipe 10 to which a plurality of pressure feed pipes 1 are connected, one rubber hose 2A of the suspension pipe 10 is connected to a pressure feed pipe 12 from a pump vehicle on the ground, and the other rubber hose 2B is discharged toward a place to be placed, and the suspension pipe 10 is lifted by using a crane 30 for lifting materials installed on the site, and is freely moved and pressure-fed in a suspended state to prevent interference with a reinforcement and a form.SELECTED DRAWING: Figure 1

To improve prediction accuracy of a prediction model constructed by machine learning.SOLUTION: Acquiring color captured image data obtained by capturing an image of an aggregate, generating input image data by sequentially performing first processing for grayscaling, second processing for darkening, and third processing for binarization on the captured image data, acquiring input information including the input image data, and using a prediction model constructed in advance by machine learning so as to output a physical property value of the aggregate according to an input of the input information, A prediction step of acquiring the physical property value corresponding to the input information acquired in the second acquisition step.SELECTED DRAWING: Figure 5

This invention proposes a carbonized calcined coal gangue solid waste-based cementitious material and its preparation method, belonging to the technical field of coal gangue solid waste utilization. The raw materials for the carbonized coal gangue-based cementitious material of this invention include 30-70 parts of calcined coal gangue powder, 20-50 parts of premixed concrete waste, 10-20 parts of cement, 0-5 parts of gypsum, 0.5-1.0 parts of surfactant, and 0.1-0.5 parts of organic amine. First, the coal gangue solid waste is crushed, ground, and calcined. Then, it is mixed with premixed concrete waste, ordinary silicate cement, gypsum, surfactant, and organic amine. Finally, industrial carbon dioxide is introduced and the mixture is dried to obtain the final product. The performance indicators of the carbonized calcined coal gangue solid waste-based cementitious material of this invention are comparable to those of PO 42.5 grade cement, realizing the large-scale utilization of coal gangue solid waste and the preparation of low-carbon cementitious materials. The process is simple and has practical application value.

To provide a concrete pump vehicle that can be towed in a stable condition. [Solution] The concrete pump vehicle comprises a frame, a towed section provided at one end of the frame in the front-rear direction, a pump unit mounted on the frame for pumping ready-mix concrete, a drive section mounted on the frame for driving the pump unit, and a running section rotatably attached to the frame, wherein the drive section is positioned between the towed section and the running section in the front-rear direction.

This invention relates to the field of construction management technology and discloses a method for managing the pouring of ready-mixed concrete on construction sites, including the following steps: Step 1: Data Acquisition Stage: S1.1 By scanning the QR code on the concrete raw material packaging, the type, batch number, and production date information of cement, aggregate, fly ash, and admixtures are automatically entered. This invention constructs a full-dimensional data acquisition network by deploying temperature and humidity sensors, slump sensors, pressure sensors, and vibration sensors. Combined with LoRa wireless transmission technology, data integrity is achieved: temperature data is collected every minute (initial setting stage), and slump data is collected every 5 minutes (final setting stage), forming a continuous temperature curve; rapid response to anomalies: abnormal data is reconstructed through cubic spline interpolation to ensure monitoring continuity; decision support: a 128×128 pixel infrared thermal image and a T×N sensor matrix are provided for the CNN model, improving the accuracy of quality prediction.

The utility model provides a kind of image acquisition equipment, belong to concrete transportation monitoring technical field.The equipment includes shell, transmission assembly, driving part and acquisition component.Shell includes the first installation surface and the second installation surface oppositely arranged along first direction.Transmission assembly includes first transmission part and second transmission part, and first transmission part is slidably connected to the first installation surface, and second transmission part is slidably connected to the second installation surface.Driving part is respectively abutted with first, second transmission part along the opposite sides of first direction, to make when driving part rotates, first, second transmission part can move in opposite direction along second direction.Acquisition component is connected with second transmission part.When acquisition component is in standby state, first transmission part can be covered and set in the opening of first installation surface, when acquisition component is in working state, acquisition component can pass through opening and gather image.The image acquisition equipment of the utility model can monitor the state of ready-mixed concrete in real time during transportation.

