78 results about "Rock classification" patented technology

The invention discloses a lithology identification method. The lithology identification method comprises the steps that firstly, conventional three-porosity (sound waves, density and neutrons) logging measured values of N rock core samples are obtained through the steps of thin section authentication, X-ray diffraction analysis, rock core true depth determination and the like; secondly, the relative distance between two parameters of conventional three-porosity logging is obtained, and the quantitative relation between the relative distance of the two parameters and primary mineral components obtained through X-ray diffraction total rock analysis is obtained according to the relative distance of the two parameters and the mineral components of the N rock core samples; thirdly, rock classification based on the relative distance of the two parameters is established and can be applied to lithology identification of fine grain sedimentary facies area logging, and continuous lithology identification can be carried out on well stratums without core sampled.

The invention discloses a hard rock tunnel construction method based on water power cutting. The hard rock tunnel construction method based on the water power cutting is characterized by constructing multiple tunnel sections from back to front along the longitudinal extending direction of a tunnel. When any one tunnel section is constructed, the process is as follows: 1, surrounding rock classification advanced detection; 2, construction parameter confirmation, wherein the confirmed construction parameters comprise cutting parameters of a water power cutting machine and split force of a hydraulic splitter; 3, current constructed tunnel section construction: constructing multiple cutting sections of the current constructed tunnel sections from back to front along the longitudinal extending direction of the tunnel, wherein when any one cutting section is constructed, the process is as follows: construction preparation, water power cutting, hydraulic splitting and rectangular cutting block outward transporting; 4, repeating steps one, two and three for many times until the construction process of the constructed hard rock tunnel is finished. The method provided by the invention is simple in steps, convenient to implement, lower in input cost, high in construction efficiency, good in construction effect, and can simply, conveniently and quickly finish the construction process of the hard rock tunnel.

The invention provides a method suitable for TBM tunneling tunnel surrounding rock grading joint prediction and application. The method comprises: preliminarily judging the classification of the surrounding rock of the unexcavated section in front of the tunnel TBM according to geological exploration data, detecting the condition of the surrounding rock of the unexcavated section by utilizing an advanced geological prediction method, obtaining surrounding rock parameters, and correcting and preliminarily judging a surrounding rock classification result according to the obtained detection data;according to the obtained surrounding rock parameters of the non-excavated section obtained through the advanced geological forecast, using a data analysis method for the non-excavated section, and obtaining TBM tunneling parameters of the section; and establishing a neural network model, calling the obtained TBM tunneling parameters as input values to the neural network model for prediction, outputting non-excavated section surrounding rock classification, and obtaining a final prediction result by combining a corrected surrounding rock classification result.

The invention discloses a surrounding rock plastic zone size-based quantitative roadway support design method. The method comprises the following steps of: 1, carrying out calculation to determine a size of a radius R of a roadway surrounding rock plastic zone; 2, classifying roadway surrounding rocks according to the calculation result; 3, carrying out targeted support parameter design on different types of surrounding rocks according to the roadway surrounding rock classification result; and 4, modifying and adjusting support parameters according to on-site monitoring feedback information. According to the method, support parameters designed on the basis of plastic zone sizes are scientific and reasonable, and roadway surrounding rock classification is carried out by taking plastic zoneradius sizes as main indexes, so that targeted support parameter design is carried out on different types of surrounding rocks so as to ensure the scientificity and economy of roadway support design.For roadway support, the method is capable of playing a part of preventing roadways from roof fall accidents.

