52results about How to "Avoid subjective judgment" patented technology

The invention discloses an urban gas buried pipeline leakage detection and locating method and applications thereof. Based on an acoustic emission technology and combined with the current gas pipeline laying situation of Changzhou city, layout schemes and relevant parameters of sensors are designed, and the leakage detection method under the situation of guaranteeing normal gas transmission of buried pipelines and not excavating pipelines is determined. Simultaneously, wavelet noise reduction and relevant analysis methods are introduced, and accordingly, the locating accuracy is improved, and objective and credible results are obtained. According to the urban gas buried pipeline leakage detection and locating method and applications thereof, the application of the acoustic emission detection technology in gas buried pipeline leakage detection is facilitated and improved to a large extent, and hence, while the method is effective and accurate in detection and cost saving, popularization and use values are increased, and the method has great significances in enhancement of urban gas buried pipeline risk control.

The invention relates to a method for adjusting the position and the size of a projection picture with the full degree of freedom. The method comprises the steps of projecting a standard testing image through digital light process (DLP); aiming at a projection screen and shooting the projection picture through CCD; acquiring the adjustment amount of a zoom adjustment to conduct zoom adjustment by processing of shot data by a computer; and sequentially using rotating adjustment, vertical inclination adjustment, horizontal displacement adjustment and vertical displacement adjustment as an adjustment object, loop executing of the following steps and completing the adjustment to the projection picture. The CCD is directed at the projection screen to shoot the projection picture, analyzing and processing are conducted on the shot data by using an approximation algorithm through the computer to obtain the adjustment amount and the adjustment direction corresponding to the adjustment object, and the computer automatically controls a corresponding knob to conduct adjustment. By means of the method for adjusting the position and the size of the projection picture with the full degree of freedom, the computer automatically controls the five shafts of six shafts to adjust the knob, so that the relative position of a light machine and the projection screen can be adjusted accurately, the projection image can be fully displayed on the screen inerrably, manual operation is needless, and time and labor can be saved.

The invention discloses a driving motor system performance evaluation method for an electric vehicle. The driving motor system performance evaluation method analyzes from different dimensions such as motor control performance, motor body design and enterprise qualification and ability of the driving motor system according to performance characteristics of a driving motor used for the electric vehicle, adopts an analytic hierarchy process to determine a driving motor performance evaluation index system and index weights thereof, establishes a BP neural network model for driving motor system performance evaluation, organically integrates a bat algorithm with a particle swarm algorithm to form a bat-particle particle swarm hybrid algorithm, and optimizes parameters of the neural network structural model by adopting the bat-particle particle swarm hybrid algorithm. Simulation examples show that, through training and testing data samples, the driving motor system performance evaluation method which optimizes the neural network based on the analytic hierarchy process and the bat-particle particle swarm hybrid algorithm has the advantages of fast evaluation speed and high accuracy rate, achieves satisfying evaluation results, and has certain promotion value in evaluation, selection and application of a driving motor system for the electric vehicle.

The invention provides an image recognition method based on color and texture features. The method includes the steps of evenly and respectively dividing a detection image A and a matched image B into n sub-blocks, calculating the color feature similarity distance Dk(A,B) and the texture feature similarity distance Tk(A,B) between the sub-block k of the of the detection image A and the sub-block k of the matched image B, calculating the color feature similarity distance C(A,B) and the texture feature similarity distance T(A,B) between the detection image A and the matched image B, and judging the similarity S(A,B) of the detection image A and the matched image B according to the color feature similarity distance C(A,B) and the texture feature similarity distance T(A,B) between the detection image A and the matched image B, wherein k is larger than zero and smaller than or equal to n. Compared with the prior art, the feature similarity of the images is calculated on the basis of matching of the color features and the texture features, accuracy and objectivity are improved, and the subjective judgment of the key word index is avoided.