To improve prediction accuracy when predicting quality by using a prediction model constructed by machine learning.SOLUTION: A quality prediction method of an aggregate includes a first acquisition step of acquiring color captured image data obtained by imaging an aggregate to be evaluated, a pre-processing step of generating input image data by gray-scaling the captured image data, a second acquisition step of acquiring input information including the input image data, a prediction step of acquiring a physical property value corresponding to input information acquired in the second acquisition step using a prediction model constructed in advance so as to output the physical property value of the aggregate according to an input of the input information, and a construction step of constructing the prediction model by machine learning based on training data. IB [lx] is 0.2 times or more of IA [lx] and 5 times or less of IA [lx], where IA [lx] is the illuminance among the environmental conditions when imaging the aggregate for training, and IB [lx] is the illuminance among the environmental conditions when imaging the aggregate to be evaluated.SELECTED DRAWING: Figure 12

To improve the prediction accuracy when predicting the quality of ready-mixed concrete using a predictive model. [Solution] A method for predicting the quality of ready-mixed concrete, comprising: a construction step of constructing a predictive model by machine learning based on training data including multiple datasets; an acquisition step of acquiring multiple feature quantities obtained when manufacturing ready-mixed concrete using a mixer; and a prediction step of using the predictive model to acquire a predicted quality value corresponding to the multiple feature quantities acquired in the acquisition step, wherein each of the multiple datasets is associated with multiple feature quantities and the correct quality value, and the multiple feature quantities include one or more load feature quantities related to the power load value of the mixer when mixing concrete materials or stirring ready-mixed concrete, and in the construction step, a predictive model is constructed such that one or more feature quantities selected from the multiple feature quantities are associated with the predicted quality value by a decision tree.

The invention belongs to the field of cement admixtures, and provides a green and environment-friendly water reducing agent material and application thereof.The green and environment-friendly water reducing agent material is prepared by compounding core-shell structure nanoparticles (the particle size D50 is 80-200 nm, and the shell thickness is 5-25 nm) with polycarboxylic acid macromolecules as cores and silicon dioxide as shells, the polycarboxylic acid macromolecules and sodium gluconate; high-solid low-viscosity preparation with the solid content being 40-50% and the viscosity being 50-200 mPa.s is achieved, the initial fluidity of neat paste is larger than or equal to 260 mm and the retention rate in 30 min is larger than or equal to 90% when the water-binder ratio is 0.28-0.32 and the mixing amount is 0.2-1.5%, and the water reducing rate is larger than or equal to 25% and the slump retention rate in 60 min is larger than or equal to 85% when concrete is prepared with the water-binder ratio being 0.28-0.40. The technical contradictions of high water-reducing rate and high fluidity keeping coupling, high solid content-low viscosity and nanoparticle dispersion stability synergy and high early strength and long construction slump retaining time balance are synchronously solved, and the water-reducing agent is suitable for the fields of premixed concrete and cast-in-place concrete.

To improve prediction accuracy of a prediction model constructed by machine learning.SOLUTION: Acquiring color captured image data obtained by capturing an image of an aggregate, generating input image data by sequentially performing first processing for grayscaling and second processing for performing edge detection on the captured image data, acquiring input information including the input image data, and using a prediction model constructed in advance by machine learning so as to output a physical property value of the aggregate according to an input of the input information, A prediction step of acquiring the physical property value corresponding to the input information acquired in the second acquisition step.SELECTED DRAWING: Figure 5

The present application relates to the technical field of remote control, in particular to a ready-mixed concrete multi-station remote centralized control system and a control method, the control system comprising a control node arranged at each production line of a mixing station; a remote centralized control module comprising an engineer station computer and n control units, each control unit being used to control the control nodes of at least two production lines; a communication module used to communicatively connect the control nodes arranged in the mixing station in a region to the same network to realize collaborative control of multiple control nodes; the remote centralized control module and the control nodes arranged at the production lines in the mixing station perform data interaction through the communication module, and the engineer station computer uniformly manages and schedules the control units and the control nodes to dynamically manage and schedule the collaborative production of any two production lines in the region. The present application realizes collaborative production of multiple mixing stations, optimizes resource allocation and production scheduling, improves the working environment, saves costs and improves production efficiency.

