WO2017092180A1 - 一种惯性导航与激光扫描融合的采煤机定位装置及方法 - Google Patents

一种惯性导航与激光扫描融合的采煤机定位装置及方法 Download PDF

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WO2017092180A1
WO2017092180A1 PCT/CN2016/074617 CN2016074617W WO2017092180A1 WO 2017092180 A1 WO2017092180 A1 WO 2017092180A1 CN 2016074617 W CN2016074617 W CN 2016074617W WO 2017092180 A1 WO2017092180 A1 WO 2017092180A1
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shearer
positioning
laser scanning
inertial navigation
microprocessor
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PCT/CN2016/074617
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English (en)
French (fr)
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刘万里
刘一鸣
张博渊
杨滨海
左雪
李雨潭
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中国矿业大学
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Priority to CA2973038A priority Critical patent/CA2973038C/en
Publication of WO2017092180A1 publication Critical patent/WO2017092180A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/165—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation combined with non-inertial navigation instruments
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/166—Mechanical, construction or arrangement details of inertial navigation systems
    • E—FIXED CONSTRUCTIONS
    • E21—EARTH OR ROCK DRILLING; MINING
    • E21C—MINING OR QUARRYING
    • E21C35/00—Details of, or accessories for, machines for slitting or completely freeing the mineral from the seam, not provided for in groups E21C25/00 - E21C33/00, E21C37/00 or E21C39/00
    • E21C35/08—Guiding the machine
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
    • G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
    • G01C21/10—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration
    • G01C21/12—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning
    • G01C21/16—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00 by using measurements of speed or acceleration executed aboard the object being navigated; Dead reckoning by integrating acceleration or speed, i.e. inertial navigation
    • G01C21/18—Stabilised platforms, e.g. by gyroscope

Definitions

  • the invention relates to a device and a method for positioning a coal mining machine, in particular to a coal mining machine positioning device and method which combines inertial navigation and laser scanning.
  • Positioning technology refers to the technique of taking some measure to the target to obtain the target location information.
  • the position of positioning in production and life is getting higher and higher.
  • the positioning of various types of equipment under the mine is slowly entering people's field of vision. Due to the frequent occurrence of frequent safety accidents and serious disasters in mines in recent years, the positioning of underground equipment is particularly important, which is also a prerequisite for automatic production and safe production.
  • the shearer is one of the important equipments for underground operations. Therefore, the positional positioning of the shearer is particularly important.
  • the coal mining machine positioning methods generally used in coal mines mainly include gear counting method, infrared beam shooting method, ultrasonic reflection method, wireless sensor network positioning method and pure inertial navigation method.
  • the shearer gear counting and positioning method is to count the number of turns of the running gear, and to locate the position of the shearer according to the hydraulic support. This method is relatively simple and low in cost, but because the shearer is During the operation, the machine moves horizontally and vertically along the working surface, and the gear counting method can only determine the walking distance of the shearer, thus causing inaccurate positioning and large error; the infrared radiation positioning method is installed in the shearer body.
  • the infrared emitting device has an infrared receiving device fixed in the hydraulic support.
  • the receiving device analyzes the strength of the received signal to determine the specific position of the shearer.
  • the disadvantage of adopting this method is that it cannot be continuously detected.
  • the position of the shearer, while the transmission and reception of the infrared signal must be at the same level, otherwise it is difficult to receive the signal effectively. Therefore, in the actual downhole environment, due to numerous interference factors, it is often impossible to accurately locate; wireless sensor network positioning
  • the location of the shearer is located through WIFI, ZIGBEE, UWB or Bluetooth technology. Due to the instability of the positioning system and the immature technical research, the cost is too high to be used in the underground.
  • the pure inertial positioning method uses the accelerometer and the gyroscope to obtain the axial acceleration and the angular velocity of the shearer, and then determines the algorithm by algorithm.
  • the position of the coal machine the disadvantage of this method is that due to the drift of the gyroscope and the accelerometer, the cumulative error is increasing, so the accuracy is difficult to guarantee, and the absolute positioning of the shearer cannot be realized.
  • the existing coal mining machine positioning methods such as gear counting method, infrared beam shooting method, ultrasonic reflection method, wireless sensor network positioning method and pure inertial navigation method, etc., locate the position of the coal mining machine under the mine. There is still a large error, which is often subject to the influence of the detection method itself and the detection environment under the mine. The positioning of the shearer cannot meet the accuracy requirements.
  • the object of the present invention is to overcome the deficiencies in the prior art, and to provide a coal mining machine positioning device and method for integrating inertial navigation and laser scanning, and to solve the problem that the cumulative error of the inertial navigation positioning is increased continuously.
  • the problem is to achieve precise positioning of the position of the shearer.
  • the technical solution adopted by the present invention is: a coal mining machine positioning device and a positioning method which are integrated by the inertial navigation and the laser scanning;
  • the shearer positioning device comprises: a coal mining machine, an inertial navigation positioning device, a laser scanning device, an explosion-proof outer casing of the positioning device and a host computer; a laser signal receiving module of the explosion-proof housing of the positioning device and the laser scanning device is fixed on the body of the shearer
  • the inertial navigation positioning device is installed in the explosion-proof housing of the positioning device;
  • the inertial navigation positioning device comprises a three-axis gyroscope, a three-axis accelerometer and an inertial navigation microprocessor; the three-axis gyroscope comprises a three-axis gyroscope, the three-axis accelerometer comprises a three-axis acceleration sensor; and the shearer is in operation
  • the inertial navigation positioning device measures the real-time angular rate in three directions by a three-axis gyroscope, and the real-time acceleration values in three directions are measured by a three-axis accelerometer, and the three-axis gyro sensor and the three-axis acceleration sensor are
  • the measurement data is sampled to the inertial navigation microprocessor, and the inertial navigation microprocessor is connected to the host computer through the serial port;
  • the laser scanning device comprises a laser scanning base station, a laser signal receiving module and a laser scanning microprocessor; the laser scanning base station is arranged in the working area of the shearer; the laser scanning microprocessor is installed in the explosion-proof housing of the positioning device; the laser signal receiving module Connected with the laser scanning microprocessor, the laser scanning microprocessor is connected to the host computer through the serial port, and transmits the laser scanning positioning data to the coal mining machine positioning control system of the upper computer; the laser scanning base station emits laser light from the shearer body
  • the laser signal receiving module receives the received time information, and the received time information is collected and processed by the laser scanning microprocessor; the upper computer determines the coefficient weight and the neural network algorithm for positioning evaluation by using the least square method to discriminate and process the data information.