The invention provides a post-evaluation method for comprehensively evaluating power grid science and technology projects. The post-evaluation method includes the following steps of step one, firstly establishing an index set U=(u<1>, u<2>...u<n>) and a judgment set Q=(q<1>, q<2>...q<m>); step two, calculating a comprehensive membership vector using an operator of a generalized fuzzy synthetic operation, and obtaining an ultimate evaluation result according to a membership degree maximum principle. By means of the post-evaluation method, professional experience of industry experts is considered, and subjective judgment with large deviation is avoided, so that arrangement of index weighting is more accurate; during a multi-stage fuzzy comprehensive evaluation process of the power grid science and technology projects, acquiring of index data is normalized by subdividing content options of ground layer indexes, standards for multi-stage fuzzy comprehensive evaluation are unified, and accuracy of evaluation results is guaranteed.

The invention provides a live music competition method, system and device. The method comprises the following steps of displaying a two-dimensional code comprising competition link information on a display screen on the site, so as to enable users on the site to scan a two-dimensional code with cellphone competition APPs to sign up; receiving registration information sent by the users on the site through the cellphone competition APPs, and determining participating users according to the registration information; sending competition notification information, comprising use of competition devices on the site, to the cellphone competition APP of the participating users; collecting live singing audios and videos of the participating users by multiple competition devices on the site simultaneously, and scoring the audios according to preset scoring rules; displaying score and video information of the participating users on the display screen on the site; and ranking the participating users, acquiring the audio of the first participant user, and playing the audio of the first participating user through the audio system on the site. The live music competition method, system and device enable multiple participants to compete on the site simultaneously and realizes auto scoring, thereby improving the competition efficiency.

The invention discloses a work evaluation system, comprising a work locking module, a work segmentation module, a work diary module, a work hour analysis module and an effective work analysis module, wherein the work locking module is used for locking work tasks, the work segmentation module is used for dividing a work processing flow into a plurality of work stages, the work diary module is used for workers to input work diaries, the content of which comprises work hours everyday as well as work tasks, work stages and/or event termination marks, corresponding to the work hours, the work hour analysis module is used for analyzing the work hour curve of a worker in a preset time segment according to the work diary of the worker, and the effective work analysis module is used for analyzing the effective work curve of the worker in a preset time segment according to the work diary. Accordingly, the system can realize artificially intelligentized work evaluation, not only can improve evaluation efficiency, but also can greatly improve the accuracy, the objectivity and the fairness of an evaluation result.

The invention provides a system and method for testing a notebook computer external display port. The system at least comprises an external displayer, a camera device and a notebook computer. The external displayer is connected with the notebook computer through the external display port of the notebook computer and used for displaying a plurality of two-dimension code images. The camera device is connected with the notebook computer and used for shooting images displayed on the external displayer. The notebook computer is used for controlling the external displayer to display the two-dimension code images, and analyzing the images shot by the camera device so as to judge whether the external display port of the notebook computer is normal or not. According to the system and method for testing the notebook computer external display port, the display effect of the external displayer does not need to be checked by persons, and subjective judgment on the display effect is avoided; meanwhile, the external camera is utilized for analyzing the display effect of the external displayer, the testing coverage rate is increased, the testing efficiency is improved, and the labor cost is reduced.

The invention provides a shallow stratum boundary division method based on the sediment quality factor and the echo loss level curve peak and valley. The method comprises the steps of (1) eliminatingmultiples from sea surface and the shallow stratum boundary in original shallow stratum profile data by combining a predictive deconvolution method and a feedback loop method; (2) performing submarineline tracking to align the shallow stratum profile data with borehole data; (3) identifying plain peaks of the shallow stratum boundary by using the echo loss level curve peak and valley, and extracting stable peaks of in the stratum boundary according to the stability of the stratum trend; (4) calculating a control peak of the stratum boundary by combining with the sediment quality factor on thebasis of the stable peaks of the stratum boundary; (5) based on the control peak of the stratum boundary, searching for the plain peaks satisfying requirements, that is, obtaining a high-reliabilityshallow stratum boundary; and (6) assessing the precision of the stratum boundary division method by the use of borehole sampling data. The method in the invention not only can realize the automationand intelligentization of stratum boundary division, but also can accurately classify the shallow stratum boundaries and achieve the precision of the same magnitude with the borehole sampling data.

