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library(vegan) library(dplyr) library(corrplot) library(Hmisc) library(psych) library(tidyverse) mydata <- read.csv(file.choose()) head(mydata) M <- cor(mydata,method = 'spearman') class(M) M[1:5,1:5] symnum(M) res1 <- cor.mtest(M,conf.level = 0.95) # ???嵼?????ݵ??????? corrplot(M, method = "circle", type = 'upper', order = "hclust",addrect = 3, p.mat = res1$p, insig = "label_sig", sig.level = c(.001, .01, .05), pch.cex = .9, pch.col = "white") #corr_matrix <- corr.test(M, method = 'spearman') # ??д???????? #corr_matrix$r #corr_matrix$p head(mtcars) set.seed(20190420) n <- ncol(mtcars) grp <- c('Cluster_1', 'Cluster_2', 'Cluster_3') # ???????? sp <- c(rep(0.0008, 6), rep(0.007, 2), rep(0.03, 3), rep(0.13, 22)) # Pֵ gx <- c(-4.5, -2.5, 1) # ??????X???? gy <- c(n-1, n-5, 2.5) # ??????Y???? df <- data.frame( grp = rep(grp, each = n), # ???????ƣ?ÿ???ظ?n?? gx = rep(gx, each = n), # ??X???꣬ÿ???ظ?n?? gy = rep(gy, each = n), # ??Y???꣬ÿ???ظ?n?? x = rep(0:(n - 1) - 0.5, 3), # ??����?ӵ?X???? y = rep(n:1, 3), # ??����?ӵ?Y???? p = sample(sp), # ???˹?????pֵ???????????? r = sample(c(rep(0.8, 4), rep(0.31, 7), rep(0.12, 22))) # ???˹?????rֵ???????????? ) length(rep(grp, each = n)) length(rep(gx, each = n)) length(rep(gy, each = n)) length(rep(0:(n - 1) - 0.5, 3)) length(rep(n:1, 3)) length(sample(sp)) length(sample(c(rep(0.8, 4), rep(0.31, 7), rep(0.12, 22))) ) # ??һ???ִ????ǰ???ԭͼͼ??˵?????????????Ⱥ???ɫӳ?? df <- df %>% mutate( lcol = ifelse(p <= 0.001, '#1B9E77', NA), # pֵС??0.001ʱ????ɫΪ??ɫ???????��????? lcol = ifelse(p > 0.001 & p <= 0.01, '#88419D', lcol), lcol = ifelse(p > 0.01 & p <= 0.05, '#A6D854', lcol), lcol = ifelse(p > 0.05, '#B3B3B3', lcol), lwd = ifelse(r >= 0.5, 14, NA), # r >= 0.5 ʱ?????Կ???Ϊ14???????��????? lwd = ifelse(r >= 0.25 & r < 0.5, 7, lwd), lwd = ifelse(r < 0.25, 1, lwd) ) segments(df$gx, df$gy, df$x, df$y, lty = 'solid', lwd = df$lwd, col = df$lcol, xpd = TRUE) # ????��???? points(gx, gy, pch = 24, col = 'blue', bg = 'blue', cex = 3, xpd = TRUE) # ?????ǵ? text(gx - 0.5, gy, labels = grp, adj = c(1, 0.5), cex = 1.5, xpd = TRUE) # ?????? labels01 <- c('<= 0.001','0.001 < x <= 0.01','0.01 < x <= 0.05','> 0.05') labels02 <- c('>= 0.5', '0.25 - 0.5', '< 0.25') labels_x <- rep(-6, 4) labels_y <- seq(4.6, 2.6, length.out = 4) text(-6.5, 5.2, 'P-value', adj = c(0, 0.5), cex = 1.2, font = 2, xpd = TRUE) text(labels_x, labels_y, labels01, adj = c(0, 0.5), cex = 1.2, xpd = TRUE) points(labels_x - 0.5, labels_y, pch = 20, col = c('#1B9E77', '#88419D','#A6D854', '#B3B3B3'), cex = 3, xpd = TRUE) lines_x <- c(-6.5, -3, 0.5) lines_y <- rep(1.2, 3) text(-6.5, 1.9, "Mantel's r", adj = c(0, 0.5), cex = 1.2, font = 2, xpd = TRUE) text(lines_x + 1.5, lines_y, labels02, adj = c(0, 0.5), cex = 1.2, xpd = TRUE) segments(lines_x, lines_y, lines_x + 1, lines_y, lwd = c(14, 7, 2.5), lty = 'solid', col = '#B3B3B3', xpd = TRUE) segments(-6.9, 