  • the algorithm is used to finalize the position of the shearer for precise positioning.
  • the shearer positioning method comprises the following steps:
  • the explosion-proof casing of the positioning device is fixed and fixed on the fuselage body, and the whole inertial navigation positioning device is installed in the explosion-proof casing; the positioning device measures the real-time angle in three directions through the three-axis gyroscope and the three-axis accelerometer respectively. Rate, real-time acceleration value, and send the measured value to the inertial navigation microprocessor, and solve the calculation result of the coal mining machine by inertial navigation measurement;
  • Inertial navigation microprocessor and laser scanning microprocessor are connected with the host computer through the serial port to establish data communication, and respectively transmit the results of the shearer positioning obtained by the respective solvers to the positioning control system of the upper machine shearer to realize the data.
  • the coal mining machine positioning model is established.
  • the model includes laser scanning system and inertial navigation system to realize positioning data classification and accurate measurement of laser scanning.
  • the three-dimensional position coordinates of the base station are input into the laser scanning system, and the coordinates of the initial position of the shearer are accurately measured and input into the inertial navigation system;
  • step B the following steps are included:
  • the arrangement of the laser scanning base station should be arranged according to the working environment of the current coal mining machine, according to the principle that every point in the operation of the shearer can be scanned by more than two base stations, and considering the cost of the base station, 3 base stations achieve positioning;
  • the laser signal receiving module is installed on the fuser body, and the number of modules is three to realize the reception of the laser signal; the laser scanning microprocessor in the explosion-proof casing is connected to the laser signal receiving module through the serial port to realize the data. Reading
  • the laser scanning microprocessor includes a signal threshold setting part. Since the laser signal is easily affected by dust and shielding, when the laser signal is poor and the intensity is low, the required signal for positioning cannot be achieved, and the microprocessor does not perform data. The solution is set to a value of ⁇ . When the received signal strength is greater than ⁇ , the microprocessor performs positioning data calculation, and calculates the position information of the shearer through an algorithm.
  • the step E includes the following steps:
  • the shearer works normally, the inertial navigation system and the laser scanning system operate normally. Because of the signal threshold judgment in the laser scanning microprocessor, when the signal strength is satisfied, the shearer positioning data given by the two systems is sent. Into the fusion algorithm, optimize; when When the signal strength does not meet the requirements of laser scanning, only inertial navigation positioning data is used as the position information of the shearer;
  • the distribution of weight coefficients is determined by least squares method, and the artificial neural network algorithm is used to evaluate the assigned coefficients and positioning positions, and finally realize the positional positioning of the shearer;
  • the input layer is the two positioning coordinates for assigning weights, that is, the input layer vector P is as follows:
  • n is the number of nodes in the output layer
  • c is a constant within 1-10
  • L is the number of nodes in the hidden layer
  • the number of nodes in the selected hidden layer is 3, according to the neural network Algorithm requirements, establishing a model
  • T refers to the expected output value and E is the error value
  • Implicit layer weight change ⁇ w ij adjustment formula
  • Implicit layer threshold change ⁇ i adjustment formula
  • the beneficial effects, due to the adoption of the above scheme, the coal mining machine positioning device and method, the inertial navigation positioning, the laser scanning positioning are integrated to achieve the positioning of the shearer; the simple use of inertial navigation positioning will increase the cumulative error
  • the big problem causes the shearer positioning accuracy to be out of alignment.
  • the laser scanning positioning method can achieve accurate positioning, and the accurate position information can be assigned to the inertial navigation system to set the initial value of each positioning, thereby eliminating the accumulation. Error; although the laser scanning method is accurate in positioning, scanning is often affected by the harsh environment in the well, such as dust, shielding, etc., so that the scanning can not produce results, and there are errors due to time synchronization, time delay, etc.
  • the inertial navigation system can give the coal mining machine positioning result when the laser scanning position information deviation is too large or unable to locate; the two methods are combined with each other, and the fusion optimization algorithm is further processed to obtain the shearer position coordinates. Achieve precise positioning of the position of the shearer.
  • the coal mining machine positioning method combining inertial navigation and laser scanning is adopted, which takes advantage of the advantages of the two positioning methods, namely, the advantages of strong anti-interference ability of inertial navigation positioning and accurate laser scanning positioning, and effectively suppresses inertial navigation.
  • the time accumulation error and the shortcomings of laser scanning are easily affected by interference and occlusion, which ensures the accuracy of positioning, reduces positioning error, and meets the requirements of coal mining machine positioning.
  • the method of the invention is safe and reliable, convenient to install and operate, and avoids the situation of error in actual dynamic measurement, and has important reference value and practical significance.
  • 1 is a flow chart of the working system of the shearer of the present invention.
  • FIG. 2 is a layout view of a shearer positioning device in which the inertial navigation and laser scanning of the present invention are combined.
  • Figure 3 is a schematic view of the interior of the explosion-proof housing of the positioning device of the present invention.