The invention discloses a feedback analytical method and a feedback analytical device during tunnel construction and based on an extreme learning machine. The feedback analytical method comprises the following steps: the optimal input layer weight and the optimal hidden layer offset are utilized to train and learn a training sample set I and a training sample set II through the extreme learning machine so as to obtain a rock classification evolution extreme learning machine model and a rock parameter identification evolution extreme learning machine model; rock classification influence factors disclosed during the tunnel construction process are obtained; the rock classification influence factors are inputted, and a rock classification result is outputted through the rock classification evolution extreme learning machine model; the rock displacement of a tunnel is monitored and obtained; according to the rock classification result, and within different rock classification ranges, the obtained rock displacement is combined, and the rock mechanical parameter is obtained by utilizing the differential evolution algorithm and the rock parameter identification evolution extreme learning machine model. According to the invention, the rock classification result and the rock mechanical parameter can be rapidly obtained, the predication is accurate, and the accuracy is high.

The invention discloses a TBM construction surrounding rock drillability grading method based on data mining, and the method comprises the steps: building a penetration prediction model by using a stepwise regression method and considering the operation experience of a master driver according to the principle of safety and high efficiency; Performing regression analysis on the engineering project,and establishing a rotating speed prediction model; Summarizing engineering cases at home and abroad, and establishing a TBM construction tunneling utilization rate prediction model on the basis of data mining; And by taking the TBM tunneling speed as an evaluation index, finally establishing a surrounding rock drillability grading model based on TBM construction. The method aims at the current situation that traditional tunnel surrounding rock classification is incapable of well adapting to TBM construction by taking surrounding rock stability as an evaluation basis. A data mining method isprovided, a tunnel surrounding rock systematized classification method under the TBM construction condition is established, the TBM tunneling performance under various surrounding rock grades is accurately predicted, a decision basis is provided for TBM construction cost and construction period prediction, and optimization adjustment of TBM tunneling parameters is achieved.

The invention discloses a coal and rock identification method based on image discrete multi-wavelet transform. The method includes obtaining a group of coal sample images and rock sample images under the same image-forming conditions according to kinds of coal and rocks in a coal mine to be identified; extracting m samples from the images respectively and capturing sub-images f1, f2,..., fm and g1, g2,..., gm which have the same size and contain no backgrounds; performing a first-level Geronimo Hardin Massopust (GHM) multi-wavelet transform respectively on f1, f2,..., fm and g1, g2,..., gm and calculating multi-scale texture energy distribution vectors based on transform domain data for all the sub-images to obtain average multi-scale texture energy distribution vectors Vcoal and Vrock of the coal samples and the rock samples; during a coal and rock classification and identification stage, collecting to-be-identified coal and rock images under the same image-forming conditions, capturing a sub-image fx with the same size with the samples, performing the first-level GHM multi-wavelet transform on fx, and calculating the multi-scale texture energy distribution vector Vx; and determining coal and rock object types according to relations among the Vx, Vcoal and Vrock. According to the method, the coal and rock object types are identified through images, devices for collecting and processing images are convenient to arrange, the reliability and the identification rate are high, and upgrade maintenance of software and hardware is convenient.

The invention discloses a super-large-cross-section tunnel-based surrounding rock classification method. The super-large-cross-section tunnel-based surrounding rock classification method comprises the following steps of (1) obtaining a tunnel excavation section area S; (2) calculating and determining the number of excavation faces according to a formula S / 50, and ensuring the excavation faces to be same in area, wherein S is the tunnel excavation section area in the step (1); (3) performing finite element numerical simulation analysis on practical engineering, and performing strength reduction on the excavation faces and expanded regions of the excavation faces to obtain different safety coefficients a1, a2, a3 and a4; (4) determining weight values b1, b2, b3 and b4 according to the reciprocals of the different safety coefficients a1, a2, a3 and a4 in the step (3); (5) performing zoning on the excavation faces on site; (6) calculating [BQ] of zones, and performing weighting according to [BQ] so as to obtain [BQ]A; and (7) finishing excavation face sketches according to an actual situation, and marking [BQ] and [BQ]A of the zones.