5.6, -2.8, 5.6, lty = 'solid', lwd = 1.2, col = 'grey50', xpd = TRUE) segments(-2.8, 5.6, -2.8, 1.8, lty = 'solid', lwd = 1.2, col = 'grey50', xpd = TRUE) segments(-2.8, 1.8, 3.6, 1.8, lty = 'solid', lwd = 1.2, col = 'grey50', xpd = TRUE) segments(3.6, 1.8, 3.6, 0.7, lty = 'solid', lwd = 1.2, col = 'grey50', xpd = TRUE) segments(3.6, 0.7, -6.9, 0.7, lty = 'solid', lwd = 1.2, col = 'grey50', xpd = TRUE) segments(-6.9, 0.7, -6.9, 5.6, lty = 'solid', lwd = 1.2, col = 'grey50', xpd = TRUE) library(pheatmap) library(vegan) library(dplyr) library(corrplot) library(Hmisc) library(psych) library(tidyverse) df<-read.csv("cluster.csv",header=T) df[is.na(df)]<-0 df pheatmap(df)这是什么代码
12-23
import pdfplumber import pandas as pd import os import re def extract_materials_from_pdf(pdf_path, filename): """ 从PDF文件中提取材料信息 - 专门针对ISO图纸格式 """ materials = [] try: with pdfplumber.open(pdf_path) as pdf: for page in pdf.pages: text = page.extract_text() if text: materials.extend(parse_iso_materials(text, filename)) return materials except Exception as e: print(f"处理文件 {filename} 时出错: {e}") return [] def parse_iso_materials(text, filename): """ 专门解析ISO图纸的材料表格 """ materials = [] lines = text.split('\n') current_category = "" pipeline_number = get_pipeline_number(text) # 查找材料表格的开始 table_start = -1 for i, line in enumerate(lines): if re.search(r'PT\s*NO|COMPONENT\s*DESCRIPTION|N\.S\.\(MM\)|IDENT\s*CODE|QTY', line, re.IGNORECASE): table_start = i break if table_start == -1: print(f" 在文件 {filename} 中未找到材料表格") return materials print(f" 找到材料表格,开始位置: {table_start}") # 从表格开始位置解析 i = table_start while i < len(lines): line = lines[i].strip() # 检测类别行 if is_category_line(line): current_category = get_category(line) print(f" 发现类别: {current_category}") i += 1 continue # 跳过空行 if not line: i += 1 continue # 检查是否是切割长度表或其他非材料行 if re.search(r'CUT LENGTH TABLE|SPOOL N|ɍɁɅȺ|LENGTH\(MM\)|ȾɅɂɇȺ\(MM\)', line, re.IGNORECASE): print(f" 遇到切割长度表,停止解析") break # 检查是否是图纸信息行 if re.search(r'ISSUED FOR|N-PLANT NORTH|E \d+|N \d+|EL\. \+\d+', line, re.IGNORECASE): i += 1 continue # 尝试解析材料行 material = parse_material_line(lines, i, current_category) if material and material['材料代码'] and material['材料介绍']: material['单线图文件名'] = filename material['管线号'] = pipeline_number materials.append(material) print(f" 提取材料: {material['材料代码']} - 规格: {material['材料规格']} - 数量: {material['数量']}") # 跳过已处理的行 i += material.get('lines_processed', 1) else: i += 1 # 如果遇到明显的表格结束标记,提前退出 if i < len(lines) and re.search(r'CUT LENGTH TABLE|CONT\. ON|CONT\. FROM', lines[i], re.IGNORECASE): print(f" 遇到表格结束标记,停止解析") break return materials def parse_material_line(lines, start_index, category): """ 解析材料行,特别处理管道支架和螺栓 """ line = lines[start_index].strip() # 检查是否是以数字开头的行(材料行) if not re.match(r'^\d+\s', line): return None # 提取项目编号 item_no_match = re.match(r'^(\d+)\s+', line) if not item_no_match: return None item_no = item_no_match.group(1) remaining_line = line[len(item_no):].strip() # 特殊处理管道支架 if category == "PIPE SUPPORTS": return parse_pipe_support_line(lines, start_index, category) # 特殊处理螺栓 if category == "BOLTS": return parse_bolt_line(lines, start_index, category) # 特殊处理垫片(可能有多行描述) if category == "GASKETS": return parse_gasket_line(lines, start_index, category) # 常规材料解析 # 尝试提取数量(通常是行尾的数字,可能带有M) qty_match = re.search(r'(\d+\.?