  • a coal mining machine positioning device combining inertial navigation and laser scanning
  • the coal mining machine positioning device comprises: a coal mining machine 1, an inertial navigation positioning device 4, a laser scanning device, and an explosion-proof housing of the positioning device 2 And the upper computer 6; the laser device receiving module of the positioning device explosion-proof housing 2 and the laser scanning device is fixed on the body of the shearer 1; the inertial navigation positioning device 4 is installed in the explosion-proof housing 2 of the positioning device;
  • the inertial navigation positioning device 4 includes a three-axis gyroscope 4-1, a three-axis accelerometer 4-2, and an inertial navigation microprocessor 4-3; the three-axis gyroscope 4-1 includes a three-axis gyro sensor, three-axis acceleration Meter 4-2 includes a three-axis acceleration sensor; during the operation of the shearer, the inertial navigation positioning device 4 measures the real-time angular rate in three directions through the three-axis gyroscope 4-1, through the three-axis accelerometer 4-2 The real-time acceleration values in three directions are measured, and the measurement data of the three-axis gyro sensor and the three-axis acceleration sensor are sampled to the inertial navigation microprocessor, and the inertial navigation microprocessor is connected to the upper computer through the serial port;
  • the laser scanning device comprises a laser scanning base station, a laser signal receiving module 3 and a laser scanning microprocessor 5; the laser scanning base station is arranged in the working area of the shearer; the laser scanning microprocessor 5 is installed in the explosion-proof housing 2 of the positioning device;
  • the laser signal receiving module 3 is connected to the laser scanning microprocessor 5, and the laser scanning microprocessor 5 is connected to the upper computer 6 through the serial port, and transmits the laser scanning positioning data to the coal mining machine positioning control system of the upper computer 6;
  • the laser scanning base station transmits
  • the laser is received by the laser signal receiving module on the shearer body, and the received time information is collected and processed by the laser scanning microprocessor 5; the host computer 6 determines the coefficient by using the least square method by discriminating the data information.
  • the weighting and neural network algorithm performs a fusion algorithm for positioning evaluation to finally determine the position of the shearer and achieve precise positioning.
  • a coal mining machine positioning method combining inertial navigation and laser scanning includes the following steps:
  • the explosion-proof casing of the positioning device is fixed and fixed on the fuser body, and the whole inertial navigation positioning device is installed in the explosion-proof casing.
  • the positioning device measures the real-time angular rate and real-time acceleration values in three directions through a three-axis gyroscope and a three-axis accelerometer, and sends the measured values to the inertial navigation micro-processing unit, and obtains the inertial navigation measurement by algorithm solution. Shearer positioning results.
  • the inertial navigation micro-processing unit and the laser scanning micro-processing unit are connected with the host computer through the serial port to establish data communication, and respectively transmit the results of the shearer positioning obtained by the respective solvers to the positioning control system of the upper machine shearer to realize the data. Interaction.
  • the coal mining machine positioning model is established.
  • the model includes laser scanning system and inertial navigation system to realize positioning data classification and accurate measurement of laser scanning.
  • the three-dimensional position coordinates of the base station are input into the laser scanning system, and the coordinates of the initial position of the shearer are accurately measured and input into the inertial navigation system.
  • step B the following steps are included:
  • the arrangement of the laser scanning base station should be arranged according to the working environment of the current shearer, according to the principle that every point in the operation of the shearer can be scanned by more than two base stations, and considering the cost of the base station, the general arrangement 3 base stations to achieve positioning.
  • the laser signal receiving module is installed on the shearer body, and the number of modules is three to realize the reception of the laser signal.
  • the laser scanning micro processing unit in the explosion-proof housing is connected to the laser signal receiving module through the serial port to realize data reading.
  • the laser scanning micro-processing unit includes a signal threshold setting part. Since the laser signal is easily affected by dust and shielding, when the laser signal is poor, the intensity is low and the required signal for positioning cannot be achieved, and the micro-processing unit does not perform data. Solution.
  • the threshold of the set signal is ⁇ . When the received signal strength is greater than ⁇ , the micro-processing unit performs positioning data calculation, and solves the position information of the shearer by an algorithm.
  • FIG. 1 is a working flow chart of the shearer positioning system.
  • the working process of the shearer positioning system is as described in E1 ⁇ E5:
  • the shearer works normally, the inertial navigation system and the laser scanning system operate normally. Because of the signal threshold judgment in the laser scanning microprocessor, when the signal strength is satisfied, the shearer positioning data given by the two systems is sent. Into the fusion algorithm, to optimize; when the signal strength does not meet the needs of laser scanning, only the inertial navigation positioning data is used as the shearer position information;
  • the distribution of weight coefficients is determined by least squares method, and the artificial neural network algorithm is used to evaluate the assigned coefficients and positioning positions, and finally realize the positional positioning of the shearer;
  • the input layer is the two positioning coordinates for assigning weights, that is, the input layer vector P is as follows:
  • n is the number of nodes in the output layer
  • c is a constant within 1-10
  • L is the number of nodes in the hidden layer
  • the number of nodes in the selected hidden layer is 3, according to the neural network Algorithm requirements, establishing a model
  • T refers to the expected output value and E is the error value
  • Implicit layer weight change ⁇ w ij adjustment formula
  • Implicit layer threshold change ⁇ i adjustment formula
  • the coal mining machine positioning result processed by the algorithm is input to the inertial navigation micro processing unit through the serial port, and is used as the initial value of the position calculation of the next inertial navigation micro processing unit. At the same time, the positioning results are given in the shearer positioning model.