The application discloses a kind of pre-mixed concrete intelligent sampling and working performance monitoring device, including power system, sampling system, test system, determination system and cleaning system;Wherein sampling system is set to the test system directly above, wherein sampling system includes rounded trapezoidal sampling bucket with gate, test system is located below the sampling bucket for receiving and sample recovery, and the determination system is used to detect the slump and spread of concrete sample in the sampling system.The application realizes the automatic sampling and working performance real-time monitoring of pre-mixed concrete in the production process, is convenient to operate, effectively reduces the work pressure of staff, and guarantees product quality, promotes the development of concrete quality control application field, lays a good foundation for intelligent monitoring of building materials, and has significant practical engineering value.

To improve prediction accuracy of a prediction model constructed by machine learning.SOLUTION: A first acquisition step of acquiring color captured image data obtained by capturing an image of a bone material; and a second acquisition step of sequentially performing a first process of converting the captured image data into grayscale data and a second process of binarizing the captured image data by Otsu's binarization on the captured image data. A quality prediction method of an aggregate, comprising a pre-processing step of generating input image data, a second acquisition step of acquiring input information including the input image data, and a prediction step of acquiring a physical property value according to the input information acquired in the second acquisition step by using a prediction model constructed in advance by machine learning so as to output the physical property value of the aggregate according to an input of the input information.SELECTED DRAWING: Figure 5

An advanced concrete drum cleaning system that includes a dynamically controlled oscillating nozzle, a boom zeroing function, a breakaway mounting plate, and a hydraulic assembly for enhanced safety. The system features a motor-driven nozzle having a stroke length that can be dynamically adjusted in real-time using feedback from an encoder. A controller with a user interface allows operators to precisely control and monitor the nozzle's position. Additionally, the system includes a boom zeroing function, enabling the operator to set and maintain a reference position for the boom within the concrete drum. The hydraulic assembly, consisting of lifting and lowering components, allows the nozzle housing to quickly disengage from obstructions to prevent damage. Moreover, the breakaway mounting plate provides a means for limiting damage when the nozzle housing is unable to disengage from obstructions.

To improve the prediction accuracy when using predictive models to forecast the quality of ready-mixed concrete. [Solution] A method for predicting the quality of ready-mixed concrete, comprising: a construction step of constructing a predictive model by machine learning based on training data including multiple datasets; an acquisition step of acquiring multiple feature quantities obtained when manufacturing ready-mixed concrete using a mixer; and a prediction step of using the predictive model to acquire a predicted quality value corresponding to the multiple feature quantities acquired in the acquisition step, wherein each of the multiple datasets is associated with multiple feature quantities and the correct quality value, and the multiple feature quantities include one or more load feature quantities related to the power load value of the mixer when mixing concrete materials or stirring ready-mixed concrete, and in the construction step, a predictive model is constructed such that one or more feature quantities selected from the multiple feature quantities are associated with the predicted quality value by a decision tree.

An advanced concrete drum cleaning system that includes a dynamically controlled oscillating nozzle, a boom zeroing function, a breakaway mounting plate, and a hydraulic assembly for enhanced safety. The system features a motor-driven nozzle having a stroke length that can be dynamically adjusted in real-time using feedback from an encoder. A controller with a user interface allows operators to precisely control and monitor the nozzle's position. Additionally, the system includes a boom zeroing function, enabling the operator to set and maintain a reference position for the boom within the concrete drum. The hydraulic assembly, consisting of lifting and lowering components, allows the nozzle housing to quickly disengage from obstructions to prevent damage. Moreover, the breakaway mounting plate provides a means for limiting damage when the nozzle housing is unable to disengage from obstructions.

The invention provides a premixed concrete quality detection method and device, a medium and a product, and relates to the technical field of image processing, and the method enables a target image detection model to capture and enhance time sequence change information related to concrete internal flow from an input image sequence through a space-time dynamic sensing module and a space-time attention module. Characteristics containing dynamic information are purified on different scales through a channel-space double attention module, and key apparent characteristics under each scale are focused. And finally, the adaptive feature pyramid network dynamically adjusts the fusion strategy according to the image content, and performs intelligent weighted fusion on the multi-scale dynamic features. The mode of combining time sequence dynamic analysis and self-adaptive multi-scale space analysis enables the target image detection model to form more comprehensive identification on the state of the concrete, and the technical problem that a concrete state identification scheme is poor in identification effect under complex and dynamic actual working conditions in a transportation tank car is solved.