\d*\s*M?)$', remaining_line) if not qty_match: # 尝试从下一行获取数量 if start_index + 1 < len(lines): next_line = lines[start_index + 1].strip() qty_match = re.search(r'(\d+\.?\d*\s*M?)$', next_line) if not qty_match: return None quantity = qty_match.group(1) # 从行中移除数量部分 remaining_line = re.sub(r'\s*' + re.escape(quantity) + r'$', '', remaining_line) # 尝试提取材料代码(通常是大写字母、数字、下划线和连字符的组合) code_match = re.search(r'([A-Z0-9][A-Z0-9_\-]{5,})\s*$', remaining_line) if not code_match: # 尝试从下一行获取代码 if start_index + 1 < len(lines): next_line = lines[start_index + 1].strip() code_match = re.search(r'([A-Z0-9][A-Z0-9_\-]{5,})\s*$', next_line) if not code_match: # 对于没有明确代码的材料,检查是否有有效的描述 if not re.search(r'[A-Za-z]', remaining_line): return None # 使用描述的一部分作为代码 ident_code = f"MAT-{item_no}-{re.sub(r'[^A-Z0-9]', '', remaining_line.upper())[:10]}" else: ident_code = code_match.group(1) # 从行中移除代码部分 remaining_line = re.sub(r'\s*' + re.escape(ident_code) + r'\s*$', '', remaining_line) # 尝试提取规格(通常是数字或数字x数字格式) size_match = re.search(r'(\d+(?:\s?[x×]\s?\d+)?)\s*(?:MM|mm|")?$', remaining_line) if size_match: size = size_match.group(1) # 从行中移除规格部分 remaining_line = re.sub(r'\s*' + re.escape(size) + r'\s*(?:MM|mm|")?\s*$', '', remaining_line) else: size = "" # 剩余部分就是描述 description = remaining_line.strip() # 检查描述是否有效 if not re.search(r'[A-Za-z]', description): return None # 清理描述中的多余空格 description = re.sub(r'\s+', ' ', description).strip() return { '材料代码': ident_code, '材料规格': size, '材料介绍': f"{category}: {description}" if category else description, '数量': quantity, 'lines_processed': 1 } def parse_pipe_support_line(lines, start_index, category): """ 专门解析管道支架行 """ # 管道支架的格式通常是: 项目编号 描述 规格 数量 # 例如: "6 J(S1)-8"-CS1-100 200 4" line = lines[start_index].strip() # 提取项目编号 item_no_match = re.match(r'^(\d+)\s+', line) if not item_no_match: return None item_no = item_no_match.group(1) remaining_line = line[len(item_no):].strip() # 尝试提取数量(通常是行尾的数字) qty_match = re.search(r'(\d+)$', remaining_line) if not qty_match: return None quantity = qty_match.group(1) # 从行中移除数量部分 remaining_line = re.sub(r'\s*' + re.escape(quantity) + r'$', '', remaining_line) # 尝试提取规格(通常是数字) size_match = re.search(r'(\d+)\s*(?:MM|mm|")?$', remaining_line) if size_match: size = size_match.group(1) # 从行中移除规格部分 remaining_line = re.sub(r'\s*' + re.escape(size) + r'\s*(?:MM|mm|")?