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Abstract

一种惯性导航与激光扫描融合的采煤机定位装置及方法。该定位装置包括：在采煤机（1）机身上固定有定位装置防爆外壳（2）、激光信号接收模块（3）；惯性导航定位装置（4）、激光扫描微处理器（5）安装在防爆装置内；当采煤机（1）工作时，惯性导航定位装置（4）通过传感器得到实时角速率、实时加速度，并将数据传至惯性导航微处理器（4-3）；激光扫描装置中，激光扫描基站布置在采煤机（1）工作区域，其激光信号被激光信号接收模块（3）接收，同时数据传至激光扫描微处理器（5）；微处理器（4-3、5）通过串口与上位机（6）连接，将各自采集的定位数据传至采煤机定位控制系统以实现数据的处理，其采用基于最小二乘法—神经网络算法的融合算法确定采煤机（1）的位置，实现精确定位。

Description

一种惯性导航与激光扫描融合的采煤机定位装置及方法 技术领域
本发明涉及一种采煤机定位的装置及方法，特别是一种惯性导航与激光扫描融合的采煤机定位装置及方法。
背景技术
定位技术，是指对目标采取某种手段进行测量，进而获得目标位置信息的技术。随着现代技术的不断进步，在生产生活中，定位的地位也越来越高。在诸多定位领域中，对矿井下各类设备的定位正慢慢步入人们的视野。由于近年来矿井下安全事故频发、灾害严重等问题突出，因此对矿井下设备的定位显得尤为重要，这同时也是实现自动化生产和安全生产的前提条件。在煤炭资源的开采过程中，采煤机是井下作业重要的设备之一，因此，对采煤机的位置定位就显得尤为重要。然而，由于矿井下的特殊条件，其环境的复杂性使得很多通常采用的定位手段在矿井下达不到定位精度的要求，甚至在矿井下无法实现对采煤机位置的确定。在这种背景下，惯性导航定位、激光扫描定位等技术的不断发展，使得对采煤机位置的精确定位成为可能。
在采煤机的传统校准方式中，往往不能实现精确校准，存在固有误差。当前，煤矿井下一般采用的采煤机定位方式主要有齿轮计数法、红外对射法、超声波反射法、无线传感网络定位法及纯惯性导航法。其中，采煤机齿轮计数定位法是通过对行走部齿轮转动的圈数进行计数，并依据液压支架来定位出采煤机的位置，这种方法比较简单，成本低，但由于采煤机在作业过程中是沿着工作面横向及纵向运动，而齿轮计数法只能确定采煤机行走路程，因此造成定位不精确，产生很大误差；红外对射定位法则是在采煤机机身安装红外发射装置，在液压支架固定有红外接收装置，在采煤机作业过程中，通过接收装置对接收信号强弱的分析，从而判断采煤机具体位置，采用这个方法的缺点是不能连续的检测采煤机的位置，同时红外信号的发射和接收必须处于同一水平面，否则很难有效的接收信号，因此在实际的井下环境中，由于干扰因素众多，往往也不能精确定位；无线传感网络定位是通过WIFI、ZIGBEE、UWB或蓝牙等技术对采煤机位置进行定位，这种定位方式往往受制于定位系统不稳定以及技术研究不成熟、成本过高因此无法在井下运用；纯惯性定位法是利用加速度计和陀螺仪得出采煤机的轴加速度及轴角速度，然后通过算法来确定采煤机的位置，这种方法缺点是由于陀螺仪和加速度计存在漂移，累积误差不断增大，因此精度很难保证，也无法实现对采煤机的绝对定位。
综上所述，现有的采煤机定位方式，如齿轮计数法、红外对射法、超声波反射法、无线传感网络定位法及纯惯性导航法等，对矿井下采煤机的位置定位仍存在较大误差，往往受制于其检测方式自身与矿井下检测环境的影响，对采煤机的定位无法满足对精度的要求。
发明内容
技术问题：本发明的目的是为了克服现有技术中存在的不足，提供一种惯性导航与激光扫描融合的采煤机定位装置和方法，解决单纯的采用惯性导航定位存在累积误差不断增大的问题，实现对采煤机的位置精确定位。
技术方案：为了实现上述目的，本发明采用的技术方案为：该惯性导航与激光扫描融合的采煤机定位装置和定位方法；
采煤机定位装置包括：采煤机、惯性导航定位装置、激光扫描装置、定位装置防爆外壳及上位机；在采煤机机身上固定有定位装置防爆外壳和激光扫描装置的激光信号接收模块；惯性导航定位装置安装在定位装置防爆外壳内；
所述的惯性导航定位装置包括三轴陀螺仪、三轴加速度计、惯性导航微处理器；三轴陀螺仪包括有三轴陀螺传感器，三轴加速度计包括有三轴加速度传感器；在采煤机运行过程中，惯性导航定位装置通过三轴陀螺仪测得三个方向上的实时角速率，通过三轴加速度计测得三个方向上的实时加速度值，并将三轴陀螺传感器和三轴加速度传感器的测量数据采样至惯性导航微处理器，惯性导航微处理器通过串口与上位机连接；
所述的激光扫描装置包括激光扫描基站、激光信号接收模块和激光扫描微处理器；激光扫描基站布置在采煤机工作区域；激光扫描微处理器安装在定位装置防爆外壳内；激光信号接收模块与激光扫描微处理器连接，激光扫描微处理器通过串口与上位机连接，将激光扫描定位数据传至上位机中采煤机定位控制系统；激光扫描基站发射的激光由采煤机机身上的激光信号接收模块进行接收，接收到的时间信息被激光扫描微处理器进行采集处理；上位机通过对数据信息进行判别处理，采用最小二乘法确定系数权值、神经网络算法进行定位评估的融合算法以最终确定采煤机位置，实现精确定位。
采煤机定位方法，包括如下步骤：
A.采煤机机身上安装固定有定位装置防爆外壳，将整个惯性导航定位装置安装在防爆外壳内；定位装置通过三轴陀螺仪、三轴加速度计分别测得三个方向上的实时角速率、实时加速度值，并将测量值送入惯性导航微处理器，通过算法解算，得到惯性导航测量的采煤机定位结果；
B.在采煤机工作区域布置激光扫描基站，在采煤机机身上安装激光信号接收模块，同时将激光扫描微处理器固定在防爆外壳内，以实现激光扫描的采煤机定位。
C.惯性导航微处理器、激光扫描微处理器通过串口与上位机连接，建立数据通讯，分别将各自解算得到的采煤机定位结果传送至上位机采煤机定位控制系统，实现数据的交互；
D.在上位机的采煤机定位控制系统中，根据实际工作区域及装置布置情况，建立采煤机定位模型，模型中包括激光扫描系统、惯性导航系统以实现定位数据分类，精确测量激光扫描基站的三维位置坐标输入激光扫描系统，精确测量采煤机初始位置坐标输入惯性导航系统；