The invention provides a fire-fighting acceptance intelligent quantification method and a fire-fighting acceptance intelligent quantification system. The method comprises the following steps of S110,receiving a fire-fighting acceptance request initiated by a user, the fire-fighting acceptance request carrying a total standard acceptance parameter configuration file, each single standard acceptance parameter configuration file and each sub-item standard acceptance parameter configuration file which are formulated according to a preset fire-fighting acceptance evaluation rule; S120, acquiring the on-site actual input data of each sub-item of the to-be-checked and accepted project; and S130, generating a fire-fighting acceptance record report based on the standard acceptance parameter configuration file of each sub-item, the on-site actual input data of each sub-item and a preset judgment rule, the fire-fighting acceptance record report comprising each sub-item acceptance report, each single acceptance report and a total acceptance report. Through making a unified acceptance standard, the subjective judgment of the acceptance personnel can be avoided, the acceptance report accuracy can be effectively improved, the acceptance time can be saved, the time and labor consumption can be avoided, the manpower and material resource cost can be saved, and the economic benefit can be improved.

The invention relates to an automatic anti-overturn alarm system for the safety carrying capacity of an excavator. The system is formed by four parts, i.e. a gravity sensor, a weighing machine, a dataprocessor and a voice prompt alarm. According to the automatic anti-overturn alarm system for the safety carrying capacity of the excavator provided by the invention, the excavator can be monitored dynamically, so that a driver can conveniently know the carrying capacity information of the excavator, and can conveniently control the carrying capacity of the excavator, the excavator is effectivelyprevented from overturning, and a safety factor of the excavator carrying heavy objects is improved.

The invention discloses a road safety self-checking analysis system based on a cloud platform. The system comprises a pavement maintenance terminal, a cloud management platform and a plurality of vehicle-mounted detection terminals, wherein the cloud management platform is connected with the pavement maintenance terminal and the vehicle-mounted detection terminals through a wireless communicationnetwork, each vehicle-mounted detection terminal comprises a vehicle speed detection module, an amplitude detection module, a wheel deviation detection module, a vehicle-mounted processing module anda positioning acquisition module, and the vehicle-mounted processing modules are connected with the vehicle speed detection modules, the amplitude detection modules, the wheel deviation detection modules and the positioning acquisition modules. According to the system, bumpy driving parameters of vehicles passing through the same position are analyzed to obtain the maximum sunken depth and a pavement sunken elastic danger coefficient of the position, then a to-be-maintained grade corresponding to the position is analyzed, and pavements with high to-be-maintained grades are subjected to priority maintenance treatment in sequence, so that it is guaranteed that the pavement with the large pavement driving danger degree is maintained preferentially, and maintenance timeliness is achieved.

The invention discloses an image processing method and device, a readable storage medium and electronic equipment, and the method comprises the steps of obtaining an RGB image, and enabling a photographing object contained in the RGB image to be a test card; determining at least one connected region of the RGB image; for each connected region, determining a distance value set in the connected region to obtain a distance value set corresponding to the at least one connected region; and determining the chromatic aberration of the RGB image according to the distance value set corresponding to each of the at least one connected region, so as to correct the RGB image according to the chromatic aberration. By determining the distance value set of the connected regions in the RGB image and determining the chromatic aberration of the RGB image according to the distance value set, the purposes of quantifying the measurement of the chromatic aberration of the image, avoiding the subjective judgment of the chromatic aberration and improving the chromatic aberration measurement precision are achieved.

The invention provides a fire-fighting acceptance industry standard application system based on an APP. The APP comprises an account registration module, a part determination module, a synchronous uploading module, a comprehensive evaluation module, an automatic auditing module and a summary generation module. The account registration module is used for a user to register an account. The part determination module is used for randomly determining an inspection part (such as a floor); the synchronous uploading module is used for acquiring check data input into the site through an operation interface of the APP. The comprehensive evaluation module is used for directly generating an evaluation result; the automatic auditing module is used for automatically auditing and checking whether the data meet the requirements or not. The summarizing and generating module is used for automatically generating an acceptance report by applying the Internet of Things integration technology. The format ofthe generated acceptance report completely corresponds to the industrial standard fire-fighting acceptance evaluation rule for construction engineering (GA836-2016). Both the APP and the PC terminalcan check, download and print the acceptance report. Data is synchronously uploaded. Records are automatically audited. Results are directly judged, and archives are electronized.