\s*$', '', remaining_line) else: size = "" # 剩余部分就是描述 description = remaining_line.strip() # 检查描述是否有效 if not re.search(r'[A-Za-z]', description): return None # 生成一个代码(使用描述的前几个字符和项目编号) clean_desc = re.sub(r'[^A-Z0-9]', '', description.upper()) ident_code = f"PS-{item_no}-{clean_desc[:10]}" if clean_desc else f"PS-{item_no}" return { '材料代码': ident_code, '材料规格': size, '材料介绍': f"{category}: {description}", '数量': quantity, 'lines_processed': 1 } def parse_bolt_line(lines, start_index, category): """ 专门解析螺栓行 """ # 螺栓的格式通常是多行的,例如: # "15 95 mm BOLTS/NUTS,-,A320 Gr.L7/A194 GR.7 S3,FT" # "S.BOLT/2 HHN,ASME B18.31.2" # "5/8 PLLS60NZZ-95 4" # 首先尝试提取项目编号 line = lines[start_index].strip() item_no_match = re.match(r'^(\d+)\s+', line) if not item_no_match: return None item_no = item_no_match.group(1) remaining_line = line[len(item_no):].strip() # 合并多行描述 description_lines = [remaining_line] lines_processed = 1 # 检查下一行是否也是描述的一部分 while start_index + lines_processed < len(lines): next_line = lines[start_index + lines_processed].strip() # 如果下一行以数字开头(可能是下一个项目),则停止 if re.match(r'^\d+\s', next_line): break # 如果下一行包含明显的数量或代码模式,则停止 if re.search(r'\d+$|PLLS\d+', next_line): break description_lines.append(next_line) lines_processed += 1 # 现在处理包含数量、规格和代码的行 if start_index + lines_processed >= len(lines): return None data_line = lines[start_index + lines_processed].strip() lines_processed += 1 # 尝试提取数量 qty_match = re.search(r'(\d+)$', data_line) if not qty_match: return None quantity = qty_match.group(1) # 从行中移除数量部分 data_line = re.sub(r'\s*' + re.escape(quantity) + r'$', '', data_line) # 尝试提取代码 code_match = re.search(r'([A-Z0-9][A-Z0-9_\-]{5,})\s*$', data_line) if not code_match: # 如果没有明确代码,生成一个 ident_code = f"BOLT-{item_no}" else: ident_code = code_match.group(1) # 从行中移除代码部分 data_line = re.sub(r'\s*' + re.escape(ident_code) + r'\s*$', '', data_line) # 剩余部分可能是规格 size = data_line.strip() # 合并描述 description = ' '.join(description_lines).strip() # 检查描述是否有效 if not re.search(r'[A-Za-z]', description): return None return { '材料代码': ident_code, '材料规格': size, '材料介绍': f"{category}: {description}", '数量': quantity, 'lines_processed': lines_processed } def parse_gasket_line(lines, start_index, category): """ 专门解析垫片行(可能有多行描述) """ line = lines[start_index].strip() # 提取项目编号 item_no_match = re.match(r'^(\d+)\s+', line) if not item_no_match: return None item_no = item_no_match.group(1) remaining_line = line[len(item_no):].strip() # 尝试提取数量 qty_match = re.search(r'(\d+)$', remaining_line) if not qty_match: return None quantity = qty_match.group(1) # 从行中移除数量部分 remaining_line = re.sub(r'\s*' + re.escape(quantity) + r'$', '', remaining_line) # 尝试提取代码 code_match = re.search(r'([A-Z0-9][A-Z0-9_\-]{5,})\s*$', remaining_line) if not code_match: return None ident_code = code_match.group(1) # 从行中移除代码部分 remaining_line = re.sub(r'\s*' + re.escape(ident_code) + r'\s*$', '', remaining_line) # 尝试提取规格 size_match = re.search(r'(\d+)\s*(?:MM|mm|")?$', remaining_line) if size_match: size = size_match.group(1) # 从行中移除规格部分 remaining_line = re.sub(r'\s*' + re.escape(size) + r'\s*(?:MM|mm|")?