E.采煤机正常工作，采煤机定位系统运行。
所述的步骤B中，包含以下步骤：
B1.激光扫描基站的布置应根据当前采煤机的工作环境，按照采煤机运行过程中每一点都能被两个以上的基站扫描到的原则进行布置，同时考虑到基站成本问题，以布置3个基站实现定位；
B2.采煤机机身上安装激光信号接收模块，模块数量为3个，以实现对激光信号的接收；防爆外壳内的激光扫描微处理器通过串口与激光信号接收模块相连接，以实现数据的读取；
B3.激光扫描微处理器包含信号阈值设定部分，由于激光信号容易受到粉尘、遮蔽物的影响，当激光信号较差，强度较低无法达到定位所需信号的要求，微处理器不进行数据解算；设定信号阈值为δ，当接收信号强度大于δ时，微处理器进行定位数据解算，通过算法解算出采煤机位置信息。
所述的步骤E中包含以下步骤：
E1.采煤机正常工作，惯性导航系统、激光扫描系统正常运行，由于在激光扫描微处理器内有信号阈值判断，当信号强度满足情况下，两个系统给出的采煤机定位数据送入融合算法，进行优化；当 信号强度不满足激光扫描的需求时，只采用惯性导航定位数据作为采煤机位置信息；
E2.假设惯性导航系统定位采煤机位置为(x1、y1、z1)，激光扫描系统采煤机定位位置为(x2、y2、z2)，则根据当前检测条件，分配权值系数a、b，即采煤机位置坐标(x、y、z)：
(x、y、z)＝a(x1、y1、z1)+b(x2、y2、z2)
同时满足系数a+b＝1；
E3.权值系数的分配采用最小二乘法确定，并采用人工神经网络算法对分配后的系数及定位位置进行评估，最终实现对采煤机位置定位；
最小二乘法原理：假设有函数：
Pn(x)＝(x、y、z)＝a(x1、y1、z1)+b(x2、y2、z2)＝anxn+an-1xn-1+…+a1x+a0
其中，a0，a1，...，an为系数常数，Pn(x)为展开多项式。则假定数组为{(xi，yi)|i＝1，2…，m}
选择常数a0，a1，…，an使得方差最小，即
Figure PCTCN2016074617-appb-000001
其中S为方差，为了使S最小化，满足对于系数常数a0，a1，…，an，
Figure PCTCN2016074617-appb-000002
则确定多项式Pn(x)，进而可求得权重系数a、b；
人工神经网络算法：结合采煤机定位实际要求，建立采煤机融合定位系统神经网络模型，其输入层为分配好权值的两个定位坐标，即输入层向量P如下：
P＝[a(x1、y1、z1)、b(x2、y2、z2)]
输出层O为想要得到的采煤机位置坐标，即：O＝[(x、y、z)]
根据经验公式
Figure PCTCN2016074617-appb-000003
式中，m指输入层的节点数，n为输出层的节点数，c为1—10之内的常数，L为隐含层节点数，选择隐含层节点数为3，则根据神经网络算法要求，建立模型；
Pj表示输入层第j个节点的输入，j＝1、2；wij表示隐含层第i个节点到输入层第j个节点之间的权值；θi表示隐含层第i个节点的阈值；
Figure PCTCN2016074617-appb-000004
表示隐含层的激励函数；wi表示输出层到隐含层第i个节点之间的权值，i＝1、2、3；τ表示输出层的阈值；
Figure PCTCN2016074617-appb-000005
表示输出层的激励函数；O表示输出层的输出；对于
Figure PCTCN2016074617-appb-000006
一般取为(0，1)内连续取值的sigmoid函数：
Figure PCTCN2016074617-appb-000007
对于
Figure PCTCN2016074617-appb-000008
一般采用purelin函数，选择
Figure PCTCN2016074617-appb-000009
则
(1)信号的前向传播过程
隐含层第i个节点的输入neti：neti＝wi1P1+wi2P2+θi；隐含层第i个节点的输出yi
Figure PCTCN2016074617-appb-000010
输出层输入net：
Figure PCTCN2016074617-appb-000011
输出层输出O：
Figure PCTCN2016074617-appb-000012
(2)误差的反向传播过程
对于每一个输入的位置信息，且假设每次只有一组样本，定义误差函数：
Figure PCTCN2016074617-appb-000013
其中，T指的是预期的输出值，E为误差值大小；
根据误差梯度下降原理，输出层权值变化Δwi公式：
Figure PCTCN2016074617-appb-000014
输出层阈值变化Δτ调整公式：
Figure PCTCN2016074617-appb-000015
隐含层权值变化Δwij调整公式：
Figure PCTCN2016074617-appb-000016
隐含层阈值变化Δθi调整公式：
Figure PCTCN2016074617-appb-000017
最终经过网络优化，输出采煤机坐标向量O＝[(x、y、z)]；
E4.将算法处理后的采煤机定位结果通过串口输入至惯性导航微处理器，作为下一次惯性导航微处理单元进行位置解算的初值，同时，在采煤机定位模型中给出定位结果；
E5.当采煤机运行至端头位置，采煤机处于停止工作状态，此时惯性导航系统停止工作，由激光扫描进行多次重复测量，剔除错误数据后采用最小包容圆算法得到采煤机位置，并将此位置结果赋值给惯性导航系统中采煤机位置初值；采煤机继续工作，重复E1～E4。
有益效果，由于采用了上述方案，采煤机定位装置和方法，将惯性导航定位、激光扫描定位进行融合来实现对采煤机的定位；解决了单纯的采用惯性导航定位会存在累积误差不断增大的问题，造成采煤机定位精度失准，采用激光扫描的定位方式可以实现准确定位，并可以将准确的位置信息赋值给惯性导航系统内设定为每一次的定位初值，从而去除累积误差；激光扫描方式虽然定位精确，但是扫描往往因为井下恶劣的环境而受到影响，如粉尘、遮蔽物等，使得扫描无法得出结果，同时也存在因时间同步、时间延迟等问题产生误差，此时，惯性导航系统可以在激光扫描位置信息偏差过大或无法定位的时刻，给出采煤机定位结果；两种方式进行相互结合，采用融合优化算法进一步的处理，得到采煤机位置坐标，实现对采煤机位置的精确定位。