The invention provides an inspection data processing method, an inspection data processing device, computer equipment and a storage medium. The method comprises the following steps: acquiring an inspection video; wherein the inspection video comprises a plurality of image frames; adding one or more area breakpoints in the inspection video according to the inspection area involved in the inspectionvideo; generating breakpoint description of breakpoints of the corresponding regions based on the involved inspection regions; identifying an image frame with construction abnormality in the inspection video through a plurality of abnormality detection models; adding an abnormal breakpoint to the position of each image frame with construction abnormality in the inspection video; and generating breakpoint description of the corresponding abnormal breakpoint based on the abnormality type associated with the abnormality detection model which detects the construction abnormality and the inspection time corresponding to the image frame with the corresponding construction abnormality. By adopting the method, the inspection efficiency can be improved.

The invention relates to the technical field of geometric quantity measurement, in particular to a hole cavity diameter measuring device. According to the technical scheme, the hole cavity diameter measuring device comprises a measuring rod and a push rod, a ball head is arranged at one end of the measuring rod, a displacement sensor is arranged at the other end of the measuring rod, and a displacement rod of the displacement sensor can slide in the length direction of the measuring rod; and one end of the push rod is hinged with the middle part of the measuring rod. When the device is used, the size of a groove or a hole with a known size is measured firstly, and the displacement sensor is reset; then the measuring device is sent into a target hole cavity to enable the ball head to be incontact with the side wall of the hole cavity, the measuring rod is pushed to rotate around the contact point of the ball head and the part, the minimum value of the displacement sensor in the rotating process is measured, and thus, the diameter of the target cavity can be measured. The device can guarantee the measurement precision and accuracy, is simple and convenient in operation, is accuratein measurement, is repeatable, is high in measurement precision, and is portable.

The invention provides a computer-aided breast cancer pathology image diagnosis method based on artificial intelligence, and the method comprises the steps: carrying out the model training of a breast cancer pathology image set, and obtaining a trained slice prediction model and a whole image prediction model; and secondly, based on the trained slice prediction model and the whole image prediction model, performing breast cancer diagnosis classification on the breast cancer pathological image. According to the method, the trained neural network can be used for layering a large number of breast cancer pathology images at different positions, the data processing speed and accuracy are greatly improved, and the problems of subjectivity, low efficiency and the like existing in existing breast cancer pathology subtype manual interpretation are solved.

The invention discloses a method and a system for predicting an image quality level, the method includes the following steps: selecting multiple specific images, calculating a first IQM value of each selected specific image, determining a specific NIIRS value of each specific image based on the first IQM value; fitting in conducted according to an image quality grade forecast formula based on the calculated the first IQM value and the specific NIIRS value, and determining the coefficient a and the coefficient b in the image quality grade forecast formula, wherein the image quality grade forecast formula is NIIRS=a-Log10 * IQM+b; calculating a second IQM value of the to-be-evaluated image; substituting the second IQM value into the determined image quality grade forecast formula, and calculating a NIIRS value of the to-be-evaluated image. By combination of the IQM and the NIIRS and optimization of a traditional NIIRS criterion content based on the IQM, the accuracy and consistency of image quality grade evaluation results are improved.

The embodiment of the invention discloses an interface testing device for a notebook computer. The interface testing device comprises a control module, and an HDMI interface testing module, a USB testing module and a Type-c function testing module which are connected with the control module; the test device can effectively test each interface of the notebook computer, does not need to use additional equipment, achieves the effect of saving material resources, receives test information of the HDMI interface test module, the USB test module and the Type-c function test module by utilizing the control module, and can play a role in visualizing a test result; the display effect of the external display does not need to be checked manually, subjective judgment on the display effect is avoided, the test coverage rate is increased, the test efficiency is high, the labor cost is low, and great benefits are brought to production and operation of enterprises.