\s*$', '', remaining_line) else: size = "" # 剩余部分就是描述 description = remaining_line.strip() # 检查下一行是否也是描述的一部分 if start_index + 1 < len(lines): next_line = lines[start_index + 1].strip() if not re.match(r'^\d+\s', next_line) and not is_category_line(next_line): description += " " + next_line # 检查描述是否有效 if not re.search(r'[A-Za-z]', description): return None return { '材料代码': ident_code, '材料规格': size, '材料介绍': f"{category}: {description}", '数量': quantity, 'lines_processed': 1 } def is_category_line(line): """ 判断是否是类别行 """ categories = ['PIPES', 'FITTINGS', 'FLANGES', 'GASKETS', 'BOLTS', 'VALVES', 'INSTRUMENTS', 'PIPE SUPPORTS', 'VALVES / IN-LINE ITEMS'] return any(cat in line.upper() for cat in categories) def get_category(line): """ 从行中提取类别 """ categories = ['PIPES', 'FITTINGS', 'FLANGES', 'GASKETS', 'BOLTS', 'VALVES', 'INSTRUMENTS', 'PIPE SUPPORTS', 'VALVES / IN-LINE ITEMS'] for cat in categories: if cat in line.upper(): return cat return "" def get_pipeline_number(text): """ 从文本中提取管线号 """ # 首先尝试查找明确的管线号模式 patterns = [ r'9170-\d{4}-[A-Z0-9]+-[A-Z]{2,4}', r'9170-\d{4}-[A-Z0-9]+', r'CA911[EF]', r'91-E-\d+-T\d+', ] for pattern in patterns: matches = re.findall(pattern, text) if matches: # 返回最长的匹配项(通常更完整) return max(matches, key=len) # 如果找不到明确模式,尝试从文件名提取 filename_match = re.search(r'9170[^\s]*-(?:PRP|LN)', text) if filename_match: return filename_match.group(0) return "未识别" def batch_process_pdfs(folder_path): """ 批量处理文件夹中的所有PDF文件 """ all_materials = [] pdf_files = [f for f in os.listdir(folder_path) if f.lower().endswith('.pdf')] if not pdf_files: print("文件夹中没有找到PDF文件") return None print(f"找到 {len(pdf_files)} 个PDF文件,开始处理...") for pdf_file in pdf_files: pdf_path = os.path.join(folder_path, pdf_file) print(f"\n处理文件: {pdf_file}") materials = extract_materials_from_pdf(pdf_path, pdf_file) if materials: print(f" 提取到 {len(materials)} 条材料记录") for j, material in enumerate(materials[:min(3, len(materials))]): print(f" {j+1}. {material['材料代码']}: {material['材料介绍']} - {material['数量']}") else: print(f" 未提取到材料记录") all_materials.extend(materials) return all_materials def create_excel(materials_data, output_path): """ 创建Excel文件 """ if not materials_data: print("没有提取到材料数据") return False df = pd.DataFrame(materials_data) # 重新排列列顺序 columns = ['单线图文件名', '材料代码', '材料规格', '材料介绍', '数量', '管线号'] df = df[columns] # 去重(保留第一条记录) df = df.drop_duplicates(subset=['单线图文件名', '材料代码', '数量'], keep='first') # 确保所有材料介绍都有类别前缀 def ensure_category_prefix(description): if not re.match(r'^[A-Z]+:', description): # 如果没有类别前缀,尝试从描述中推断类别 if 'PIPE' in description.upper() and 'SUPPORT' not in description.upper(): return f"PIPES: {description}" elif 'SUPPORT' in description.upper() or description.startswith('J('): return f"PIPE SUPPORTS: {description}" elif 'FITTING' in description.upper() or 'ELBOW' in description.upper() or 'TEE' in description.upper(): return f"FITTINGS: {description}" elif 'FLANGE' in description.upper(): return f"FLANGES: {description}" elif 'GASKET' in description.upper(): return f"GASKETS: {description}" elif 'BOLT' in description.upper() or 'NUT' in description.upper(): return f"BOLTS: {description}" elif 'VALVE' in description.upper(): return f"VALVES: {description}" elif 'INSTRUMENT' in description.upper(): return f"INSTRUMENTS: {description}" else: return description return description df['材料介绍'] = df['材料介绍'].apply(ensure_category_prefix) df.to_excel(output_path, index=False, engine='openpyxl') return True def main(): # 设置文件夹路径 pdf_folder = r"C:\Users\10196\Desktop\PDF文件夹" output_excel = r"C:\Users\10196\Desktop\材料清单汇总_精确版.xlsx" print("开始处理PDF文件...") materials_data = batch_process_pdfs(pdf_folder) if materials_data: if create_excel(materials_data, output_excel): print(f"\n✅ Excel文件已生成: {output_excel}") print(f"✅ 共提取 {len(materials_data)} 条材料记录") # 显示统计信息 files = set(m['单线图文件名'] for m in materials_data) print(f"✅ 处理了 {len(files)} 个文件") # 显示材料类别统计 categories = {} for m in materials_data: cat = m['材料介绍'].split(':')[0] if ':' in m['材料介绍'] else '其他' categories[cat] = categories.get(cat, 0) + 1 print("✅ 材料类别统计:") for cat, count in categories.items(): print(f" {cat}: {count}条") else: print("❌ 生成Excel文件失败") else: print("❌ 没有提取到任何材料数据") if __name__ == "__main__": main()这个代码提取pdf里面的支架资料老是提取不全该怎么办
08-25
<html> <head> <title>9���ֵ�����</title> <meta http-equiv="Content-Type" content="text/html; charset=gb2312"> <meta charset="utf-8"> <style type="text/css"> <!-- .9points { font-family: "����"; font-size: 9pt; color: #000099; } .style2 {font-size: 10pt} .style3 { font-size: 12pt; font-weight: bold; } --> </style> </head> <body bgcolor="#FFFee7" text="#000000"> <div align="center"> <table width="600" border="1" align="center" cellpadding="0" cellspacing="0" bordercolor="#009900"> <tr> <td width="150" bordercolor="#fffee7"><img src="image/logo.gif" width="200" height="67"></td> <td width="444" align="right" valign="middle" bordercolor="#FFFee7"><strong><font color="#009900" size="6" face="��Բ"><img src="image/dwmx.gif" width="43" height="45">Dreamweaver MX 2004 </font></strong></td> </tr> <tr align="center" valign="middle"> <td height="15" colspan="2" bordercolor="#fffee7"> </td> </tr> </table> <table cellspacing=0 cellpadding=0 width=600 align=center border=0> <tbody> <tr> <td width=168 background=bj1.gif><font color=#990000><font color=#ff0000><font color=#cccccc> </font></font></font> <div align=center> <font color=#990000><font size="4" face="��Բ">�����ө��� <font color="#009900">�ֲ�����</font></font></font></div> </td> <td width=37><img src="image/bj2.gif" width="37" height="56"></td> <td valign=top> <table height=29 cellspacing=0 cellpadding=0 width="100%" border=0> <tbody> <tr> <td width=600 height=29 background="bj3.gif">  </td> </tr> </tbody> </table></td> </tr> </tbody> </table> <table width="600" border="3" align="center" cellpadding="2" cellspacing="2" bordercolor="#009900" background="BKG1.JPG"> <tr align="center" valign="middle"> <td background="file:///D|/电子商务网页设计网站/images/tu/0002.JPG"><div