优点：
(1)选取惯性导航与激光扫描融合的采煤机定位方法，利用了两种定位方法本身的优势，即惯性导航定位抗干扰能力强、激光扫描定位准确的优点，同时有效的抑制了惯性导航时间累积误差以及激光扫描容易受到干扰和遮挡影响的缺点，保证了定位的精度，减少定位误差，符合采煤机定位的要求。
(2)本发明方法使用，安全可靠，安装和操作方便，规避了在实际动态测量中产生误差的情形，具有重要的参考价值和实际意义。
附图说明
图1是本发明采煤机定位系统工作流程图。
图2是本发明惯性导航与激光扫描融合的采煤机定位装置布置图。
图3是本发明定位装置防爆外壳内部示意图。
图4是本发明算法流程图。
图中：1、采煤机；2、定位装置防爆外壳；3、激光信号接收模块；4、惯性导航定位装置；4-1、三轴陀螺仪；4-2、三轴加速度计；4-3、惯性导航微处理器；5、激光扫描微处理器；6、上位机。
具体实施方式
下面结合附图对本发明做更进一步的说明：
由图2、图3可知，一种惯性导航与激光扫描融合的采煤机定位装置，采煤机定位装置包括：采煤机1、惯性导航定位装置4、激光扫描装置、定位装置防爆外壳2及上位机6；在采煤机1机身上固定有定位装置防爆外壳2和激光扫描装置的激光信号接收模块；惯性导航定位装置4安装在定位装置防爆外壳2内；
所述的惯性导航定位装置4包括三轴陀螺仪4-1、三轴加速度计4-2、惯性导航微处理器4-3；三轴陀螺仪4-1包括有三轴陀螺传感器，三轴加速度计4-2包括有三轴加速度传感器；在采煤机运行过程中，惯性导航定位装置4通过三轴陀螺仪4-1测得三个方向上的实时角速率，通过三轴加速度计4-2测得三个方向上的实时加速度值，并将三轴陀螺传感器和三轴加速度传感器的测量数据采样至惯性导航微处理器，惯性导航微处理器通过串口与上位机连接；
所述的激光扫描装置包括激光扫描基站、激光信号接收模块3和激光扫描微处理器5；激光扫描基站布置在采煤机工作区域；激光扫描微处理器5安装在定位装置防爆外壳2内；激光信号接收模块3与激光扫描微处理器5连接，激光扫描微处理器5通过串口与上位机6连接，将激光扫描定位数据传至上位机6中采煤机定位控制系统；激光扫描基站发射的激光由采煤机机身上的激光信号接收模块进行接收，接收到的时间信息被激光扫描微处理器5进行采集处理；上位机6通过对数据信息进行判别处理，采用最小二乘法确定系数权值、神经网络算法进行定位评估的融合算法以最终确定采煤机位置，实现精确定位。
一种惯性导航与激光扫描融合的采煤机定位方法，包括如下步骤：
A.采煤机机身上安装固定有定位装置防爆外壳，将整个惯性导航定位装置安装在防爆外壳内。定位装置通过三轴陀螺仪、三轴加速度计分别测得三个方向上的实时角速率、实时加速度值，并将测量值送入惯性导航微处理单元，通过算法解算，得到惯性导航测量的采煤机定位结果。
B.在采煤机工作区域布置激光扫描基站，在采煤机机身上安装激光信号接收模块，同时将激光扫描微处理单元固定在防爆外壳内，以实现激光扫描的采煤机定位。
C.惯性导航微处理单元、激光扫描微处理单元通过串口与上位机连接，建立数据通讯，分别将各自解算得到的采煤机定位结果传送至上位机采煤机定位控制系统，实现数据的交互。
D.在上位机的采煤机定位控制系统中，根据实际工作区域及装置布置情况，建立采煤机定位模型，模型中包括激光扫描系统、惯性导航系统以实现定位数据分类，精确测量激光扫描基站的三维位置坐标输入激光扫描系统，精确测量采煤机初始位置坐标输入惯性导航系统。
E.采煤机正常工作，采煤机定位系统运行。
所述的步骤B中，包含以下步骤：
B1.激光扫描基站的布置应根据当前采煤机的工作环境，按照采煤机运行过程中每一点都能被两个以上的基站扫描到的原则进行布置，同时考虑到基站成本问题，一般布置3个基站以实现定位。
B2.采煤机机身上安装激光信号接收模块，模块数量为3个，以实现对激光信号的接收。防爆外壳内的激光扫描微处理单元通过串口与激光信号接收模块相连接，以实现数据的读取。
B3.激光扫描微处理单元包含信号阈值设定部分，由于激光信号容易受到粉尘、遮蔽物的影响，当激光信号较差，强度较低无法达到定位所需信号的要求，微处理单元不进行数据解算。设定信号阈值为δ，当接收信号强度大于δ时，微处理单元进行定位数据解算，通过算法解算出采煤机位置信息。
图1为采煤机定位系统工作流程图，采煤机定位系统工作流程如E1～E5所述：
E1.采煤机正常工作，惯性导航系统、激光扫描系统正常运行，由于在激光扫描微处理器内有信号阈值判断，当信号强度满足情况下，两个系统给出的采煤机定位数据送入融合算法，进行优化；当信号强度不满足激光扫描的需求时，只采用惯性导航定位数据作为采煤机位置信息；
E2.假设惯性导航系统定位采煤机位置为(x1、y1、z1)，激光扫描系统采煤机定位位置为(x2、y2、z2)，则根据当前检测条件，分配权值系数a、b，即采煤机位置坐标(x、y、z)：
(x、y、z)＝a(x1、y1、z1)+b(x2、y2、z2)
同时满足系数a+b＝1；
E3.权值系数的分配采用最小二乘法确定，并采用人工神经网络算法对分配后的系数及定位位置进行评估，最终实现对采煤机位置定位；
最小二乘法原理：假设有函数：
Pn(x)＝(x、y、z)＝a(x1、y1、z1)+b(x2、y2、z2)＝anxn+an-1xn-1+…+a1x+a0
其中，a0，a1，…，an为系数常数，Pn(x)为展开多项式。则假定数组为{(xi，yi)|i＝1，2…，m}
选择常数a0，a1，…，an使得方差最小，即
Figure PCTCN2016074617-appb-000018
其中S为方差，为了使S最小化，满足对于系数常数a0，a1，…，an，
Figure PCTCN2016074617-appb-000019
则确定多项式Pn(x)，进而可求得权重系数a、b；
人工神经网络算法：结合采煤机定位实际要求，建立采煤机融合定位系统神经网络模型，其输入层为分配好权值的两个定位坐标，即输入层向量P如下：