The invention discloses an on-site tunnel real-time surrounding rock classification system and a method. The system includes a bearing platform, the bearing platform bears a measuring ruler, a point load tester for conducting point load test on an on-site surrounding rock sample, and a geological compass for determining weak structural plane occurrence, the measuring ruler, the point load tester and the geological compass are detachably disposed on the bearing platform, and the lower part of the bearing platform is provided with moving components for driving the bearing platform to move. The setting of the whole system is convenient for moving a measurement component to the site for real-time measurement, realizes real-time classification work of tunnel surrounding rock, effectively improves the efficiency of tunnel surrounding rock classification work, improves the flexibility of classification work, and can acquire real-time feedback of rock mass classification near a tunnel face, thus being convenient for directly carrying out follow-up work.

The invention discloses a rock classification method based on a laser induced breakdown spectrum. The method comprises the steps that 1) a rock sample is prepared; 2) a laser induced breakdown spectrum device is used to collect a spectral image of the rock sample, and the acquired spectral image is pre-processed and divided into three data sets; and 3) the data sets composed of the spectral imageare used as an input end to establish a convolutional neural network model, and the convolutional neural network model is optimized and tested; a convolutional neural network based on spectral image recognition is combined with a laser induced breakdown spectrum technology to realize accurate classification of rock samples.

The invention relates to a loess tunnel surrounding rock classification method. By means of the loess tunnel surrounding rock classification method, loess tunnel preliminary supporting and secondary lining can be performed in targeted mode, construction difficulty can be reduced, and construction safety and tunnel structure stability are ensured. The loess tunnel surrounding rock classification method adopts qualitative characteristic division and qualitative division combination method to perform comprehensive judgment; division is performed according to the indexes including loess formation age, plastic state, joint development degree, surrounding rock stability state after tunnel excavation and the like, and loess tunnel surrounding rock grades are subjected to division according to tunnel soil texture characteristics, underground water and tunnel deep embedding and other factors; loess surrounding rock grade indexes, an obtaining method and the correspondence relation between a loess (clay soil) surrounding rock humidity degree qualitative value and quantity are given.

The invention discloses a tunnel dynamic feedback analysis system based on an IFC standard, and the system comprises a BIM model library operation module for establishing a tunnel model, a model analysis module, a data reading module, an analysis report module, and a surrounding rock classification module. The BIM model library operation module is used for creating a typical tunnel model and a parameterized component library and exporting the typical tunnel model into an IFC format file to form an IFC model; the model analysis module, the surrounding rock classification module and the analysis report module obtain surrounding rock dynamic classification and surrounding rock identification parameters through extracting the IFC format file related attribute data and performing calculation, and generate a report form; a feedback analysis calculation program is called to obtain an excavation construction scheme and support parameters, the data reading module writes dynamical classification of the surrounding rock and the surrounding rock identification parameters into the IFC model. According to the invention, comprehensive rapid analysis and accurate processing of various data and information are ensured, feedback analysis is carried out on the data, and accurate presentation of the data is realized.

The invention discloses a tunnel excavation water pressure blasting construction method. The method comprises following steps that firstly, according to the surrounding rock classification, the drilling depth is determined, a cutting hole is drilled in the center of the excavation face, an auxiliary hole is drilled outwards in the excavation face along the cutting hole, a bottom side hole is drilled in the bottom of the excavation face, and periphery holes are drilled in the periphery of the excavation face; secondly, the interiors of the drilled holes are cleaned; thirdly, explosives, water bags and stemming are arranged in the drilled holes; and fourthly, a detonating tube or detonating cord is ignited for blasting. According to the method, the water bag is added, during blasting, the water wedge effect is generated, the energy use rate is improved, surrounding rock breaking is facilitated, and the explosive consumption amount is reduced; after blasting, water in blat holes can carryout atomizing so as to achieve dust falling, the ventilation dust falling time after blasting can be shortened, and the one-time excavation depth is improved.