align="center"> <span class="style2"><span class="style3">������</span> �Ϻ��� ����� ������ �Ĵ�ʡ ɽ��ʡ</span>      ��ϵ���� <p align="center"><font color="#FF0033">��������ʷ ���� ���� ��ζ���� �ط����� ������Դ</font></p> <p align="left"><font color="#FF0033"><b>��ʷ��</b></font><br> 50����ǰ�ܿڵ�ͳ��֡������ˡ�������ս��Ϊ������ǣ��Ƽ�����Ϊ�㶼�����Ͼ��������ྩ���𽨶��ڴˣ����ж����˺�800�꣬Ԫ�ƴ󶼣�������ƾ�ʦ�����ij�Ϊ��ƽ����������������꣬��Ϊ�׶���<br> << </p> <p align="left"> <b><font color="#FF3333">������</font></b><br> λ�ڻ���ƽԭ���ˣ�����115��25'��117��30'����γ39��26'�����16807ƽ����������ĺ���43.71�ף��������11.5�ȡ�<br> << </p> <p align="left"> <b><font color="#FF3333">������</font></b><br> ȫ�й���10����8�أ����ಳ��150���<br> << </p> <p align="left"> <b><font color="#FF3333">��ζ����:</font></b><br> �����������ϱ���ˣ���ζ�뱸�����������͢��ˡ�����ȫϯ��Ϊͻ�������з�ʽ����ʽ����ʽ�����ͺ������ζ�͡�������Ѽ����ϸ�ۣ�����������������һ��Ϊ��ķ�ζ��ҩ�Ž���������չ�����������Ч������С��Ʒ�ּ��࣬���ǡ��೦�������ԡ���֭�����Ρ���衢��ͷ�⡢±����ա������ѡ����黨��ը�⡢�㶹�Ƶ�Ӧ�о��У����Ѳ��࣬���Դ󱥿ڸ���<br> << </p> <p align="left"> <b><font color="#FF3333">�ط�����:</font></b><br> �������ϱ�Ϸ��֮�����γ��е���ȫ�����ݾ�տ�����ݹ㷺���˲ű��������������й�Ϸ��Ĵ������֣���Ӱ�켫Ϊ��Զ��������ʷ��̣���������ϢŨ�����̻�����ϸ����������ǻ�������ܻ�ӭ����������������Ժ��"��ζ����"���������ĵط���ɫ������¯���࣬���ܺ��������������������������������Ĭ�����˹��Ⱥ�ڡ�<br> << </p> <p align="left"><b><font color="#FF3333">������Դ��</font></b><b><font color="#FF3333"><img src="image/beijing01.jpg" width="350" height="237" align="right"></font></b><br> 70����ǰ����Գ�˼��������ܿڵ����������ս��ʱ��������ڼ������Ͼ������ж���<b></b>��<b></b>�˵�����Ԫ��������������������Ϊȫ�������Ρ��Ļ����ġ���ˣ��ʼҹ�ͥ��԰�󡢳�̳���ڽ�<b></b>�����鲼���Ҵ�ౣ����á����泤���������˺��Դ�Ϊ���ˣ�������ż������DZ���������Դ��������ơ�40�������½���������񣬱������˽����й��Ĵ��ڡ������಻����Ȼ�羰������Դ����ɽ��ɭ�֡���ԭ���ܶ�����Ȫ��������һ���㡣��ˣ�������Ϊȫ������Ҫ�������ȵ����֮һ�� <b></b><br> << </p> <div align="left"></div> <p align="left" class="9points">�������ӣ������� ������ �ѻ���</p> </div></td> </tr> </table> <p class="9points">  </p> </div> </body> </html>怎么修改
09-23
代码下载地址: https://pan.quark.cn/s/bc087ffa872a "测控电路课后习题详解"文件.pdf是一份极具价值的学术资料,其中系统地阐述了测控电路的基础理论、系统构造、核心特性及其实际应用领域。 以下是对该文献的深入解读和系统梳理:1.1测控电路在测控系统中的核心功能测控电路在测控系统的整体架构中扮演着不可或缺的角色。 它承担着对传感器输出信号进行放大、滤除杂音、提取有效信息等关键任务,并且依据测量与控制的需求,执行必要的计算、处理与变换操作,最终输出能够驱动执行机构运作的指令信号。 测控电路作为测控系统中最具可塑性的部分,具备易于放大信号、转换模式、传输数据以及适应多样化应用场景的优势。 1.2决定测控电路精确度的关键要素影响测控电路精确度的核心要素包括:(1)噪声与干扰的存在;(2)失调现象与漂移效应,尤其是温度引起的漂移;(3)线性表现与保真度水平;(4)输入输出阻抗的特性影响。 在这些要素中,噪声干扰与失调漂移(含温度效应)是最为关键的因素,需要给予高度关注。 1.3测控电路的适应性表现测控电路在测控系统中展现出高度的适应性,具体表现在:* 具备选择特定信号、灵活实施各类转换以及进行信号处理与运算的能力* 实现模数转换与数模转换功能* 在直流与交流、电压与电流信号之间进行灵活转换* 在幅值、相位、频率与脉宽信号等不同参数间进行转换* 实现量程调整功能* 对信号实施多样化的处理与运算,如计算平均值、差值、峰值、绝对值,进行求导数、积分运算等,以及实现非线性环节的线性化处理、逻辑判断等操作1.4测量电路输入信号类型对电路结构设计的影响测量电路的输入信号类型对其电路结构设计产生显著影响。 依据传感器的类型差异,输入信号的形态也呈现多样性。 主要可分为...
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