P＝[a(x1、y1、z1)、b(x2、y2、z2)]
输出层O为想要得到的采煤机位置坐标，即：O＝[(x、y、z)]
根据经验公式
Figure PCTCN2016074617-appb-000020
式中，m指输入层的节点数，n为输出层的节点数，c为1—10之内的常数，L为隐含层节点数，选择隐含层节点数为3，则根据神经网络算法要求，建立模型；
Pj表示输入层第j个节点的输入，j＝1、2；wij表示隐含层第i个节点到输入层第j个节点之间的权值；θi表示隐含层第i个节点的阈值；
Figure PCTCN2016074617-appb-000021
表示隐含层的激励函数；wi表示输出层到隐含层第i个节点之间的权值，i＝1、2、3；τ表示输出层的阈值；
Figure PCTCN2016074617-appb-000022
表示输出层的激励函数；O表示输出层的输出；对于
Figure PCTCN2016074617-appb-000023
一般取为(0，1)内连续取值的sigmoid函数：
Figure PCTCN2016074617-appb-000024
对于
Figure PCTCN2016074617-appb-000025
一般采用purelin函数，选择
Figure PCTCN2016074617-appb-000026
则
(1)信号的前向传播过程
隐含层第i个节点的输入neti：neti＝wi1P1+wi2P2+θi；隐含层第i个节点的输出yi
Figure PCTCN2016074617-appb-000027
输出层输入net：
Figure PCTCN2016074617-appb-000028
输出层输出O：
Figure PCTCN2016074617-appb-000029
(2)误差的反向传播过程
对于每一个输入的位置信息，且假设每次只有一组样本，定义误差函数：
Figure PCTCN2016074617-appb-000030
其中，T指的是预期的输出值，E为误差值大小；
根据误差梯度下降原理，输出层权值变化Δwi公式：
Figure PCTCN2016074617-appb-000031
输出层阈值变化Δτ调整公式：
Figure PCTCN2016074617-appb-000032
隐含层权值变化Δwij调整公式：
Figure PCTCN2016074617-appb-000033
隐含层阈值变化Δθi调整公式：
Figure PCTCN2016074617-appb-000034
最终经过网络优化，输出采煤机坐标向量O＝[(x、y、z)]；
E4.将算法处理后的采煤机定位结果通过串口输入至惯性导航微处理单元，作为下一次惯性导航微处理单元进行位置解算的初值。同时，在采煤机定位模型中给出定位结果。
E5.当采煤机运行至端头位置，采煤机处于停止工作状态，此时惯性导航系统停止工作，由激光扫描进行多次重复测量，剔除错误数据后采用最小包容圆算法得到采煤机位置，并将此位置结果赋值给惯性导航系统中采煤机位置初值。采煤机继续工作，重复E1～E4。

Claims (6)

  1. 一种惯性导航与激光扫描融合的采煤机定位装置，其特征是：采煤机定位装置包括：采煤机、惯性导航定位装置、激光扫描装置、定位装置防爆外壳及上位机；在采煤机机身上固定有定位装置防爆外壳和激光扫描装置的激光信号接收模块；惯性导航定位装置安装在定位装置防爆外壳内。
  2. 根据权利要求1所述的一种惯性导航与激光扫描融合的采煤机定位装置，其特征是：所述的惯性导航定位装置包括三轴陀螺仪、三轴加速度计、惯性导航微处理器；三轴陀螺仪包括有三轴陀螺传感器，三轴加速度计包括有三轴加速度传感器；在采煤机运行过程中，惯性导航定位装置通过三轴陀螺仪测得三个方向上的实时角速率，通过三轴加速度计测得三个方向上的实时加速度值，并将三轴陀螺传感器和三轴加速度传感器的测量数据采样至惯性导航微处理器，惯性导航微处理器通过串口与上位机连接。
  3. 根据权利要求1所述的一种惯性导航与激光扫描融合的采煤机定位装置，其特征是：所述的激光扫描装置包括激光扫描基站、激光信号接收模块和激光扫描微处理器；激光扫描基站布置在采煤机工作区域；激光扫描微处理器安装在定位装置防爆外壳内；激光信号接收模块与激光扫描微处理器连接，激光扫描微处理器通过串口与上位机连接，将激光扫描定位数据传至上位机中采煤机定位控制系统；激光扫描基站发射的激光由采煤机机身上的激光信号接收模块进行接收，接收到的时间信息被激光扫描微处理器进行采集处理；上位机通过对数据信息进行判别处理，采用最小二乘法确定系数权值、神经网络算法进行定位评估的融合算法以最终确定采煤机位置，实现精确定位。
  4. 权利要求1所述的一种惯性导航与激光扫描融合的采煤机定位装置的定位方法，其特征是：采煤机定位方法，包括如下步骤：
    A.采煤机机身上安装固定有定位装置防爆外壳，将整个惯性导航定位装置安装在防爆外壳内；定位装置通过三轴陀螺仪、三轴加速度计分别测得三个方向上的实时角速率、实时加速度值，并将测量值送入惯性导航微处理器，通过算法解算，得到惯性导航测量的采煤机定位结果；
    B.在采煤机工作区域布置激光扫描基站，在采煤机机身上安装激光信号接收模块，同时将激光扫描微处理器固定在防爆外壳内，以实现激光扫描的采煤机定位。
    C.惯性导航微处理器、激光扫描微处理器通过串口与上位机连接，建立数据通讯，分别将各自解算得到的采煤机定位结果传送至上位机采煤机定位控制系统，实现数据的交互；
    D.在上位机的采煤机定位控制系统中，根据实际工作区域及装置布置情况，建立采煤机定位模型，模型中包括激光扫描系统、惯性导航系统以实现定位数据分类，精确测量激光扫描基站的三维位置坐标输入激光扫描系统，精确测量采煤机初始位置坐标输入惯性导航系统；
    E.采煤机正常工作，采煤机定位系统运行。
  5. 根据权利要求4所述的一种惯性导航与激光扫描融合的采煤机定位方法，其特征在于，所述的步骤B中，包含以下步骤：