To improve the accuracy of quality prediction while avoiding the complication of work involved in quality prediction when performing quality prediction using a prediction model.SOLUTION: A quality prediction method for ready-mixed concrete includes: an acquisition step of acquiring input information including first information relating to at least one of a power load value of a mixer that produces ready-mixed concrete by mixing concrete materials or that mixes the ready-mixed concrete, vibration caused by falling or flowing down of the ready-mixed concrete, and an image of the ready-mixed concrete, and second information relating to a target quality of the ready-mixed concrete when in use; and a prediction step of predicting the quality of the ready-mixed concrete based on a prediction model previously constructed by machine learning so as to output quality information indicating the quality of the ready-mixed concrete in response to input of the input information and the input information acquired in the acquisition step.SELECTED DRAWING: Figure 5

To improve prediction accuracy of a prediction model constructed by machine learning.SOLUTION: Acquiring color captured image data obtained by capturing an image of an aggregate; generating input image data by sequentially performing a first process of grayscaling and a second process of binarizing by adaptive binarization on the captured image data; acquiring input information including the input image data; and using a prediction model constructed in advance by machine learning so as to output a physical property value of the aggregate in response to an input of the input information, A prediction step of acquiring the physical property value corresponding to the input information acquired in the second acquisition step, wherein in the adaptive binarization in the second processing, a binarization threshold is set for each pixel by weighted averaging.SELECTED DRAWING: Figure 5

To provide a concrete pump vehicle that can stably fix the control device that controls the pump unit. [Solution] The concrete pump vehicle comprises a pair of frames arranged in the left-right direction, a pump unit fixed between the pair of frames for pumping ready-mix concrete, and a control device mounted on the pair of frames for controlling at least the pump unit, the control device being fixed to the frame and the pump unit.

The utility model discloses water adding equipment for producing premixed concrete, which comprises a bottom plate and a stirring box, the upper surface of the bottom plate is fixedly connected with a fixed rod, the fixed rod is internally provided with a groove, the inner surface of the groove is slidably connected with a sliding block, the inner surface of the sliding block is in threaded connection with a lead screw, and the lead screw is in threaded connection with the stirring box. The upper surface of the lead screw is fixedly connected with a driving motor, the output end of the driving motor is fixedly connected with the lead screw, the positions of a water spraying plate and a nozzle can be adjusted to proper positions according to the height of materials in the stirring box, and the situation that water falls from the top to generate large impact force is avoided; according to the stirring box, materials are prevented from splashing to the ground and equipment around the stirring box, so that the cleanliness of a production site is kept, the diffusion of pollutants is reduced, the workload of cleaning the surrounding environment is reduced, water can be conveniently added into the stirring box, and the labor intensity of manually moving a water pipe or a water bucket is reduced.

The invention relates to the technical field of quality early warning of premixed concrete. The method comprises the steps of analyzing the data distribution condition of a fusion data set in the same enterprise and project based on a K-Means clustering result, identifying an abnormal matching relationship, calculating a comparison abnormal value based on the abnormal matching relationship, and determining the quality of the premixed concrete based on the comparison abnormal value. The method comprises the steps of calculating abnormal scores of enterprises and projects, quantifying the abnormal degree of each enterprise and project in construction quality control to obtain a multi-dimensional quality score, performing comprehensive weighted calculation on a single-dimensional quality score, the multi-dimensional quality score and a supervision and detection score by adopting an analytic hierarchy process to obtain a comprehensive quality score, and calculating the quality of the enterprises and projects according to the comprehensive quality score. And comparing the comprehensive quality score with a preset quality score threshold, and if the comprehensive quality score is lower than the preset quality score threshold, generating early warning data. The method has the effect of ensuring stable concrete construction quality.