The invention provides an identification method for tunnel surrounding rock classification, which comprises the following steps of acquiring while-drilling parameter data of a rock drill during tunnelface drilling and rock geological information at a position corresponding to the while-drilling parameter data, and carrying out standardization processing on the while-drilling parameter data; carrying out data analysis on the standard-processed while-drilling parameter data, and determining the relationship between the while-drilling parameters at the same position and the surrounding rock strength in combination with the rock geological information; acquiring a tunnel face image of the tunnel face, performing image processing on the tunnel face image, and determining a discrimination relationship between the tunnel face image at the same position and the rock integrity degree; and carrying out grading judgment on the tunnel surrounding rock by integrating the relationship between the drilling-while-drilling parameters and the surrounding rock strength at the same position and the judgment relationship between the tunnel face image and the rock integrity degree at the same position,and determining the grade of the tunnel surrounding rock. According to the method, the grade of the tunnel surrounding rock can be determined through the collected tunnel face image, the drilling parameter data and the rock geological information.

The invention discloses a construction method of advanced geological forecast, which belongs to the technical field of geological forecast. The construction method comprises the steps of conducting tunnel engineering geological investigation; completing on-site data collection; establishing a wave velocity model; obtaining chromatography scanning image; conducting the analysis of tunnel engineering underground water advanced forecast, the analysis of tunnel engineering empty cavity advanced forecast, the analysis of tunnel engineering fault fracture zone advanced forecast, and the analysis of tunnel engineering surrounding rocks classification advanced forecast. The construction method of the invention is advantageous in that before data collection and data processing, the engineering geological condition of the tunnel can be basically grasped; the data processing should be objectives-oriented, and then the advanced geological forecast can be accurately conducted; the primary engineering geological problems of the tunnel and the influence of the problems to the tunnel can be estimated, and thereby suggestions of how to deal with the problems can be made in the manner of being geared to engineering practice; the technical advantages of TRT can be fully developed, and the construction progress and safety can be well guaranteed.

The invention relates to a high-efficiency filling mining method for controlling rock mass movement, and belongs to the technical field of mining. According to the technical scheme, the method comprises the following steps of: dividing an ore body into levels for mining, and mining along the levels from bottom to top; dividing panels along the strike of the ore body, stoping each panel of the ore body through two steps, namely stoping charmers and stoping ore pillars, wherein cemented fill after stage open-stope is adopted in the process of stoping the charmers, and non-cemented fill is adopted in the process of stoping the ore pillars; arranging strip pillars among the panels, wherein panel intervening pillars are pillars arranged at unequal spacing; and optimizing and obtaining the sizes of the panel intervening pillars, the ore pillars and the strip pillars through setting up an optimization mode. The high-efficiency filling mining method has the advantages that the stability of stope roof is improved, and the safety of mining is ensured; sizes of the panel intervening pillars and the panel pointed pillars are optimized, the strength of a filling body of the roof is improved, and ore resources are recovered to the maximum extent; bottom-to-top level stoping sequence is adopted, the influence of underground mining on a quaternary aquifer is avoided, single-step stoping span is determined by adopting rock classification and an empirical formula, stoping span meeting stable ore rock conditions is enlarged, and stoping production capacity is improved.

The invention discloses a coal and rock classification method based on a wavelet domain asymmetric generalized Gaussian model. The method comprises the steps of obtaining m known coal sample images and m known rock sample images which are of the same size and do not contain backgrounds in the sample training stage, conducting wavelet transform image decomposition on each image, calculating parameters of each wavelet coefficient sub-band meeting the asymmetric generalized Gaussian distribution condition of each image, and using all the parameters of each image for constructing a training sample characteristic column vector; in the coal and rock recognition stage, collecting and obtaining unknown type coal and rock images ux which are of the same size of the training sample image and do not contain the background, conducting wavelet transform image decomposition on the ux, calculating parameters of each wavelet coefficient sub-band meeting the asymmetric generalized Gaussian distribution condition of the ux to form a characteristic column vector Vux, and judging the type of coal and rock of the ux by comparing the similarities between the Vux and the training sample characteristic column vector. The coal and rock classification method is good in reliability and high in classification accuracy, and software and hardware are convenient to maintain.