    B1.激光扫描基站的布置应根据当前采煤机的工作环境，按照采煤机运行过程中每一点都能被两个以上的基站扫描到的原则进行布置，同时考虑到基站成本问题，以布置3个基站实现定位；
    B2.采煤机机身上安装激光信号接收模块，模块数量为3个，以实现对激光信号的接收；防爆外壳内的激光扫描微处理器通过串口与激光信号接收模块相连接，以实现数据的读取；
    B3.激光扫描微处理器包含信号阈值设定部分，由于激光信号容易受到粉尘、遮蔽物的影响，当 激光信号较差，强度较低无法达到定位所需信号的要求，微处理器不进行数据解算；设定信号阈值为δ，当接收信号强度大于δ时，微处理器进行定位数据解算，通过算法解算出采煤机位置信息。
  6. 根据权利要求4所述的一种惯性导航与激光扫描融合的采煤机定位方法，其特征在于，所述的步骤E中包含以下步骤：
    E1.采煤机正常工作，惯性导航系统、激光扫描系统正常运行，由于在激光扫描微处理器内有信号阈值判断，当信号强度满足情况下，两个系统给出的采煤机定位数据送入融合算法，进行优化；当信号强度不满足激光扫描的需求时，只采用惯性导航定位数据作为采煤机位置信息；
    E2.假设惯性导航系统定位采煤机位置为(x1、y1、z1)，激光扫描系统采煤机定位位置为(x2、y2、z2)，则根据当前检测条件，分配权值系数a、b，即采煤机位置坐标(x、y、z)：
    (x、y、z)＝a(x1、y1、z1)+b(x2、y2、z2)
    同时满足系数a+b＝1；
    E3.权值系数的分配采用最小二乘法确定，并采用人工神经网络算法对分配后的系数及定位位置进行评估，最终实现对采煤机位置定位；
    最小二乘法原理：假设有函数：
    Pn(x)＝(x、y、z)＝a(x1、y1、z1)+b(x2、y2、z2)＝anxn+an-1xn-1+…+a1x+a0
    其中，a0，a1，…，an为系数常数，Pn(x)为展开多项式。则假定数组为{(xi，yi)|i＝1，2…，m}
    选择常数a0，a1，…，an使得方差最小，即
    Figure PCTCN2016074617-appb-100001
    其中S为方差，为了使S最小化，满足对于系数常数a0，a1，…，an，
    Figure PCTCN2016074617-appb-100002
    则确定多项式Pn(x)，进而可求得权重系数a、b；
    人工神经网络算法：结合采煤机定位实际要求，建立采煤机融合定位系统神经网络模型，其输入层为分配好权值的两个定位坐标，即输入层向量P如下：
    P＝[a(x1、y1、z1)、b(x2、y2、z2)]
    输出层O为想要得到的采煤机位置坐标，即：O＝[(x、y、z)]
    根据经验公式
    Figure PCTCN2016074617-appb-100003
    式中，m指输入层的节点数，n为输出层的节点数，c为1—10之内的常数，L为隐含层节点数，选择隐含层节点数为3，则根据神经网络算法要求，建立模型；
    Pj表示输入层第j个节点的输入，j＝1、2；wij表示隐含层第i个节点到输入层第j个节点之间的权值；θi表示隐含层第i个节点的阈值；
    Figure PCTCN2016074617-appb-100004
    表示隐含层的激励函数；wi表示输出层到隐含层第i个节点之间的权值，i＝1、2、3；τ表示输出层的阈值；
    Figure PCTCN2016074617-appb-100005
    表示输出层的激励函数；O表示输出层的输出；对于
    Figure PCTCN2016074617-appb-100006
    一般取为(0，1)内连续取值的sigmoid函数：
    Figure PCTCN2016074617-appb-100007
    对于
    Figure PCTCN2016074617-appb-100008
    一般采用purelin函数，选择
    Figure PCTCN2016074617-appb-100009
    则
    (1)信号的前向传播过程
    隐含层第i个节点的输入neti：neti＝wi1P1+wi2P2+θi；隐含层第i个节点的输出yi
    Figure PCTCN2016074617-appb-100010
    输出层输入net：
    Figure PCTCN2016074617-appb-100011
    输出层输出O：
    Figure PCTCN2016074617-appb-100012
    (2)误差的反向传播过程
    对于每一个输入的位置信息，且假设每次只有一组样本，定义误差函数：
    Figure PCTCN2016074617-appb-100013
    其中，T指的是预期的输出值，E为误差值大小；
    根据误差梯度下降原理，输出层权值变化Δwi公式：
    Figure PCTCN2016074617-appb-100014
    输出层阈值变化Δτ调整公式：
    Figure PCTCN2016074617-appb-100015
    隐含层权值变化Δwij调整公式：
    Figure PCTCN2016074617-appb-100016
    隐含层阈值变化Δθi调整公式：
    Figure PCTCN2016074617-appb-100017
    最终经过网络优化，输出采煤机坐标向量O＝[(x、y、z)]；
    E4.将算法处理后的采煤机定位结果通过串口输入至惯性导航微处理器，作为下一次惯性导航微处理单元进行位置解算的初值，同时，在采煤机定位模型中给出定位结果；
    E5.当采煤机运行至端头位置，采煤机处于停止工作状态，此时惯性导航系统停止工作，由激光扫描进行多次重复测量，剔除错误数据后采用最小包容圆算法得到采煤机位置，并将此位置结果赋值给惯性导航系统中采煤机位置初值；采煤机继续工作，重复E1～E4。
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