A system and method are disclosed for removing residual concrete from the interior of a ready mixed concrete truck drum using a high-pressure water jet without requiring drum entry. A nozzle housing on an elongated boom contains a rotatable nozzle driven by a motor. An encoder provides nozzle position feedback to a control system that can dynamically set and adjust the nozzle sweep limits, including independent forward and rear stop limits, and can hold the nozzle at a selected angular position. Boom translation can be referenced from a user-set zero position and displayed as travel from the reference. In some embodiments, a dual-controller arrangement includes a mounted controller and a handheld controller synchronized over a communication link with command arbitration. Safety features can include sensor-initiated rapid hydraulic power-down and a breakaway hinge configured to separate at a threshold below a boom plastic deformation threshold.

To provide an information processor, an information processing method and a program for specifying a blending plan document suitable for a predetermined condition from among a large number of blending plan documents.SOLUTION: In a management system that manages at least a part of exchanges between a client company and a plurality of client companies of ready-mixed concrete, a client device A11, which is an information processor, includes a control unit A36 that associates an S-value relating to placement of ready-mixed concrete and an application period with a blending plan document generated by reading a blending plan document of the ready-mixed concrete by an OCR, and a storage unit A34 that stores association information for associating the S-value with the blending plan document.SELECTED DRAWING: Figure 2

The invention relates to a mineral additive for cement, comprising: - 10% to 90% (w / w) sulfoaluminate clinker; - 10% to 90% (w / w) Prompt natural cement; and - 1% to 50% anhydrite C$; said mineral additive being free from accelerators and set retarders. The invention also relates to a cementitious composition comprising the aforementioned additive, and ready-mixed concrete prepared from said cementitious composition.

To simply grasp the quality of ready mixed concrete.SOLUTION: According to one aspect of the present disclosure, a ready mixed concrete prediction method includes an acquisition step, and a prediction step. The acquisition step acquires input information including vibration information showing the magnitude of vibrations caused by falling or flowing down of ready mixed concrete manufactured by a mixer for kneading concrete materials. The prediction step predicts the quality of the ready mixed concrete on the basis of a prediction model constructed in advance by machine learning so as to output quality information showing the quality of the ready mixed concrete according to an input of input information, and the input information acquired in the acquisition step.SELECTED DRAWING: Figure 1

The invention discloses a ready-mixed concrete test piece personalized processing system based on a concrete mold, and relates to the technical field of industrial processing. The premixed concrete test piece personalized processing system based on the concrete mold comprises a discharging device, a vibration system, a stirring device, an injection molding device and a master control system, the master control system is used for controlling the discharging device to add each concrete ingredient with the corresponding proportion and weight into the vibration system for constant-speed transmission according to the processed component model and the processing quantity selected by a user; meanwhile, the stirring device is controlled to add water into various concrete ingredients for stirring; the component volume is calculated according to the standard weight and density of the component model, and the stirred concrete of the component volume is injected into a mold corresponding to the component model. Efficient, accurate and personalized production of the premixed concrete test piece can be achieved, and meanwhile material waste and energy consumption are reduced.

The invention discloses a high-foam-stability concrete air entraining agent with a multi-substructure and a preparation method of the high-foam-stability concrete air entraining agent. The air entraining agent comprises a polyamine main chain, a hydrophobic chain mounted on the polyamine main chain and a phosphonate anion functional group grafted on the polyamine main chain. The molecular structure of the air entraining agent provided by the invention has the advantages of multi-type, high surface activity, lower solid doping amount compared with the conventional air entraining agent, uniform and fine bubbles can be generated when the air entraining agent is added into premixed concrete, the stability of the bubbles in time is excellent, the workability of the premixed concrete can be greatly improved, and the bleeding rate and the slurry bleeding rate are obviously reduced; the branched chains are multi-sub-chains, good air entraining and foam stabilizing effects are achieved, the main chain has a good reinforcing effect, concrete strength reduction caused by increase of the air content is made up, and the air entraining and foam stabilizing performance of the whole system is kept excellent; phosphonic acid groups in molecules of the air entraining agent are insensitive to components of concrete and mineral admixtures and have relatively weak adsorption capacity to clay, so that the air entraining agent has relatively good retarding and slump retaining properties.