The invention discloses a partition detecting method and device for flyover crossing tunnel construction. The partition detecting method comprises the steps that first data are received and comprise surrounding rock classification, the crossing angle and the crossing clear distance; the strength criterion value of a position, to be detected, on a first tunnel is obtained according to the first data; the calculated strength criterion value of the position to the detected is compared with a pre-stored partition reference value, and the partition classification of the position to be detected is determined. The first data are received, the strength criterion value of any detected position of the first newly-built tunnel is calculated, the strength criterion value is compared with the pre-stored partition reference value, therefore, the strength classification of any position of the first tunnel is determined, the interaction degree of flyover crossing tunnels is quantized conveniently before the flyover crossing tunnel construction, selection of a tunnel supporting structure and a tunneling construction method is guided, and the safety and reliability of the construction are guaranteed.

The invention discloses a point loading test analysis method based on surrounding rock classification of a super-large section tunnel. The point loading test analysis method comprises the following steps: obtaining an excavation section area S of a working face; according to different excavation section areas S of a tunnel, adopting N=S / 2 irregular rock block bodies at places near a construction site of the working face; carrying out a point loading test on the irregular rock block bodies on the construction site; calculating according to an engineering rock body test method standard to obtain Is(50); carrying out conversion on the Is(50) obtained by step (4) according to specifications, so as to obtain N Rcs; drawing a histogram, wherein horizontal ordinates are the Rcs obtained by conversion for the point loading test in step (5), the width of the histogram according to the size of extreme difference is reasonably determined, and vertical coordinates are frequencies of corresponding Rc values; carrying out multi-peak normal distribution fitting according to the histogram obtained by step (6) to obtain M normal peaks and the Rc values corresponding to M peak values; determining different surrounding rock rigidity indexes according to the Rc values in ste.p (7), and determining surrounding rock classification of the super-large section tunnel.

The invention relates to a timely yield supporting system for deep high-stress broken-expansion surrounding rocks. The system mainly comprises a surrounding rock classification and evaluation submodule RC, a timely yield supporting design submodule SY and a feedback design submodule DR; the surrounding rock classification and evaluation submodule RC is used for performing computation and analysis according to parameter input from an engineering geological survey so as to obtain an overall supporting scheme; the timely yield supporting design submodule SY is used for receiving computed results and the overall supporting scheme obtained from the surrounding rock classification and evaluation submodule RC, performing integrated optimization to obtain an optimal scheme, and then performing construction and supporting tests on a high-stress soft rock roadway; and the feedback design submodule DR is used for performing feedback design on the original supporting scheme by using real-time monitoring data, which is obtained by monitoring the roadway surrounding rocks in real time, in a use process after the supporting is finished, and obtaining an adjusted supporting scheme, wherein the adjusted supporting scheme is used for performing graphic generating and processing mainly through a graphic processing and generating module CAD (Computer-Aided Design), a displayer, graph outputting equipment and the like. The timely yield supporting system disclosed by the invention has a very good effect on optimizing an excavation sequence and supporting after proper yielding and provides safety guarantee for mining.

The invention relates to the field of civil engineering, and discloses a surrounding rock grading method, a processor and a storage medium. The method for surrounding rock grading comprises the steps: collecting the first images of a cave wall and a cave top, wherein the cave wall and the cave top are the cave wall and the cave top of a cave chamber corresponding to surrounding rock; performing distortion correction and mosaic on the first image to generate a base image; measuring the structural plane occurrence on the base map, selecting a measurement interval on the base map, measuring the volume joint number of the rock mass in the selected measurement interval according to the structural plane occurrence, and determining the integrity coefficient of the rock mass according to the volume joint number; collecting a plurality of rocks, and performing a point load test on the rocks to obtain the uniaxial saturated compressive strength of the rocks; obtaining a first quality index of the surrounding rock according to the integrity coefficient of the rock mass and the uniaxial saturated compressive strength of the rock; and determining surrounding rock classification according to the first quality index. According to the embodiment of the invention, the surrounding rock grading accuracy can be improved.

The invention discloses a machine vision-based discharged ballast monitoring method for a heading machine. The method comprises a surrounding rock discharged ballast crushing degree monitoring step, a conveying belt load monitoring step and a surrounding rock classification monitoring step. In the discharged ballast crushing degree monitoring step, a maximum size, a minimum size and an average size of rock ballast are subjected to statistics, and a surrounding rock crushing capability in a current heading condition is provided; in the conveying belt load monitoring step, a load condition of a current belt machine is assessed by detecting a depth of the discharged ballast in the whole belt machine; and in the surrounding rock classification monitoring step, a current surrounding rock heading condition is judged through surface features of the discharged ballast. By use of a machine vision method, the discharged ballast monitoring efficiency and accuracy are improved; the problems of inaccurate monitoring and the like caused by a severe environment are avoided; and the labor cost also can be reduced.

The invention provides a geological prospecting method applied to shallow-buried underground engineering in a water-deficient area. The geological prospecting method comprises the steps that geological prospecting is conducted, geological information of an engineering site is preliminarily obtained through remote sensing geological interpretation and engineering geological survey; comprehensive geophysical prospecting is carried out, and a small amount of drilling and logging work is carried out on key parts; in combination with an indoor rock-soil mechanics test, engineering geological condition comprehensive evaluation of an engineering site is obtained and comprises conventional stratum lithology, geological structure and surrounding rock classification, foundation bearing capacity anddynamic physical and mechanical parameters of a rock-soil body, and the parameters are used for engineering stability calculation of national defense engineering under the strong dynamic load condition. The investigation result meets the conventional requirements of shallow-buried underground engineering design construction, and meets the special purpose of national defense engineering. The geological prospecting method overcomes the defect that time and money are wasted when conventional prospecting mainly based on drilling is adopted, the prospecting cost is low, the efficiency is high, andthe geological prospecting method is more suitable for geological prospecting of shallow-buried underground engineering in arid and water-deficient areas.

The invention provides a rock recognition method and device, equipment and a storage medium, and relates to the technical field of rock recognition. A convenient website can be used as a tool to identify rocks, the influence of personal subjective factors is eliminated, and a way is provided for rock enthusiasts to quickly and accurately identify rock types in the field. Feature extraction is madeon the picture of the rock to be identified to obtain a feature vector; the rock category to which the feature vector belongs is judged by utilizing a preset rock classification space to obtain an intermediate classification feature vector; the probability that the rock to be identified belongs to different rock categories is calculated according to the intermediate classification feature vectorto obtain a probability distribution vector; and according to the probability distribution vector, at least outputting the probability that the to-be-identified rock belongs to a class of rocks or anupper class of the class of rocks to which the to-be-identified rock belongs.

The invention discloses a coal rock recognition method based on relativity measurement learning. According to the method, a new relativity measurement function is learnt from a training sample set in a monitoring mode to measure the relativity of coal and rock image samples, so that the relativity measurement value of samples in the same type is larger and larger, the relativity measurement value between samples in different types is smaller and smaller, and the classification rate of unknown samples is increased. The method includes an image preprocessing process, a training process and a recognition process. A preprocessing module is used for simple preprocessing of collected coal and rock images to obtain the training sample set. A training module is used for learning the optimal coal rock classification effect relativity measurement function from the training sample set. A recognition module is used for performing measurement classification by means of the optimal relativity measurement function. By means of the method, images of coal and rock under different illuminances and different viewpoints serve as the training samples, the method is little influenced by illuminance and imaging viewpoint changes, the recognition rate is high, and stability is good.

The invention belongs to the field of engineering surrounding rock classification, and in particular, relates to a method for remote sensing pre-judging of the grade of engineering surrounding rocks. The method comprises the following steps: step one, extracting engineering geological type and geological structure factor remote sensing information; step two, determining the rock uniaxial saturated compressive strength and the rock mass integrality index; step three, calculating the rock mass basic quality index BQ; and step four, classifying the surrounding rocks. Through the steps of extraction of the remote sensing information, determination of the rock mass integrality index and the rock uniaxial saturated compressive strength, calculation of the rock mass basic quality index BQ, surrounding rock classification and the like, rapid classification of the engineering surrounding rock grade is realized, the method is not restricted by topography landform and spatial regions, avoids the blindness of data blank area working, improves the work efficiency, reduces the workload, reduces the cost for investigation, and provides reliable reference data for engineering later detailed investigation and design and construction.

The invention discloses a partition detecting method and device for flyover crossing tunnel construction. The partition detecting method comprises the steps that first data are received and comprise surrounding rock classification, the crossing angle and the crossing clear distance; the displacement criterion value of a position, to be detected, on a first tunnel is obtained according to the first data; the calculated displacement criterion value of the position to the detected is compared with a pre-stored partition reference value, and the partition classification of the position to be detected is determined. The first data are received, the displacement criterion value of any detected position of the first newly-built tunnel is calculated, the displacement criterion value is compared with the pre-stored partition reference value, therefore, the partition classification of any position of the first tunnel is determined, the interaction degree of flyover crossing tunnels can be quantized conveniently before the flyover crossing tunnel construction, selection of a tunnel supporting structure and a tunneling construction method is guided, and the safety and reliability of the construction are guaranteed.

The invention discloses a tunnel advance geology forecast method based on surrounding rock deformation monitoring and numerical simulation. The method comprises the steps that the actual classification condition of surrounding rock at the current section and preliminary qualitative classification which is conducted on surrounding rock in front of the surrounding rock at the current section by a distance through a comprehensive advance geology forecast method are combined, comprehensive quantity analysis is conducted on the surrounding rock in front of the surrounding rock at the current section by a distance, qualitative classification data obtained by conducting advance forecast on the surrounding rock in front of the surrounding rock by a distance at the current section through the comprehensive advance geology forecast method are amended, the man-made subjectivity in the advance forecast is reduced, and the objectivity of geology forecast is increased. The mode that 'one section is verified and one section is forecasted when one section is passed' is used for comparing the surrounding rock classification obtained qualitatively at the next section with the classification, obtained qualitatively, of the surrounding rock at the current section, so that the classification of the surrounding rock at the next section is obtained through qualitative analysis, and the classification and parameter, obtained through qualitative analysis, of the surrounding rock at the next section are amended. Comprehensive evaluation can be conducted on the advance geology forecast of the tunnel surrounding rock, and the accuracy of tunnel advance forecast is greatly improved.

The invention relates to the technical field of tunnel engineering and further discloses a tunnel surrounding rock rapid grading equipment system and an operation method thereof. The tunnel surrounding rock rapid grading equipment system is mainly composed of three parts of software and hardware including a rock mass integrity coefficient rapid test and analysis module, a rock uniaxial saturated compressive strength rapid test and analysis module and a surrounding rock grading correction index test and analysis module. The invention discloses a tunnel surrounding rock rapid grading equipment system and an operation method thereof. A set of integrated tunnel surrounding rock grade rapid identification equipment system integrating acquisition, storage, calling, input, calculation and resultoutput is developed for the first time in the field of surrounding rock grading. The method has the characteristics of high resolution, low energy consumption, portability and function integration, has the characteristics of dust prevention, moisture prevention, interference prevention and the like, is more suitable for being applied to severe environments in tunnel holes, realizes the rapidness,quantification and standardization of tunnel surrounding rock classification, and avoids the problems of subjectivity of artificial identification, lack of operability of conventional identification and the like.